Podcasts about heygen

Victor Lazarte is a General Partner @ Benchmark, one of the mot renowned venture firms in the world. At Benchmark, Victor has led deals into the likes of HeyGen and Mercor. As an angel, he was the first investor and board member of Brex, and as a Founder he scaled Wildlife Studios, bootstrapping into the largest gaming company in LatAm, with about 4 billion downloads.  In Today's Episode We Discuss: 04:10 Lessons Scaling Wildlife Studios to 4BN Downloads 04:49 Why Predicting the Future is Wrong When Starting a Company 07:11 Three Different Categories of Company in an AI World: Who Wins & Loses? 09:25 Why You Should Always Ask What a Founder Does in Their Free Time? 17:30 Two Traits That All the Best Founders Have? 23:17 Why If You Start a Company in SF You are 1,000x More Likely to be Successful? 35:30 Why Spreadsheet SaaS Investing is Dead 36:10 Why Replacing Humans is the Most Exciting Opportunity in AI 37:02 Why Knowledge Work Will Be Destroyed and What Happens Then? 37:30 Why China is a Stabilising Force for the US 38:59 China vs. US: The AI Race 42:33 Why All Students Today Should Study Computer Science 44:38 Why Portfolio Construction is BS 47:04 What Makes Peter Fenton One of the Best Ever 51:31 Why Duolingo Will Be One of the Most Valuable Companies in the World 01:00:17 Quick Fire Round: Insights and Predictions  

In this episode, recorded at the 2025 Abundance Summit, Joshua Xu dives into HeyGen, the future of AI avatars, and Steve Brown displays a use case for AI clones.   Recorded on March 10th, 2025 Views are my own thoughts; not Financial, Medical, or Legal Advice. Joshua Xu is the co-founder and CEO of HeyGen, an AI-powered video creation platform revolutionizing how businesses produce content by making video production significantly faster, cheaper, and scalable across languages. With a background in software engineering at Meta and Bloomberg LP, Xu brings deep technical expertise to his role, driving HeyGen's rapid growth to over $35 million in annual recurring revenue. A graduate of Duke University with a degree in Electrical Engineering and Computer Science, he's passionate about leveraging AI to democratize high-quality video communication for companies around the world. Steve Brown is a technologist and filmmaker passionate about media and innovation that strengthen human connection and sustainability. With a Physics degree from Stanford, he's founded and sold two tech startups and developed award-winning documentaries. As Chief AI Officer at Abundance360, he builds tools that help people harness AI and exponential tech for creativity and impact. Learn more about HeyGen: https://www.heygen.com/  Learn more about Abundance360: https://bit.ly/ABUNDANCE360  For free access to the Abundance Summit Summary click: https://bit.ly/Diamandisbreakthroughs ____________ I only endorse products and services I personally use. To see what they are,  please support this podcast by checking out our sponsors:  Get started with Fountain Life and become the CEO of your health: https://fountainlife.com/peter/ AI-powered precision diagnosis you NEED for a healthy gut: https://www.viome.com/peter  Get 15% off OneSkin with the code PETER at  https://www.oneskin.co/ #oneskinpod ____________ I send weekly emails with the latest insights and trends on today's and tomorrow's exponential technologies. Stay ahead of the curve, and sign up now:  Blog _____________ Connect With Peter: Twitter Instagram Youtube Moonshots

AI is reshaping the way brands create and test ads, and mobile marketing is at the forefront of this revolution. With AI-generated UGC (aka User Generated Content), creative testing at scale is no longer a challenge—it is an opportunity. Today, I'm joined by Andy to explore how their partnership with HeyGen is unlocking new possibilities for mobile advertisers. How is AI changing the game, and what does this mean for the future of creative? Let's find out. Today's Topics Include: Andy Willers' bio About Favoured Challenges Favoured faced before integrating AI-generated UGC What impact AI UGC had on one of the campaigns Favoured was running Biggest opportunities and risks for brands scaling creative testing with AI-generated content Android or iOS? Leaving his  smartphone at home, what features would Andy miss most? What features he would like to see added to his smartphone? Links and Resources: Andy Willers on LinkedIn Favoured website HeyGen - AI video generator Business Of Apps - connecting the app industry Quotes from Andy Willers " What AI has allowed us to do, particularly on the UGC side, is massively increase our capability for creative testing,” Andy said. “HeyGen's digital avatars enable us to quickly generate multiple UGC scripts or executions—allowing us to test different messaging and ad styles at scale.." "We're not at a stage where you type in a prompt and AI spits out a perfect execution. The human touch is still essential,” he explained. “HeyGen gives us the raw material—high-quality AI avatars—but it still requires skilled video editors to integrate them effectively with B-roll footage and visual elements." Host Business Of Apps - connecting the app industry since 2012

I sat down with podcast regular Sam Thompson (https://x.com/ImSamThompson), and we talked about how he's planning to launch an AI-powered recipe app using no-code tools and Facebook ads. We discussed his idea to become a free proposal consultant to get into the wedding business. He also shared his views on the importance of understanding business math like CAC and cash conversion cycle. We also touched on using affiliate marketing to generate revenue with a lead magnet created with ChatGPT and promoted using ads, and using tools like Creative OS and HeyGen to make ad creatives and videos.This is part 1 of a two-part conversation with Sam. Be sure to tune in next week for part 2.Timestamps below. Enjoy!---Watch this on YouTube instead here: tkopod.co/p-ytAsk me a question on or off the show here: http://tkopod.co/p-askLearn more about me: http://tkopod.co/p-cjkLearn about my company: http://tkopod.co/p-cofFollow me on Twitter here: http://tkopod.co/p-xFree weekly business ideas newsletter: http://tkopod.co/p-nlShare this podcast: http://tkopod.co/p-allScrape small business data: http://tkopod.co/p-os---00:00 Introduction and Initial Thoughts on AI and Apps00:49 Wedding Planning Business Strategy02:29 Personal Reflections and Technology Evolution04:15 Exploring No-Code App Development05:42 Recipe App Concept and Monetization07:52 Marketing Strategies and Business Models14:11 Collaborations and Future Plans16:07 Cold Audience Strategies16:40 The Power of Facebook Ads17:19 Optimizing Ad Campaigns22:33 Affiliate Marketing Tactics29:17 AI in Marketing30:00 Viral Marketing Case Studies32:35 Conclusion and Next Steps

In this episode of Create Like the Greats, instead of breaking down top SaaS and business strategies, Ross is going tactical—real tactical. You're getting 100 practical content marketing tips, tools, and strategies that you can implement starting today. This is an episode to bookmark, return to, and share with your team. Whether you're a beginner or an expert, these insights will help you level up your content game. Key Takeaways & Topics Covered Develop a Content Marketing Strategy Set clear goals, audience personas, and distribution plans. Review and adjust your strategy quarterly. Align your strategy with your organization's goals to maintain focus. Leverage AI to Streamline Content Creation  Use tools like Frase, ContentShake (SEMrush), and Jasper for SEO research and content optimization. Automate SERP analysis and keyword research. Utilize Distribution.ai and HubSpot for content distribution. Quality Over Quantity  Stand out with highly unscalable content—create work that AI can't easily replicate. Seth Godin's wisdom: "Remarkable content is content worth making a remark about." Challenge your team—how can this content be even better? Optimize for Generative Engine Optimization (GEO)  Prepare for the era of AI-driven search, voice assistants, and chat-based search engines. Learn about GEO best practices in this article on Foundation Inc. The Double-E-E-A-T Strategy  Experience, Expertise, Authority, and Trustworthiness (E-E-A-T). Ground content in your unique expertise—not just rehashed insights. Share real-world examples and case studies. Repurpose and Distribute Your Content Adopt a Create Once, Distribute Forever mindset. Reuse past high-performing content across channels. Study Disney's content repurposing for inspiration. Use Video to Build Trust Video is the last frontier of AI—people trust authentic video more than AI-generated text. Leverage tools like Loom, Descript, and HeyGen. Check out Cut30 for short-form video best practices. Content Personalization & Engagement  AI-powered personalization through tools like Singulate and HubSpot. Engage consistently on social media—don't just post and ghost. Build email lists to avoid reliance on social media platforms. SEO is Still Alive—Ignore the Naysayers  Despite what some say, Google isn't going anywhere anytime soon. SEO techniques still apply to AI-driven search models like ChatGPT and Perplexity. Implement pillar content and topic clusters to thrive in 2030 and beyond. Optimize for Mobile & User Experience Ensure content loads fast and is mobile-friendly. Avoid complex UI—users prioritize simplicity and ease of navigation. Resources & Tools Mentioned

In this solo episode of the podcast, I address some recent questions I've gotten specifically about A.I. in CS. A few tangents are included as per usual:Chapters:00:00 - Intro02:42 - When is your program ready for A.I.?04:10 - Data readiness for installing A.I.08:14 - Using AI for content generation 11:05 - Staying current or getting up to speed on A.I. 13:25 - Ticket deflection with A.I.16:00 - Utilizing A.I. in establishing integrations and configurations17:03 - A.I. Chatbots18:03 - Google's NotebookLM use cases20:35 - What to watch out for in adopting A.I.23:10 - Start with the Simple Things!Enjoy! I know I sure did...Special shoutouts in this episode go out to Ariglad, Clueso, HeyGen, QueryPal and Vitally! Thank you to our sponsor, QueryPal!QueryPal is an incredible platform for support leaders who want to optimize their operations! Support the show+++++++++++++++++Like/Subscribe/Review:If you are getting value from the show, please follow/subscribe so that you don't miss an episode and consider leaving us a review. Website:For more information about the show or to get in touch, visit DigitalCustomerSuccess.com. Buy Alex a Cup of Coffee:This show runs exclusively on caffeine - and lots of it. If you like what we're, consider supporting our habit by buying us a cup of coffee: https://bmc.link/dcspThank you for all of your support!The Digital Customer Success Podcast is hosted by Alex Turkovic

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Send Everyday AI and Jordan a text messageWhat AI tools or features should your company be using in 2025? We'll save you like 254 hours by telling you the Top AI Features and Tools of 2024. (And ranking the ones that are most useful for your biz.)  Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on AIUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:1. Top AI Tools and Features Discussion2. AI Tools of the Year & Rankings3. In-depth Discussion of Specific Tools4. AI Industry OverviewTimestamps:00:00 Network with tech professionals; explore AI tools.10:16 Share show for AI tools honorable mention.12:32 Siri uses ChatGPT for complex queries.18:09 Inline AI enhances collaborative document editing efficiently.23:23 ChatGPT search tool flawed after limited beta.31:06 Cursor went viral as first user-friendly AI.34:52 Google excelled with Gemini 2.0 updates.37:56 Google deep research: fast, comprehensive answers engine.46:17 Use Microsoft 365 Copilot Studio for automation.50:03 Microsoft Copilot Vision simplifies travel bookings. Limited.55:32 Iterative prompting guides advanced language models.01:02:47 Gemini app enables video and voice interaction.01:07:42 Google's Veo AI video tool released, concerns remain.01:13:52 Notebook LM prioritizes trust and transparency in AI.01:15:49 Top AI tools and features 2024 list.Keywords:Jordan Wilson, live stream, AI tools ranking, people's choice award, Midjourney v6.1, Microsoft Copilot Studio, Copilot Vision, Notebook LM, Sora, Veo 2, Zapier Agents, AI tool tiers, podcast, AI developments, generative AI, AI tool selection, AI tool ratings, AI 2024, audience participation, Claude's Artifacts, Claude Computer Use, Cursor AI, 11 Labs conversational agents, Google Gemini 2.0, Google Deep Research, HeyGen's new v3 avatars, AI in documents, Canva's Magic Studio, Chat GPT's new search, OpenAI's 01 Pro. Ready for ROI on GenAI? Go to youreverydayai.com/partner

Support Good Morning Gwinnett $5.99 A Month https://www.spreaker.com/podcast/good-morning-gwinnett-podcast--3262933/support_____________________________________________In this episode, we explore how businesses can use video to report company news, enhance engagement, and drive traffic to their websites. We discuss the benefits of video, how it improves SEO and social media visibility, and how AI-powered tools like HeyGen and Eleven Labs simplify video creation. Whether you're a small business or a growing enterprise, this episode will show you how to make video an essential part of your communication strategy.Key Takeaways:Why Video Matters – Learn why video content is more engaging and memorable than text-based news updates.Driving Website Traffic – Discover how video boosts SEO, increases time spent on your site, and improves conversions.AI Tools for Video Creation – Explore how HeyGen and Eleven Labs can help you create high-quality video content quickly.Embedding Video on Your Website – Understand the benefits of integrating video into your site to enhance credibility and reduce bounce rates.Best Practices for Success – Get actionable tips on optimizing video content for engagement, accessibility, and maximum reach.

„Videocontent mit KI-Avataren – Zeit sparen und überzeugen“ mit Thomas Hruska   Das KI-Summit Germany 2025 bietet am 31. Januar und 1. Februar die perfekte Gelegenheit, neue Impulse und wertvolle Kontakte zu gewinnen. Im inspirierenden Ambiente des Güterbahnhofs in Bad Homburg treffen Vordenker und Visionäre aufeinander, um die Zukunft der KI gemeinsam zu gestalten. Freu Dich auf ein abwechslungsreiches Programm mit spannenden Keynotes, praxisorientierten Workshops und einzigartigen Networking-Möglichkeiten. Sichere Dir jetzt Dein Ticket und werde Teil dieses richtungsweisenden Events! Thomas Hruska ist ein Pionier im Bereich der Video-Avatare und KI-gestützten Videoproduktion. Er unterstützt vor allem selbstständige Unternehmer und Marketingagenturen dabei, ihre Videopräsenz zu revolutionieren. Mithilfe von Avatar-Plattformen wie Eleven Labs oder HeyGen macht er Videoproduktion effizienter und zugänglicher. Sein Fokus liegt darauf, Technologie nicht nur zu vermitteln, sondern auch Vorbehalte – wie etwa Kamerascheu – abzubauen. Thomas Hruska auf LinkedIn: LinkedIn - https://www.linkedin.com/in/thomas--hruska/ KI-Summit Germany 2025: Hier anmelden - www.ki-summit-germany.de/   Was sind die Kerninhalte seines Impulsvortrags? Psychologische Aspekte von Avataren: Thomas beleuchtet, warum visuelle Repräsentationen – sei es realistisch oder im Comic-Stil – den Zugang zu KI-Technologien erleichtern und die Akzeptanz fördern. Herausforderungen und Grenzen der Technologie: Er zeigt auf, wo die Avatar-Technologie heute steht und welche Limitationen es gibt. Praxisorientierte Use Cases: Es werden konkrete Anwendungsfälle präsentiert, etwa zur Wissensweitergabe in Unternehmen. Diese Beispiele machen greifbar, wie Avatare Prozesse optimieren und Wissen nachhaltig sichern können. Deutschland als Innovationsstandort: Thomas betont, dass Deutschland nicht hinterherhinkt, sondern bereits vielversprechende KI-Lösungen entwickelt, insbesondere im Bereich Unternehmenswissen und Effizienzsteigerung.   Was ist das Besondere an seinem Impulsvortrag? Thomas' Vortrag besticht durch seine greifbare und praxisorientierte Herangehensweise. Statt abstrakter Theorie erhalten die Teilnehmer konkrete Use Cases und Beispiele, die sie direkt umsetzen können. Er vermittelt, wie mit aktuellen Tools und bestehenden „Bordmitteln“ bereits erhebliche Effizienzgewinne erzielt werden können – ohne auf zukünftige Technologien warten zu müssen. Besonders beeindruckend ist der Fokus auf die Zeitersparnis bei der Videoproduktion: Was früher Stunden dauerte, kann dank Avatar-Technologie in wenigen Minuten erledigt werden.   Welche Kernbotschaft lässt sich aus dem Vortrag ableiten? „Die Zukunft der Videoproduktion ist jetzt.“ Es gibt bereits Tools, die Unternehmern und Kreativen enorme Hebelwirkung bieten. Insbesondere kleine Unternehmen können durch Avatar-Technologien Zeit und Ressourcen sparen, während sie ihre digitale Präsenz stärken. Die Möglichkeit, sich selbst „zu klonen“ und Avatare für die Content-Produktion einzusetzen, eröffnet völlig neue Möglichkeiten der Effizienz und Flexibilität.     Noch mehr von den Koertings ...  Das KI-Café ... jede Woche Mittwoch (>300 Teilnehmer) von 08:30 bis 10:00 Uhr ... online via Zoom .. kostenlos und nicht umsonstJede Woche Mittwoch um 08:30 Uhr öffnet das KI-Café seine Online-Pforten ... wir lösen KI-Anwendungsfälle live auf der Bühne ... moderieren Expertenpanel zu speziellen Themen (bspw. KI im Recruiting ... KI in der Qualitätssicherung ... KI im Projektmanagement ... und vieles mehr) ... ordnen die neuen Entwicklungen in der KI-Welt ein und geben einen Ausblick ... und laden Experten ein für spezielle Themen ... und gehen auch mal in die Tiefe und durchdringen bestimmte Bereiche ganz konkret ... alles für dein Weiterkommen. 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Mitglieder erhalten exklusive monatliche KI-Updates, Experten-Interviews, Vorträge des KI-Speaker-Slams, KI-Café-Aufzeichnungen und einen 3-stündigen ChatGPT-Kurs. Tausche dich mit über 900 KI-Enthusiasten aus, stelle Fragen und starte durch. Initiiert von Torsten & Birgit Koerting, bietet die KI-Lounge Orientierung und Inspiration für den Einstieg in die KI-Revolution. Hier findet der Austausch statt ... www.koerting-institute.com/ki-lounge/   Starte mit uns in die 1:1 Zusammenarbeit Wenn du direkt mit uns arbeiten und KI in deinem Business integrieren möchtest, buche dir einen Termin für ein persönliches Gespräch. Gemeinsam finden wir Antworten auf deine Fragen und finden heraus, wie wir dich unterstützen können. Klicke hier, um einen Termin zu buchen und deine Fragen zu klären. Buche dir jetzt deinen Termin mit uns ... www.koerting-institute.com/termin/   Weitere Impulse im Netflix Stil ... Wenn du auf der Suche nach weiteren spannenden Impulsen für deine Selbstständigkeit bist, dann gehe jetzt auf unsere Impulseseite und lass die zahlreichen spannenden Impulse auf dich wirken. Inspiration pur ... www.koerting-institute.com/impulse/   Die Koertings auf die Ohren ... Wenn dir diese Podcastfolge gefallen hat, dann höre dir jetzt noch weitere informative und spannende Folgen an ... über 370 Folgen findest du hier ... www.koerting-institute.com/podcast/   Wir freuen uns darauf, dich auf deinem Weg zu begleiten

