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Send Everyday AI and Jordan a text messageThe entire AI market is about to go super-friggin-nova in 2025. ↳ I'm not just talking about open source throwing hands with Big Tech (though THAT'S happening). ↳ I'm talking about tectonic shifts that are going to reshape who holds the power, who pays what, how LLMs will work and who's about to get LEFT BEHIND. ↳ From API prices falling through the floor to embodied AI stepping out of sci-fi and into your office – the next wave makes ChatGPT's launch look kinda like a kiddy splash pool. I'm sharing the REAL market forces at play in Vol 2 of our 2025 AI Predictions series: AI Market Forces Collide. 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. Prediction of Open Source Models2. Chinese AI Influence3. Future of Perplexity4. Drop in API prices5. Rise of Embodied AITimestamps:00:00 Jordan's 2024 Predictions Explained03:28 "AI Market Forces Collide"09:25 Open Source Surge in AI Models10:29 Open Source Models Rising15:32 AI's Political Impact by 202519:17 Google's New AI Search Tool21:53 Open Source Impact on AI Pricing22:58 Token Pricing Drop for GPT Models26:35 Embodied AI to Surpass TeslaKeywords:AI predictions, Artificial Intelligence, everyday AI, API, AI models, GPT-4, NVIDIA, GTC conference, generative AI, data collection, livestream, AI companies, AI agents, AI model prices, embodied AI, humanoids, OpenAI, Anthropic, Google Gemini, Perplexity, open source models, language models, Chinese AI, AI audio, aqua hire, large language models, autonomous vehicles, drones, wearable AI, robo taxis. 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/
As revelations about Meta's use of pirated books for AI training send shockwaves through the tech industry, the battle over copyright and AI reaches a critical juncture. In this final episode of The Dynamist's series on AI and copyright, Evan is joined by FAI's Senior Fellow Tim Hwang and Tech Policy Manager Joshua Levine to discuss how these legal battles could determine whether world-leading AI development happens in Silicon Valley or Shenzhen.The conversation examines the implications of Meta's recently exposed use of Library Genesis - a shadow library of pirated books - to train its LLaMA models, highlighting the desperate measures even tech giants will take to source training data. This scandal crystallizes a core tension: U.S. companies face mounting copyright challenges while Chinese competitors can freely use these same materials without fear of legal repercussions. The discussion delves into potential policy solutions, from expanding fair use doctrine to creating new statutory licensing frameworks, that could help American AI development remain competitive while respecting creator rights.Drawing on historical parallels from past technological disruptions like Napster and Google Books, the guests explore how market-based solutions and policy innovation could help resolve these conflicts. As courts weigh major decisions in cases involving OpenAI, Anthropic, and others in 2024, the episode frames copyright not just as a domestic policy issue, but as a key factor in national technological competitiveness. What's at stake isn't just compensation for creators, but whether IP disputes could cede AI leadership to nations with fewer or no constraints on training data.
Hugo speaks with Alex Strick van Linschoten, Machine Learning Engineer at ZenML and creator of a comprehensive LLMOps database documenting over 400 deployments. Alex's extensive research into real-world LLM implementations gives him unique insight into what actually works—and what doesn't—when deploying AI agents in production. In this episode, we dive into: - The current state of AI agents in production, from successes to common failure modes - Practical lessons learned from analyzing hundreds of real-world LLM deployments - How companies like Anthropic, Klarna, and Dropbox are using patterns like ReAct, RAG, and microservices to build reliable systems - The evolution of LLM capabilities, from expanding context windows to multimodal applications - Why most companies still prefer structured workflows over fully autonomous agents We also explore real-world case studies of production hurdles, including cascading failures, API misfires, and hallucination challenges. Alex shares concrete strategies for integrating LLMs into your pipelines while maintaining reliability and control. Whether you're scaling agents or building LLM-powered systems, this episode offers practical insights for navigating the complex landscape of LLMOps in 2025. LINKS - The podcast livestream on YouTube (https://youtube.com/live/-8Gr9fVVX9g?feature=share) - The LLMOps database (https://www.zenml.io/llmops-database) - All blog posts about the database (https://www.zenml.io/category/llmops) - Anthropic's Building effective agents essay (https://www.anthropic.com/research/building-effective-agents) - Alex on LinkedIn (https://www.linkedin.com/in/strickvl/) - Hugo on twitter (https://x.com/hugobowne) - Vanishing Gradients on twitter (https://x.com/vanishingdata) * Vanishing Gradients on YouTube (https://www.youtube.com/channel/UC_NafIo-Ku2loOLrzm45ABA) * Vanishing Gradients on Twitter (https://x.com/vanishingdata) * Vanishing Gradients on Lu.ma (https://lu.ma/calendar/cal-8ImWFDQ3IEIxNWk)
The Twenty Minute VC: Venture Capital | Startup Funding | The Pitch
Victor Riparbelli is the CEO and Co-founder of Synthesia, the world's leading AI video communications platform for enterprises. To date, Victor has raised over $250M from Accel, GV, NEA, and more. More than 1,000,000 users and 55,000 businesses, including 60% of the Fortune 100, use it to communicate efficiently and share knowledge at scale using AI avatars. In Today's Episode with Victor Riperbelli: 1. The Future of Models: Are we seeing the commoditisation of models? Will scaling laws continue to prove out? How far into the application layer will model providers go? Will we see a world of few large generalist models or many fragmented smaller models? X.ai, Anthropic, or OpenAI? Which would Victor most want to invest in and why? 2. The Future of Content: What will the future of content look like? In 5 years time will we have more AI or human made content? What will be the future of distribution for content? Why is TikTok the future for content distribution? How does Victor think about the future of identity verification? What is the right approach? What does everyone think will happen in the future with content that will never happen? 3. Startup Rules That are BS: Why does Victor believe it is total BS to say you have to be the first to a market? Why does Victor believe the speed of execution religion is BS? Why does Victor believe that London and Europe is a great place to start a startup? Does Victor believe Americans work harder than Europeans? Why does Victor believe Europeans are more loyal to their companies?
