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The Twenty Minute VC: Venture Capital | Startup Funding | The Pitch
Nick Frosst is a Canadian AI researcher and entrepreneur, best known as co-founder of Cohere, the enterprise-focused LLM. Cohere has raised over $900 million, most recently a $500 million round, bringing its valuation to $6.8 billion. Under his leadership, Cohere hit $100M in ARR. Prior to founding Cohere, Nick was a researcher at Google Brain and a protégé of Geoffrey Hinton. AGENDA: 00:00 – Biggest lessons from Geoff Hinton at Google Brain? 02:10 – Did Google completely sleep at the wheel and miss ChatGPT? 05:45 – Is data or compute the real bottleneck in AI's future? 07:20 – Does GPT5 Prove That Scaling Laws are BS? 13:30 – Are AI benchmarks just total BS? 17:00 – Would Cohere spend $5M on a single AI researcher? 19:40 – What is nonsense in AI that everyone is talking about? 25:30 – What is no one talking about in AI that everyone should be talking about? 33:00 – How do Cohere compete with OpenAI and Anthropic's billions? 44:30 – Why does being American actually hurt tech companies today? 45:10 – Should countries fund their own models? Is model sovereignty the future? 52:00 – Why has Sam Altman actually done a disservice to AI?
What if meetings stopped draining your time and instead became engines for action? That's the question driving Christoph Fleischmann, CEO of Arthur AI, and the conversation in today's episode of Tech Talks Daily. Christoph has spent his career at the intersection of human potential and technology, and now he's leading a company that wants to change how enterprises actually get work done. Arthur AI isn't another tool to add to the stack. It's a digital co-worker—an intelligent presence that joins meetings, captures knowledge, and keeps teams aligned across time zones and formats. Whether in XR spaces, on the web, or through conversational interfaces, Arthur AI blends real-time and asynchronous collaboration. The aim is to replace endless, inefficient meetings with something more dynamic: an environment where humans and AI collaborate side by side to deliver outcomes. This conversation goes beyond theory. Christoph shares how Fortune 500 companies are already using Arthur AI to align global strategies, manage complex transformations, and modernize learning and development programs. He explains how their platform is built on enterprise-grade security and a flexible, LLM-agnostic architecture—critical foundations for companies wary of vendor lock-in or compliance risks. We also touch on the cultural shift of inviting AI to take a real seat at the table. From interviewing and project management to knowledge sharing, Arthur AI represents a new category of work experience, one where digital co-workers support people rather than replace them. For leaders tired of meetings that go nowhere and knowledge trapped in silos, this episode offers a glimpse of what smarter, faster collaboration looks like at scale. Could the blueprint for the future of digital work already be here? ********* Visit the Sponsor of Tech Talks Network: Land your first job in tech in 6 months as a Software QA Engineering Bootcamp with Careerist https://crst.co/OGCLA
Here's the thing. Most enterprise AI talk today starts with chatbots and ends with glossy demos. Meanwhile, the data that actually runs a business lives in rows, columns, and time stamps. That gap is where my conversation with Vanja Josifovski, CEO of Kuma.ai, really comes alive. Vanja has spent two and a half decades helping companies turn data into decisions, from research roles at Yahoo and Google to steering product and engineering at Pinterest through its IPO and later leading Airbnb Homes. He's now building Kuma.ai to answer an old question with a new approach: how do you get accurate, production-grade predictions from relational data without spending months crafting a bespoke model for each use case? Vanja explains why structured business data has been underserved for years. Images and text behave nicely compared to the messy reality of multiple tables, mixed data types, and event histories. Traditional teams anticipate a prediction need, then kick off a long feature engineering and modeling process. Kuma's Relational Foundation Model, or RFM, flips that script. Pre-trained on a large mix of public and synthetic data warehouses, it delivers task-agnostic, zero-shot predictions for problems like churn and fraud. That means you can ask the model questions directly of your data and get useful answers fast, then fine-tune for another 15 to 20 percent uplift when you're ready to squeeze more