Due to overwhelming demand (>15x applications:slots), we are closing CFPs for AI Engineer Summit NYC today. Last call! Thanks, we'll be reaching out to all shortly!The world's top AI blogger and friend of every pod, Simon Willison, dropped a monster 2024 recap: Things we learned about LLMs in 2024. Brian of the excellent TechMeme Ride Home pinged us for a connection and a special crossover episode, our first in 2025. The target audience for this podcast is a tech-literate, but non-technical one. You can see Simon's notes for AI Engineers in his World's Fair Keynote.Timestamp* 00:00 Introduction and Guest Welcome* 01:06 State of AI in 2025* 01:43 Advancements in AI Models* 03:59 Cost Efficiency in AI* 06:16 Challenges and Competition in AI* 17:15 AI Agents and Their Limitations* 26:12 Multimodal AI and Future Prospects* 35:29 Exploring Video Avatar Companies* 36:24 AI Influencers and Their Future* 37:12 Simplifying Content Creation with AI* 38:30 The Importance of Credibility in AI* 41:36 The Future of LLM User Interfaces* 48:58 Local LLMs: A Growing Interest* 01:07:22 AI Wearables: The Next Big Thing* 01:10:16 Wrapping Up and Final ThoughtsTranscript[00:00:00] Introduction and Guest Welcome[00:00:00] Brian: Welcome to the first bonus episode of the Tech Meme Write Home for the year 2025. I'm your host as always, Brian McCullough. Listeners to the pod over the last year know that I have made a habit of quoting from Simon Willison when new stuff happens in AI from his blog. Simon has been, become a go to for many folks in terms of, you know, Analyzing things, criticizing things in the AI space.[00:00:33] Brian: I've wanted to talk to you for a long time, Simon. So thank you for coming on the show. No, it's a privilege to be here. And the person that made this connection happen is our friend Swyx, who has been on the show back, even going back to the, the Twitter Spaces days but also an AI guru in, in their own right Swyx, thanks for coming on the show also.[00:00:54] swyx (2): Thanks. I'm happy to be on and have been a regular listener, so just happy to [00:01:00] contribute as well.[00:01:00] Brian: And a good friend of the pod, as they say. Alright, let's go right into it.[00:01:06] State of AI in 2025[00:01:06] Brian: Simon, I'm going to do the most unfair, broad question first, so let's get it out of the way. The year 2025. Broadly, what is the state of AI as we begin this year?[00:01:20] Brian: Whatever you want to say, I don't want to lead the witness.[00:01:22] Simon: Wow. So many things, right? I mean, the big thing is everything's got really good and fast and cheap. Like, that was the trend throughout all of 2024. The good models got so much cheaper, they got so much faster, they got multimodal, right? The image stuff isn't even a surprise anymore.[00:01:39] Simon: They're growing video, all of that kind of stuff. So that's all really exciting.[00:01:43] Advancements in AI Models[00:01:43] Simon: At the same time, they didn't get massively better than GPT 4, which was a bit of a surprise. So that's sort of one of the open questions is, are we going to see huge, but I kind of feel like that's a bit of a distraction because GPT 4, but way cheaper, much larger context lengths, and it [00:02:00] can do multimodal.[00:02:01] Simon: is better, right? That's a better model, even if it's not.[00:02:05] Brian: What people were expecting or hoping, maybe not expecting is not the right word, but hoping that we would see another step change, right? Right. From like GPT 2 to 3 to 4, we were expecting or hoping that maybe we were going to see the next evolution in that sort of, yeah.[00:02:21] Brian: We[00:02:21] Simon: did see that, but not in the way we expected. We thought the model was just going to get smarter, and instead we got. Massive drops in, drops in price. We got all of these new capabilities. You can talk to the things now, right? They can do simulated audio input, all of that kind of stuff. And so it's kind of, it's interesting to me that the models improved in all of these ways we weren't necessarily expecting.[00:02:43] Simon: I didn't know it would be able to do an impersonation of Santa Claus, like a, you know, Talked to it through my phone and show it what I was seeing by the end of 2024. But yeah, we didn't get that GPT 5 step. And that's one of the big open questions is, is that actually just around the corner and we'll have a bunch of GPT 5 class models drop in the [00:03:00] next few months?[00:03:00] Simon: Or is there a limit?[00:03:03] Brian: If you were a betting man and wanted to put money on it, do you expect to see a phase change, step change in 2025?[00:03:11] Simon: I don't particularly for that, like, the models, but smarter. I think all of the trends we're seeing right now are going to keep on going, especially the inference time compute, right?[00:03:21] Simon: The trick that O1 and O3 are doing, which means that you can solve harder problems, but they cost more and it churns away for longer. I think that's going to happen because that's already proven to work. I don't know. I don't know. Maybe there will be a step change to a GPT 5 level, but honestly, I'd be completely happy if we got what we've got right now.[00:03:41] Simon: But cheaper and faster and more capabilities and longer contexts and so forth. That would be thrilling to me.[00:03:46] Brian: Digging into what you've just said one of the things that, by the way, I hope to link in the show notes to Simon's year end post about what, what things we learned about LLMs in 2024. Look for that in the show notes.[00:03:59] Cost Efficiency in AI[00:03:59] Brian: One of the things that you [00:04:00] did say that you alluded to even right there was that in the last year, you felt like the GPT 4 barrier was broken, like IE. Other models, even open source ones are now regularly matching sort of the state of the art.[00:04:13] Simon: Well, it's interesting, right? So the GPT 4 barrier was a year ago, the best available model was OpenAI's GPT 4 and nobody else had even come close to it.[00:04:22] Simon: And they'd been at the, in the lead for like nine months, right? That thing came out in what, February, March of, of 2023. And for the rest of 2023, nobody else came close. And so at the start of last year, like a year ago, the big question was, Why has nobody beaten them yet? Like, what do they know that the rest of the industry doesn't know?[00:04:40] Simon: And today, that I've counted 18 organizations other than GPT 4 who've put out a model which clearly beats that GPT 4 from a year ago thing. Like, maybe they're not better than GPT 4. 0, but that's, that, that, that barrier got completely smashed. And yeah, a few of those I've run on my laptop, which is wild to me.[00:04:59] Simon: Like, [00:05:00] it was very, very wild. It felt very clear to me a year ago that if you want GPT 4, you need a rack of 40, 000 GPUs just to run the thing. And that turned out not to be true. Like the, the, this is that big trend from last year of the models getting more efficient, cheaper to run, just as capable with smaller weights and so forth.[00:05:20] Simon: And I ran another GPT 4 model on my laptop this morning, right? Microsoft 5. 4 just came out. And that, if you look at the benchmarks, it's definitely, it's up there with GPT 4. 0. It's probably not as good when you actually get into the vibes of the thing, but it, it runs on my, it's a 14 gigabyte download and I can run it on a MacBook Pro.[00:05:38] Simon: Like who saw that coming? The most exciting, like the close of the year on Christmas day, just a few weeks ago, was when DeepSeek dropped their DeepSeek v3 model on Hugging Face without even a readme file. It was just like a giant binary blob that I can't run on my laptop. It's too big. But in all of the benchmarks, it's now by far the best available [00:06:00] open, open weights model.[00:06:01] Simon: Like it's, it's, it's beating the, the metalamas and so forth. And that was trained for five and a half million dollars, which is a tenth of the price that people thought it costs to train these things. So everything's trending smaller and faster and more efficient.[00:06:15] Brian: Well, okay.[00:06:16] Challenges and Competition in AI[00:06:16] Brian: I, I kind of was going to get to that later, but let's, let's combine this with what I was going to ask you next, which is, you know, you're talking, you know, Also in the piece about the LLM prices crashing, which I've even seen in projects that I'm working on, but explain Explain that to a general audience, because we hear all the time that LLMs are eye wateringly expensive to run, but what we're suggesting, and we'll come back to the cheap Chinese LLM, but first of all, for the end user, what you're suggesting is that we're starting to see the cost come down sort of in the traditional technology way of Of costs coming down over time,[00:06:49] Simon: yes, but very aggressively.[00:06:51] Simon: I mean, my favorite thing, the example here is if you look at GPT-3, so open AI's g, PT three, which was the best, a developed model in [00:07:00] 2022 and through most of 20 2023. That, the models that we have today, the OpenAI models are a hundred times cheaper. So there was a 100x drop in price for OpenAI from their best available model, like two and a half years ago to today.[00:07:13] Simon: And[00:07:14] Brian: just to be clear, not to train the model, but for the use of tokens and things. Exactly,[00:07:20] Simon: for running prompts through them. And then When you look at the, the really, the top tier model providers right now, I think, are OpenAI, Anthropic, Google, and Meta. And there are a bunch of others that I could list there as well.[00:07:32] Simon: Mistral are very good. The, the DeepSeq and Quen models have got great. There's a whole bunch of providers serving really good models. But even if you just look at the sort of big brand name providers, they all offer models now that are A fraction of the price of the, the, of the models we were using last year.[00:07:49] Simon: I think I've got some numbers that I threw into my blog entry here. Yeah. Like Gemini 1. 5 flash, that's Google's fast high quality model is [00:08:00] how much is that? It's 0. 075 dollars per million tokens. Like these numbers are getting, So we just do cents per million now,[00:08:09] swyx (2): cents per million,[00:08:10] Simon: cents per million makes, makes a lot more sense.[00:08:12] Simon: Yeah they have one model 1. 5 flash 8B, the absolute cheapest of the Google models, is 27 times cheaper than GPT 3. 5 turbo was a year ago. That's it. And GPT 3. 5 turbo, that was the cheap model, right? Now we've got something 27 times cheaper, and the Google, this Google one can do image recognition, it can do million token context, all of those tricks.[00:08:36] Simon: But it's, it's, it's very, it's, it really is startling how inexpensive some of this stuff has got.[00:08:41] Brian: Now, are we assuming that this, that happening is directly the result of competition? Because again, you know, OpenAI, and probably they're doing this for their own almost political reasons, strategic reasons, keeps saying, we're losing money on everything, even the 200.[00:08:56] Brian: So they probably wouldn't, the prices wouldn't be [00:09:00] coming down if there wasn't intense competition in this space.[00:09:04] Simon: The competition is absolutely part of it, but I have it on good authority from sources I trust that Google Gemini is not operating at a loss. Like, the amount of electricity to run a prompt is less than they charge you.[00:09:16] Simon: And the same thing for Amazon Nova. Like, somebody found an Amazon executive and got them to say, Yeah, we're not losing money on this. I don't know about Anthropic and OpenAI, but clearly that demonstrates it is possible to run these things at these ludicrously low prices and still not be running at a loss if you discount the Army of PhDs and the, the training costs and all of that kind of stuff.[00:09:36] Brian: One, one more for me before I let Swyx jump in here. To, to come back to DeepSeek and this idea that you could train, you know, a cutting edge model for 6 million. I, I was saying on the show, like six months ago, that if we are getting to the point where each new model It would cost a billion, ten billion, a hundred billion to train that.[00:09:54] Brian: At some point it would almost, only nation states would be able to train the new models. Do you [00:10:00] expect what DeepSeek and maybe others are proving to sort of blow that up? Or is there like some sort of a parallel track here that maybe I'm not technically, I don't have the mouse to understand the difference.[00:10:11] Brian: Is the model, are the models going to go, you know, Up to a hundred billion dollars or can we get them down? Sort of like DeepSeek has proven[00:10:18] Simon: so I'm the wrong person to answer that because I don't work in the lab training these models. So I can give you my completely uninformed opinion, which is, I felt like the DeepSeek thing.[00:10:27] Simon: That was a bomb shell. That was an absolute bombshell when they came out and said, Hey, look, we've trained. One of the best available models and it cost us six, five and a half million dollars to do it. I feel, and they, the reason, one of the reasons it's so efficient is that we put all of these export controls in to stop Chinese companies from giant buying GPUs.[00:10:44] Simon: So they've, were forced to be, go as efficient as possible. And yet the fact that they've demonstrated that that's possible to do. I think it does completely tear apart this, this, this mental model we had before that yeah, the training runs just keep on getting more and more expensive and the number of [00:11:00] organizations that can afford to run these training runs keeps on shrinking.[00:11:03] Simon: That, that's been blown out of the water. So yeah, that's, again, this was our Christmas gift. This was the thing they dropped on Christmas day. Yeah, it makes me really optimistic that we can, there are, It feels like there was so much low hanging fruit in terms of the efficiency of both inference and training and we spent a whole bunch of last year exploring that and getting results from it.[00:11:22] Simon: I think there's probably a lot left. I think there's probably, well, I would not be surprised to see even better models trained spending even less money over the next six months.[00:11:31] swyx (2): Yeah. So I, I think there's a unspoken angle here on what exactly the Chinese labs are trying to do because DeepSea made a lot of noise.[00:11:41] swyx (2): so much for joining us for around the fact that they train their model for six million dollars and nobody quite quite believes them. Like it's very, very rare for a lab to trumpet the fact that they're doing it for so cheap. They're not trying to get anyone to buy them. So why [00:12:00] are they doing this? They make it very, very obvious.[00:12:05] swyx (2): Deepseek is about 150 employees. It's an order of magnitude smaller than at least Anthropic and maybe, maybe more so for OpenAI. And so what's, what's the end game here? Are they, are they just trying to show that the Chinese are better than us?[00:12:21] Simon: So Deepseek, it's the arm of a hedge, it's a, it's a quant fund, right?[00:12:25] Simon: It's an algorithmic quant trading thing. So I, I, I would love to get more insight into how that organization works. My assumption from what I've seen is it looks like they're basically just flexing. They're like, hey, look at how utterly brilliant we are with this amazing thing that we've done. And it's, it's working, right?[00:12:43] Simon: They but, and so is that it? Are they, is this just their kind of like, this is, this is why our company is so amazing. Look at this thing that we've done, or? I don't know. I'd, I'd love to get Some insight from, from within that industry as to, as to how that's all playing out.[00:12:57] swyx (2): The, the prevailing theory among the Local Llama [00:13:00] crew and the Twitter crew that I indexed for my newsletter is that there is some amount of copying going on.[00:13:06] swyx (2): It's like Sam Altman you know, tweet, tweeting about how they're being copied. And then also there's this, there, there are other sort of opening eye employees that have said, Stuff that is similar that DeepSeek's rate of progress is how U. S. intelligence estimates the number of foreign spies embedded in top labs.[00:13:22] swyx (2): Because a lot of these ideas do spread around, but they surprisingly have a very high density of them in the DeepSeek v3 technical report. So it's, it's interesting. We don't know how much, how many, how much tokens. I think that, you know, people have run analysis on how often DeepSeek thinks it is cloud or thinks it is opening GPC 4.[00:13:40] swyx (2): Thanks for watching! And we don't, we don't know. We don't know. I think for me, like, yeah, we'll, we'll, we basically will never know as, as external commentators. I think what's interesting is how, where does this go? Is there a logical floor or bottom by my estimations for the same amount of ELO started last year to the end of last year cost went down by a thousand X for the [00:14:00] GPT, for, for GPT 4 intelligence.[00:14:02] swyx (2): Would, do they go down a thousand X this year?[00:14:04] Simon: That's a fascinating question. Yeah.[00:14:06] swyx (2): Is there a Moore's law going on, or did we just get a one off benefit last year for some weird reason?[00:14:14] Simon: My uninformed hunch is low hanging fruit. I feel like up until a year ago, people haven't been focusing on efficiency at all. You know, it was all about, what can we get these weird shaped things to do?[00:14:24] Simon: And now once we've sort of hit that, okay, we know that we can get them to do what GPT 4 can do, When thousands of researchers around the world all focus on, okay, how do we make this more efficient? What are the most important, like, how do we strip out all of the weights that have stuff in that doesn't really matter?[00:14:39] Simon: All of that kind of thing. So yeah, maybe that was it. Maybe 2024 was a freak year of all of the low hanging fruit coming out at once. And we'll actually see a reduction in the, in that rate of improvement in terms of efficiency. I wonder, I mean, I think we'll know for sure in about three months time if that trend's going to continue or not.[00:14:58] swyx (2): I agree. You know, I [00:15:00] think the other thing that you mentioned that DeepSeq v3 was the gift that was given from DeepSeq over Christmas, but I feel like the other thing that might be underrated was DeepSeq R1,[00:15:11] Speaker 4: which is[00:15:13] swyx (2): a reasoning model you can run on your laptop. And I think that's something that a lot of people are looking ahead to this year.[00:15:18] swyx (2): Oh, did they[00:15:18] Simon: release the weights for that one?[00:15:20] swyx (2): Yeah.[00:15:21] Simon: Oh my goodness, I missed that. I've been playing with the quen. So the other great, the other big Chinese AI app is Alibaba's quen. Actually, yeah, I, sorry, R1 is an API available. Yeah. Exactly. When that's really cool. So Alibaba's Quen have released two reasoning models that I've run on my laptop.[00:15:38] Simon: Now there was, the first one was Q, Q, WQ. And then the second one was QVQ because the second one's a vision model. So you can like give it vision puzzles and a prompt that these things, they are so much fun to run. Because they think out loud. It's like the OpenAR 01 sort of hides its thinking process. The Query ones don't.[00:15:59] Simon: They just, they [00:16:00] just churn away. And so you'll give it a problem and it will output literally dozens of paragraphs of text about how it's thinking. My favorite thing that happened with QWQ is I asked it to draw me a pelican on a bicycle in SVG. That's like my standard stupid prompt. And for some reason it thought in Chinese.[00:16:18] Simon: It spat out a whole bunch of like Chinese text onto my terminal on my laptop, and then at the end it gave me quite a good sort of artistic pelican on a bicycle. And I ran it all through Google Translate, and yeah, it was like, it was contemplating the nature of SVG files as a starting point. And the fact that my laptop can think in Chinese now is so delightful.[00:16:40] Simon: It's so much fun watching you do that.[00:16:43] swyx (2): Yeah, I think Andrej Karpathy was saying, you know, we, we know that we have achieved proper reasoning inside of these models when they stop thinking in English, and perhaps the best form of thought is in Chinese. But yeah, for listeners who don't know Simon's blog he always, whenever a new model comes out, you, I don't know how you do it, but [00:17:00] you're always the first to run Pelican Bench on these models.[00:17:02] swyx (2): I just did it for 5.[00:17:05] Simon: Yeah.[00:17:07] swyx (2): So I really appreciate that. You should check it out. These are not theoretical. Simon's blog actually shows them.[00:17:12] Brian: Let me put on the investor hat for a second.[00:17:15] AI Agents and Their Limitations[00:17:15] Brian: Because from the investor side of things, a lot of the, the VCs that I know are really hot on agents, and this is the year of agents, but last year was supposed to be the year of agents as well. Lots of money flowing towards, And Gentic startups.[00:17:32] Brian: But in in your piece that again, we're hopefully going to have linked in the show notes, you sort of suggest there's a fundamental flaw in AI agents as they exist right now. Let me let me quote you. And then I'd love to dive into this. You said, I remain skeptical as to their ability based once again, on the Challenge of gullibility.[00:17:49] Brian: LLMs believe anything you tell them, any systems that attempt to make meaningful decisions on your behalf, will run into the same roadblock. How good is a travel agent, or a digital assistant, or even a research tool, if it [00:18:00] can't distinguish truth from fiction? So, essentially, what you're suggesting is that the state of the art now that allows agents is still, it's still that sort of 90 percent problem, the edge problem, getting to the Or, or, or is there a deeper flaw?[00:18:14] Brian: What are you, what are you saying there?[00:18:16] Simon: So this is the fundamental challenge here and honestly my frustration with agents is mainly around definitions Like any if you ask anyone who says they're working on agents to define agents You will get a subtly different definition from each person But everyone always assumes that their definition is the one true one that everyone else understands So I feel like a lot of these agent conversations, people talking past each other because one person's talking about the, the sort of travel agent idea of something that books things on your behalf.[00:18:41] Simon: Somebody else is talking about LLMs with tools running in a loop with a cron job somewhere and all of these different things. You, you ask academics and they'll laugh at you because they've been debating what agents mean for over 30 years at this point. It's like this, this long running, almost sort of an in joke in that community.[00:18:57] Simon: But if we assume that for this purpose of this conversation, an [00:19:00] agent is something that, Which you can give a job and it goes off and it does that thing for you like, like booking travel or things like that. The fundamental challenge is, it's the reliability thing, which comes from this gullibility problem.[00:19:12] Simon: And a lot of my, my interest in this originally came from when I was thinking about prompt injections as a source of this form of attack against LLM systems where you deliberately lay traps out there for this LLM to stumble across,[00:19:24] Brian: and which I should say you have been banging this drum that no one's gotten any far, at least on solving this, that I'm aware of, right.[00:19:31] Brian: Like that's still an open problem. The two years.[00:19:33] Simon: Yeah. Right. We've been talking about this problem and like, a great illustration of this was Claude so Anthropic released Claude computer use a few months ago. Fantastic demo. You could fire up a Docker container and you could literally tell it to do something and watch it open a web browser and navigate to a webpage and click around and so forth.[00:19:51] Simon: Really, really, really interesting and fun to play with. And then, um. One of the first demos somebody tried was, what if you give it a web page that says download and run this [00:20:00] executable, and it did, and the executable was malware that added it to a botnet. So the, the very first most obvious dumb trick that you could play on this thing just worked, right?[00:20:10] Simon: So that's obviously a really big problem. If I'm going to send something out to book travel on my behalf, I mean, it's hard enough for me to figure out which airlines are trying to scam me and which ones aren't. Do I really trust a language model that believes the literal truth of anything that's presented to it to go out and do those things?[00:20:29] swyx (2): Yeah I definitely think there's, it's interesting to see Anthropic doing this because they used to be the safety arm of OpenAI that split out and said, you know, we're worried about letting this thing out in the wild and here they are enabling computer use for agents. Thanks. The, it feels like things have merged.[00:20:49] swyx (2): You know, I'm, I'm also fairly skeptical about, you know, this always being the, the year of Linux on the desktop. And this is the equivalent of this being the year of agents that people [00:21:00] are not predicting so much as wishfully thinking and hoping and praying for their companies and agents to work.[00:21:05] swyx (2): But I, I feel like things are. Coming along a little bit. It's to me, it's kind of like self driving. I remember in 2014 saying that self driving was just around the corner. And I mean, it kind of is, you know, like in, in, in the Bay area. You[00:21:17] Simon: get in a Waymo and you're like, Oh, this works. Yeah, but it's a slow[00:21:21] swyx (2): cook.[00:21:21] swyx (2): It's a slow cook over the next 10 years. We're going to hammer out these things and the cynical people can just point to all the flaws, but like, there are measurable or concrete progress steps that are being made by these builders.[00:21:33] Simon: There is one form of agent that I believe in. I believe, mostly believe in the research assistant form of agents.[00:21:39] Simon: The thing where you've got a difficult problem and, and I've got like, I'm, I'm on the beta for the, the Google Gemini 1. 5 pro with deep research. I think it's called like these names, these names. Right. But. I've been using that. It's good, right? You can give it a difficult problem and it tells you, okay, I'm going to look at 56 different websites [00:22:00] and it goes away and it dumps everything to its context and it comes up with a report for you.[00:22:04] Simon: And it's not, it won't work against adversarial websites, right? If there are websites with deliberate lies in them, it might well get caught out. Most things don't have that as a problem. And so I've had some answers from that which were genuinely really valuable to me. And that feels to me like, I can see how given existing LLM tech, especially with Google Gemini with its like million token contacts and Google with their crawl of the entire web and their, they've got like search, they've got search and cache, they've got a cache of every page and so forth.[00:22:35] Simon: That makes sense to me. And that what they've got right now, I don't think it's, it's not as good as it can be, obviously, but it's, it's, it's, it's a real useful thing, which they're going to start rolling out. So, you know, Perplexity have been building the same thing for a couple of years. That, that I believe in.[00:22:50] Simon: You know, if you tell me that you're going to have an agent that's a research assistant agent, great. The coding agents I mean, chat gpt code interpreter, Nearly two years [00:23:00] ago, that thing started writing Python code, executing the code, getting errors, rewriting it to fix the errors. That pattern obviously works.[00:23:07] Simon: That works really, really well. So, yeah, coding agents that do that sort of error message loop thing, those are proven to work. And they're going to keep on getting better, and that's going to be great. The research assistant agents are just beginning to get there. The things I'm critical of are the ones where you trust, you trust this thing to go out and act autonomously on your behalf, and make decisions on your behalf, especially involving spending money, like that.[00:23:31] Simon: I don't see that working for a very long time. That feels to me like an AGI level problem.[00:23:37] swyx (2): It's it's funny because I think Stripe actually released an agent toolkit which is one of the, the things I featured that is trying to enable these agents each to have a wallet that they can go and spend and have, basically, it's a virtual card.[00:23:49] swyx (2): It's not that, not that difficult with modern infrastructure. can[00:23:51] Simon: stick a 50 cap on it, then at least it's an honor. Can't lose more than 50.[00:23:56] Brian: You know I don't, I don't know if either of you know Rafat Ali [00:24:00] he runs Skift, which is a, a travel news vertical. And he, he, he constantly laughs at the fact that every agent thing is, we're gonna get rid of booking a, a plane flight for you, you know?[00:24:11] Brian: And, and I would point out that, like, historically, when the web started, the first thing everyone talked about is, You can go online and book a trip, right? So it's funny for each generation of like technological advance. The thing they always want to kill is the travel agent. And now they want to kill the webpage travel agent.[00:24:29] Simon: Like it's like I use Google flight search. It's great, right? If you gave me an agent to do that for me, it would save me, I mean, maybe 15 seconds of typing in my things, but I still want to see what my options are and go, yeah, I'm not flying on that airline, no matter how cheap they are.[00:24:44] swyx (2): Yeah. For listeners, go ahead.[00:24:47] swyx (2): For listeners, I think, you know, I think both of you are pretty positive on NotebookLM. And you know, we, we actually interviewed the NotebookLM creators, and there are actually two internal agents going on internally. The reason it takes so long is because they're running an agent loop [00:25:00] inside that is fairly autonomous, which is kind of interesting.[00:25:01] swyx (2): For one,[00:25:02] Simon: for a definition of agent loop, if you picked that particularly well. For one definition. And you're talking about the podcast side of this, right?[00:25:07] swyx (2): Yeah, the podcast side of things. They have a there's, there's going to be a new version coming out that, that we'll be featuring at our, at our conference.[00:25:14] Simon: That one's fascinating to me. Like NotebookLM, I think it's two products, right? On the one hand, it's actually a very good rag product, right? You dump a bunch of things in, you can run searches, that, that, it does a good job of. And then, and then they added the, the podcast thing. It's a bit of a, it's a total gimmick, right?[00:25:30] Simon: But that gimmick got them attention, because they had a great product that nobody paid any attention to at all. And then you add the unfeasibly good voice synthesis of the podcast. Like, it's just, it's, it's, it's the lesson.[00:25:43] Brian: It's the lesson of mid journey and stuff like that. If you can create something that people can post on socials, you don't have to lift a finger again to do any marketing for what you're doing.[00:25:53] Brian: Let me dig into Notebook LLM just for a second as a podcaster. As a [00:26:00] gimmick, it makes sense, and then obviously, you know, you dig into it, it sort of has problems around the edges. It's like, it does the thing that all sort of LLMs kind of do, where it's like, oh, we want to Wrap up with a conclusion.[00:26:12] Multimodal AI and Future Prospects[00:26:12] Brian: I always call that like the the eighth grade book report paper problem where it has to have an intro and then, you know But that's sort of a thing where because I think you spoke about this again in your piece at the year end About how things are going multimodal and how things are that you didn't expect like, you know vision and especially audio I think So that's another thing where, at least over the last year, there's been progress made that maybe you, you didn't think was coming as quick as it came.[00:26:43] Simon: I don't know. I mean, a year ago, we had one really good vision model. We had GPT 4 vision, was, was, was very impressive. And Google Gemini had just dropped Gemini 1. 0, which had vision, but nobody had really played with it yet. Like Google hadn't. People weren't taking Gemini [00:27:00] seriously at that point. I feel like it was 1.[00:27:02] Simon: 5 Pro when it became apparent that actually they were, they, they got over their hump and they were building really good models. And yeah, and they, to be honest, the video models are mostly still using the same trick. The thing where you divide the video up into one image per second and you dump that all into the context.[00:27:16] Simon: So maybe it shouldn't have been so surprising to us that long context models plus vision meant that the video was, was starting to be solved. Of course, it didn't. Not being, you, what you really want with videos, you want to be able to do the audio and the images at the same time. And I think the models are beginning to do that now.[00:27:33] Simon: Like, originally, Gemini 1. 5 Pro originally ignored the audio. It just did the, the, like, one frame per second video trick. As far as I can tell, the most recent ones are actually doing pure multimodal. But the things that opens up are just extraordinary. Like, the the ChatGPT iPhone app feature that they shipped as one of their 12 days of, of OpenAI, I really can be having a conversation and just turn on my video camera and go, Hey, what kind of tree is [00:28:00] this?[00:28:00] Simon: And so forth. And it works. And for all I know, that's just snapping a like picture once a second and feeding it into the model. The, the, the things that you can do with that as an end user are extraordinary. Like that, that to me, I don't think most people have cottoned onto the fact that you can now stream video directly into a model because it, it's only a few weeks old.[00:28:22] Simon: Wow. That's a, that's a, that's a, that's Big boost in terms of what kinds of things you can do with this stuff. Yeah. For[00:28:30] swyx (2): people who are not that close I think Gemini Flashes free tier allows you to do something like capture a photo, one photo every second or a minute and leave it on 24, seven, and you can prompt it to do whatever.[00:28:45] swyx (2): And so you can effectively have your own camera app or monitoring app that that you just prompt and it detects where it changes. It detects for, you know, alerts or anything like that, or describes your day. You know, and, and, and the fact that this is free I think [00:29:00] it's also leads into the previous point of it being the prices haven't come down a lot.[00:29:05] Simon: And even if you're paying for this stuff, like a thing that I put in my blog entry is I ran a calculation on what it would cost to process 68, 000 photographs in my photo collection, and for each one just generate a caption, and using Gemini 1. 5 Flash 8B, it would cost me 1. 68 to process 68, 000 images, which is, I mean, that, that doesn't make sense.[00:29:28] Simon: None of that makes sense. Like it's, it's a, for one four hundredth of a cent per image to generate captions now. So you can see why feeding in a day's worth of video just isn't even very expensive to process.[00:29:40] swyx (2): Yeah, I'll tell you what is expensive. It's the other direction. So we're here, we're talking about consuming video.[00:29:46] swyx (2): And this year, we also had a lot of progress, like probably one of the most excited, excited, anticipated launches of the year was Sora. We actually got Sora. And less exciting.[00:29:55] Simon: We did, and then VO2, Google's Sora, came out like three [00:30:00] days later and upstaged it. Like, Sora was exciting until VO2 landed, which was just better.[00:30:05] swyx (2): In general, I feel the media, or the social media, has been very unfair to Sora. Because what was released to the world, generally available, was Sora Lite. It's the distilled version of Sora, right? So you're, I did not[00:30:16] Simon: realize that you're absolutely comparing[00:30:18] swyx (2): the, the most cherry picked version of VO two, the one that they published on the marketing page to the, the most embarrassing version of the soa.[00:30:25] swyx (2): So of course it's gonna look bad, so, well, I got[00:30:27] Simon: access to the VO two I'm in the VO two beta and I've been poking around with it and. Getting it to generate pelicans on bicycles and stuff. I would absolutely[00:30:34] swyx (2): believe that[00:30:35] Simon: VL2 is actually better. Is Sora, so is full fat Sora coming soon? Do you know, when, when do we get to play with that one?[00:30:42] Simon: No one's[00:30:43] swyx (2): mentioned anything. I think basically the strategy is let people play around with Sora Lite and get info there. But the, the, keep developing Sora with the Hollywood studios. That's what they actually care about. Gotcha. Like the rest of us. Don't really know what to do with the video anyway. Right.[00:30:59] Simon: I mean, [00:31:00] that's my thing is I realized that for generative images and images and video like images We've had for a few years and I don't feel like they've broken out into the talented artist community yet Like lots of people are having fun with them and doing and producing stuff. That's kind of cool to look at but what I want you know that that movie everything everywhere all at once, right?[00:31:20] Simon: One, one ton of Oscars, utterly amazing film. The VFX team for that were five people, some of whom were watching YouTube videos to figure out what to do. My big question for, for Sora and and and Midjourney and stuff, what happens when a creative team like that starts using these tools? I want the creative geniuses behind everything, everywhere all at once.[00:31:40] Simon: What are they going to be able to do with this stuff in like a few years time? Because that's really exciting to me. That's where you take artists who are at the very peak of their game. Give them these new capabilities and see, see what they can do with them.[00:31:52] swyx (2): I should, I know a little bit here. So it should mention that, that team actually used RunwayML.[00:31:57] swyx (2): So there was, there was,[00:31:57] Simon: yeah.[00:31:59] swyx (2): I don't know how [00:32:00] much I don't. So, you know, it's possible to overstate this, but there are people integrating it. Generated video within their workflow, even pre SORA. Right, because[00:32:09] Brian: it's not, it's not the thing where it's like, okay, tomorrow we'll be able to do a full two hour movie that you prompt with three sentences.[00:32:15] Brian: It is like, for the very first part of, of, you know video effects in film, it's like, if you can get that three second clip, if you can get that 20 second thing that they did in the matrix that blew everyone's minds and took a million dollars or whatever to do, like, it's the, it's the little bits and pieces that they can fill in now that it's probably already there.[00:32:34] swyx (2): Yeah, it's like, I think actually having a layered view of what assets people need and letting AI fill in the low value assets. Right, like the background video, the background music and, you know, sometimes the sound effects. That, that maybe, maybe more palatable maybe also changes the, the way that you evaluate the stuff that's coming out.[00:32:57] swyx (2): Because people tend to, in social media, try to [00:33:00] emphasize foreground stuff, main character stuff. So you really care about consistency, and you, you really are bothered when, like, for example, Sorad. Botch's image generation of a gymnast doing flips, which is horrible. It's horrible. But for background crowds, like, who cares?[00:33:18] Brian: And by the way, again, I was, I was a film major way, way back in the day, like, that's how it started. Like things like Braveheart, where they filmed 10 people on a field, and then the computer could turn it into 1000 people on a field. Like, that's always been the way it's around the margins and in the background that first comes in.[00:33:36] Brian: The[00:33:36] Simon: Lord of the Rings movies were over 20 years ago. Although they have those giant battle sequences, which were very early, like, I mean, you could almost call it a generative AI approach, right? They were using very sophisticated, like, algorithms to model out those different battles and all of that kind of stuff.[00:33:52] Simon: Yeah, I know very little. I know basically nothing about film production, so I try not to commentate on it. But I am fascinated to [00:34:00] see what happens when, when these tools start being used by the real, the people at the top of their game.[00:34:05] swyx (2): I would say like there's a cultural war that is more that being fought here than a technology war.[00:34:11] swyx (2): Most of the Hollywood people are against any form of AI anyway, so they're busy Fighting that battle instead of thinking about how to adopt it and it's, it's very fringe. I participated here in San Francisco, one generative AI video creative hackathon where the AI positive artists actually met with technologists like myself and then we collaborated together to build short films and that was really nice and I think, you know, I'll be hosting some of those in my events going forward.[00:34:38] swyx (2): One thing that I think like I want to leave it. Give people a sense of it's like this is a recap of last year But then sometimes it's useful to walk away as well with like what can we expect in the future? I don't know if you got anything. I would also call out that the Chinese models here have made a lot of progress Hyde Law and Kling and God knows who like who else in the video arena [00:35:00] Also making a lot of progress like surprising him like I think maybe actually Chinese China is surprisingly ahead with regards to Open8 at least, but also just like specific forms of video generation.[00:35:12] Simon: Wouldn't it be interesting if a film industry sprung up in a country that we don't normally think of having a really strong film industry that was using these tools? Like, that would be a fascinating sort of angle on this. Mm hmm. Mm hmm.[00:35:25] swyx (2): Agreed. I, I, I Oh, sorry. Go ahead.[00:35:29] Exploring Video Avatar Companies[00:35:29] swyx (2): Just for people's Just to put it on people's radar as well, Hey Jen, there's like there's a category of video avatar companies that don't specifically, don't specialize in general video.[00:35:41] swyx (2): They only do talking heads, let's just say. And HeyGen sings very well.[00:35:45] Brian: Swyx, you know that that's what I've been using, right? Like, have, have I, yeah, right. So, if you see some of my recent YouTube videos and things like that, where, because the beauty part of the HeyGen thing is, I, I, I don't want to use the robot voice, so [00:36:00] I record the mp3 file for my computer, And then I put that into HeyGen with the avatar that I've trained it on, and all it does is the lip sync.[00:36:09] Brian: So it looks, it's not 100 percent uncanny valley beatable, but it's good enough that if you weren't looking for it, it's just me sitting there doing one of my clips from the show. And, yeah, so, by the way, HeyGen. Shout out to them.[00:36:24] AI Influencers and Their Future[00:36:24] swyx (2): So I would, you know, in terms of like the look ahead going, like, looking, reviewing 2024, looking at trends for 2025, I would, they basically call this out.[00:36:33] swyx (2): Meta tried to introduce AI influencers and failed horribly because they were just bad at it. But at some point that there will be more and more basically AI influencers Not in a way that Simon is but in a way that they are not human.[00:36:50] Simon: Like the few of those that have done well, I always feel like they're doing well because it's a gimmick, right?[00:36:54] Simon: It's a it's it's novel and fun to like Like that, the AI Seinfeld thing [00:37:00] from last year, the Twitch stream, you know, like those, if you're the only one or one of just a few doing that, you'll get, you'll attract an audience because it's an interesting new thing. But I just, I don't know if that's going to be sustainable longer term or not.[00:37:11] Simon: Like,[00:37:12] Simplifying Content Creation with AI[00:37:12] Brian: I'm going to tell you, Because I've had discussions, I can't name the companies or whatever, but, so think about the workflow for this, like, now we all know that on TikTok and Instagram, like, holding up a phone to your face, and doing like, in my car video, or walking, a walk and talk, you know, that's, that's very common, but also, if you want to do a professional sort of talking head video, you still have to sit in front of a camera, you still have to do the lighting, you still have to do the video editing, versus, if you can just record, what I'm saying right now, the last 30 seconds, If you clip that out as an mp3 and you have a good enough avatar, then you can put that avatar in front of Times Square, on a beach, or whatever.[00:37:50] Brian: So, like, again for creators, the reason I think Simon, we're on the verge of something, it, it just, it's not going to, I think it's not, oh, we're going to have [00:38:00] AI avatars take over, it'll be one of those things where it takes another piece of the workflow out and simplifies it. I'm all[00:38:07] Simon: for that. I, I always love this stuff.[00:38:08] Simon: I like tools. Tools that help human beings do more. Do more ambitious things. I'm always in favor of, like, that, that, that's what excites me about this entire field.[00:38:17] swyx (2): Yeah. We're, we're looking into basically creating one for my podcast. We have this guy Charlie, he's Australian. He's, he's not real, but he pre, he opens every show and we are gonna have him present all the shorts.[00:38:29] Simon: Yeah, go ahead.[00:38:30] The Importance of Credibility in AI[00:38:30] Simon: The thing that I keep coming back to is this idea of credibility like in a world that is full of like AI generated everything and so forth It becomes even more important that people find the sources of information that they trust and find people and find Sources that are credible and I feel like that's the one thing that LLMs and AI can never have is credibility, right?[00:38:49] Simon: ChatGPT can never stake its reputation on telling you something useful and interesting because That means nothing, right? It's a matrix multiplication. It depends on who prompted it and so forth. So [00:39:00] I'm always, and this is when I'm blogging as well, I'm always looking for, okay, who are the reliable people who will tell me useful, interesting information who aren't just going to tell me whatever somebody's paying them to tell, tell them, who aren't going to, like, type a one sentence prompt into an LLM and spit out an essay and stick it online.[00:39:16] Simon: And that, that to me, Like, earning that credibility is really important. That's why a lot of my ethics around the way that I publish are based on the idea that I want people to trust me. I want to do things that, that gain credibility in people's eyes so they will come to me for information as a trustworthy source.[00:39:32] Simon: And it's the same for the sources that I'm, I'm consulting as well. So that's something I've, I've been thinking a lot about that sort of credibility focus on this thing for a while now.[00:39:40] swyx (2): Yeah, you can layer or structure credibility or decompose it like so one thing I would put in front of you I'm not saying that you should Agree with this or accept this at all is that you can use AI to generate different Variations and then and you pick you as the final sort of last mile person that you pick The last output and [00:40:00] you put your stamp of credibility behind that like that everything's human reviewed instead of human origin[00:40:04] Simon: Yeah, if you publish something you need to be able to put it on the ground Publishing it.[00:40:08] Simon: You need to say, I will put my name to this. I will attach my credibility to this thing. And if you're willing to do that, then, then that's great.[00:40:16] swyx (2): For creators, this is huge because there's a fundamental asymmetry between starting with a blank slate versus choosing from five different variations.[00:40:23] Brian: Right.[00:40:24] Brian: And also the key thing that you just said is like, if everything that I do, if all of the words were generated by an LLM, if the voice is generated by an LLM. If the video is also generated by the LLM, then I haven't done anything, right? But if, if one or two of those, you take a shortcut, but it's still, I'm willing to sign off on it.[00:40:47] Brian: Like, I feel like that's where I feel like people are coming around to like, this is maybe acceptable, sort of.[00:40:53] Simon: This is where I've been pushing the definition. I love the term slop. Where I've been pushing the definition of slop as AI generated [00:41:00] content that is both unrequested and unreviewed and the unreviewed thing is really important like that's the thing that elevates something from slop to not slop is if A human being has reviewed it and said, you know what, this is actually worth other people's time.[00:41:12] Simon: And again, I'm willing to attach my credibility to it and say, hey, this is worthwhile.[00:41:16] Brian: It's, it's, it's the cura curational, curatorial and editorial part of it that no matter what the tools are to do shortcuts, to do, as, as Swyx is saying choose between different edits or different cuts, but in the end, if there's a curatorial mind, Or editorial mind behind it.[00:41:32] Brian: Let me I want to wedge this in before we start to close.[00:41:36] The Future of LLM User Interfaces[00:41:36] Brian: One of the things coming back to your year end piece that has been a something that I've been banging the drum about is when you're talking about LLMs. Getting harder to use. You said most users are thrown in at the deep end.[00:41:48] Brian: The default LLM chat UI is like taking brand new computer users, dropping them into a Linux terminal and expecting them to figure it all out. I mean, it's, it's literally going back to the command line. The command line was defeated [00:42:00] by the GUI interface. And this is what I've been banging the drum about is like, this cannot be.[00:42:05] Brian: The user interface, what we have now cannot be the end result. Do you see any hints or seeds of a GUI moment for LLM interfaces?[00:42:17] Simon: I mean, it has to happen. It absolutely has to happen. The the, the, the, the usability of these things is turning into a bit of a crisis. And we are at least seeing some really interesting innovation in little directions.[00:42:28] Simon: Just like OpenAI's chat GPT canvas thing that they just launched. That is at least. Going a little bit more interesting than just chat, chats and responses. You know, you can, they're exploring that space where you're collaborating with an LLM. You're both working in the, on the same document. That makes a lot of sense to me.[00:42:44] Simon: Like that, that feels really smart. The one of the best things is still who was it who did the, the UI where you could, they had a drawing UI where you draw an interface and click a button. TL draw would then make it real thing. That was spectacular, [00:43:00] absolutely spectacular, like, alternative vision of how you'd interact with these models.[00:43:05] Simon: Because yeah, the and that's, you know, so I feel like there is so much scope for innovation there and it is beginning to happen. Like, like, I, I feel like most people do understand that we need to do better in terms of interfaces that both help explain what's going on and give people better tools for working with models.[00:43:23] Simon: I was going to say, I want to[00:43:25] Brian: dig a little deeper into this because think of the conceptual idea behind the GUI, which is instead of typing into a command line open word. exe, it's, you, you click an icon, right? So that's abstracting away sort of the, again, the programming stuff that like, you know, it's, it's a, a, a child can tap on an iPad and, and make a program open, right?[00:43:47] Brian: The problem it seems to me right now with how we're interacting with LLMs is it's sort of like you know a dumb robot where it's like you poke it and it goes over here, but no, I want it, I want to go over here so you poke it this way and you can't get it exactly [00:44:00] right, like, what can we abstract away from the From the current, what's going on that, that makes it more fine tuned and easier to get more precise.[00:44:12] Brian: You see what I'm saying?[00:44:13] Simon: Yes. And the this is the other trend that I've been following from the last year, which I think is super interesting. It's the, the prompt driven UI development thing. Basically, this is the pattern where Claude Artifacts was the first thing to do this really well. You type in a prompt and it goes, Oh, I should answer that by writing a custom HTML and JavaScript application for you that does a certain thing.[00:44:35] Simon: And when you think about that take and since then it turns out This is easy, right? Every decent LLM can produce HTML and JavaScript that does something useful. So we've actually got this alternative way of interacting where they can respond to your prompt with an interactive custom interface that you can work with.[00:44:54] Simon: People haven't quite wired those back up again. Like, ideally, I'd want the LLM ask me a [00:45:00] question where it builds me a custom little UI, For that question, and then it gets to see how I interacted with that. I don't know why, but that's like just such a small step from where we are right now. But that feels like such an obvious next step.[00:45:12] Simon: Like an LLM, why should it, why should you just be communicating with, with text when it can build interfaces on the fly that let you select a point on a map or or move like sliders up and down. It's gonna create knobs and dials. I keep saying knobs and dials. right. We can do that. And the LLMs can build, and Claude artifacts will build you a knobs and dials interface.[00:45:34] Simon: But at the moment they haven't closed the loop. When you twiddle those knobs, Claude doesn't see what you were doing. They're going to close that loop. I'm, I'm shocked that they haven't done it yet. So yeah, I think there's so much scope for innovation and there's so much scope for doing interesting stuff with that model where the LLM, anything you can represent in SVG, which is almost everything, can now be part of that ongoing conversation.[00:45:59] swyx (2): Yeah, [00:46:00] I would say the best executed version of this I've seen so far is Bolt where you can literally type in, make a Spotify clone, make an Airbnb clone, and it actually just does that for you zero shot with a nice design.[00:46:14] Simon: There's a benchmark for that now. The LMRena people now have a benchmark that is zero shot app, app generation, because all of the models can do it.[00:46:22] Simon: Like it's, it's, I've started figuring out. I'm building my own version of this for my own project, because I think within six months. I think it'll just be an expected feature. Like if you have a web application, why don't you have a thing where, oh, look, the, you can add a custom, like, so for my dataset data exploration project, I want you to be able to do things like conjure up a dashboard, just via a prompt.[00:46:43] Simon: You say, oh, I need a pie chart and a bar chart and put them next to each other, and then have a form where submitting the form inserts a row into my database table. And this is all suddenly feasible. It's, it's, it's not even particularly difficult to do, which is great. Utterly bizarre that these things are now easy.[00:47:00][00:47:00] swyx (2): I think for a general audience, that is what I would highlight, that software creation is becoming easier and easier. Gemini is now available in Gmail and Google Sheets. I don't write my own Google Sheets formulas anymore, I just tell Gemini to do it. And so I think those are, I almost wanted to basically somewhat disagree with, with your assertion that LMS got harder to use.[00:47:22] swyx (2): Like, yes, we, we expose more capabilities, but they're, they're in minor forms, like using canvas, like web search in, in in chat GPT and like Gemini being in, in Excel sheets or in Google sheets, like, yeah, we're getting, no,[00:47:37] Simon: no, no, no. Those are the things that make it harder, because the problem is that for each of those features, they're amazing.[00:47:43] Simon: If you understand the edges of the feature, if you're like, okay, so in Google, Gemini, Excel formulas, I can get it to do a certain amount of things, but I can't get it to go and read a web. You probably can't get it to read a webpage, right? But you know, there are, there are things that it can do and things that it can't do, which are completely undocumented.[00:47:58] Simon: If you ask it what it [00:48:00] can and can't do, they're terrible at answering questions about that. So like my favorite example is Claude artifacts. You can't build a Claude artifact that can hit an API somewhere else. Because the cause headers on that iframe prevents accessing anything outside of CDNJS. So, good luck learning cause headers as an end user in order to understand why Like, I've seen people saying, oh, this is rubbish.[00:48:26] Simon: I tried building an artifact that would run a prompt and it couldn't because Claude didn't expose an API with cause headers that all of this stuff is so weird and complicated. And yeah, like that, that, the more that with the more tools we add, the more expertise you need to really, To understand the full scope of what you can do.[00:48:44] Simon: And so it's, it's, I wouldn't say it's, it's, it's, it's like, the question really comes down to what does it take to understand the full extent of what's possible? And honestly, that, that's just getting more and more involved over time.[00:48:58] Local LLMs: A Growing Interest[00:48:58] swyx (2): I have one more topic that I, I [00:49:00] think you, you're kind of a champion of and we've touched on it a little bit, which is local LLMs.[00:49:05] swyx (2): And running AI applications on your desktop, I feel like you are an early adopter of many, many things.[00:49:12] Simon: I had an interesting experience with that over the past year. Six months ago, I almost completely lost interest. And the reason is that six months ago, the best local models you could run, There was no point in using them at all, because the best hosted models were so much better.[00:49:26] Simon: Like, there was no point at which I'd choose to run a model on my laptop if I had API access to Cloud 3. 5 SONNET. They just, they weren't even comparable. And that changed, basically, in the past three months, as the local models had this step changing capability, where now I can run some of these local models, and they're not as good as Cloud 3.[00:49:45] Simon: 5 SONNET, but they're not so far away that It's not worth me even using them. The other, the, the, the, the continuing problem is I've only got 64 gigabytes of RAM, and if you run, like, LLAMA370B, it's not going to work. Most of my RAM is gone. So now I have to shut down my Firefox tabs [00:50:00] and, and my Chrome and my VS Code windows in order to run it.[00:50:03] Simon: But it's got me interested again. Like, like the, the efficiency improvements are such that now, if you were to like stick me on a desert island with my laptop, I'd be very productive using those local models. And that's, that's pretty exciting. And if those trends continue, and also, like, I think my next laptop, if when I buy one is going to have twice the amount of RAM, At which point, maybe I can run the, almost the top tier, like open weights models and still be able to use it as a computer as well.[00:50:32] Simon: NVIDIA just announced their 3, 000 128 gigabyte monstrosity. That's pretty good price. You know, that's that's, if you're going to buy it,[00:50:42] swyx (2): custom OS and all.[00:50:46] Simon: If I get a job, if I, if, if, if I have enough of an income that I can justify blowing $3,000 on it, then yes.[00:50:52] swyx (2): Okay, let's do a GoFundMe to get Simon one it.[00:50:54] swyx (2): Come on. You know, you can get a job anytime you want. Is this, this is just purely discretionary .[00:50:59] Simon: I want, [00:51:00] I want a job that pays me to do exactly what I'm doing already and doesn't tell me what else to do. That's, thats the challenge.[00:51:06] swyx (2): I think Ethan Molik does pretty well. Whatever, whatever it is he's doing.[00:51:11] swyx (2): But yeah, basically I was trying to bring in also, you know, not just local models, but Apple intelligence is on every Mac machine. You're, you're, you seem skeptical. It's rubbish.[00:51:21] Simon: Apple intelligence is so bad. It's like, it does one thing well.[00:51:25] swyx (2): Oh yeah, what's that? It summarizes notifications. And sometimes it's humorous.[00:51:29] Brian: Are you sure it does that well? And also, by the way, the other, again, from a sort of a normie point of view. There's no indication from Apple of when to use it. Like, everybody upgrades their thing and it's like, okay, now you have Apple Intelligence, and you never know when to use it ever again.[00:51:47] swyx (2): Oh, yeah, you consult the Apple docs, which is MKBHD.[00:51:49] swyx (2): The[00:51:51] Simon: one thing, the one thing I'll say about Apple Intelligence is, One of the reasons it's so disappointing is that the models are just weak, but now, like, Llama 3b [00:52:00] is Such a good model in a 2 gigabyte file I think give Apple six months and hopefully they'll catch up to the state of the art on the small models And then maybe it'll start being a lot more interesting.[00:52:10] swyx (2): Yeah. Anyway, I like This was year one And and you know just like our first year of iPhone maybe maybe not that much of a hit and then year three They had the App Store so Hey I would say give it some time, and you know, I think Chrome also shipping Gemini Nano I think this year in Chrome, which means that every app, every web app will have for free access to a local model that just ships in the browser, which is kind of interesting.[00:52:38] swyx (2): And then I, I think I also wanted to just open the floor for any, like, you know, any of us what are the apps that, you know, AI applications that we've adopted that have, that we really recommend because these are all, you know, apps that are running on our browser that like, or apps that are running locally that we should be, that, that other people should be trying.[00:52:55] swyx (2): Right? Like, I, I feel like that's, that's one always one thing that is helpful at the start of the [00:53:00] year.[00:53:00] Simon: Okay. So for running local models. My top picks, firstly, on the iPhone, there's this thing called MLC Chat, which works, and it's easy to install, and it runs Llama 3B, and it's so much fun. Like, it's not necessarily a capable enough novel that I use it for real things, but my party trick right now is I get my phone to write a Netflix Christmas movie plot outline where, like, a bunch of Jeweller falls in love with the King of Sweden or whatever.[00:53:25] Simon: And it does a good job and it comes up with pun names for the movies. And that's, that's deeply entertaining. On my laptop, most recently, I've been getting heavy into, into Olama because the Olama team are very, very good at finding the good models and patching them up and making them work well. It gives you an API.[00:53:42] Simon: My little LLM command line tool that has a plugin that talks to Olama, which works really well. So that's my, my Olama is. I think the easiest on ramp to to running models locally, if you want a nice user interface, LMStudio is, I think, the best user interface [00:54:00] thing at that. It's not open source. It's good.[00:54:02] Simon: It's worth playing with. The other one that I've been trying with recently, there's a thing called, what's it called? Open web UI or something. Yeah. The UI is fantastic. It, if you've got Olama running and you fire this thing up, it spots Olama and it gives you an interface onto your Olama models. And t