How close is artificial intelligence to building a catastrophic bioweapon or causing other superhuman damage? WSJ's Sam Schechner reports on the team at Anthropic testing for AI dangers. And the team leader, Logan Graham, explains how the tests work. Further Listening: -Artificial: The OpenAI Story -The Big Changes Tearing OpenAI Apart Further Reading: -Their Job Is to Push Computers Toward AI Doom -AI Startup Anthropic Raising Funds Valuing It at $60 Billion Learn more about your ad choices. Visit megaphone.fm/adchoices
Send Everyday AI and Jordan a text messageLast year, I said don't touch the free version of ChatGPT with a 10-foot pole. Is it still THAT bad? A TON has changed since OpenAI's '12 days of Shipmas' in December. So is the free version of ChatGPT better? Or, are the new paid-only features TOO good to pass up? Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on ChatGPTUpcoming 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. ChatGPT Features and Plans2. Alternatives to ChatGPT3. Shift in OpenAI's Goals4. Updates from OpenAI5. Model Usage and Limits6. ChatGPT Advice and RecommendationsTimestamps:03:00 Daily AI news06:30 ChatGPT free vs. Paid08:18 Free ChatGPT version significantly improved model performance.10:00 Free ChatGPT is decent but not superior.15:03 They aim to replace Google with AI chatbots.17:22 Custom instructions streamline limited ChatGPT use.20:21 Canvas Mode enables inline AI document editing.25:44 Addressing ChatGPT questions; submit queries anytime.28:39 Google VO 2 superior; limited access available now.30:18 Free ChatGPT improved, but Plus requires payment.34:31 Google AI Studio: powerful, free, data-trained trade-off.37:40 Free ChatGPT exists, full features require payment.40:48 Google AI Studio best for literature reviews.44:33 Free version useful, but paid plan recommended.Keywords:ChatGPT, OpenAI, Everyday AI podcast, AI developments, AI news, AI infrastructure, AI use risks, AI applications, large language models, ChatGPT plans, GPT-4, ChatGPT free version, ChatGPT Pro, ChatGPT Plus, AI for business, AI data security, Gemini 2, Claude 35 SONET, GPT-4o, Anthropic, Google AI Studio, Meta Lama, Microsoft Copilot, Typing Mind, Microsoft CoreAI, model training, DALL-E Image Generator, Canvas Mode, AI chat tools, context windows 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/
On this episode of Unsupervised Learning, Razib catches up with Nikolai Yakovenko about the state of AI at the end of 2024. Yakovenko is a former professional poker player,and research scientist at Google, Twitter and Nvidia. With a decade in computer science, Yakovenko has been at the forefront of the large-language-model revolution that has given rise to multi-billion dollar companies like OpenAI, Anthropic and Perplexity and hundreds of smaller startups. Currently, he is the CEO of DeepNewz, an AI-driven news startup that leverages OpenAI's latest model. Full disclosure: Razib actively uses and recommends the service and is an advisor to the company. Razib and Yakovenko first review what makes the last few years special, the rise of large-language-models on top of neural network architecture of transformers. Yakovenkoi discusses how far they've come since OpenAI released ChatGPT to the public in the fall of 2022, and how people have been using the underlying technology to develop applications atop it. Despite predictions of mass unemployment, Razib points out that two years later America is at full employment, and only niche fields like translation have been impacted. In contrast, Yakovenko points out that most software developers use artificial intelligence in some form to aid in their daily engineering work, noting the possibility that the AI revolution is integrating itself seamlessly as a utility for preexistent jobs. They also discuss the fact that though AI is a booming field, only one brand-name company has so far emerged in the industry, OpenAI. Though they agree that the current hype cycle is now abating, it is clear that the major investments in the field like data centers will continue from major players as AI-driven applications like self-driving cars become more and more mainstream.
Since the release of OpenAI's ChatGPT, generative AI tools have been helping us answer questions, write essays and create AI images and videos. But now, tech companies are promising AI tools that actually complete everyday tasks on our behalf. Murad Ahmed is joined by Madhumita Murgia, the FT's AI editor, who has been speaking to Dario Amodei, chief executive of Silicon Valley AI company Anthropic. They discuss plans to create ‘AI agents' that could do anything from replying to emails on our behalf to ordering our weekly grocery shopping online, as well as some of the challenges that leading AI companies face as they develop ever-more sophisticated AI systems. Free to read:Move over copilots: meet the next generation of AI powered assistantsOpenAI bets on AI agents becoming mainstream by 2025Anthropic's Dario Amodei: Democracies must maintain the lead in AIThis season of Tech Tonic is presented by Murad Ahmed, and produced by Persis Love. Edwin Lane is the senior producer and Manuela Saragosa is the executive producer. Sound design by Breen Turner and Samantha Giovinco, with original music from Metaphor Music. The FT's head of audio is Cheryl Brumley.Read a transcript of this episode on FT.com Hosted on Acast. See acast.com/privacy for more information.
Send us a text00:00 - Intro00:16 - TikTok US shutting down at $50b valuation?!08:33 - xAI launches Grok iOS app18:00 - Anthropic raise at $60b
A groundbreaking World Economic Forum report reveals massive shifts ahead in how we work, while Sam Altman drops major hints about AGI and superintelligence in a new Bloomberg interview. Plus, surprising new data on why enterprises are choosing proprietary AI over open source, unpack a $20B investment in U.S. data centers, and examine Anthropic's massive new funding round. In this packed episode, Paul and Mike break down these developments and much more reshaping the AI landscape. Access the show notes and show links here Timestamps: 00:04:55 — World Economic Forum Releases Future of Jobs Report 00:17:35 — Sam Altman's “Reflections” and Bloomberg Interview 00:28:31 — Prophecies of the Flood by Ethan Mollick 00:40:17 — The Law of Uneven AI Distribution 00:44:35 — Notes on the State of AI in the Enterprise from Box CEO Aaron Levie 00:48:47 — Why OpenAI Is Taking So Long to Launch Agents 00:53:11 —CES + AI 00:58:41 — AI Startup Anthropic Raising Funds Valuing It at $60 Billion 01:02:16 — Trump Announces $20B Foreign Investment in New US Data Centers 01:05:52 —Grok/xAI Updates 01:10:02 — AI Researcher François Chollet Co-Founding Nonprofit to Build AGI Benchmarks 01:13:46 — Why Businesses Are Skipping Open-Source Models This episode is brought to you by our AI Mastery Membership, this 12-month membership gives you access to all the education, insights, and answers you need to master AI for your company and career. To learn more about the membership, go to www.smarterx.ai/ai-mastery. As a special thank you to our podcast audience, you can use the code POD150 to save $150 on a membership. Today's episode is also brought to you by Marketing AI Institute's AI for Writers Summit, happening virtually on Thursday, March 6 from 12pm - 5pm Eastern Time. Learn to craft compelling stories faster, boost your productivity, and build a sustainable writing strategy for the years ahead. Choose between free live access or premium tickets with on-demand replay. Don't miss this opportunity to transform your writing. Register now at aiwritersummit.com Visit our website Receive our weekly newsletter Join our community: Slack LinkedIn Twitter Instagram Facebook Looking for content and resources? Register for a free webinar Come to our next Marketing AI Conference Enroll in AI Academy for Marketers
AI to Replace Mid-Level Developers: Meta's 2025 Plan and More AI Advancements In today's episode of Hashtag Trending, host Jim Love delves into the latest advancements in Artificial Intelligence, starting with Meta's plan to replace mid-level software engineers with AI by 2025. The episode also covers UC Berkeley's affordable AI model Sky T1, Accenture's prediction that AI agents will surpass humans as primary app users by 2030, and Anthropic's breakthrough in AI agents with direct computer control. Additionally, the UK aims to build a national AI rival to OpenAI, and TD Bank emerges as a leader in AI innovation and patent filing. 00:00 Introduction and Headlines 00:38 Affordable AI: Sky T1 32B Preview 02:27 Meta's AI-Driven Future 03:43 AI Agents as Primary App Users 05:19 Anthropic's Claude: Direct Computer Control 06:33 UK's Ambitious AI Plans 07:45 Canada's AI Potential and Challenges 09:10 Conclusion and Sign-Off 09:30 Afterword: Canadian Banking Innovation
Follow Prof G Markets: Apple Podcasts Spotify Scott and Ed open the show by discussing Anthropic's upcoming funding round, a huge drawdown in quantum stocks, and Getty Images' acquisition of Shutterstock. Then Scott breaks down the Department of Justice's lawsuit against some of the nation's largest real estate firms, arguing why he believes the move doesn't address the broader housing crisis. Finally, Scott and Ed discuss why Trump wants to buy Greenland and the Panama Canal and explain why the plans are unlikely to materialize. Order "The Algebra of Wealth," out now Subscribe to No Mercy / No Malice Follow the podcast across socials @profgpod: Instagram Threads X Reddit Follow Scott on Instagram Follow Ed on Instagram and X Learn more about your ad choices. Visit podcastchoices.com/adchoices
Our 196th episode with a summary and discussion of last week's* big AI news! *and sometimes last last week's Recorded on 01/10/2024 Join our brand new Discord here! https://discord.gg/wDQkratW Hosted by Andrey Kurenkov and Jeremie Harris. Feel free to email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.ai Read out our text newsletter and comment on the podcast at https://lastweekin.ai/. Sponsors: The Generator - An interdisciplinary AI lab empowering innovators from all fields to bring visionary ideas to life by harnessing the capabilities of artificial intelligence. In this episode: - Nvidia announced a $3,000 personal AI supercomputer called Digits, featuring the GB10 Grace Blackwell Superchip, aiming to lower the barrier for developers working on large models. - The U.S. Department of Justice finalizes a rule restricting the transmission of specific data types to countries of concern, including China and Russia, under executive order 14117. - Meta allegedly trained Llama on pirated content from LibGen, with internal concerns about the legality confirmed through court filings. - Microsoft paused construction on a section of a large data center project in Wisconsin to reassess based on new technological changes. If you would like to become a sponsor for the newsletter, podcast, or both, please fill out this form. Timestamps + Links: (00:00:00) Intro / Banter (00:04:52) Sponsor Break Tools & Apps (00:05:55) Nvidia announces $3,000 personal AI supercomputer called Digits (00:10:23) Meta removes AI character accounts after users criticize them as ‘creepy and unnecessary' Applications & Business (00:16:16) NVIDIA Is Reportedly Focused Towards “Custom Chip” Manufacturing, Recruiting Top Taiwanese Talent (00:21:54) AI start-up Anthropic