Ep 291 How can AI revolutionize content creation by 2025? Kieran dives into the essential AI tools that will define the future landscape of digital marketing and content creation. Learn more about leveraging AI for email optimization and tailored audience engagement, the significance of personality-led content amid advancing AI, and which AI tools like Delphi, and HeyGen will be indispensable for video content creation and professional image generation in 2025. Mentions Delphi https://www.delphi.ai/ HeyGen https://www.heygen.com/ Argil https://www.argil.ai/ Opus https://www.opus.pro/ Replit https://replit.com/ NotebookLM https://notebooklm.google/ Napkin https://www.napkin.ai/ Get our guide to build your own Custom GPT: https://clickhubspot.com/customgpt We're creating our next round of content and want to ensure it tackles the challenges you're facing at work or in your business. To understand your biggest challenges we've put together a survey and we'd love to hear from you! https://bit.ly/matg-research Resource [Free] Steal our favorite AI Prompts featured on the show! Grab them here: https://clickhubspot.com/aip We're on Social Media! Follow us for everyday marketing wisdom straight to your feed YouTube: ​​https://www.youtube.com/channel/UCGtXqPiNV8YC0GMUzY-EUFg  Twitter: https://twitter.com/matgpod  TikTok: https://www.tiktok.com/@matgpod  Join our community https://landing.connect.com/matg Thank you for tuning into Marketing Against The Grain! Don't forget to hit subscribe and follow us on Apple Podcasts (so you never miss an episode)! https://podcasts.apple.com/us/podcast/marketing-against-the-grain/id1616700934   If you love this show, please leave us a 5-Star Review https://link.chtbl.com/h9_sjBKH and share your favorite episodes with friends. We really appreciate your support. Host Links: Kipp Bodnar, https://twitter.com/kippbodnar   Kieran Flanagan, https://twitter.com/searchbrat  ‘Marketing Against The Grain' is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Produced by Darren Clarke.