closes in on $60bn valuation (00:25:38) Why OpenAI is Taking So Long to Launch Agents (00:30:08) TSMC Set to Expand CoWoS Capacity to Record 75,000 Wafers in 2025, Doubling 2024 Output (00:33:10) Microsoft 'pauses construction' on part of data center site in Mount Pleasant, Wisconsin (00:37:23) Google folds more AI teams into DeepMind to ‘accelerate the research to developer pipeline' Projects & Open Source (00:41:59) Cosmos World Foundation Model Platform for Physical AI (00:48:21) Microsoft releases Phi-4 language model on Hugging Face Research & Advancements (00:50:16) PRIME: Online Reinforcement Learning with Process Rewards (00:58:29) ICLR: In-Context Learning of Representations (01:07:38) Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs (01:11:44) METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring (01:15:45) TransPixar: Advancing Text-to-Video Generation with Transparency (01:18:03) The amount of compute used to train frontier models has been growing at a breakneck pace of over 4x per year since 2018, resulting in an overall scale-up of more than 10,000x! But what factors are enabling this rapid growth? Policy & Safety (01:23:45) InfAlign: Inference-aware language model alignment (01:28:44) Mark Zuckerberg gave Meta's Llama team the OK to train on copyrighted works, filing claims (01:33:19) Anthropic gives court authority to intervene if chatbot spits out song lyrics (01:35:57) US government says companies are no longer allowed to send bulk data to these nations (01:39:10) Trump announces $20B plan to build new data centers in the US
Welcome to a new episode of the EUVC podcast, where our good friends Dan Bowyer and Mads Jensen from SuperSeed have a discussion with Lomax Ward, General Partner at Outsized Ventures to cover recent news and movements in the European tech landscape.
The AI Breakdown: Daily Artificial Intelligence News and Discussions
A reading and discussion inspired by: https://www.wsj.com/opinion/trump-can-keep-americas-ai-advantage-china-chips-data-eccdce91 https://www.bloomberg.com/opinion/articles/2025-01-09/chinese-ai-deepseek-shows-why-trump-s-trade-war-will-be-hard-to-win?sref=qUxVp6JU Brought to you by: Vanta - Simplify compliance - https://vanta.com/nlw The Agent Readiness Audit from Superintelligent - Go to https://besuper.ai/ to request your company's agent readiness score. The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: https://pod.link/1680633614 Subscribe to the newsletter: https://aidailybrief.beehiiv.com/ Join our Discord: https://bit.ly/aibreakdown
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
Ranjan Roy from Margins is back for our weekly discussion of the latest tech news. We cover 1) Sam Altman declares the path to AGI is clear 2) Could AGI come before GPT-5? 3) Up next: Superintelligence 4) Anthropic raising $2 billion 5) NVIDIA says robotics is a multi-trillion opportunity 6) NVIDIA has a personal 'supercomputer' 7) Smarter NPCs are here 8) Meta's AI training copyright issues 9) Zuckerberg's fact check reality check 10) Motives of Zuckerberg's moderation moves 11) TikTok ban might actually happen 12) Alex's visit to China --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. For weekly updates on the show, sign up for the pod newsletter on LinkedIn: https://www.linkedin.com/newsletters/6901970121829801984/ Want a discount for Big Technology on Substack? Here's 40% off for the first year: https://tinyurl.com/bigtechnology Questions? Feedback? Write to: bigtechnologypodcast@gmail.com
We're experimenting and would love to hear from you!In today's episode of 'Discover Daily', we explore Anthropic's meteoric rise as the AI startup eyes a staggering $60 billion valuation, backed by major partnerships with tech giants and impressive revenue growth. We then uncover fascinating research about how widespread lead pollution during the Roman Empire may have caused significant cognitive decline, with evidence preserved in Arctic ice cores revealing the extent of this ancient environmental crisis.Our main segment delves into the revolutionary world of AI chips, where innovations are potentially surpassing Moore's Law's traditional limitations. We explore how NVIDIA's groundbreaking Blackwell platform and GB200 NVL72 Superchip are setting new standards in AI processing capabilities, demonstrating unprecedented performance improvements that could reshape the future of computing and artificial intelligence.From Perplexity's Discover Feed: https://www.perplexity.ai/page/roman-empire-lead-poisoning-lo-2TticnTyRcmBLAeTKfupRghttps://www.perplexity.ai/page/anthropic-eyes-60-billion-valu-kKKiArFkRFyRd9rrkEwuDAhttps://www.perplexity.ai/page/ai-chips-may-outpace-moore-s-l-HcJymVppT6CVb.t_Kyjw4QPerplexity is the fastest and most powerful way to search the web. Perplexity crawls the web and curates the most relevant and up-to-date sources (from academic papers to Reddit threads) to create the perfect response to any question or topic you're interested in. Take the world's knowledge with you anywhere. Available on iOS and Android Join our growing Discord community for the latest updates and exclusive content. Follow us on: Instagram Threads X (Twitter) YouTube Linkedin
In this episode, Jaeden Schafer discusses the challenges faced by Alpha Alpha, a German LLM that raised $500 million but struggles to compete with giants like OpenAI and Anthropic. The conversation explores Alpha Alpha's innovative beginnings, their pivot towards enterprise-focused AI solutions, and the competitive landscape of the AI industry. My Podcast Course: https://podcaststudio.com/courses/ Get on the AI Box Waitlist: https://AIBox.ai/ Join my AI Hustle Community: https://www.skool.com/aihustle/about
The Twenty Minute VC: Venture Capital | Startup Funding | The Pitch
Mikey Shulman is the Co-Founder and CEO of Suno, the leading music AI company. Suno lets everyone make and share music. Mikey has raised over $125M for the company from the likes of Lightspeed, Founder Collective and Nat Friedman and Daniel Gross. Prior to founding Suno, Mikey was the first machine learning engineer and head of machine learning at Kensho technologies, which was acquired by S&P Global for over $500 million. In Today's Episode with Mikey Shulman: 1. The Future of Models: Who wins the future of models? Anthropic, OpenAI or X? Will we live in a world of many smaller models? When does it make sense for specialised vs generalised models? Does Mikey believe we will continue to see the benefits of scaling laws? 2. The Future of UI and Consumer Apps: Why does Mikey believe that OpenAI did AI consumer companies a massive disservice? Why does Mikey believe consumers will not choose their model or pay for a superior model in the future? Why does Mikey believe that good taste is more important than good skills? Why does Mikey argue physicists and economists make the best ML engineers? 3. The Future of Music: What is going on with Suno's lawsuit against some of the biggest labels in music? How does Mikey see the future of music discovery? How does Mikey see the battle between Spotify and YouTube playing out? How does Mikey see the battle between TikTok and Spotify playing out?
Undiscovered Entrepreneur ..Start-up, online business, podcast
Did you like the episode? Send me a text and let me know!!In this episode of Business Conversations with Pi, hosted by Skoob, the discussion focuses on essential questions that new entrepreneurs commonly face. Special emphasis is placed on selecting the appropriate business structure, such as sole proprietorship, partnership, LLC, corporation, or S corporation. Skoob and Pi, an AI assistant developed by Anthropic, provide thorough insights and examples to help entrepreneurs make informed decisions. Key considerations, steps for forming a business entity, and helpful resources and books are discussed to guide listeners through their entrepreneurial journey.BOOKS Start Your Own Corporation by Garrett Sutton Small Business for Dummies by Eric Tyson and Jim Schell Limited Liability Companies for Dummies by Jennifer Reuting Legal Guide for Starting & Running a Small Business by Fred S. Steingold00:00 Introduction to Business Conversations with Pi00:38 Meet Your Hosts: Scoob and Pi01:51 Choosing the Right Business Structure03:02 Examples of Business Structures04:00 Best Business Structure for Podcasters04:55 Steps to Forming a Business Entity06:02 Recommended Reading for Business Formation07:31 Final Thoughts and Encouragement08:01 Conclusion and Next Steps Thank you for being a Skoobeliever!! If you have questions about the show or you want to be a guest please contact me at one of these social mediasTwitter......... ..@djskoob2021 Facebook.........Facebook.com/skoobamiInstagram..... instagram.com/uepodcast2021tiktok....... @djskoob2021Email............... Uepodcast2021@gmail.comAcross The Start Line Facebook Community If you would like to be coached on your entrepreneurial adventure please email me at for a 2 hour free discovery call! This is a $700 free gift to my Skoobelievers!! Contact me Now!! On Twitter @doittodaycoachdoingittodaycoaching@gmailcom
Matt Cohen and John Ruffolo discuss the fast-moving events shaping Canada's political and economic landscape. Topics include the fallout from Prime Minister Justin Trudeau's resignation, the complexities of the CRA's proposed capital gains tax adjustments, and the legal challenges tied to Parliament's prorogation. The conversation then pivots to groundbreaking developments in AI, spotlighting RBC's partnership with Cohere to build a generative AI platform. The episode wraps with a critical analysis of the sudden closure of Vancouver-based Bench Accounting and its surprising acquisition.Topics:* (00:45) CRA's enforcement of capital gains tax changes and taxpayer strategies* (02:41) Legislative uncertainty surrounding the federal budget and prorogation* (04:08) Legal arguments challenging prorogation and their implications* (06:04) External perceptions of Canadian governance* (08:22) RBC's partnership with Cohere for AI development* (11:36) Anthropic's funding round and global AI investment trends* (11:52) Bench Accounting's shutdown and its acquisition by employer.comFollow Matt Cohen and Tank Talks here!Podcast production support provided by Agentbee.ai This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit tanktalks.substack.com
Send us a textNEW FUND ANNOUNCEMENT*: The AG Dillon Anduril Pre-IPO Stock Fund is now accepting investors. Anduril Industries is a defense technology company that specializes in building advanced artificial intelligence (AI) and autonomous systems for military and national security purposes. Financial advisors only. Email aaron.dillon@agdillon.com to invest or request fund materials. Note important disclosures at the end of this post.Subscribe to AG Dillon Pre-IPO Stock Research at agdillon.com/subscribe;- Wednesday = secondary market valuations, revenue multiples, performance, index fact sheets- Saturdays = pre-IPO news and insights, webinar replays00:00 - Intro00:07 - Anthropic Targets $60B Valuation with $2B Raise01:33 - Whatnot Hits $4.97B Valuation with $265M Raise02:31 - xAI Reaches $83B Valuation, Launches iOS App for Grok03:55 - SandboxAQ Raises $300M at $5.6B Valuation05:03 - Wiz Prepares for IPO, Valued at $20.5B06:10 - Cohere Launches North, Valued at $5.4B07:38 - Epirus in Talks for $1B Valuation Amid Defense Focus08:38 - Hippocratic AI Raises $141M, Valued at $1.64B09:27 - Pre-IPO Stock Market Weekly Performance10:18 - Pre-IPO Stock Vintage Index Weekly Performance* NOTE: AG Dillon ("AGD") is not affiliated with Anduril. Anduril may require company approval for purchases (aka transfers). AGD has not been pre-approved by Anduril to purchase their stock. AGD purchases pre-IPO stocks in the secondary market and may gain exposure by directly purchasing the stock (on the company's capitalization table) and/or through a third-party fund (aka special purpose vehicle, or SPV).