Send Everyday AI and Jordan a text messageJust in the past 3 weeks, we've seen enough AI releases for like 3 years. But what AI features and tech tools are actually worth using? We recap and rank the top AI features and tools of 2024. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on AIUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:1. Top AI Tools and Features Discussion2. AI Tools of the Year & Rankings3. In-depth Discussion of Specific Tools4. AI Industry OverviewTimestamps:00:00 Network with tech professionals; explore AI tools.10:16 Share show for AI tools honorable mention.12:32 Siri uses ChatGPT for complex queries.18:09 Inline AI enhances collaborative document editing efficiently.23:23 ChatGPT search tool flawed after limited beta.31:06 Cursor went viral as first user-friendly AI.34:52 Google excelled with Gemini 2.0 updates.37:56 Google deep research: fast, comprehensive answers engine.46:17 Use Microsoft 365 Copilot Studio for automation.50:03 Microsoft Copilot Vision simplifies travel bookings. Limited.55:32 Iterative prompting guides advanced language models.01:02:47 Gemini app enables video and voice interaction.01:07:42 Google's Veo AI video tool released, concerns remain.01:13:52 Notebook LM prioritizes trust and transparency in AI.01:15:49 Top AI tools and features 2024 list.Keywords:Jordan Wilson, live stream, AI tools ranking, people's choice award, Midjourney v6.1, Microsoft Copilot Studio, Copilot Vision, Notebook LM, Sora, Veo 2, Zapier Agents, AI tool tiers, podcast, AI developments, generative AI, AI tool selection, AI tool ratings, AI 2024, audience participation, Claude's Artifacts, Claude Computer Use, Cursor AI, 11 Labs conversational agents, Google Gemini 2.0, Google Deep Research, HeyGen's new v3 avatars, AI in documents, Canva's Magic Studio, Chat GPT's new search, OpenAI's 01 Pro. Get more out of ChatGPT by learning our PPP method in this live, interactive and free training! Sign up now: https://youreverydayai.com/ppp-registration/