Meta is ending its fact-checking program in favor of a 'community notes' system similar to X (30+) kottke.org: "oh shit new logo just dropped" Masnick: The Good, The Bad, And The Stupid In Meta's New Content Moderation Policies Social-Media Companies Decide Content Moderation Is Trending Down I watched the Nvidia keynote; can summarize -jj The Bitter Lesson Hank Green's Cripslock Test for AGI Public Domain Day 2025 CES 2025 New AI powered Samsung refrigerators will allow direct grocery ordering with Instacart Gemini is taking over Google TV - in a good way Google's AI Help Me Read feature Deepseek seems to be a big deal: Chinese model, cheaper to train Altman's latest gospel Choose your Silicon Valley Thinkbro Nicvember Post Mortum The Habermas Machine: AI mediating disagreements VPN Demand Surge in Florida after Adult Sites Age Restriction Kicks In Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Download or subscribe to This Week in Google at https://twit.tv/shows/this-week-in-google. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Sponsor: zscaler.com/security
Meta is ending its fact-checking program in favor of a 'community notes' system similar to X (30+) kottke.org: "oh shit new logo just dropped" Masnick: The Good, The Bad, And The Stupid In Meta's New Content Moderation Policies Social-Media Companies Decide Content Moderation Is Trending Down I watched the Nvidia keynote; can summarize -jj The Bitter Lesson Hank Green's Cripslock Test for AGI Public Domain Day 2025 CES 2025 New AI powered Samsung refrigerators will allow direct grocery ordering with Instacart Gemini is taking over Google TV - in a good way Google's AI Help Me Read feature Deepseek seems to be a big deal: Chinese model, cheaper to train Altman's latest gospel Choose your Silicon Valley Thinkbro Nicvember Post Mortum The Habermas Machine: AI mediating disagreements VPN Demand Surge in Florida after Adult Sites Age Restriction Kicks In Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Download or subscribe to This Week in Google at https://twit.tv/shows/this-week-in-google. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Sponsor: zscaler.com/security
Meta is ending its fact-checking program in favor of a 'community notes' system similar to X (30+) kottke.org: "oh shit new logo just dropped" Masnick: The Good, The Bad, And The Stupid In Meta's New Content Moderation Policies Social-Media Companies Decide Content Moderation Is Trending Down I watched the Nvidia keynote; can summarize -jj The Bitter Lesson Hank Green's Cripslock Test for AGI Public Domain Day 2025 CES 2025 New AI powered Samsung refrigerators will allow direct grocery ordering with Instacart Gemini is taking over Google TV - in a good way Google's AI Help Me Read feature Deepseek seems to be a big deal: Chinese model, cheaper to train Altman's latest gospel Choose your Silicon Valley Thinkbro Nicvember Post Mortum The Habermas Machine: AI mediating disagreements VPN Demand Surge in Florida after Adult Sites Age Restriction Kicks In Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Download or subscribe to This Week in Google at https://twit.tv/shows/this-week-in-google. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Sponsor: zscaler.com/security
Meta is ending its fact-checking program in favor of a 'community notes' system similar to X (30+) kottke.org: "oh shit new logo just dropped" Masnick: The Good, The Bad, And The Stupid In Meta's New Content Moderation Policies Social-Media Companies Decide Content Moderation Is Trending Down I watched the Nvidia keynote; can summarize -jj The Bitter Lesson Hank Green's Cripslock Test for AGI Public Domain Day 2025 CES 2025 New AI powered Samsung refrigerators will allow direct grocery ordering with Instacart Gemini is taking over Google TV - in a good way Google's AI Help Me Read feature Deepseek seems to be a big deal: Chinese model, cheaper to train Altman's latest gospel Choose your Silicon Valley Thinkbro Nicvember Post Mortum The Habermas Machine: AI mediating disagreements VPN Demand Surge in Florida after Adult Sites Age Restriction Kicks In Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Download or subscribe to This Week in Google at https://twit.tv/shows/this-week-in-google. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Sponsor: zscaler.com/security
The episode of TheChatGPTReport focuses primarily on CES 2025 highlights and new AI developments, with the biggest news being NVIDIA's Project DIGITS - a $3,000 personal AI supercomputer with the size of a Mac Mini but 1,000x more powerful than a typical laptop. The host also covered exciting developments in AI-powered CAD software, particularly Zoo's new solution that could revolutionize mechanical engineering by reducing design time by up to 50x. Other notable mentions included Anthropic's potential $2 billion fundraising at a $60 billion valuation, Microsoft's $80 billion AI investment plan, and an interesting statistic showing that only 5% of workers use AI tools extensively. Ryan emphasized that many of the CES announcements, while promising, would take time to reach consumers, including Jensen Huang's note that practical quantum computers are likely 20 years away. The episode included a spotlight on creator Jason Zada for his short film made with Google's Veo 2, demonstrating the growing capabilities of AI in creative fields.