Applications for the 2025 AI Engineer Summit are up, and you can save the date for AIE Singapore in April and AIE World's Fair 2025 in June.Happy new year, and thanks for 100 great episodes! Please let us know what you want to see/hear for the next 100!Full YouTube Episode with Slides/ChartsLike and subscribe and hit that bell to get notifs!Timestamps* 00:00 Welcome to the 100th Episode!* 00:19 Reflecting on the Journey* 00:47 AI Engineering: The Rise and Impact* 03:15 Latent Space Live and AI Conferences* 09:44 The Competitive AI Landscape* 21:45 Synthetic Data and Future Trends* 35:53 Creative Writing with AI* 36:12 Legal and Ethical Issues in AI* 38:18 The Data War: GPU Poor vs. GPU Rich* 39:12 The Rise of GPU Ultra Rich* 40:47 Emerging Trends in AI Models* 45:31 The Multi-Modality War* 01:05:31 The Future of AI Benchmarks* 01:13:17 Pionote and Frontier Models* 01:13:47 Niche Models and Base Models* 01:14:30 State Space Models and RWKB* 01:15:48 Inference Race and Price Wars* 01:22:16 Major AI Themes of the Year* 01:22:48 AI Rewind: January to March* 01:26:42 AI Rewind: April to June* 01:33:12 AI Rewind: July to September* 01:34:59 AI Rewind: October to December* 01:39:53 Year-End Reflections and PredictionsTranscript[00:00:00] Welcome to the 100th Episode![00:00:00] Alessio: Hey everyone, welcome to the Latent Space Podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co host Swyx for the 100th time today.[00:00:12] swyx: Yay, um, and we're so glad that, yeah, you know, everyone has, uh, followed us in this journey. How do you feel about it? 100 episodes.[00:00:19] Alessio: Yeah, I know.[00:00:19] Reflecting on the Journey[00:00:19] Alessio: Almost two years that we've been doing this. We've had four different studios. Uh, we've had a lot of changes. You know, we used to do this lightning round. When we first started that we didn't like, and we tried to change the question. The answer[00:00:32] swyx: was cursor and perplexity.[00:00:34] Alessio: Yeah, I love mid journey. It's like, do you really not like anything else?[00:00:38] Alessio: Like what's, what's the unique thing? And I think, yeah, we, we've also had a lot more research driven content. You know, we had like 3DAO, we had, you know. Jeremy Howard, we had more folks like that.[00:00:47] AI Engineering: The Rise and Impact[00:00:47] Alessio: I think we want to do more of that too in the new year, like having, uh, some of the Gemini folks, both on the research and the applied side.[00:00:54] Alessio: Yeah, but it's been a ton of fun. I think we both started, I wouldn't say as a joke, we were kind of like, Oh, we [00:01:00] should do a podcast. And I think we kind of caught the right wave, obviously. And I think your rise of the AI engineer posts just kind of get people. Sombra to congregate, and then the AI engineer summit.[00:01:11] Alessio: And that's why when I look at our growth chart, it's kind of like a proxy for like the AI engineering industry as a whole, which is almost like, like, even if we don't do that much, we keep growing just because there's so many more AI engineers. So did you expect that growth or did you expect that would take longer for like the AI engineer thing to kind of like become, you know, everybody talks about it today.[00:01:32] swyx: So, the sign of that, that we have won is that Gartner puts it at the top of the hype curve right now. So Gartner has called the peak in AI engineering. I did not expect, um, to what level. I knew that I was correct when I called it because I did like two months of work going into that. But I didn't know, You know, how quickly it could happen, and obviously there's a chance that I could be wrong.[00:01:52] swyx: But I think, like, most people have come around to that concept. Hacker News hates it, which is a good sign. But there's enough people that have defined it, you know, GitHub, when [00:02:00] they launched GitHub Models, which is the Hugging Face clone, they put AI engineers in the banner, like, above the fold, like, in big So I think it's like kind of arrived as a meaningful and useful definition.[00:02:12] swyx: I think people are trying to figure out where the boundaries are. I think that was a lot of the quote unquote drama that happens behind the scenes at the World's Fair in June. Because I think there's a lot of doubt or questions about where ML engineering stops and AI engineering starts. That's a useful debate to be had.[00:02:29] swyx: In some sense, I actually anticipated that as well. So I intentionally did not. Put a firm definition there because most of the successful definitions are necessarily underspecified and it's actually useful to have different perspectives and you don't have to specify everything from the outset.[00:02:45] Alessio: Yeah, I was at um, AWS reInvent and the line to get into like the AI engineering talk, so to speak, which is, you know, applied AI and whatnot was like, there are like hundreds of people just in line to go in.[00:02:56] Alessio: I think that's kind of what enabled me. People, right? Which is what [00:03:00] you kind of talked about. It's like, Hey, look, you don't actually need a PhD, just, yeah, just use the model. And then maybe we'll talk about some of the blind spots that you get as an engineer with the earlier posts that we also had on on the sub stack.[00:03:11] Alessio: But yeah, it's been a heck of a heck of a two years.[00:03:14] swyx: Yeah.[00:03:15] Latent Space Live and AI Conferences[00:03:15] swyx: You know, I was, I was trying to view the conference as like, so NeurIPS is I think like 16, 17, 000 people. And the Latent Space Live event that we held there was 950 signups. I think. The AI world, the ML world is still very much research heavy. And that's as it should be because ML is very much in a research phase.[00:03:34] swyx: But as we move this entire field into production, I think that ratio inverts into becoming more engineering heavy. So at least I think engineering should be on the same level, even if it's never as prestigious, like it'll always be low status because at the end of the day, you're manipulating APIs or whatever.[00:03:51] swyx: But Yeah, wrapping GPTs, but there's going to be an increasing stack and an art to doing these, these things well. And I, you know, I [00:04:00] think that's what we're focusing on for the podcast, the conference and basically everything I do seems to make sense. And I think we'll, we'll talk about the trends here that apply.[00:04:09] swyx: It's, it's just very strange. So, like, there's a mix of, like, keeping on top of research while not being a researcher and then putting that research into production. So, like, people always ask me, like, why are you covering Neuralibs? Like, this is a ML research conference and I'm like, well, yeah, I mean, we're not going to, to like, understand everything Or reproduce every single paper, but the stuff that is being found here is going to make it through into production at some point, you hope.[00:04:32] swyx: And then actually like when I talk to the researchers, they actually get very excited because they're like, oh, you guys are actually caring about how this goes into production and that's what they really really want. The measure of success is previously just peer review, right? Getting 7s and 8s on their um, Academic review conferences and stuff like citations is one metric, but money is a better metric.[00:04:51] Alessio: Money is a better metric. Yeah, and there were about 2200 people on the live stream or something like that. Yeah, yeah. Hundred on the live stream. So [00:05:00] I try my best to moderate, but it was a lot spicier in person with Jonathan and, and Dylan. Yeah, that it was in the chat on YouTube.[00:05:06] swyx: I would say that I actually also created.[00:05:09] swyx: Layen Space Live in order to address flaws that are perceived in academic conferences. This is not NeurIPS specific, it's ICML, NeurIPS. Basically, it's very sort of oriented towards the PhD student, uh, market, job market, right? Like literally all, basically everyone's there to advertise their research and skills and get jobs.[00:05:28] swyx: And then obviously all the, the companies go there to hire them. And I think that's great for the individual researchers, but for people going there to get info is not great because you have to read between the lines, bring a ton of context in order to understand every single paper. So what is missing is effectively what I ended up doing, which is domain by domain, go through and recap the best of the year.[00:05:48] swyx: Survey the field. And there are, like NeurIPS had a, uh, I think ICML had a like a position paper track, NeurIPS added a benchmarks, uh, datasets track. These are ways in which to address that [00:06:00] issue. Uh, there's always workshops as well. Every, every conference has, you know, a last day of workshops and stuff that provide more of an overview.[00:06:06] swyx: But they're not specifically prompted to do so. And I think really, uh, Organizing a conference is just about getting good speakers and giving them the correct prompts. And then they will just go and do that thing and they do a very good job of it. So I think Sarah did a fantastic job with the startups prompt.[00:06:21] swyx: I can't list everybody, but we did best of 2024 in startups, vision, open models. Post transformers, synthetic data, small models, and agents. And then the last one was the, uh, and then we also did a quick one on reasoning with Nathan Lambert. And then the last one, obviously, was the debate that people were very hyped about.[00:06:39] swyx: It was very awkward. And I'm really, really thankful for John Franco, basically, who stepped up to challenge Dylan. Because Dylan was like, yeah, I'll do it. But He was pro scaling. And I think everyone who is like in AI is pro scaling, right? So you need somebody who's ready to publicly say, no, we've hit a wall.[00:06:57] swyx: So that means you're saying Sam Altman's wrong. [00:07:00] You're saying, um, you know, everyone else is wrong. It helps that this was the day before Ilya went on, went up on stage and then said pre training has hit a wall. And data has hit a wall. So actually Jonathan ended up winning, and then Ilya supported that statement, and then Noam Brown on the last day further supported that statement as well.[00:07:17] swyx: So it's kind of interesting that I think the consensus kind of going in was that we're not done scaling, like you should believe in a better lesson. And then, four straight days in a row, you had Sepp Hochreiter, who is the creator of the LSTM, along with everyone's favorite OG in AI, which is Juergen Schmidhuber.[00:07:34] swyx: He said that, um, we're pre trading inside a wall, or like, we've run into a different kind of wall. And then we have, you know John Frankel, Ilya, and then Noam Brown are all saying variations of the same thing, that we have hit some kind of wall in the status quo of what pre trained, scaling large pre trained models has looked like, and we need a new thing.[00:07:54] swyx: And obviously the new thing for people is some make, either people are calling it inference time compute or test time [00:08:00] compute. I think the collective terminology has been inference time, and I think that makes sense because test time, calling it test, meaning, has a very pre trained bias, meaning that the only reason for running inference at all is to test your model.[00:08:11] swyx: That is not true. Right. Yeah. So, so, I quite agree that. OpenAI seems to have adopted, or the community seems to have adopted this terminology of ITC instead of TTC. And that, that makes a lot of sense because like now we care about inference, even right down to compute optimality. Like I actually interviewed this author who recovered or reviewed the Chinchilla paper.[00:08:31] swyx: Chinchilla paper is compute optimal training, but what is not stated in there is it's pre trained compute optimal training. And once you start caring about inference, compute optimal training, you have a different scaling law. And in a way that we did not know last year.[00:08:45] Alessio: I wonder, because John is, he's also on the side of attention is all you need.[00:08:49] Alessio: Like he had the bet with Sasha. So I'm curious, like he doesn't believe in scaling, but he thinks the transformer, I wonder if he's still. So, so,[00:08:56] swyx: so he, obviously everything is nuanced and you know, I told him to play a character [00:09:00] for this debate, right? So he actually does. Yeah. He still, he still believes that we can scale more.[00:09:04] swyx: Uh, he just assumed the character to be very game for, for playing this debate. So even more kudos to him that he assumed a position that he didn't believe in and still won the debate.[00:09:16] Alessio: Get rekt, Dylan. Um, do you just want to quickly run through some of these things? Like, uh, Sarah's presentation, just the highlights.[00:09:24] swyx: Yeah, we can't go through everyone's slides, but I pulled out some things as a factor of, like, stuff that we were going to talk about. And we'll[00:09:30] Alessio: publish[00:09:31] swyx: the rest. Yeah, we'll publish on this feed the best of 2024 in those domains. And hopefully people can benefit from the work that our speakers have done.[00:09:39] swyx: But I think it's, uh, these are just good slides. And I've been, I've been looking for a sort of end of year recaps from, from people.[00:09:44] The Competitive AI Landscape[00:09:44] swyx: The field has progressed a lot. You know, I think the max ELO in 2023 on LMSys used to be 1200 for LMSys ELOs. And now everyone is at least at, uh, 1275 in their ELOs, and this is across Gemini, Chadjibuti, [00:10:00] Grok, O1.[00:10:01] swyx: ai, which with their E Large model, and Enthopic, of course. It's a very, very competitive race. There are multiple Frontier labs all racing, but there is a clear tier zero Frontier. And then there's like a tier one. It's like, I wish I had everything else. Tier zero is extremely competitive. It's effectively now three horse race between Gemini, uh, Anthropic and OpenAI.[00:10:21] swyx: I would say that people are still holding out a candle for XAI. XAI, I think, for some reason, because their API was very slow to roll out, is not included in these metrics. So it's actually quite hard to put on there. As someone who also does charts, XAI is continually snubbed because they don't work well with the benchmarking people.[00:10:42] swyx: Yeah, yeah, yeah. It's a little trivia for why XAI always gets ignored. The other thing is market share. So these are slides from Sarah. We have it up on the screen. It has gone from very heavily open AI. So we have some numbers and estimates. These are from RAMP. Estimates of open AI market share in [00:11:00] December 2023.[00:11:01] swyx: And this is basically, what is it, GPT being 95 percent of production traffic. And I think if you correlate that with stuff that we asked. Harrison Chase on the LangChain episode, it was true. And then CLAUD 3 launched mid middle of this year. I think CLAUD 3 launched in March, CLAUD 3. 5 Sonnet was in June ish.[00:11:23] swyx: And you can start seeing the market share shift towards opening, uh, towards that topic, uh, very, very aggressively. The more recent one is Gemini. So if I scroll down a little bit, this is an even more recent dataset. So RAM's dataset ends in September 2 2. 2024. Gemini has basically launched a price war at the low end, uh, with Gemini Flash, uh, being basically free for personal use.[00:11:44] swyx: Like, I think people don't understand the free tier. It's something like a billion tokens per day. Unless you're trying to abuse it, you cannot really exhaust your free tier on Gemini. They're really trying to get you to use it. They know they're in like third place, um, fourth place, depending how you, how you count.[00:11:58] swyx: And so they're going after [00:12:00] the Lower tier first, and then, you know, maybe the upper tier later, but yeah, Gemini Flash, according to OpenRouter, is now 50 percent of their OpenRouter requests. Obviously, these are the small requests. These are small, cheap requests that are mathematically going to be more.[00:12:15] swyx: The smart ones obviously are still going to OpenAI. But, you know, it's a very, very big shift in the market. Like basically 2023, 2022, To going into 2024 opening has gone from nine five market share to Yeah. Reasonably somewhere between 50 to 75 market share.[00:12:29] Alessio: Yeah. I'm really curious how ramped does the attribution to the model?[00:12:32] Alessio: If it's API, because I think it's all credit card spin. . Well, but it's all, the credit card doesn't say maybe. Maybe the, maybe when they do expenses, they upload the PDF, but yeah, the, the German I think makes sense. I think that was one of my main 2024 takeaways that like. The best small model companies are the large labs, which is not something I would have thought that the open source kind of like long tail would be like the small model.[00:12:53] swyx: Yeah, different sizes of small models we're talking about here, right? Like so small model here for Gemini is AB, [00:13:00] right? Uh, mini. We don't know what the small model size is, but yeah, it's probably in the double digits or maybe single digits, but probably double digits. The open source community has kind of focused on the one to three B size.[00:13:11] swyx: Mm-hmm . Yeah. Maybe[00:13:12] swyx: zero, maybe 0.5 B uh, that's moon dream and that is small for you then, then that's great. It makes sense that we, we have a range for small now, which is like, may, maybe one to five B. Yeah. I'll even put that at, at, at the high end. And so this includes Gemma from Gemini as well. But also includes the Apple Foundation models, which I think Apple Foundation is 3B.[00:13:32] Alessio: Yeah. No, that's great. I mean, I think in the start small just meant cheap. I think today small is actually a more nuanced discussion, you know, that people weren't really having before.[00:13:43] swyx: Yeah, we can keep going. This is a slide that I smiley disagree with Sarah. She's pointing to the scale SEAL leaderboard. I think the Researchers that I talked with at NeurIPS were kind of positive on this because basically you need private test [00:14:00] sets to prevent contamination.[00:14:02] swyx: And Scale is one of maybe three or four people this year that has really made an effort in doing a credible private test set leaderboard. Llama405B does well compared to Gemini and GPT 40. And I think that's good. I would say that. You know, it's good to have an open model that is that big, that does well on those metrics.[00:14:23] swyx: But anyone putting 405B in production will tell you, if you scroll down a little bit to the artificial analysis numbers, that it is very slow and very expensive to infer. Um, it doesn't even fit on like one node. of, uh, of H100s. Cerebras will be happy to tell you they can serve 4 or 5B on their super large chips.[00:14:42] swyx: But, um, you know, if you need to do anything custom to it, you're still kind of constrained. So, is 4 or 5B really that relevant? Like, I think most people are basically saying that they only use 4 or 5B as a teacher model to distill down to something. Even Meta is doing it. So with Lama 3. [00:15:00] 3 launched, they only launched the 70B because they use 4 or 5B to distill the 70B.[00:15:03] swyx: So I don't know if like open source is keeping up. I think they're the, the open source industrial complex is very invested in telling you that the, if the gap is narrowing, I kind of disagree. I think that the gap is widening with O1. I think there are very, very smart people trying to narrow that gap and they should.[00:15:22] swyx: I really wish them success, but you cannot use a chart that is nearing 100 in your saturation chart. And look, the distance between open source and closed source is narrowing. Of course it's going to narrow because you're near 100. This is stupid. But in metrics that matter, is open source narrowing?[00:15:38] swyx: Probably not for O1 for a while. And it's really up to the open source guys to figure out if they can match O1 or not.[00:15:46] Alessio: I think inference time compute is bad for open source just because, you know, Doc can donate the flops at training time, but he cannot donate the flops at inference time. So it's really hard to like actually keep up on that axis.[00:15:59] Alessio: Big, big business [00:16:00] model shift. So I don't know what that means for the GPU clouds. I don't know what that means for the hyperscalers, but obviously the big labs have a lot of advantage. Because, like, it's not a static artifact that you're putting the compute in. You're kind of doing that still, but then you're putting a lot of computed inference too.[00:16:17] swyx: Yeah, yeah, yeah. Um, I mean, Llama4 will be reasoning oriented. We talked with Thomas Shalom. Um, kudos for getting that episode together. That was really nice. Good, well timed. Actually, I connected with the AI meta guy, uh, at NeurIPS, and, um, yeah, we're going to coordinate something for Llama4. Yeah, yeah,[00:16:32] Alessio: and our friend, yeah.[00:16:33] Alessio: Clara Shi just joined to lead the business agent side. So I'm sure we'll have her on in the new year.[00:16:39] swyx: Yeah. So, um, my comment on, on the business model shift, this is super interesting. Apparently it is wide knowledge that OpenAI wanted more than 6. 6 billion dollars for their fundraise. They wanted to raise, you know, higher, and they did not.[00:16:51] swyx: And what that means is basically like, it's very convenient that we're not getting GPT 5, which would have been a larger pre train. We should have a lot of upfront money. And [00:17:00] instead we're, we're converting fixed costs into variable costs, right. And passing it on effectively to the customer. And it's so much easier to take margin there because you can directly attribute it to like, Oh, you're using this more.[00:17:12] swyx: Therefore you, you pay more of the cost and I'll just slap a margin in there. So like that lets you control your growth margin and like tie your. Your spend, or your sort of inference spend, accordingly. And it's just really interesting to, that this change in the sort of inference paradigm has arrived exactly at the same time that the funding environment for pre training is effectively drying up, kind of.[00:17:36] swyx: I feel like maybe the VCs are very in tune with research anyway, so like, they would have noticed this, but, um, it's just interesting.[00:17:43] Alessio: Yeah, and I was looking back at our yearly recap of last year. Yeah. And the big thing was like the mixed trial price fights, you know, and I think now it's almost like there's nowhere to go, like, you know, Gemini Flash is like basically giving it away for free.[00:17:55] Alessio: So I think this is a good way for the labs to generate more revenue and pass down [00:18:00] some of the compute to the customer. I think they're going to[00:18:02] swyx: keep going. I think that 2, will come.[00:18:05] Alessio: Yeah, I know. Totally. I mean, next year, the first thing I'm doing is signing up for Devin. Signing up for the pro chat GBT.[00:18:12] Alessio: Just to try. I just want to see what does it look like to spend a thousand dollars a month on AI?[00:18:17] swyx: Yes. Yes. I think if your, if your, your job is a, at least AI content creator or VC or, you know, someone who, whose job it is to stay on, stay on top of things, you should already be spending like a thousand dollars a month on, on stuff.[00:18:28] swyx: And then obviously easy to spend, hard to use. You have to actually use. The good thing is that actually Google lets you do a lot of stuff for free now. So like deep research. That they just launched. Uses a ton of inference and it's, it's free while it's in preview.[00:18:45] Alessio: Yeah. They need to put that in Lindy.[00:18:47] Alessio: I've been using Lindy lately. I've been a built a bunch of things once we had flow because I liked the new thing. It's pretty good. I even did a phone call assistant. Um, yeah, they just launched Lindy voice. Yeah, I think once [00:19:00] they get advanced voice mode like capability today, still like speech to text, you can kind of tell.[00:19:06] Alessio: Um, but it's good for like reservations and things like that. So I have a meeting prepper thing. And so[00:19:13] swyx: it's good. Okay. I feel like we've, we've covered a lot of stuff. Uh, I, yeah, I, you know, I think We will go over the individual, uh, talks in a separate episode. Uh, I don't want to take too much time with, uh, this stuff, but that suffice to say that there is a lot of progress in each field.[00:19:28] swyx: Uh, we covered vision. Basically this is all like the audience voting for what they wanted. And then I just invited the best people I could find in each audience, especially agents. Um, Graham, who I talked to at ICML in Vienna, he is currently still number one. It's very hard to stay on top of SweetBench.[00:19:45] swyx: OpenHand is currently still number one. switchbench full, which is the hardest one. He had very good thoughts on agents, which I, which I'll highlight for people. Everyone is saying 2025 is the year of agents, just like they said last year. And, uh, but he had [00:20:00] thoughts on like eight parts of what are the frontier problems to solve in agents.[00:20:03] swyx: And so I'll highlight that talk as well.[00:20:05] Alessio: Yeah. The number six, which is the Hacken agents learn more about the environment, has been a Super interesting to us as well, just to think through, because, yeah, how do you put an agent in an enterprise where most things in an enterprise have never been public, you know, a lot of the tooling, like the code bases and things like that.[00:20:23] Alessio: So, yeah, there's not indexing and reg. Well, yeah, but it's more like. You can't really rag things that are not documented. But people know them based on how they've been doing it. You know, so I think there's almost this like, you know, Oh, institutional knowledge. Yeah, the boring word is kind of like a business process extraction.[00:20:38] Alessio: Yeah yeah, I see. It's like, how do you actually understand how these things are done? I see. Um, and I think today the, the problem is that, Yeah, the agents are, that most people are building are good at following instruction, but are not as good as like extracting them from you. Um, so I think that will be a big unlock just to touch quickly on the Jeff Dean thing.[00:20:55] Alessio: I thought it was pretty, I mean, we'll link it in the, in the things, but. I think the main [00:21:00] focus was like, how do you use ML to optimize the systems instead of just focusing on ML to do something else? Yeah, I think speculative decoding, we had, you know, Eugene from RWKB on the podcast before, like he's doing a lot of that with Fetterless AI.[00:21:12] swyx: Everyone is. I would say it's the norm. I'm a little bit uncomfortable with how much it costs, because it does use more of the GPU per call. But because everyone is so keen on fast inference, then yeah, makes sense.[00:21:24] Alessio: Exactly. Um, yeah, but we'll link that. Obviously Jeff is great.[00:21:30] swyx: Jeff is, Jeff's talk was more, it wasn't focused on Gemini.[00:21:33] swyx: I think people got the wrong impression from my tweet. It's more about how Google approaches ML and uses ML to design systems and then systems feedback into ML. And I think this ties in with Lubna's talk.[00:21:45] Synthetic Data and Future Trends[00:21:45] swyx: on synthetic data where it's basically the story of bootstrapping of humans and AI in AI research or AI in production.[00:21:53] swyx: So her talk was on synthetic data, where like how much synthetic data has grown in 2024 in the pre training side, the post training side, [00:22:00] and the eval side. And I think Jeff then also extended it basically to chips, uh, to chip design. So he'd spend a lot of time talking about alpha chip. And most of us in the audience are like, we're not working on hardware, man.[00:22:11] swyx: Like you guys are great. TPU is great. Okay. We'll buy TPUs.[00:22:14] Alessio: And then there was the earlier talk. Yeah. But, and then we have, uh, I don't know if we're calling them essays. What are we calling these? But[00:22:23] swyx: for me, it's just like bonus for late in space supporters, because I feel like they haven't been getting anything.[00:22:29] swyx: And then I wanted a more high frequency way to write stuff. Like that one I wrote in an afternoon. I think basically we now have an answer to what Ilya saw. It's one year since. The blip. And we know what he saw in 2014. We know what he saw in 2024. We think we know what he sees in 2024. He gave some hints and then we have vague indications of what he saw in 2023.[00:22:54] swyx: So that was the Oh, and then 2016 as well, because of this lawsuit with Elon, OpenAI [00:23:00] is publishing emails from Sam's, like, his personal text messages to Siobhan, Zelis, or whatever. So, like, we have emails from Ilya saying, this is what we're seeing in OpenAI, and this is why we need to scale up GPUs. And I think it's very prescient in 2016 to write that.[00:23:16] swyx: And so, like, it is exactly, like, basically his insights. It's him and Greg, basically just kind of driving the scaling up of OpenAI, while they're still playing Dota. They're like, no, like, we see the path here.[00:23:30] Alessio: Yeah, and it's funny, yeah, they even mention, you know, we can only train on 1v1 Dota. We need to train on 5v5, and that takes too many GPUs.[00:23:37] Alessio: Yeah,[00:23:37] swyx: and at least for me, I can speak for myself, like, I didn't see the path from Dota to where we are today. I think even, maybe if you ask them, like, they wouldn't necessarily draw a straight line. Yeah,[00:23:47] Alessio: no, definitely. But I think like that was like the whole idea of almost like the RL and we talked about this with Nathan on his podcast.[00:23:55] Alessio: It's like with RL, you can get very good at specific things, but then you can't really like generalize as much. And I [00:24:00] think the language models are like the opposite, which is like, you're going to throw all this data at them and scale them up, but then you really need to drive them home on a specific task later on.[00:24:08] Alessio: And we'll talk about the open AI reinforcement, fine tuning, um, announcement too, and all of that. But yeah, I think like scale is all you need. That's kind of what Elia will be remembered for. And I think just maybe to clarify on like the pre training is over thing that people love to tweet. I think the point of the talk was like everybody, we're scaling these chips, we're scaling the compute, but like the second ingredient which is data is not scaling at the same rate.[00:24:35] Alessio: So it's not necessarily pre training is over. It's kind of like What got us here won't get us there. In his email, he predicted like 10x growth every two years or something like that. And I think maybe now it's like, you know, you can 10x the chips again, but[00:24:49] swyx: I think it's 10x per year. Was it? I don't know.[00:24:52] Alessio: Exactly. And Moore's law is like 2x. So it's like, you know, much faster than that. And yeah, I like the fossil fuel of AI [00:25:00] analogy. It's kind of like, you know, the little background tokens thing. So the OpenAI reinforcement fine tuning is basically like, instead of fine tuning on data, you fine tune on a reward model.[00:25:09] Alessio: So it's basically like, instead of being data driven, it's like task driven. And I think people have tasks to do, they don't really have a lot of data. So I'm curious to see how that changes, how many people fine tune, because I think this is what people run into. It's like, Oh, you can fine tune llama. And it's like, okay, where do I get the data?[00:25:27] Alessio: To fine tune it on, you know, so it's great that we're moving the thing. And then I really like he had this chart where like, you know, the brain mass and the body mass thing is basically like mammals that scaled linearly by brain and body size, and then humans kind of like broke off the slope. So it's almost like maybe the mammal slope is like the pre training slope.[00:25:46] Alessio: And then the post training slope is like the, the human one.[00:25:49] swyx: Yeah. I wonder what the. I mean, we'll know in 10 years, but I wonder what the y axis is for, for Ilya's SSI. We'll try to get them on.[00:25:57] Alessio: Ilya, if you're listening, you're [00:26:00] welcome here. Yeah, and then he had, you know, what comes next, like agent, synthetic data, inference, compute, I thought all of that was like that.[00:26:05] Alessio: I don't[00:26:05] swyx: think he was dropping any alpha there. Yeah, yeah, yeah.[00:26:07] Alessio: Yeah. Any other new reps? Highlights?[00:26:10] swyx: I think that there was comparatively a lot more work. Oh, by the way, I need to plug that, uh, my friend Yi made this, like, little nice paper. Yeah, that was really[00:26:20] swyx: nice.[00:26:20] swyx: Uh, of, uh, of, like, all the, he's, she called it must read papers of 2024.[00:26:26] swyx: So I laid out some of these at NeurIPS, and it was just gone. Like, everyone just picked it up. Because people are dying for, like, little guidance and visualizations And so, uh, I thought it was really super nice that we got there.[00:26:38] Alessio: Should we do a late in space book for each year? Uh, I thought about it. For each year we should.[00:26:42] Alessio: Coffee table book. Yeah. Yeah. Okay. Put it in the will. Hi, Will. By the way, we haven't introduced you. He's our new, you know, general organist, Jamie. You need to[00:26:52] swyx: pull up more things. One thing I saw that, uh, Okay, one fun one, and then one [00:27:00] more general one. So the fun one is this paper on agent collusion. This is a paper on steganography.[00:27:06] swyx: This is secret collusion among AI agents, multi agent deception via steganography. I tried to go to NeurIPS in order to find these kinds of papers because the real reason Like NeurIPS this year has a lottery system. A lot of people actually even go and don't buy tickets because they just go and attend the side events.[00:27:22] swyx: And then also the people who go and end up crowding around the most popular papers, which you already know and already read them before you showed up to NeurIPS. So the only reason you go there is to talk to the paper authors, but there's like something like 10, 000 other. All these papers out there that, you know, are just people's work that they, that they did on the air and they failed to get attention for one reason or another.[00:27:42] swyx: And this was one of them. Uh, it was like all the way at the back. And this is a deep mind paper that actually focuses on collusion between AI agents, uh, by hiding messages in the text that they generate. Uh, so that's what steganography is. So a very simple example would be the first letter of every word.[00:27:57] swyx: If you Pick that out, you know, and the code sends a [00:28:00] different message than that. But something I've always emphasized is to LLMs, we read left to right. LLMs can read up, down, sideways, you know, in random character order. And it's the same to them as it is to us. So if we were ever to get You know, self motivated, underlined LLMs that we're trying to collaborate to take over the planet.[00:28:19] swyx: This would be how they do it. They spread messages among us in the messages that we generate. And he developed a scaling law for that. So he marked, I'm showing it on screen right now, the emergence of this phenomenon. Basically, for example, for Cypher encoding, GPT 2, Lama 2, mixed trial, GPT 3. 5, zero capabilities, and sudden 4.[00:28:40] swyx: And this is the kind of Jason Wei type emergence properties that people kind of look for. I think what made this paper stand out as well, so he developed the benchmark for steganography collusion, and he also focused on shelling point collusion, which is very low coordination. For agreeing on a decoding encoding format, you kind of need to have some [00:29:00] agreement on that.[00:29:00] swyx: But, but shelling point means like very, very low or almost no coordination. So for example, if I, if I ask someone, if the only message I give you is meet me in New York and you're not aware. Or when you would probably meet me at Grand Central Station. That is the Grand Central Station is a shelling point.[00:29:16] swyx: And it's probably somewhere, somewhere during the day. That is the shelling point of New York is Grand Central. To that extent, shelling points for steganography are things like the, the, the common decoding methods that we talked about. It will be interesting at some point in the future when we are worried about alignment.[00:29:30] swyx: It is not interesting today, but it's interesting that DeepMind is already thinking about this.[00:29:36] Alessio: I think that's like one of the hardest things about NeurIPS. It's like the long tail. I[00:29:41] swyx: found a pricing guy. I'm going to feature him on the podcast. Basically, this guy from NVIDIA worked out the optimal pricing for language models.[00:29:51] swyx: It's basically an econometrics paper at NeurIPS, where everyone else is talking about GPUs. And the guy with the GPUs is[00:29:57] Alessio: talking[00:29:57] swyx: about economics instead. [00:30:00] That was the sort of fun one. So the focus I saw is that model papers at NeurIPS are kind of dead. No one really presents models anymore. It's just data sets.[00:30:12] swyx: This is all the grad students are working on. So like there was a data sets track and then I was looking around like, I was like, you don't need a data sets track because every paper is a data sets paper. And so data sets and benchmarks, they're kind of flip sides of the same thing. So Yeah. Cool. Yeah, if you're a grad student, you're a GPU boy, you kind of work on that.[00:30:30] swyx: And then the, the sort of big model that people walk around and pick the ones that they like, and then they use it in their models. And that's, that's kind of how it develops. I, I feel like, um, like, like you didn't last year, you had people like Hao Tian who worked on Lava, which is take Lama and add Vision.[00:30:47] swyx: And then obviously actually I hired him and he added Vision to Grok. Now he's the Vision Grok guy. This year, I don't think there was any of those.[00:30:55] Alessio: What were the most popular, like, orals? Last year it was like the [00:31:00] Mixed Monarch, I think, was like the most attended. Yeah, uh, I need to look it up. Yeah, I mean, if nothing comes to mind, that's also kind of like an answer in a way.[00:31:10] Alessio: But I think last year there was a lot of interest in, like, furthering models and, like, different architectures and all of that.[00:31:16] swyx: I will say that I felt the orals, oral picks this year were not very good. Either that or maybe it's just a So that's the highlight of how I have changed in terms of how I view papers.[00:31:29] swyx: So like, in my estimation, two of the best papers in this year for datasets or data comp and refined web or fine web. These are two actually industrially used papers, not highlighted for a while. I think DCLM got the spotlight, FineWeb didn't even get the spotlight. So like, it's just that the picks were different.[00:31:48] swyx: But one thing that does get a lot of play that a lot of people are debating is the role that's scheduled. This is the schedule free optimizer paper from Meta from Aaron DeFazio. And this [00:32:00] year in the ML community, there's been a lot of chat about shampoo, soap, all the bathroom amenities for optimizing your learning rates.[00:32:08] swyx: And, uh, most people at the big labs are. Who I asked about this, um, say that it's cute, but it's not something that matters. I don't know, but it's something that was discussed and very, very popular. 4Wars[00:32:19] Alessio: of AI recap maybe, just quickly. Um, where do you want to start? Data?[00:32:26] swyx: So to remind people, this is the 4Wars piece that we did as one of our earlier recaps of this year.[00:32:31] swyx: And the belligerents are on the left, journalists, writers, artists, anyone who owns IP basically, New York Times, Stack Overflow, Reddit, Getty, Sarah Silverman, George RR Martin. Yeah, and I think this year we can add Scarlett Johansson to that side of the fence. So anyone suing, open the eye, basically. I actually wanted to get a snapshot of all the lawsuits.[00:32:52] swyx: I'm sure some lawyer can do it. That's the data quality war. On the right hand side, we have the synthetic data people, and I think we talked about Lumna's talk, you know, [00:33:00] really showing how much synthetic data has come along this year. I think there was a bit of a fight between scale. ai and the synthetic data community, because scale.[00:33:09] swyx: ai published a paper saying that synthetic data doesn't work. Surprise, surprise, scale. ai is the leading vendor of non synthetic data. Only[00:33:17] Alessio: cage free annotated data is useful.[00:33:21] swyx: So I think there's some debate going on there, but I don't think it's much debate anymore that at least synthetic data, for the reasons that are blessed in Luna's talk, Makes sense.[00:33:32] swyx: I don't know if you have any perspectives there.[00:33:34] Alessio: I think, again, going back to the reinforcement fine tuning, I think that will change a little bit how people think about it. I think today people mostly use synthetic data, yeah, for distillation and kind of like fine tuning a smaller model from like a larger model.[00:33:46] Alessio: I'm not super aware of how the frontier labs use it outside of like the rephrase, the web thing that Apple also did. But yeah, I think it'll be. Useful. I think like whether or not that gets us the big [00:34:00] next step, I think that's maybe like TBD, you know, I think people love talking about data because it's like a GPU poor, you know, I think, uh, synthetic data is like something that people can do, you know, so they feel more opinionated about it compared to, yeah, the optimizers stuff, which is like,[00:34:17] swyx: they don't[00:34:17] Alessio: really work[00:34:18] swyx: on.[00:34:18] swyx: I think that there is an angle to the reasoning synthetic data. So this year, we covered in the paper club, the star series of papers. So that's star, Q star, V star. It basically helps you to synthesize reasoning steps, or at least distill reasoning steps from a verifier. And if you look at the OpenAI RFT, API that they released, or that they announced, basically they're asking you to submit graders, or they choose from a preset list of graders.[00:34:49] swyx: Basically It feels like a way to create valid synthetic data for them to fine tune their reasoning paths on. Um, so I think that is another angle where it starts to make sense. And [00:35:00] so like, it's very funny that basically all the data quality wars between Let's say the music industry or like the newspaper publishing industry or the textbooks industry on the big labs.[00:35:11] swyx: It's all of the pre training era. And then like the new era, like the reasoning era, like nobody has any problem with all the reasoning, especially because it's all like sort of math and science oriented with, with very reasonable graders. I think the more interesting next step is how does it generalize beyond STEM?[00:35:27] swyx: We've been using O1 for And I would say like for summarization and creative writing and instruction following, I think it's underrated. I started using O1 in our intro songs before we killed the intro songs, but it's very good at writing lyrics. You know, I can actually say like, I think one of the O1 pro demos.[00:35:46] swyx: All of these things that Noam was showing was that, you know, you can write an entire paragraph or three paragraphs without using the letter A, right?[00:35:53] Creative Writing with AI[00:35:53] swyx: So like, like literally just anything instead of token, like not even token level, character level manipulation and [00:36:00] counting and instruction following. It's, uh, it's very, very strong.[00:36:02] swyx: And so no surprises when I ask it to rhyme, uh, and to, to create song lyrics, it's going to do that very much better than in previous models. So I think it's underrated for creative writing.[00:36:11] Alessio: Yeah.[00:36:12] Legal and Ethical Issues in AI[00:36:12] Alessio: What do you think is the rationale that they're going to have in court when they don't show you the thinking traces of O1, but then they want us to, like, they're getting sued for using other publishers data, you know, but then on their end, they're like, well, you shouldn't be using my data to then train your model.[00:36:29] Alessio: So I'm curious to see how that kind of comes. Yeah, I mean, OPA has[00:36:32] swyx: many ways to publish, to punish people without bringing, taking them to court. Already banned ByteDance for distilling their, their info. And so anyone caught distilling the chain of thought will be just disallowed to continue on, on, on the API.[00:36:44] swyx: And it's fine. It's no big deal. Like, I don't even think that's an issue at all, just because the chain of thoughts are pretty well hidden. Like you have to work very, very hard to, to get it to leak. And then even when it leaks the chain of thought, you don't know if it's, if it's [00:37:00] The bigger concern is actually that there's not that much IP hiding behind it, that Cosign, which we talked about, we talked to him on Dev Day, can just fine tune 4.[00:37:13] swyx: 0 to beat 0. 1 Cloud SONET so far is beating O1 on coding tasks without, at least O1 preview, without being a reasoning model, same for Gemini Pro or Gemini 2. 0. So like, how much is reasoning important? How much of a moat is there in this, like, All of these are proprietary sort of training data that they've presumably accomplished.[00:37:34] swyx: Because even DeepSeek was able to do it. And they had, you know, two months notice to do this, to do R1. So, it's actually unclear how much moat there is. Obviously, you know, if you talk to the Strawberry team, they'll be like, yeah, I mean, we spent the last two years doing this. So, we don't know. And it's going to be Interesting because there'll be a lot of noise from people who say they have inference time compute and actually don't because they just have fancy chain of thought.[00:38:00][00:38:00] swyx: And then there's other people who actually do have very good chain of thought. And you will not see them on the same level as OpenAI because OpenAI has invested a lot in building up the mythology of their team. Um, which makes sense. Like the real answer is somewhere in between.[00:38:13] Alessio: Yeah, I think that's kind of like the main data war story developing.[00:38:18] The Data War: GPU Poor vs. GPU Rich[00:38:18] Alessio: GPU poor versus GPU rich. Yeah. Where do you think we are? I think there was, again, going back to like the small model thing, there was like a time in which the GPU poor were kind of like the rebel faction working on like these models that were like open and small and cheap. And I think today people don't really care as much about GPUs anymore.[00:38:37] Alessio: You also see it in the price of the GPUs. Like, you know, that market is kind of like plummeted because there's people don't want to be, they want to be GPU free. They don't even want to be poor. They just want to be, you know, completely without them. Yeah. How do you think about this war? You[00:38:52] swyx: can tell me about this, but like, I feel like the, the appetite for GPU rich startups, like the, you know, the, the funding plan is we will raise 60 million and [00:39:00] we'll give 50 of that to NVIDIA.[00:39:01] swyx: That is gone, right? Like, no one's, no one's pitching that. This was literally the plan, the exact plan of like, I can name like four or five startups, you know, this time last year. So yeah, GPU rich startups gone.[00:39:12] The Rise of GPU Ultra Rich[00:39:12] swyx: But I think like, The GPU ultra rich, the GPU ultra high net worth is still going. So, um, now we're, you know, we had Leopold's essay on the trillion dollar cluster.[00:39:23] swyx: We're not quite there yet. We have multiple labs, um, you know, XAI very famously, you know, Jensen Huang praising them for being. Best boy number one in spinning up 100, 000 GPU cluster in like 12 days or something. So likewise at Meta, likewise at OpenAI, likewise at the other labs as well. So like the GPU ultra rich are going to keep doing that because I think partially it's an article of faith now that you just need it.[00:39:46] swyx: Like you don't even know what it's going to, what you're going to use it for. You just, you just need it. And it makes sense that if, especially if we're going into. More researchy territory than we are. So let's say 2020 to 2023 was [00:40:00] let's scale big models territory because we had GPT 3 in 2020 and we were like, okay, we'll go from 1.[00:40:05] swyx: 75b to 1. 8b, 1. 8t. And that was GPT 3 to GPT 4. Okay, that's done. As far as everyone is concerned, Opus 3. 5 is not coming out, GPT 4. 5 is not coming out, and Gemini 2, we don't have Pro, whatever. We've hit that wall. Maybe I'll call it the 2 trillion perimeter wall. We're not going to 10 trillion. No one thinks it's a good idea, at least from training costs, from the amount of data, or at least the inference.[00:40:36] swyx: Would you pay 10x the price of GPT Probably not. Like, like you want something else that, that is at least more useful. So it makes sense that people are pivoting in terms of their inference paradigm.[00:40:47] Emerging Trends in AI Models[00:40:47] swyx: And so when it's more researchy, then you actually need more just general purpose compute to mess around with, uh, at the exact same time that production deployments of the old, the previous paradigm is still ramping up,[00:40:58] swyx: um,[00:40:58] swyx: uh, pretty aggressively.[00:40:59] swyx: So [00:41:00] it makes sense that the GPU rich are growing. We have now interviewed both together and fireworks and replicates. Uh, we haven't done any scale yet. But I think Amazon, maybe kind of a sleeper one, Amazon, in a sense of like they, at reInvent, I wasn't expecting them to do so well, but they are now a foundation model lab.[00:41:18] swyx: It's kind of interesting. Um, I think, uh, you know, David went over there and started just creating models.[00:41:25] Alessio: Yeah, I mean, that's the power of prepaid contracts. I think like a lot of AWS customers, you know, they do this big reserve instance contracts and now they got to use their money. That's why so many startups.[00:41:37] Alessio: Get bought through the AWS marketplace so they can kind of bundle them together and prefer pricing.[00:41:42] swyx: Okay, so maybe GPU super rich doing very well, GPU middle class dead, and then GPU[00:41:48] Alessio: poor. I mean, my thing is like, everybody should just be GPU rich. There shouldn't really be, even the GPU poorest, it's like, does it really make sense to be GPU poor?[00:41:57] Alessio: Like, if you're GPU poor, you should just use the [00:42:00] cloud. Yes, you know, and I think there might be a future once we kind of like figure out what the size and shape of these models is where like the tiny box and these things come to fruition where like you can be GPU poor at home. But I think today is like, why are you working so hard to like get these models to run on like very small clusters where it's like, It's so cheap to run them.[00:42:21] Alessio: Yeah, yeah,[00:42:22] swyx: yeah. I think mostly people think it's cool. People think it's a stepping stone to scaling up. So they aspire to be GPU rich one day and they're working on new methods. Like news research, like probably the most deep tech thing they've done this year is Distro or whatever the new name is.[00:42:38] swyx: There's a lot of interest in heterogeneous computing, distributed computing. I tend generally to de emphasize that historically, but it may be coming to a time where it is starting to be relevant. I don't know. You know, SF compute launched their compute marketplace this year, and like, who's really using that?[00:42:53] swyx: Like, it's a bunch of small clusters, disparate types of compute, and if you can make that [00:43:00] useful, then that will be very beneficial to the broader community, but maybe still not the source of frontier models. It's just going to be a second tier of compute that is unlocked for people, and that's fine. But yeah, I mean, I think this year, I would say a lot more on device, We are, I now have Apple intelligence on my phone.[00:43:19] swyx: Doesn't do anything apart from summarize my notifications. But still, not bad. Like, it's multi modal.[00:43:25] Alessio: Yeah, the notification summaries are so and so in my experience.[00:43:29] swyx: Yeah, but they add, they add juice to life. And then, um, Chrome Nano, uh, Gemini Nano is coming out in Chrome. Uh, they're still feature flagged, but you can, you can try it now if you, if you use the, uh, the alpha.[00:43:40] swyx: And so, like, I, I think, like, you know, We're getting the sort of GPU poor version of a lot of these things coming out, and I think it's like quite useful. Like Windows as well, rolling out RWKB in sort of every Windows department is super cool. And I think the last thing that I never put in this GPU poor war, that I think I should now, [00:44:00] is the number of startups that are GPU poor but still scaling very well, as sort of wrappers on top of either a foundation model lab, or GPU Cloud.[00:44:10] swyx: GPU Cloud, it would be Suno. Suno, Ramp has rated as one of the top ranked, fastest growing startups of the year. Um, I think the last public number is like zero to 20 million this year in ARR and Suno runs on Moto. So Suno itself is not GPU rich, but they're just doing the training on, on Moto, uh, who we've also talked to on, on the podcast.[00:44:31] swyx: The other one would be Bolt, straight cloud wrapper. And, and, um, Again, another, now they've announced 20 million ARR, which is another step up from our 8 million that we put on the title. So yeah, I mean, it's crazy that all these GPU pores are finding a way while the GPU riches are also finding a way. And then the only failures, I kind of call this the GPU smiling curve, where the edges do well, because you're either close to the machines, and you're like [00:45:00] number one on the machines, or you're like close to the customers, and you're number one on the customer side.[00:45:03] swyx: And the people who are in the middle. Inflection, um, character, didn't do that great. I think character did the best of all of them. Like, you have a note in here that we apparently said that character's price tag was[00:45:15] Alessio: 1B.[00:45:15] swyx: Did I say that?[00:45:16] Alessio: Yeah. You said Google should just buy them for 1B. I thought it was a crazy number.[00:45:20] Alessio: Then they paid 2. 7 billion. I mean, for like,[00:45:22] swyx: yeah.[00:45:22] Alessio: What do you pay for node? Like, I don't know what the game world was like. Maybe the starting price was 1B. I mean, whatever it was, it worked out for everybody involved.[00:45:31] The Multi-Modality War[00:45:31] Alessio: Multimodality war. And this one, we never had text to video in the first version, which now is the hottest.[00:45:37] swyx: Yeah, I would say it's a subset of image, but yes.[00:45:40] Alessio: Yeah, well, but I think at the time it wasn't really something people were doing, and now we had VO2 just came out yesterday. Uh, Sora was released last month, last week. I've not tried Sora, because the day that I tried, it wasn't, yeah. I[00:45:54] swyx: think it's generally available now, you can go to Sora.[00:45:56] swyx: com and try it. Yeah, they had[00:45:58] Alessio: the outage. Which I [00:46:00] think also played a part into it. Small things. Yeah. What's the other model that you posted today that was on Replicate? Video or OneLive?[00:46:08] swyx: Yeah. Very, very nondescript name, but it is from Minimax, which I think is a Chinese lab. The Chinese labs do surprisingly well at the video models.[00:46:20] swyx: I'm not sure it's actually Chinese. I don't know. Hold me up to that. Yep. China. It's good. Yeah, the Chinese love video. What can I say? They have a lot of training data for video. Or a more relaxed regulatory environment.[00:46:37] Alessio: Uh, well, sure, in some way. Yeah, I don't think there's much else there. I think like, you know, on the image side, I think it's still open.[00:46:45] Alessio: Yeah, I mean,[00:46:46] swyx: 11labs is now a unicorn. So basically, what is multi modality war? Multi modality war is, do you specialize in a single modality, right? Or do you have GodModel that does all the modalities? So this is [00:47:00] definitely still going, in a sense of 11 labs, you know, now Unicorn, PicoLabs doing well, they launched Pico 2.[00:47:06] swyx: 0 recently, HeyGen, I think has reached 100 million ARR, Assembly, I don't know, but they have billboards all over the place, so I assume they're doing very, very well. So these are all specialist models, specialist models and specialist startups. And then there's the big labs who are doing the sort of all in one play.[00:47:24] swyx: And then here I would highlight Gemini 2 for having native image output. Have you seen the demos? Um, yeah, it's, it's hard to keep up. Literally they launched this last week and a shout out to Paige Bailey, who came to the Latent Space event to demo on the day of launch. And she wasn't prepared. She was just like, I'm just going to show you.[00:47:43] swyx: So they have voice. They have, you know, obviously image input, and then they obviously can code gen and all that. But the new one that OpenAI and Meta both have but they haven't launched yet is image output. So you can literally, um, I think their demo video was that you put in an image of a [00:48:00] car, and you ask for minor modifications to that car.[00:48:02] swyx: They can generate you that modification exactly as you asked. So there's no need for the stable diffusion or comfy UI workflow of like mask here and then like infill there in paint there and all that, all that stuff. This is small model nonsense. Big model people are like, huh, we got you in as everything in the transformer.[00:48:21] swyx: This is the multimodality war, which is, do you, do you bet on the God model or do you string together a whole bunch of, uh, Small models like a, like a chump. Yeah,[00:48:29] Alessio: I don't know, man. Yeah, that would be interesting. I mean, obviously I use Midjourney for all of our thumbnails. Um, they've been doing a ton on the product, I would say.[00:48:38] Alessio: They launched a new Midjourney editor thing. They've been doing a ton. Because I think, yeah, the motto is kind of like, Maybe, you know, people say black forest, the black forest models are better than mid journey on a pixel by pixel basis. But I think when you put it, put it together, have you tried[00:48:53] swyx: the same problems on black forest?[00:48:55] Alessio: Yes. But the problem is just like, you know, on black forest, it generates one image. And then it's like, you got to [00:49:00] regenerate. You don't have all these like UI things. Like what I do, no, but it's like time issue, you know, it's like a mid[00:49:06] swyx: journey. Call the API four times.[00:49:08] Alessio: No, but then there's no like variate.[00:49:10] Alessio: Like the good thing about mid journey is like, you just go in there and you're cooking. There's a lot of stuff that just makes it really easy. And I think people underestimate that. Like, it's not really a skill issue, because I'm paying mid journey, so it's a Black Forest skill issue, because I'm not paying them, you know?[00:49:24] Alessio: Yeah,[00:49:25] swyx: so, okay, so, uh, this is a UX thing, right? Like, you, you, you understand that, at least, we think that Black Forest should be able to do all that stuff. I will also shout out, ReCraft has come out, uh, on top of the image arena that, uh, artificial analysis has done, has apparently, uh, Flux's place. Is this still true?[00:49:41] swyx: So, Artificial Analysis is now a company. I highlighted them I think in one of the early AI Newses of the year. And they have launched a whole bunch of arenas. So, they're trying to take on LM Arena, Anastasios and crew. And they have an image arena. Oh yeah, Recraft v3 is now beating Flux 1. 1. Which is very surprising [00:50:00] because Flux And Black Forest Labs are the old stable diffusion crew who left stability after, um, the management issues.[00:50:06] swyx: So Recurve has come from nowhere to be the top image model. Uh, very, very strange. I would also highlight that Grok has now launched Aurora, which is, it's very interesting dynamics between Grok and Black Forest Labs because Grok's images were originally launched, uh, in partnership with Black Forest Labs as a, as a thin wrapper.[00:50:24] swyx: And then Grok was like, no, we'll make our own. And so they've made their own. I don't know, there are no APIs or benchmarks about it. They just announced it. So yeah, that's the multi modality war. I would say that so far, the small model, the dedicated model people are winning, because they are just focused on their tasks.[00:50:42] swyx: But the big model, People are always catching up. And the moment I saw the Gemini 2 demo of image editing, where I can put in an image and just request it and it does, that's how AI should work. Not like a whole bunch of complicated steps. So it really is something. And I think one frontier that we haven't [00:51:00] seen this year, like obviously video has done very well, and it will continue to grow.[00:51:03] swyx: You know, we only have Sora Turbo today, but at some point we'll get full Sora. Oh, at least the Hollywood Labs will get Fulsora. We haven't seen video to audio, or video synced to audio. And so the researchers that I talked to are already starting to talk about that as the next frontier. But there's still maybe like five more years of video left to actually be Soda.[00:51:23] swyx: I would say that Gemini's approach Compared to OpenAI, Gemini seems, or DeepMind's approach to video seems a lot more fully fledged than OpenAI. Because if you look at the ICML recap that I published that so far nobody has listened to, um, that people have listened to it. It's just a different, definitely different audience.[00:51:43] swyx: It's only seven hours long. Why are people not listening? It's like everything in Uh, so, so DeepMind has, is working on Genie. They also launched Genie 2 and VideoPoet. So, like, they have maybe four years advantage on world modeling that OpenAI does not have. Because OpenAI basically only started [00:52:00] Diffusion Transformers last year, you know, when they hired, uh, Bill Peebles.[00:52:03] swyx: So, DeepMind has, has a bit of advantage here, I would say, in, in, in showing, like, the reason that VO2, while one, They cherry pick their videos. So obviously it looks better than Sora, but the reason I would believe that VO2, uh, when it's fully launched will do very well is because they have all this background work in video that they've done for years.[00:52:22] swyx: Like, like last year's NeurIPS, I already was interviewing some of their video people. I forget their model name, but for, for people who are dedicated fans, they can go to NeurIPS 2023 and see, see that paper.[00:52:32] Alessio: And then last but not least, the LLMOS. We renamed it to Ragops, formerly known as[00:52:39] swyx: Ragops War. I put the latest chart on the Braintrust episode.[00:52:43] swyx: I think I'm going to separate these essays from the episode notes. So the reason I used to do that, by the way, is because I wanted to show up on Hacker News. I wanted the podcast to show up on Hacker News. So I always put an essay inside of there because Hacker News people like to read and not listen.[00:52:58] Alessio: So episode essays,[00:52:59] swyx: I remember [00:53:00] purchasing them separately. You say Lanchain Llama Index is still growing.[00:53:03] Alessio: Yeah, so I looked at the PyPy stats, you know. I don't care about stars. On PyPy you see Do you want to share your screen? Yes. I prefer to look at actual downloads, not at stars on GitHub. So if you look at, you know, Lanchain still growing.[00:53:20] Alessio: These are the last six months. Llama Index still growing. What I've basically seen is like things that, One, obviously these things have A commercial product. So there's like people buying this and sticking with it versus kind of hopping in between things versus, you know, for example, crew AI, not really growing as much.[00:53:38] Alessio: The stars are growing. If you look on GitHub, like the stars are growing, but kind of like the usage is kind of like flat. In the last six months, have they done some[00:53:4

In this episode, Cary Weston sits down with Chris Greene, founder of the Flood Insurance Guru, a niche insurance and marketing expert who transformed his business by embracing video content and AI tools. Chris shares his journey of scaling his company with over 5,000 videos, generating millions in revenue, and how he's teaching others to harness the power of video and ChatGPT. The conversation dives into building authenticity, using AI tools for efficiency, and navigating challenges, including his personal journey of losing his vision and adapting his work approach. Key Takeaways Niche Focus and Authenticity Drive Success Chris leveraged personal experiences and a deep understanding of flood insurance to create a unique and trusted brand that resonates with customers. AI Tools Amplify Productivity and Creativity By creating custom GPTs and using AI tools like HeyGen and HubSpot integrations, Chris optimized workflows, built targeted content, and improved customer experience. Human Connection through Video Content Personalized video proposals, answering FAQs, and authentic storytelling shortened sales cycles and deepened customer trust. About Chris Greene Chris Greene is the founder of the Flood Insurance Guru, a business built to educate, empower, and assist homeowners in navigating flood insurance policies. Starting his journey after a difficult personal experience with flood insurance, Chris decided to fill the gap in public knowledge through authentic and accessible video content. Beyond his insurance work, Chris has become a sought-after marketing consultant, teaching others how to build niche businesses through video and inbound marketing strategies. You can learn more about Chris and his work at: Flood Insurance Guru YouTube Channel Website Are you ready to use ChatGPT to be more productive and efficient in your work? Check out Cary's customized, interactive workshops:

In this episode, we explore building an AI-first company and engineering org with Rong Yan (CTO @ HeyGen)! We dive into the potential of HeyGen's interactive avatars, imagining how they can help engineering leaders scale their impact, foster team alignment, coach effectively, and accelerate decision-making. Rong shares insights on the structure of an AI-first company and optimizing for AI teams with engineering capabilities. Plus what it means to “lead with speed” and balance product quality and velocity in an AI-first company and key leadership principles, like why it's crucial to invest in your top performers and how to act as a productivity multiplier.ABOUT RONG YANRong Yan is HeyGen's Chief Technology Officer. He brings the company's technological mission of making visual storytelling accessible to everyone, to life. Rong has nearly 20 years of engineering leadership experience from companies including IBM, Facebook, Square, Snap, and HubSpot.Most recently, Rong was the VP of Engineering at Hubspot where he led the Data Intelligence and Automation product line and spearheaded the development of an intelligent CRM platform using data and AI. He was also the Director of Engineering turned Senior Director of Engineering at Snap, where he led a product engineering team of over 250 engineers across six locations, responsible for developing, optimizing, and maintaining core Snapchat features, including Camera, Messaging, Stories, Discover, Memories, and Identity.He holds a Bachelor of Science in Computer Science from Tsinghua University and a PhD in Computer Science from Carnegie Mellon University.SHOW NOTES:Introducing HeyGen's interactive avatar & what this means for eng leaders (3:40)How a visual layer for AI agents could scale your leadership & build alignment in your teams and orgs (5:58)The different levels of communication flow within a company (8:17)How interactive avatars can enable interactions and coaching at scale (10:46)The possibilities of interactive avatars for personalized coaching, habit building, and behavior change (14:02)Insights on building an AI-first company (20:29)What the structure of an AI-first company looks like (22:05)How leading with speed works within an AI-first company (24:10)Navigating the balance between product velocity & quality (27:23)The impact of the “leading with speed” paradigm on hiring (30:34)The role of an engineering leaders is to be a productivity multiplier (32:40)How AI impacts productivity as an eng leader (34:43)Where to start when it comes to improving productivity (36:38)AI's role in blurring the lines between IC & management (39:48)Spend more time on your top people (42:45)Rapid fire questions (44:21)LINKS AND RESOURCESHeyGen - With HeyGen, businesses can simply write their script and generate their video. No camera, no budget, no headaches. We've helped over 45,000 companies and millions of people create, localize, and personalize videos at scale.This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/

In this episode of YourTechReport, Marc connects with Dan Ackerman, Editor in Chief of Micro Center News, to dive into their unique experiences of switching between Mac and Windows systems. Dan shares his insights on how Windows has evolved, particularly for gaming and creative tasks, and the pros and cons of each platform. They discuss the small yet powerful nuances that make each system unique—from Mac's spacebar preview to Windows' flexibility with gaming. Dan also reveals details about his recent AI cloning experiment, where he created a virtual version of himself that can respond in real-time for videos and even conduct interviews. With tools like ChatGPT, Eleven Labs, and HeyGen, Dan's exploration into AI demystifies the process of creating a realistic digital clone for under $50. They touch on the potential of AI avatars in customer service, video narration, and content creation, along with the ethical implications and future of AI in tech. With Black Friday around the corner and CES on the horizon, Marc and Dan also talk shop about the latest developments in PC gaming, the launch of new Intel and AMD chips, and Micro Center's expansion into Miami. Whether you're a tech enthusiast, curious about AI, or just looking for the next upgrade, this episode has something for everyone. Chapters: 1. 00:00 - Mac vs. Windows: A Tale of Two Systems 2. 02:15 - Transitioning Back to Windows: The Pros and Cons 3. 03:30 - Dan's AI Cloning Experiment: Cloning Yourself for $50 4. 05:00 - Tools for AI Cloning: ChatGPT, Eleven Labs, and HeyGen 5. 06:45 - Building Real-Time AI Conversations 6. 09:00 - The Future of AI in Customer Service & Content Creation 7. 11:00 - What's New in the PC World: Intel & AMD Chips 8. 12:15 - Micro Center's New Miami Store and Canada Expansion 9. 14:00 - Closing Thoughts & Upcoming Holiday Tech Buzz Learn more about your ad choices. Visit megaphone.fm/adchoices

In Episode 6, Brandon Frank and Ben Gold discuss new ways AI can help businesses create engaging content, from transforming ideas into images and videos to customizing presentations for specific audiences. They explore popular AI tools for visual and video content creation, including Midjourney, DALL-E 3, HeyGen, and Eleven Labs. Brandon also shares recent updates from PPC Packaging, highlighting how the team is diving deeper into Claude for automating tasks like quality control and call analysis. The episode wraps up with a discussion on using avatars for video content and the question of balancing human presence with AI-driven presentations.In this episode, we'll talk about:Current AI Tools for Visuals and Video: Ben shares popular AI tools like DALL-E 3 and Midjourney for creating images and HeyGen and Eleven Labs for video and voice cloning, making it easy for businesses to produce multimedia content.Going Deeper with Claude at PPC: The PPC team is using Claude to assist with quality control processes, call analysis, and custom SOPs, bringing new efficiencies to their workflows.Personalized Content Creation: Brandon and Ben brainstorm how AI can streamline content creation by generating multiple posts from one case study and even automating voice and video content.AI for Branding and Avatars: With AI's ability to create lifelike avatars, Brandon considers whether to create a consistent avatar for PPC's branding or stick with live presentations.Ben Gold is an AI strategist and consultant with over 20 years of experience in the technology sales sector. He helps organizations navigate the complex landscape of AI adoption and implementation, bridging the gap between technical concepts and business objectives. Ben's specializations include AI strategy development, change management, talent acquisition, ethical AI deployment, and AI-driven workflow optimization. Passionate about making AI accessible, Ben focuses on providing actionable steps and working hands-on with clients to implement and optimize AI strategies. He is the first video game world champion and a thought leader in the technology industry. For more information and to explore other episodes, go to https://www.ppcpackaging.com/packology-podcast-1Follow PPCPackaging on social media!  LinkedIn: https://www.linkedin.com/company/pacific-packaging-components-inc-/ Facebook: https://www.facebook.com/PPCPackaging/ Instagram: https://www.instagram.com/ppcpackaging/?hl=en Website: http://www.ppcpackaging.com/Find out more about Ben on his website and connect with him on LinkedIn and Email.Website: bengoldai.com LinkedIn: linkedin.com/in/bengoldsalesEmail: ben@bengoldai.comThe views and opinions expressed on the “Packology” podcast are solely those of the author and guests and should not be attributed to any other individual or entity. This podcast is an independent production of Packology, and the podcast production is an original work of the author. All rights of ownership and reproduction are retained—copyright 2024. 

Hey Rainmakers! Chelsey and Stephen here, and today we're pulling back the curtain on AI tools that are transforming the way we work. From streamlining our daily tasks to enhancing productivity, these tools are game-changers for any entrepreneur. Whether you're a tech enthusiast or totally new to AI, this episode is packed with practical tips and resources to integrate AI into your own business. In this episode, we focus on our top five AI tools, kicking things off with the one everyone's heard about – ChatGPT. Stephen explains how ChatGPT has replaced Google for him, not just for finding information but for summarizing data, generating story ideas for their kids, and even helping with trip planning! Chelsey admits she's slower to adopt new tech, but Stephen's approach makes it easier to dive in and start using these tools. Next, Stephen shares two AI tools specifically for content creators: Captions and HeyGen. Captions helps with adding subtitles to videos but also introduces AI-generated user models for social media, saving time on ad production. HeyGen goes a step further, letting users create a digital likeness of themselves to generate videos for different audiences or languages. Chelsey finds it fascinating and a little wild, but it's perfect for businesses looking to test video content before going all in. We wrap up with tools like Delphi and Chatbase, which streamline customer support and knowledge sharing. Delphi creates an interactive AI model that can answer questions as if it's you, based on your own resources and knowledge. Chatbase offers a similar function, embedding an AI assistant on your website to provide real-time support. As Stephen explains, these tools are part of a rapidly evolving landscape that's all about enhancing productivity and scaling effectively. So, tune in, take notes, and start thinking about how you could use AI to give your business that extra edge. Even if you're just getting started, there's something here for everyone!   Connect with us: ► Rainmaker Instagram: @therainmakerfamily   ► Chelsey Instagram: @chels_diaz   ► Stephen Instagram: @steezdiaz    ► TikTok: @therainmakerfamily   ► Facebook: @diazfamilylegacy   ► Website: @https://therainmakerfamily.com   Join Our Next Rainmaker Challenge - How To Make Passive Income From Home: https://therainmakerchallenge.com Save On Our Favorite Things: https://rainmakerfamily.com/deals Watch The Million Dollar Mama Case Study: https://www.makeitrainmomma.com/cases...   Episode Minute by Minute:  0:00 - Introduction to AI in Business 1:10 - ChatGPT: Replacing Google 7:00 - Content Creation with Captions 10:30 - HeyGen for Video AI Models 18:00 - Delphi: AI Customer Support 30:00 - Chatbase: Embedded AI Assistance

Hey Rainmakers! Chelsey and Stephen here, and today we're pulling back the curtain on AI tools that are transforming the way we work. From streamlining our daily tasks to enhancing productivity, these tools are game-changers for any entrepreneur. Whether you're a tech enthusiast or totally new to AI, this episode is packed with practical tips and resources to integrate AI into your own business. In this episode, we focus on our top five AI tools, kicking things off with the one everyone's heard about – ChatGPT. Stephen explains how ChatGPT has replaced Google for him, not just for finding information but for summarizing data, generating story ideas for their kids, and even helping with trip planning! Chelsey admits she's slower to adopt new tech, but Stephen's approach makes it easier to dive in and start using these tools. Next, Stephen shares two AI tools specifically for content creators: Captions and HeyGen. Captions helps with adding subtitles to videos but also introduces AI-generated user models for social media, saving time on ad production. HeyGen goes a step further, letting users create a digital likeness of themselves to generate videos for different audiences or languages. Chelsey finds it fascinating and a little wild, but it's perfect for businesses looking to test video content before going all in. We wrap up with tools like Delphi and Chatbase, which streamline customer support and knowledge sharing. Delphi creates an interactive AI model that can answer questions as if it's you, based on your own resources and knowledge. Chatbase offers a similar function, embedding an AI assistant on your website to provide real-time support. As Stephen explains, these tools are part of a rapidly evolving landscape that's all about enhancing productivity and scaling effectively. So, tune in, take notes, and start thinking about how you could use AI to give your business that extra edge. Even if you're just getting started, there's something here for everyone!   Connect with us: ► Rainmaker Instagram: @therainmakerfamily ► Chelsey Instagram: @chels_diaz   ► Stephen Instagram: @steezdiaz    ► TikTok: @therainmakerfamily   ► Facebook: @diazfamilylegacy   ► Website: @https://therainmakerfamily.com   Join Our Next Rainmaker Challenge - How To Make Passive Income From Home: https://therainmakerchallenge.com Save On Our Favorite Things: https://rainmakerfamily.com/deals Watch The Million Dollar Mama Case Study: https://www.makeitrainmomma.com/cases...   Episode Minute by Minute:  0:00 - Introduction to AI in Business 1:10 - ChatGPT: Replacing Google 7:00 - Content Creation with Captions 10:30 - HeyGen for Video AI Models 18:00 - Delphi: AI Customer Support 30:00 - Chatbase: Embedded AI Assistance