Meta is ending its fact-checking program in favor of a 'community notes' system similar to X (30+) kottke.org: "oh shit new logo just dropped" Masnick: The Good, The Bad, And The Stupid In Meta's New Content Moderation Policies Social-Media Companies Decide Content Moderation Is Trending Down I watched the Nvidia keynote; can summarize -jj The Bitter Lesson Hank Green's Cripslock Test for AGI Public Domain Day 2025 CES 2025 New AI powered Samsung refrigerators will allow direct grocery ordering with Instacart Gemini is taking over Google TV - in a good way Google's AI Help Me Read feature Deepseek seems to be a big deal: Chinese model, cheaper to train Altman's latest gospel Choose your Silicon Valley Thinkbro Nicvember Post Mortum The Habermas Machine: AI mediating disagreements VPN Demand Surge in Florida after Adult Sites Age Restriction Kicks In Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Download or subscribe to This Week in Google at https://twit.tv/shows/this-week-in-google. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Sponsor: zscaler.com/security
Meta is ending its fact-checking program in favor of a 'community notes' system similar to X (30+) kottke.org: "oh shit new logo just dropped" Masnick: The Good, The Bad, And The Stupid In Meta's New Content Moderation Policies Social-Media Companies Decide Content Moderation Is Trending Down I watched the Nvidia keynote; can summarize -jj The Bitter Lesson Hank Green's Cripslock Test for AGI Public Domain Day 2025 CES 2025 New AI powered Samsung refrigerators will allow direct grocery ordering with Instacart Gemini is taking over Google TV - in a good way Google's AI Help Me Read feature Deepseek seems to be a big deal: Chinese model, cheaper to train Altman's latest gospel Choose your Silicon Valley Thinkbro Nicvember Post Mortum The Habermas Machine: AI mediating disagreements VPN Demand Surge in Florida after Adult Sites Age Restriction Kicks In Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Download or subscribe to This Week in Google at https://twit.tv/shows/this-week-in-google. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Sponsor: zscaler.com/security
Tons and tons of controversy and fallout from Meta's announced content moderation changes yesterday. I've got I think a fair, comprehensive rundown of all the angles. Interesting new rounds for Bluesky and Anthropic. And the coolest stuff I've seen from CES thus far, including: are rollable laptop screens finally ready for prime time?Sponsors:Acorns.com/rideLinks:Meta's fact-checking changes are just what Trump's FCC head asked for (The Verge)Social-Media Companies Decide Content Moderation Is Trending Down (WSJ)AI Startup Anthropic Raising Funds Valuing It at $60 Billion (WSJ)Lenovo's Latest Laptop Has a Rollable OLED Screen (Wired)BMW's new iDrive turns the whole windshield into a heads-up display (The Verge)New Nike Therapeutic Shoes at CES 2025 Look Like Nothing You've Ever Seen Before (CNET)EcoFlow's Solar hat is better for the planet than your style (Engadget)Anker made a solar beach umbrella, because of course (Engadget)This Slim Little Battery I Saw at CES 2025 Is Like a Tesla Powerwall for Your Fridge (CNET)I Watched a Printer-Size Gadget Boost a Phone's Battery Life in Seconds (CNET)This toaster-looking gadget boosts your phone's battery in seconds (The Verge)If you're constantly losing cables, this could be your ideal charger (The Verge)See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
This Week in Startups is brought to you by… Gusto. Get three months free when you run your first payroll at http://gusto.com/twist Oracle. TWiST listeners can try OCI and save up to 50% on your cloud bill at https://www.oracle.com/twist Squarespace. TWiST listeners: use code TWIST to save 10% off your first purchase of a website or domain: https://www.Squarespace.com/TWIST Today's show: Jason and Alex discuss Meta's moderation announcement, Nvidia's seeming domination in the processor space, Anthropic's $2B raise and some fun products coming out of CES. (0:00) Jason and Alex kick off the show. (5:15) Fire in Pacific Palisades and Malibu: Insurance and Startup Opportunities (9:48) Gusto. Get three months free when you run your first payroll at http://gusto.com/twist (17:32) Meta's New Content Moderation Strategy and Zuckerberg's Motivations (20:09) Oracle. TWiST listeners can try OCI and save up to 50% on your cloud bill at https://www.oracle.com/twist (22:35) More on Zuck's motivations and what the new president can do (30:30) Squarespace. TWiST listeners: use code TWIST to save 10% off your first purchase of a website or domain: https://www.Squarespace.com/TWIST (40:26) NVIDIA's AI Supercomputer Chip and Tech Industry Innovations (49:15) Lenovo's Rollable Laptop and Slack's iOS Integration (56:31) BYD's Supercar and Anthropic's Valuation (1:02:45) Jason's Experience with Luxury Japanese Minivans Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com Check out the TWIST500: https://www.twist500.com Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp Follow Alex: X: https://x.com/alex LinkedIn: https://www.linkedin.com/in/alexwilhelm Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis Thank you to our partners: (9:48) Gusto. Get three months free when you run your first payroll at http://gusto.com/twist (20:09) Oracle. TWiST listeners can try OCI and save up to 50% on your cloud bill at https://www.oracle.com/twist (30:30) Squarespace. TWiST listeners: use code TWIST to save 10% off your first purchase of a website or domain: https://www.Squarespace.com/TWIST Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland Check out Jason's suite of newsletters: https://substack.com/@calacanis Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com Subscribe to the Founder University Podcast: https://www.youtube.com/@founderuniversity1916