James Carson is a content strategy consultant with some super impressive consumer facing experience including Head of SEO and Social Media at the Telegraph Media Group (huge newspaper in the UK), and MD at History Hit. Right now he's the founder of Publishing Strategy AND has just launched the AI tools directory NextGenTools.ai. In this episode, we discuss: Why a multiplatform content strategy is important Using AI tools for content creation efficiency Maintaining the human touch in your content Dive in: [04:59] iPhone age boosted social media accessibility and challenges. [07:56] Adapting content for social media is essential. [11:29] Video's promotional value in eCommerce is debated. [16:09] Plan social media strategy based on presence. [19:05] Good technical setup pays off; AI aids cleaning. [22:18] Tools like Synthesia, HeyGen becoming ubiquitous. [25:46] AI-generated content must be clearly labeled, critical. [27:29] Insider Tips from James! Find the notes here: https://keepopt.com/229 Download our ebook >> https://keepopt.com/ebook "500 Top Tips to Make Your eCommerce Business More Profitable" ****Get all the links and resources we mention & join our email list at https://keepopt.comLove the show? Chloe would love your feedback - leave a review here: https://keepopt.com/review or reply to the episode Q&A on Spotify.Interested in being a Sponsor? go here: https://keepopt.com/sponsor

How do you tell the same story with consistency across hundreds of visuals?Storytelling has evolved from spoken tales to AI-generated videos and photorealistic characters—but one challenge remains: consistency. It's easy to generate impressive individual frames with tools like Midjourney, but what if you need to maintain the same character across multiple scenes, moods, and poses?In this episode, we welcome Diana Zdybel, co-founder of Consistent Character AI and Neolemon, to break down the art of consistent character creation with AI. If you've ever felt stuck generating high-quality visuals that align perfectly with your business brand or internal messaging, this session will change your game.Through tools like Consistent Character GPT, Diana shares how to maintain visual harmony across AI-generated characters and illustrations. Whether you're an entrepreneur building pitch decks or a marketing team creating ads, Diana's insights will help you tell compelling, visual stories—efficiently and at scale.In this session, you'll discover:How AI revolutionizes storytelling for business communication.Why consistency in visuals matters for internal and external messaging.Practical tips for creating characters with Consistent Character AI.How tools like Midjourney and SegMind can streamline your workflow.A walkthrough of the most common challenges in AI-generated visuals—and how to overcome them.Bonus tools and tricks to animate avatars and characters using HeyGen and Canva.With a background in AI design and years of experience navigating the challenges of character creation, Diana helps businesses streamline their creative workflows. Connect with her on LinkedIn to stay updated on her latest projects: Diana Zdybel.Find more about Consistent Character AI here:  https://linktr.ee/neolemon About Leveraging AI The Ultimate AI Course for Business People: https://multiplai.ai/ai-course/ YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/ Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Free AI Consultation: https://multiplai.ai/book-a-call/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events If you've enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Met deze maand: Nobelprijzen! AI avatars! Mechazilla! Papegaaien! Meta Orion Bril! Jim Jansen! Ruimtemode! Brutale stofzuigers! En veel meer... Shownotes: https://podcast.nerdland.be/nerdland-maandoverzicht-november-2024/ Gepresenteerd door Lieven Scheire met Peter Berx, Marian Verhelst, Jeroen Baert en special guest Jim Jansen. Montage & mixing door Jens Paeyeneers. (00:00:00) Intro (00:05:40) Nieuw klimaatrapport is vernietigend (00:19:52) Lieven test Meta Orion bril (00:26:53) Philip Zimbardo overleden (00:32:37) Nobelprijzen Chemie, Fysica, Geneeskunde (00:45:30) Google bouwt 6 kleine kernreactoren om AI te poweren (00:56:40) Onderzoekers doen berekeningen met bacteriën (01:00:19) Onderzoekers laten schimmels groeien in robotbrein (01:01:33) Nieuwe techniek om donorharten te transporteren (01:04:39) Heygen lanceert digitale avatar (01:09:48) Microsoft lanceert AI werknemer voor bedrijven (01:14:27) SILICON VALLEY NEWS (01:17:34) Starship Super Heavy Booster landt in de armen van MechaZilla (01:23:23) OpenAI wordt for-profit bedrijf, grote namen vertrekken (01:26:59) Tesla stelt robotaxi voor (01:33:47) Starliner-astronauten nog steeds gestrand (01:35:30) Zowel China als USA stellen maanruimtepakken voor (01:36:19) Space Perspective doet onbemande testvlucht met luchtballon (01:37:51) Zotte dronevideo van exploderende Chinese raket (01:38:48) Niet sportend bewegen is belangrijk (01:45:36) 73 procent minder wilde dieren op aarde sinds 1970 (01:54:24) Papegaaien nemen wraak voor ontbossing door Argentijns dorp onder te schijten (01:57:09) Satoshi Nakamoto (02:00:00) Pairi Daiza zet zeldzame padden uit in de Ardennen (02:05:39) Robotstofzuigers schelden hun eigenaars uit (02:10:33) 23andMe bij bankroet (02:17:02) MEDEDELINGEN (02:17:29) Volkssterrenwacht MIRA zoekt medewerker (02:18:58) Makerday in Hasselt (02:20:01) Series V van QI is op antenne (02:20:45) 2025 in 26 oplossingen (02:24:23) Final Belgische AI show in Lotto Arena (02:27:16) Nerdland voor Kleine Nerds 26 en 27 december in Lotto Arena, 27 december met gebarentolk (02:28:33) Hetty premiere missie 2024 in NTGent op 9 november, derniere 5 april in Capitole (02:29:33) Hetty doet mee aan Slimste Mens! (02:30:15) Scheurkalender 2025 te koop (02:30:44) Nerdland Festival zoekt input Nerdlandfestival.be (02:31:26) SPONSOR Mediagenix

In this insightful episode of TOP CMO, Jackson Carpenter chats with Dave King, CMO at HeyGen, to explore the cutting-edge world of AI-powered video creation. Discover how Heygen is revolutionizing video production by making it faster, more personalized, and accessible to businesses of all sizes. Dive into the challenges of marketing to a global audience, the impact of AI on content creation, and strategies for building trust and safety in digital storytelling. Gain inspiration from Dave's rich career spanning Salesforce and Asana, and learn how to adapt and thrive in a fast-evolving marketing landscape.

Send us a textIn this episode of Sidecar Sync, hosts Amith and Mallory dive deep into two groundbreaking AI innovations—HeyGen's interactive avatars and Claude's new computer use feature. They explore how these tools could revolutionize the way associations handle meetings, customer interactions, and even website management. With live examples and hands-on experiences, they assess the future of AI avatars in the business world and break down how Claude's ability to control a computer can streamline tasks. Tune in to hear how these advancements could transform your association's operations and member experience.digitalNow Conference 2024

Ce mardi 22 octobre, François Sorel a reçu Claudia Cohen, journaliste au Figaro, Michel Levy Provençal, prospectiviste, fondateur de TEDxParis et de l'agence Brightness, et Bruno Guglielminetti, journaliste et animateur de « Mon Carnet de l'actualité numérique ». Ils se sont penchés sur la mise au point de Tim Cook sur le lancement du Vision Pro, l'accès gratuit à ChatGPT pour les habitants d'Arcachon, et le lancement d'avatars interactifs boostés à l'IA par HeyGen pour les réunions Zoom, dans l'émission Tech & Co, la quotidienne, sur BFM Business. Retrouvez l'émission du lundi au jeudi et réécoutez la en podcast.

In this week's episode of Mid Mic Crisis, hosts Bunchu and Chamber embark on a thrilling journey of AI avatar creation. Chamber kicks off the episode feeling on top of the world after successfully fixing his dryer with the help of YouTube and ChatGPT, blending humor with a practical use of AI in everyday life. The duo dives into their main topic: building an AI social media influencer from scratch, hilariously named Peg (or is it Pam?).Listeners are guided through each step of the process—from generating the visual look of their AI influencer using open-source tools like Flux, to crafting a unique tone of voice by analyzing the social media habits of prominent figures. Bunchu demonstrates his custom workflow for creating AI-generated scripts and content, showing how to combine tools like ChatGPT, HeyGen, and Eleven Labs to bring Peg to life.The pair discuss how AI can be used not just for content creation, but also for solving real-world problems (like Chamber's dryer situation) and reflect on the power and accessibility of these tools. The episode wraps up with a live demo of Peg, their newly created AI avatar, presenting a YouTube-style video about a $46 million deepfake scam, proving that AI can help create engaging, dynamic content in just minutes.Join Bunchu, Chamber, and special guest Executive Producer Payne for an entertaining, informative, and hands-on AI experience.Tools:Flux - https://replicate.com/black-forest-labs/flux-1.1-proHeyGen - https://app.heygen.com/Eleven Labs - https://elevenlabs.io/ChatGPT - https://chatgpt.com/Follow Us:Website: https://midmiccrisis.com/  YouTube: https://www.youtube.com/@midmiccrisisInstagram: https://www.instagram.com/midmiccrisis/?hl=enTikTok: https://www.tiktok.com/@mid.mic.crisis?lang=enTwitter: https://twitter.com/MidMicCrisisNewsletter: https://mid-mic-crisis-newsletter.beehiiv.com/subscribeMMC Push Pass: https://ks-pages-119byl.web.app/pass/66db3c111db9a79db7fdaafeFireBrain AI: https://www.skool.com/firebrainPowered by @dGenNetworkWebsite: https://dgen.network/Support the show

Joshua Xu is co-founder and CEO of HeyGen -- the fast-growing AI video creation and translation platform. You can upload a video, or create a new one from a script using an AI avatar as your star, and HeyGen will translate it into 175 languages. HeyGen now serves over 40,000 customers and is generating $35+ million in revenue. [0:00] Intro  [0:37] HeyGen's Viral Moments  [1:23] Creating Magic with AI  [3:30] The Future of AI in Video Production  [9:29] HeyGen's Use Cases and Customer Base  [13:15] AI Avatars  [25:46] The Future of Content  [26:43] Competing with Industry Giants  [27:16] Innovating for New Markets  [31:24] Enterprise Push: Lessons and Surprises  [33:07] Trust and Safety in AI  [37:03] Fundraising and Financial Strategies for AI Startups  [41:22] Quickfire With your co-hosts: @jacobeffron - Partner at Redpoint, Former PM Flatiron Health @patrickachase - Partner at Redpoint, Former ML Engineer LinkedIn @ericabrescia - Former COO Github, Founder Bitnami (acq'd by VMWare) @jordan_segall - Partner at Redpoint

In this podcast episode, Jamie and Jaeden discuss the latest advancements in AI video technology, focusing on new features from Meta, Pica, and HeyGen. They explore how these tools can enhance content creation, making it more engaging and accessible for marketers and creators. The conversation highlights the potential of AI in transforming video marketing strategies and the exciting future of AI-driven content. Our Skool Community: https://www.skool.com/aihustle/about Get on the AI Box Waitlist: ⁠⁠https://AIBox.ai/⁠⁠ Jamies's YouTube Channel: https://www.youtube.com/@JAMIEANDSARAH 00:00 Exploring AI Video Innovations 01:58 Innovative AI Tools: Pica and Heygen 07:42 The Future of AI in Video Creation

Ep. 263 "Did you know that YouTube sees a billion hours of video watched daily?"  Kipp. Kieran, and guest Joshua Xu (co-founder and CEO of HeyGen)  dive into applications of AI video in modern business today, recorded from HubSpot's Inbound 2024. Learn more about the dynamic nature of AI videos, the integration of interactive avatars, and the future of personalized and scalable video content. Mentions Indbound https://www.inbound.com/ Joshua Xu https://www.heygen.com/author/joshua-xu HeyGen https://www.heygen.com/ Resource [Free] Steal our favorite AI Prompts featured on the show! Grab them here: https://clickhubspot.com/aip We're on Social Media! Follow us for everyday marketing wisdom straight to your feed YouTube: ​​https://www.youtube.com/channel/UCGtXqPiNV8YC0GMUzY-EUFg  Twitter: https://twitter.com/matgpod  TikTok: https://www.tiktok.com/@matgpod  Join our community https://landing.connect.com/matg Thank you for tuning into Marketing Against The Grain! Don't forget to hit subscribe and follow us on Apple Podcasts (so you never miss an episode)! https://podcasts.apple.com/us/podcast/marketing-against-the-grain/id1616700934   If you love this show, please leave us a 5-Star Review https://link.chtbl.com/h9_sjBKH and share your favorite episodes with friends. We really appreciate your support. Host Links: Kipp Bodnar, https://twitter.com/kippbodnar   Kieran Flanagan, https://twitter.com/searchbrat  ‘Marketing Against The Grain' is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Produced by Darren Clarke.

Episode 25: How can AI transform your personal productivity and growth on platforms like YouTube and Twitter? Matt Wolfe (https://x.com/mreflow) and Nathan Lands (https://x.com/NathanLands) delve into this with vibrant dialogue and invaluable insights from their experiences. This is recorded from HubSpot's Inbound 2024. In this episode, Matt and Nathan discuss leveraging AI for optimizing YouTube titles, creating engaging scripts, and developing effective growth strategies. They share their personal workflows, including the use of tools like Claude, Stable Diffusion, and MidJourney. The episode also covers insightful Twitter growth tactics that helped Nathan skyrocket his follower count from 5,000 to 50,000 in a few months. Check out The Next Wave YouTube Channel if you want to see Matt and Nathan on screen: https://lnk.to/thenextwavepd — Show Notes: (00:00) Using stable diffusion to generate AI art thumbnails. (03:20) Uses AI tool Claude for video title generation. (06:39) Hook, result, tutorial, flow: establishing video structure. (10:48) Utilized Tweet Hunter for style inspiration via AI. (12:44) AI-inspired thread on top people to follow. (16:51) Repurpose YouTube tutorials, create PDFs, build software. (19:01) AI proofreads newsletter for grammar and readability. (23:26) AI simplifies creating consistent newsletters easily. (25:42) Podcast now live, available on YouTube. — Mentions: Inbound 2024: https://www.inbound.com/ Claude: https://claude.ai/ Stable Diffusion: https://stability.ai/ DreamBooth: https://dreambooth.github.io/ Tweet Hunter: https://tweethunter.io/ Midjourney: https://www.midjourney.com/ Leonardo: https://leonardo.ai/ HeyGen: https://www.heygen.com/ — Check Out Matt's Stuff: • Future Tools - https://futuretools.beehiiv.com/ • Blog - https://www.mattwolfe.com/ • YouTube- https://www.youtube.com/@mreflow — Check Out Nathan's Stuff: Newsletter: https://news.lore.com/ Blog - https://lore.com/ The Next Wave is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Darren Clarke // Editing by Ezra Bakker Trupiano

Revolutionizing Social Media with AI: How to Create Your Own AI Influencer!

Welcome to a special weekend edition of Cyber Security Today! In this long weekend episode, we delve into the world of artificial intelligence (AI) and its impact on various sectors, particularly as organizations ramp up their plans for the upcoming year. Join our host Jim Love and a distinguished panel of experts: Evgeny Koloda, Marcel Gagne, John Pinard, and Nicole Bendrich, as they explore the current state of AI, its promises, practical implementations, and the cybersecurity challenges associated with it. Discover valuable takeaways on developing an effective AI strategy and understanding the multi-modal advancements poised to revolutionize industries. 00:00 Introduction to the Special Weekend Edition 00:45 Meet the Expert Panel 02:25 The Promise and Challenges of AI 03:31 The Evolution of AI in Various Industries 06:41 Generative AI and Its Impact 07:53 AI in Cybersecurity 19:00 Human vs. AI: Decision Making and Errors 23:50 The Future of AI and Human Interaction 33:04 Expanding Human Capabilities with AI 35:04 Choosing the Right AI Model 40:09 Navigating AI in Regulated Industries 46:23 The Rise of Deepfakes and Cybersecurity Concerns 59:35 Building an Effective AI Strategy 01:04:15 Conclusion and Final Thoughts Resources: - AI Enterprise level HIPAA complaint GPT platform https://www.aivia.ai/ - EMR with AI capabilities eCW (eClinicalWorks) https://www.eclinicalworks.com/ - Digital Video Twin platform - HeyGen https://www.heygen.com/ - Canadian Digital Twin creation platform - Synthesia https://www.synthesia.io/ - Voice Cloning platform - Eleven Labs https://elevenlabs.io/ - Automation with AI - https://www.make.com Open Router https://openrouter.ai Jan.ai https://jan.ai/

00:00 Introduction and Background 09:44 AI Tools for Research and Content Creation 17:21 The Use of AI in Sales and Business 25:12 Creating Scalable Prompts and an AI-First Culture 32:36 The Future of AI and Business 39:19 Exploring the Capabilities of AI 45:13 Automation with AI 57:14 Addressing Biases and Ethical Considerations 01:06:09 Training Programs and Resources Takeaways AI can be used in various industries, such as marketing and sales, to improve efficiency and personalize interactions. Tools like ChatGPT, Claude, Perplexity, and HeyGen can assist in research, content creation, and role-playing. Creating scalable prompts and developing an AI-first culture can enhance productivity and streamline processes in businesses. Partnering with universities and online platforms can provide opportunities for upskilling employees and expanding knowledge in AI. AI, such as ChatGPT, can analyze images and provide detailed descriptions. AI can assist visually impaired individuals by reading text and describing images. Automation using AI can streamline tasks and improve efficiency. There are potential biases and ethical considerations in AI development and usage. Training programs and resources are available to learn and implement AI effectively.   Market like you mean it. Now go sell something.   Name your price for the Make Every Sale Program here: https://saleswhisperer.gumroad.com/l/OiXZk   SUBSCRIBE to sell more, faster, at higher margins, with less stress, and more fun! https://www.youtube.com/@TheSalesWhispererWes ----- Connect with me: Twitter -- https://twitter.com/saleswhisperer TikTok -- https://www.tiktok.com/@thesaleswhisperer Instagram -- http://instagram.com/saleswhisperer LinkedIn -- http://www.linkedin.com/in/thesaleswhisperer/ Facebook -- https://www.facebook.com/wes.sandiegocrm Facebook Page -- https://www.facebook.com/thesaleswhisperer Vimeo -- https://vimeo.com/thesaleswhisperer Podcast -- https://feeds.libsyn.com/44487/rss YouTube — https://www.youtube.com/@TheSalesWhispererWes Sales Book -- https://www.thesaleswhisperer.com/c/way-book   BUSINESS GROWTH TOOLS https://12WeeksToPeak.com https://CopyByWes.com https://CRMQuiz.com https://TheBestSalesSecrets.com https://MakeEverySale.com https://www.TheSalesWhisperer.com/ https://www.thesaleswhisperer.com/c/ipa

Nathan explores the future of AI-generated video with Joshua Xu, founder of HeyGen, and Victor Lazarte from Benchmark. In this episode of The Cognitive Revolution, we discuss HeyGen's success in practical AI video creation, serving over 40,000 businesses. Learn about the transformative potential of AI in video production, from content translation to personalized experiences, and HeyGen's industry-leading approach to trust and safety. Apply to join over 400 founders and execs in the Turpentine Network: https://hmplogxqz0y.typeform.com/to/JCkphVqj RECOMMENDED PODCAST: Second Opinion A new podcast for health-tech insiders from Christina Farr of the Second Opinion newsletter. Join Christina Farr, Luba Greenwood, and Ash Zenooz every week as they challenge industry experts with tough questions about the best bets in health-tech. Apple Podcasts: https://podcasts.apple.com/us/podcast/id1759267211 Spotify: https://open.spotify.com/show/0A8NwQE976s32zdBbZw6bv SPONSORS: Building an enterprise-ready SaaS app? WorkOS has got you covered with easy-to-integrate APIs for SAML, SCIM, and more. Join top startups like Vercel, Perplexity, Jasper & Webflow in powering your app with WorkOS. Enjoy a free tier for up to 1M users! Start now at https://bit.ly/WorkOS-TCR Oracle Cloud Infrastructure (OCI) is a single platform for your infrastructure, database, application development, and AI needs. OCI has four to eight times the bandwidth of other clouds; offers one consistent price, and nobody does data better than Oracle. If you want to do more and spend less, take a free test drive of OCI at https://oracle.com/cognitive The Brave search API can be used to assemble a data set to train your AI models and help with retrieval augmentation at the time of inference. All while remaining affordable with developer first pricing, integrating the Brave search API into your workflow translates to more ethical data sourcing and more human representative data sets. Try the Brave search API for free for up to 2000 queries per month at https://bit.ly/BraveTCR Omneky is an omnichannel creative generation platform that lets you launch hundreds of thousands of ad iterations that actually work customized across all platforms, with a click of a button. Omneky combines generative AI and real-time advertising data. Mention "Cog Rev" for 10% off https://www.omneky.com/ Head to Squad to access global engineering without the headache and at a fraction of the cost: head to https://choosesquad.com/ and mention “Turpentine” to skip the waitlist. CHAPTERS: (00:00:00) About the Show (00:00:22) Sponsor: WorkOS (00:01:22) About the Episode (00:05:25) Introduction (00:06:15) Joshua's Background (00:09:47) Video Consumption Trends (00:10:49) Creating with HeyGen (00:12:46) Localization Benefits (00:14:02) Cost of Localization (Part 1) (00:16:19) Sponsors: Oracle | Brave (00:18:24) Content Creation (00:19:32) User Journey (00:23:56) Avatar Usage (00:26:33) Engagement vs. Realism (00:31:44) Future of Content (00:33:50) Gaming Applications (Part 1) (00:35:43) Sponsors: Omneky | Squad (00:37:43) Personalization Challenges (00:39:27) Personalized Video Potential (00:42:57) Future of HeyGen (00:44:49) Improving Quality (00:46:53) B-Roll Generation (00:49:13) Creator Experience (00:50:56) AI Tools Integration (00:54:21) Trust and Safety (00:59:35) Celebrity Restrictions (01:01:34) Closing Remarks (01:03:03) Outro --- SOCIAL LINKS: Website : https://www.cognitiverevolution.ai Twitter (Podcast) : https://x.com/cogrev_podcast Twitter (Nathan) : https://x.com/labenz LinkedIn : https://www.linkedin.com/in/nathanlabenz/ Youtube : https://www.youtube.com/@CognitiveRevolutionPodcast Apple : https://podcasts.apple.com/de/podcast/the-cognitive-revolution-ai-builders-researchers-and/id1669813431 Spotify : https://open.spotify.com/show/6yHyok3M3BjqzR0VB5MSyk

Our Social Media Pages, follow us and engage with the Pill-grim community!Join our Entre CommunityInstagramTwitter YouTubeTikTokLinkedIn And now for this week's prescription:On this week's dose, we start (1:50) with a breakdown on Function Health, a startup that aims to empower people to live 100 healthy years through its comprehensive lab tests and personalized health dashboard, and their hearty $53M Series A. Then (10:15), we discuss HeyGen, a startup that's looking to scale visual storytelling for businesses, hot off a $60M Series A. Lastly (18:09), we wrap up this week's dose with a deepdive on Apex, a Los Angeles-based satellite manufacturing startup that secured a $95 million Series B to accelerate production of its "productized" satellite buses.Sources:https://www.functionhealth.com/ https://athletechnews.com/longevity-startup-function-raises-53m-for-personalized-health-testing/ https://www.heygen.com/https://www.heygen.com/article/announcing-our-series-ahttps://www.maginative.com/article/ai-video-startup-heygen-raises-60-million-valued-at/https://www.apexspace.com/https://techcrunch.com/2024/06/11/apex-raises-95m-to-scale-satellite-bus-production/https://spacenews.com/apex-raises-95-million-to-increase-satellite-bus-production/Music Credit: Chapter One by Cole Bauer and Dean Keetonhttps://www.colebauer.com/https://www.instagram.com/deankeeton/?hl=enDisclosure:The views, statements, and opinions,  expressed herein by the hosts and guests are their own, and their appearance on the podcast should not be construed as reflecting the views or implied endorsement of Independent Brokerage Solutions LLC or any of its officers, employees, or agents. The statements made herein should not be considered an investment opinion, advice, or a recommendation regarding securities of any company. This podcast is produced solely for informational purposes and is not to be construed as an offer to sell or the solicitation of an offer to buy a security.

Episode 612: Sam Parr ( https://twitter.com/theSamParr ) and Shaan Puri ( https://twitter.com/ShaanVP ) talk to Sarah Guo ( https://x.com/saranormous ) about the Ai ideas she thinks could be $1B swings. — Show Notes:  (0:00) Intro (4:00) IDEA: AI companions (16:00) IDEA: AI interior design / professional headshots (22:30) IDEA: A richer version of The Sims (25:00) The speedy way to do this if you're non-technical (27:00) IDEA: Your Personal Seller (32:00) IDEA: Generative Voice API for service providers, SMBs, restaurants (38:00) IDEA: Next Gen Auto-Fill (40:00) Software 3.0--what's coming (42:00) Boring verticals fertile for AI: Legal and medical (44:00) Ask: What's already being outsourced? (47:00) Ripe for disruption: energy storage, chips, (49:00) “Ai's $600B Question” (52:00) Sarah Reacts: Doomsday scenarios in Ai (56:30) If you're 22, hungry and optimistic, go west — Links: • Sarah Guo - https://sarahguo.com/ • Conviction - https://www.conviction.com/ • Replika - https://replika.com/ • Character.ai - https://character.ai/ • HeyGen - https://www.heygen.com/ • Icon - https://icon.me/ • Arcads - https://www.arcads.ai/ • Interior AI - https://interiorai.com/ • Aragon - https://aragon.ai/ • Chatbot App - https://chatbotapp.ai/ • Cartesia - https://cartesia.ai/ • Somewhere - https://www.somewhere.com/ • AI's $600B Question - https://www.sequoiacap.com/article/ais-600b-question/ • Eureka Labs - https://eurekalabs.ai/ • Conviction Embed - https://embed.conviction.com/ — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth • Sam's List - http://samslist.co/ My First Million is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano

KI-Übersetzungen begegnen uns heute schon überall: Internet-Browser übersetzen Webseiten, ein Blick durch die Smartphone-Kamera soll Speisekarten in Fremdsprachen verständlich machen und neuere Anwendungen versprechen uns den Dolmetscher für die Hosentasche. Aber wie gut kann die KI das wirklich? Und müssen wir in Zukunft überhaupt noch Sprachen lernen? // Alle Quellen und weitere Spezials findet Ihr hier: https://www.quarks.de/daily-quarks-spezial Von Theresa Gunkel.

In this episode of Create Like the Greats, Ross discusses the significant shift in the business landscape over the past year and how Reddit has emerged as a major beneficiary of this change. He delves into the Google and Reddit partnership, the importance of creating a subreddit, leveraging ads within subreddits, and the value of cross-referencing YouTube videos in search engine results. This episode offers valuable insights for businesses looking to leverage Reddit's growing influence to enhance their digital strategies and engagement. Key Takeaways and Insights The Google and Reddit Partnership - Google announced the helpful content update, highlighting their collaboration with Reddit to enhance the content they index. This partnership allows Google to access valuable user-generated content from Reddit, which had previously been overlooked. Reddit's upcoming IPO further solidifies its position as an influential platform for businesses. Creating a Subreddit - Encouraging companies with a significant customer base to consider creating their own subreddit ensures control over the subreddit's content and prevents the creation of unofficial subreddits. This allows businesses to engage directly with their customers and establish a community. STAT for Keyword Monitoring - Using a tool like STAT, created by the folks at Moz, to identify relevant keywords. STAT allows users to upload and monitor a series of keywords, providing insights into which URLs and domains are showing up in Google more frequently for these keywords compared to your own. This is crucial because, as a marketer, recognizing your SEO competitors can reveal that many people searching for your product or service are landing on Reddit threads. This insight helps in understanding where dialogues about you and your competitors are happening on Reddit, allowing you to engage more effectively with your audience on this platform. Leveraging Ads within Subreddits - A powerful strategy is to run targeted ads directly to specific subreddits where the target audience spends time. This enables businesses to reach a highly engaged and relevant audience, leading to better conversion rates. It is recommended to carefully craft ad content that aligns with the interests and values of the subreddit community. Submitting Content to Relevant Subreddits - To increase visibility and reach a wider audience, businesses should submit their content (such as blog posts, articles, or videos) to relevant subreddits. It is essential to research and understand the target audience's interests and preferences within each subreddit to ensure content resonance. Resources  How Brands Can Use STAT To Thrive Amidst SERP Chaos - https://foundationinc.co/lab/stat-seo-serp/ Reddit - https://www.reddit.com/ STAT - https://getstat.com/ HeyGen - https://heygen.com/?sid=rewardful&via=ross-simmonds —

00:16 - Photorealistic avatars- Full pod at www.youtube.com/@thisweekinpreipostocks- Tiktok avatars for advertising announced- HeyGen round at $500m (built on top of OpenAI/ElevenLabs, $24/month subscription fee, 40,000 customers, $35m ARR in 2023)- Dillon uses ElevenLabs to publish research video in chinese and Spanish- Disruption in the entertainment industry by AI-generated content and avatars18:42 - More secondary market dislocation- Full pod at www.youtube.com/@thisweekinpreipostocks- Revolut at $40b, secondary at $23b … 75% higher vs secondary- UP dislocation: Scale AI closed $13.8b valuation, secondaries at $7.4b last week- DOWN disclocation: Anduril targeting $12.5 valuation, secondaries at $13.2b and Groq targeting $3.0b valuation, secondaries at $4.4b- Are secondaries misjudging company valuations or are companies “managing” their valuations- Time between primary rounds is a factor to secondary market price accuracy24:08 - Tender offers – good for companies, good for investors?- Full pod at www.youtube.com/@thisweekinpreipostocks- VCs need liquidity, DPI back to LPs (distribute cash back to investors)- Employees need liquidity; options expire, life (house, wedding, kids in college, etc)- Structured tenders (e.g. a tender every year or every 6 months) is smart; natural price for stock, no surprises/volatility once stock is public and out of blackout window- Secondary funds are popping up all over the place … SecondaryLink highlights a new fund every week that is raising billions to buy these assets- No IPO for Stripe? “…tenders to happen annually going forward…”

Pre-IPO stock valuations = www.x.com/aarongdillon (see pinned post)Pre-IPO stock index fact sheet = www.agdillon.com/indexPre-IPO stock funds = www.agdillon.com/funds00:06 | No IPOs for Stripe- Online payments company- Stripe co-founder, John Collison; Stripe will continue to do tenders in the future- Two tenders in the last two years, perhaps one tender a year?- Tender offers = no IPO on the horizon- $76b secondary market valuation, +16% vs its last round in Feb 202401:03 | X as “everything app”- X Payments being stood up now- Approved in 28 states, aims to be live by Dec 2024- X Payments will compete with Venmo, Cash App, Zelle- No crypto- Fidelity has X at a $12.5b valuation, ballpark 3x-4x revenue multiple- Payments are foundational to be an everything app, we believe an X App Store is next02:40 | Starlink Mini launched- Starlink Mini is a compact version of standard satellite internet antenna- Weighs 2lbs, 12x10x1.5 inches in size- $599 for mini antenna, $150/month service fee- Starlink has 6,000 satellites in orbit, 3m customers in 100 countries- $192b secondary market valuation, +7% vs its last round in Jan 2024 … $200b tender announced expected to close late summer03:55 | Cerebras AI chip IPO- Hired Citigroup to lead IPO- 2H 2024 for listing- $4b+ IPO valuation, above last round in 202104:36 | SoftBank's $100b for AI companies- Goal is to deliver “artificial super-intelligence”, or ASI- SoftBank owns Arm, AI chip maker- SoftBank activity in the VC market led to the inflated valuations in 2021, could same happen now in AI ecosystem05:17 | New Anthropic AI model- AI large language model company- Claude 3.5 Sonnet launching- 2x as fast as Claude 3 Sonnet; excels in coding, text-based reasoning vs OpenAI GPT-4o- Enterprise pricing = $3 per million tokens fed into the model, $15 per million tokens generated- $1b 2024 revenue forecast- $21b secondary market valuation, +18% vs its last round in Jan 202406:21 | HeyGen raised $60m- AI-driven video content company- $500m valuation- Product = upload video of yourself, photorealistic avatar created, upload transcript, AI avatars reads as if you, translate to 40+ languages- $24/month subscription fee- 40,000 customers- $35m ARR in 2023- HeyGen builds on top of OpenAI and ElevenLabs (“last mile” AI app)08:10 | Revolut tender at $40b!- Morgan Stanley to bank tender offer- $500m raise- £1.7 billion 2023 revenue, +84% vs 2022- $23b secondary market valuation, -31% vs its last primary round in Jul 2021- Recent secondary market buyers stand to make a quick +75% return if $40b valuation holds09:30 | Pre-IPO -1.07% for week, +65.20% for last 1yr- Up week: Chime +22.3%, CoreWeave +19.3%, Wiz +13.1%, Cohere +11.3%, Scale AI +8.8%- Down week: OpenAI -5.5%, Epic Games -4.0%, Deel -2.9%, Bytedance -2.1%, Notion -1.9%- Top valuations: ByteDance $292b, SpaceX $191b, OpenAI $104b, Stripe $76b, Databricks $43b10:27 | 2024 Pre-IPO Stock Vintage Index week performance- www.agdillon.com/index for fact sheet pdf- 2024 Vintage Index top contributors since inception: Rippling +106%, Revolut +52%, Epic Games +44%, Klarna +43%, Anduril +27%- Key metric averages for all Vintage Indexes 5 years old or older…3.31 distributed paid in capital2.05 residual value to paid in capital5.36 total value to paid in capital4.1 years to return the fund

 AI video generation models still have a long way to go when it comes to making compelling and complex videos but the HeyGen team are well on their way to streamlining the video creation process by using a combination of language, video, and voice models to create videos featuring personalized avatars, b-roll, and dialogue. This week on No Priors, Joshua Xu the co-founder and CEO of HeyGen,  joins Sarah and Elad to discuss how the HeyGen team broke down the elements of a video and built or found models to use for each one, the commercial applications for these AI videos, and how they're safeguarding against deep fakes.  Links from episode: HeyGen McDonald's commercial Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil |  @joshua_xu_ Show Notes:  (0:00) Introduction (3:08) Applications of AI content creation (5:49) Best use cases for Hey Gen (7:34) Building for quality in AI video generation (11:17) The models powering HeyGen (14:49) Research approach (16:39) Safeguarding against deep fakes (18:31) How AI video generation will change video creation (24:02) Challenges in building the model (26:29) HeyGen team and company

Jeudi 20 juin, François Sorel a reçu Frédéric Simottel, journaliste BFM Business, Bruno Guglielminetti, journaliste et animateur de « Mon Carnet de l'actualité numérique », et Damien Douani, responsable de l'innovation de l'école Narratiiv et fondateur du cabinet de conseil LAB36. Ils se sont penchés sur la France qui en tête des financements IA Génératives, HeyGen qui est valorisée à 500 millions de dollars, Meta qui réorganise son activité métavers, ainsi que sur l'éventuelle menace pour le climat de Starlink, dans l'émission Tech & Co, la quotidienne, sur BFM Business. Retrouvez l'émission du lundi au jeudi et réécoutez la en podcast.

We begin this week with three thematic discussions. Generative AI myths reviews the recent Stargate rumors and why journalists are so easily co-opted into publishing stories that may have a seed of truth shrouded in impractical, nonsensical claims. We also discuss three news items highlighting how generative AI is transforming the search market and the coalition of companies that want to displace NVIDIA from its generative AI throne. That is followed by an onslaught of news from the past two weeks. We have an LLM rundown that includes announcements from Anthropic, X.ai, Databricks, and AI21 Labs, as well as a dedicated section on OpenAI announcements. Funding highlights include HeyGen and Hailo. There is also news from Adobe, Opera, Samsung, Open Interpreter, and Financial Times. Generative AI News Top Stories of the Week

In this, my second solo episode - I wanted to spend some time trying to demystify Generative AI for CSMs and CS leaders alike. According to statistics, only 25% of CS workers utilize AI in the workplace on a regular basis, which I think is WAY too low - especially considering how stretched thin most CSMs really are.So - in this episode, we focus on proper prompting, a few tools that exist out there and a plethora of use-cases for you to dig into:0:00:00 - Introduction0:03:55 - Topic introduction. Why GenAI for CSMs0:08:42 - Why prompting is a fundamental skill to have0:09:36 - Using the RISEN framework for prompting0:11:31 - Taking care with proprietary and sensitive information when using Gen AI0:19:58 - Why it's a bad idea to just copy and send, without proofreading and personalizing0:23:01 - Utilizing ChatGPTs memory feature to prevent having to copy/paste your prompts0:23:55 - Teaching ChatGPT on my tone of voice0:26:19 - Chaining prompts0:27:55 - Integrating this into your daily workflow0:30:21 - ChatGPT vs. Perplexity vs. Google0:32:42 - Perplexity research use cases for CSMs0:36:30 - The proliferation of new tools0:37:19 - AgentCopilot & HeyGen create personalized video for your contacts at scale0:39:45 - Ariglad analyzes support tickets to create and update knowledge base articles0:40:48 - Malik automates the creation of decks using your data and insights0:41:55 - OutroOne link discussed in the show is the DCS Tech Stack on the website: https://digitalcustomersuccess.com/tech-stack/Enjoy! Support the Show.+++++++++++++++++Like/Subscribe/Review:If you are getting value from the show, please follow/subscribe so that you don't miss an episode and consider leaving us a review. Website:For more information about the show or to get in touch, visit DigitalCustomerSuccess.com. Buy Alex a Cup of Coffee:This show runs exclusively on caffeine - and lots of it. If you like what we're, consider supporting our habit by buying us a cup of coffee: https://bmc.link/dcspThank you for all of your support!The Digital Customer Success Podcast is hosted by Alex Turkovic

Creating content consistently can feel like an uphill battle. From brainstorming ideas to distributing the final piece, the entire process can be daunting. However, with the advent of AI tools, content creators now have the ability to streamline their workflow and enhance their creative processes. In this episode, we explore a variety of AI tools that are revolutionizing the way we create, edit, and distribute content across various platforms. Whether you're a solo creator or part of a larger team, these insights will help you produce content more efficiently and effectively. A Simple Framework for Content Creation Creating content involves several steps — planning, creation, and distribution, each with its own set of challenges. Many creators struggle with coming up with fresh ideas, organizing their thoughts, and ensuring their content reaches the intended audience effectively. This episode outlines a straightforward three-step framework to address these challenges using powerful AI tools, making the process more manageable and less time-consuming. The Planning Phase In the planning phase, AI can offer tremendous help in organizing thoughts and generating new content ideas. Tools like ChatGPT and Oasis can transform random thoughts into structured outlines, while other tools can gather audience insights which can inform content topics. Useful links include: Capturing thoughts and ideas - Chat GPT app (https://chat.openai.com/) - Oasis app (https://www.theoasis.com/) - Cast Magic app (iOS and Android) Sourcing information from the audience - Speak Pipe (https://www.speakpipe.com/hustleandflowchart) - Google Forms (https://hustleandflowchart.com/onething) The Creation Phase During the creation phase, the emphasis shifts to using tools that can help produce audiovisual content from text scripts. Descript and Screen Studio enhance podcast and video production, while Wondercraft and HeyGen introduce innovative ways to convert text into high-quality audio and lifelike avatars. Tools that were highlighted in this discussion: Capturing and editing audio/video - Descript (https://www.descript.com/) - Screen Studio (https://screen.studio/) Creating audio from text - Wonder Craft AI (https://www.wondercraft.ai/) Creating video from text - Heygen (https://www.heygen.com/) Creating music from text - Suno (https://www.suno.com/) Creating videos with text prompts - InVideo (https://invideo.io/) The Distribution and Marketing Phase For the distribution phase, there are tools designed to optimize the reach and engagement of content across various platforms. Opus can identify engaging clips from videos for social media sharing, and Cast Magic assists in repurposing content into blog posts, emails, and other formats to maximize visibility and engagement. Important resources mentioned:  Identifying engaging clips and automating social media posting - Opus Pro (https://opus.pro/) Generating written content from audio/video - CastMagic (https://hustleandflowchart.com/castmagic) use code “Hustle100” for yourself and get a FREE Month Concluding Thoughts AI tools are not just about automation; they are about enhancing creativity and efficiency, allowing creators to produce more meaningful and impactful content. This episode has provided a practical framework encompassing various AI tools that can tackle the common challenges faced during each phase of the content creation process. By incorporating some or all of these tools into your workflow, you can substantially improve the quality of your content and the efficiency of your content production, ultimately leading residents to a more engaged and growing audience. Remember, the key is not just creating content but creating content that resonates and connects with your audience. Happy creating! Two Other Episodes You Should Check Out Unleashing the Power of AI in Content Creation with Ramon Berrios Maximize Your Content: Kick Your Content Creation Into Overdrive with Joe Fier Resources From Episode Accelerate growth with HubSpot's Sales Hub Check out other podcasts on the HubSpot Podcast Network Grab a 30-Day Trial of Kartra Connect with Joe on LinkedIn and Instagram Subscribe to the YouTube Channel Contact Joe: joe@hustleandflowchart.com Thanks for tuning into this episode of the Hustle & Flowchart Podcast! If the information in these conversations and interviews have helped you in your business journey, please head over to iTunes (or wherever you listen), subscribe to the show, and leave me an honest review. Your reviews and feedback will not only help me continue to deliver great, helpful content, but it will also help me reach even more amazing entrepreneurs just like you!

In March I attended SXSW and for 8 days immersed myself in every available AI related keynote or panel discussion.What did I learn?1.No one can say for certain how the future will unfold as we embrace these AI tools and powered robotic technologies2. Whether we like it or not AI is coming to our jobs and those using it - coming for our jobs.3. Resisting it is futile but Embracing it while being cognizant of this full range or risks and ethical issues is essential4. As futurist Amy Webb stated ‘we are in a tech Super cycle that will change every aspect of life and work' and will require governments to prepare for the transformation ahead and for business to reimagine their value networks5. What is certain is that we must focus on our humanity and celebrate what makes us uniquely human - our curiosity, and ability to build meaningful relationships, and find a sense of purpose that transcends algorithms and code.Building on my interview with ChatGPT and as I have reflected I recalled an article I wrote for The Huffington Post called the Future of Getting Lost.So in the spirit of embracing AI I have explored the potential and possibilities of using new AI avatar and chat tools like Hey Gen and Delphi and recorded my thoughts using HeyGEN delivered via my first AI Avatar. Aside from the weird accent it's pretty impressive.Now over to Mark Bot. Hosted on Acast. See acast.com/privacy for more information.

Is this AI tool too good to be safe? Maybe.  We'll be taking a look at Microsoft's impressive VASA-1 deepfake cloning technology. We'll answer the important questions:↳ What is this technology? ↳ Why do we need it? ↳ Is it so good that it's dangerous? Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on Microsoft VASA-1Related Episodes:Ep 211: OpenAI's Sora – The larger impact that no one's talking aboutEp 157: Future of AI Video – Pika Labs 1.0, Runway updates, Meta Emu and moreUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTimestamps:01:20 Daily AI news05:15 Is VASA-1 dangerous?09:12 Potential dangers of AI outweigh potential benefits.12:14 Voice inflection changes, impressive text to speech.15:29 Generative content creation: impressive, concerning, and exciting.18:54 Quickly scalable technology opens exciting possibilities but troubling.21:23 Real-time face swapping with surprising computing power.24:35 Realistic motion control, capturing human-like tendencies.29:26 Use digital avatars for efficient training purposes.30:16 Microsoft research paper VASA 1 creates human-like avatars.34:20 Discussing generative AI's potential benefits versus risks.Topics Covered in This Episode:1. Explanation of VASA-1's capabilities2. Concerns around Microsoft's VASA-13. Discussion on deepfakes4. Potential Risks and Ethical Considerations5. Potential Benefits and Positive Use CasesKeywords:Microsoft's VASA 1, deep fake model, Everyday AI, livestream podcast, AI news, Adobe, Photoshop, Google, DeepMind, Microsoft PHY 3 mini model, OpenAI's SoRUP, AI deepfakes, talking head images, Jordan Wilson, misinformation, disinformation, generative AI, AI's impact on jobs, lifelike talking faces, digital twin technology, AI avatar, AI-generated speech, Mona Lisa, Baidu's Emo, Synthesia, HeyGen, Hour 1, DID platform, training, personalized learning Get more out of ChatGPT by learning our PPP method in this live, interactive and free training! Sign up now: https://youreverydayai.com/ppp-registration/

How will last week's wild events shape the future of Ai video? Kipp and Kieran dive into the rapid rise of AI-created videos and its impact on marketing strategy. Learn more on the future of AI video, the potential legal and ethical challenges, and how it could revolutionize marketing automation, sales, and customer service.  Mentions Fiverr https://www.fiverr.com/ HeyGen https://www.heygen.com/ We're on Social Media! Follow us for everyday marketing wisdom straight to your feed YouTube: ​​https://www.youtube.com/channel/UCGtXqPiNV8YC0GMUzY-EUFg  Twitter: https://twitter.com/matgpod  TikTok: https://www.tiktok.com/@matgpod  Thank you for tuning into Marketing Against The Grain! Don't forget to hit subscribe and follow us on Apple Podcasts (so you never miss an episode)! https://podcasts.apple.com/us/podcast/marketing-against-the-grain/id1616700934   If you love this show, please leave us a 5-Star Review https://link.chtbl.com/h9_sjBKH and share your favorite episodes with friends. We really appreciate your support. Host Links: Kipp Bodnar, https://twitter.com/kippbodnar   Kieran Flanagan, https://twitter.com/searchbrat  ‘Marketing Against The Grain' is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Produced by Darren Clarke.

Ralph and Kasim take a deep dive into the evolving landscape of digital marketing, offering a treasure trove of knowledge gleaned from recent mastermind events. They explore an array of cutting-edge tools shaping the industry: from KNO Commerce and Shopper Approved for capturing post-purchase insights, to Metricool's comprehensive approach to social media management. They also touch on Canva's innovative design solutions, including its AI assistant and brand kit creator, as well as HeyGen and Synthesia.io's prowess in AI-driven video creation. Focusing on e-commerce, Ralph and Kasim discuss the indispensability of tools like SmartScout for Amazon sellers, and the impact of Opus.pro and video.ai in the realm of video marketing. They also dive into Descript's revolutionary approach to video editing through transcript modification. Additionally, the episode highlights the significance of Designer.io in creating compelling lead magnets and ebooks, and Repurpose.io's effectiveness in streamlining content syndication across various platforms. Chapters:00:00:00 - Kick-off: Ralph & Kasim on Recent Mastermind Insights00:03:25 - Tool Exploration: Deep Dive into Post-Purchase Surveys00:11:13 - Lead Generation Talk: Unpacking Leadsy & High Level Strategies00:13:29 - Metrics Mastery: A Close Look at Metricool & HubSpot00:15:35 - Design Revolution: Revisiting Canva's Capabilities & the Wonders of Canva's AI Assistant00:18:47 - Video Content & AI: Introducing HeyGen for AI Video Creation00:21:27 - E-commerce Innovation: SmartScout for Amazon Sellers00:22:53 - Multimedia Tools: The Flexibility of Opus and Video.ai00:28:54 - Content Strategy: Simplifying Repurposing with Designer00:32:07 - Amplifying Reach: Mastering Content SyndicationLINKS AND RESOURCES:How we used Ai and Deep Fakes to create a Spanish version of Perpetual TrafficEpisode 383: Using AI To Create An Ad In Less Than 5 Minutes With Dennis YuGet the 101 on 7-11-4 and improve your customer engagementHigh LevelTier 11 JobsPerpetual Traffic on YouTubeTiereleven.comSolutions 8 Perpetual Traffic SurveyPerpetual Traffic WebsiteFollow Perpetual Traffic on TwitterConnect with Kasim on Twitter and Connect with Ralph on LinkedInThanks so much for joining us this week. Want to subscribe to Perpetual Traffic? Have some feedback you'd like to share? Connect with us on