Send Everyday AI and Jordan a text messageMeetings. Speeches. Quick thoughts to self. Those words are more than words. That's your company's secret sauce. Philip Kiely, Head of Developer Relations at Baseten, joins us to discuss.Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan and Philip questions on AI transcriptionUpcoming 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. AI Transcription Benefits2. Whisper Model by OpenAI3. Cost of Transcription4. Business Applications for AI TranscriptionTimestamps:00:00 Conversations are gold; AI makes them valuable.03:56 NVIDIA advances exceed Moore's Law; Apple's AI inaccurate.09:48 Text transcription technology error-prone; manual transcription necessary.11:19 Whisper V3: Low error rate, multilingual accuracy.14:58 Whisper rapidly transcribes audio with high efficiency.17:26 Emotion inflection crucial for text-to-speech synthesis.23:58 AI transcriptions need human verification for accuracy.25:35 Chain cheap AI models for efficient calls.30:53 On-device AI less powerful than cloud AI.33:07 Build prototypes now; technology improving rapidly.Keywords:Whisper by OpenAI, Automatic Speech Recognition, Open-source ASR, Accuracy, Multilingual ASR, MIT licensed, Amazon Transcribe, Whisper V3 Turbo, Live transcription, Speech inflection, ChatGPT, Philip Kiely, Jordan Wilson, Everyday AI podcast, Unstructured data, Anthropic funding, NVIDIA AI advancements, Apple AI alerts, AI transcription, Base 10, Searchable data, AI infrastructure platform, AI cost efficiency, Wearable technology, Voice control, On-device inference, Cloud inference, Speech synthesis, Business applications of transcription, Future of work Learn how work is changing on WorkLab, available wherever you get your podcasts.
Copyright law and artificial intelligence are on a collision course, with major implications for the future of AI development, research, and innovation. In this first episode of The Dynamist's four-part series exploring AI and copyright, we're joined by Professor Pamela Samuelson of Berkeley Law, a pioneering scholar in intellectual property law and a leading voice on copyright in the digital age. FAI Senior Fellow Tim Hwang guest hosts. The conversation covers the wave of recent lawsuits against AI companies, including The New York Times suit against OpenAI and litigation facing Anthropic, NVIDIA, Microsoft, and others. These cases center on two key issues: the legality of using copyrighted materials as training data and the potential for AI models to reproduce copyrighted content. Professor Samuelson breaks down the complex legal landscape, explaining how different types of media (books, music, software) might fare differently under copyright law due to industry structure and existing precedent.Drawing on historical parallels from photocopying to the Betamax case, Professor Samuelson provides crucial context for understanding today's AI copyright battles. She discusses how courts have historically balanced innovation with copyright protection, and what that might mean for AI's future. With several major decisions expected in the coming months, including potential summary judgments, these cases could reshape the AI landscape - particularly for startups and research institutions that lack the resources of major tech companies.
Sam Altman, de topman van ChatGPT-maker OpenAI, is aangeklaagd door zijn zus Ann wegens jarenlang seksueel misbruik in haar jeugd. Joe van Burik vertelt erover in deze Tech Update. Sam Altman heeft volgens Ann haar vanaf het eind van de jaren 90 misbruikt en gemanipuleerd. Het misbruik zou zijn begonnen toen zij 3 jaar was en zijn gestopt toen de OpenAI-topman volwassen was en zij nog minderjarig. Zijn zus heeft hem op sociale media eerder al beschuldigd van misbruik. Ze eist van haar broer een schadevergoeding en stelt dat ze ernstige emotionele schade heeft geleden. Ook zou ze steeds hogere medische kosten hebben voor haar psychische behandeling. Bloomberg News heeft het persoonlijk vermogen van Sam Altman vorig jaar geschat op meer dan 2 miljard dollar, ongeveer 1,9 miljard euro. De aanklacht is ingediend bij de rechtbank in de Amerikaanse stad Saint Louis in Missouri. In die staat kunnen mensen aanklachten over seksueel misbruik in hun jeugd indienen totdat ze 31 jaar zijn. Sam Altman reageerde via een bericht op X op de aanklacht. "Deze situatie veroorzaakt enorm veel pijn voor onze hele familie", stelt hij mede namens zijn moeder en broers. Verder in deze Tech Update: OpenAI-concurrent Anthropic heeft bijna een extra investering van 2 miljard dollar voor elkaar, waarmee er in totaal 6 miljard wordt opgehaald tegen een waardering van 60 miljard Nvidia-topman Jensen Huang claimt dat de ontwikkeling van chips voor AI bij zijn bedrijf nog sneller gaat dan de fameuze Moore's Law, die voorschrijft dat elke twee jaar een verdubbeling van aantal transistors en rekenkracht kan worden behaald met halfgeleiders See omnystudio.com/listener for privacy information.