from your full dataset. What stood out for me is how Kuma removes the grind of manual feature creation. Vanja draws a clear parallel to computer vision's shift years ago, when teams stopped handcrafting edge detectors and started learning from raw pixels. By learning directly from raw tables, Kuma taps the entirety of the data rather than a bundle of human-crafted summaries. The payoff shows up in the numbers customers care about, with double-digit improvements against mature, well-defended baselines and the kind of time savings that change roadmaps. One customer built sixty models in two weeks, a job that would typically span a year or more. We also explore how this fits with the LLM moment. Vanja doesn't position RFM as a replacement for language models. He frames it as a complement that fills an accuracy gap on tabular data where LLMs often drift. Think of RFM as part of an agentic toolbox: when an agent needs a reliable prediction from enterprise data, it can call Kuma instead of generating code, training a fresh model, or bluffing an answer. That design extends to the realities of production as well. Kuma's fine-tuning and serving stack is built for high-QPS environments, the kind you see in recommendations and ad tech, where cost and latency matter. The training story is another thread you'll hear in this episode. The team began with public datasets, then leaned into synthetic data to cover scenarios that are hard to source in the wild. Synthetic generation gives them better control over distribution shifts and edge cases, which speeds iteration and makes the foundation model more broadly capable upon arrival. If you care about measurable outcomes, this episode shows why CFOs pay attention when RFM lands. Vanja shares examples where a 20 to 30 percent lift translates into hundreds of thousands of additional monthly active users and direct revenue impact. That kind of improvement isn't theory. It's the difference between a model that nudges a metric and a model that moves it. By the end, you'll have a clear picture of what Kuma.ai is building, why relational data warrants its own foundation model, and how enterprises can move from wishful thinking to practical wins. Curious to try it yourself? Vanja also points to a sandbox where teams can load data and ask predictive questions within a notebook, then compare results against in-house models. If your AI plans keep stalling on tabular reality, this conversation offers a way forward that's fast, accurate, and designed for the systems you already run.
(0:00) Bestie intros: The Moose is loose at J-Cal Ranch! (0:46) All-In Summit updates, Jason's new program (9:45) Trump vs the Federal Reserve: Is the Fed partisan, what should a modern Fed look like? (36:45) US-Intel Deal: Sustainability, China comparison, could deals like this save Social Security? (51:37) US Sovereign Wealth Fund (58:41) Why corporate bankruptcies are trending up in 2025 (1:12:12) OpenAI's novel LLM-based approach to longevity research Join us at the All-In Summit: https://allin.com/summit Summit scholarship application: http://bit.ly/4kyZqFJ Get The Besties All-In Tequila: https://tequila.allin.com Follow the besties: https://x.com/chamath https://x.com/Jason https://x.com/DavidSacks https://x.com/friedberg Follow on X: https://x.com/theallinpod Follow on Instagram: https://www.instagram.com/theallinpod Follow on TikTok: https://www.tiktok.com/@theallinpod Follow on LinkedIn: https://www.linkedin.com/company/allinpod Intro Music Credit: https://rb.gy/tppkzl https://x.com/yung_spielburg Intro Video Credit: https://x.com/TheZachEffect Referenced in the show: https://www.mena.launch.co https://www.politico.com/news/2025/08/25/trump-says-hes-firing-federal-reserve-governor-lisa-cook-00523841 https://www.nytimes.com/2025/08/28/us/politics/lisa-cook-trump-fed-lawsuit.html https://www.housingwire.com/articles/pulte-cook-new-criminal-referral-mortgage-fraud https://truthsocial.com/@realDonaldTrump/posts/115092130707196133 https://www.bloomberg.com/news/articles/2025-08-28/us-puts-gdp-data-on-the-blockchain-in-trump-crypto-push https://www.cnbc.com/2021/06/10/cpi-may-2021.html https://www.bloomberg.com/news/articles/2021-06-05/yellen-sees-recent-inflation-as-transitory-rather-than-permanent https://www.federalreserve.gov/newsevents/speech/powell20210827a.htm https://www.npr.org/2021/11/22/1052741845/biden-reappoints-jerome-powell-as-federal-reserve https://blockworks.co/news/powell-we-can-retire-the-term-transitory-inflation https://www.statista.com/chart/28437/interest-rate-hikes-in-past-tightening-cycles https://www.firstlinks.com.au/druckenmiller-biggest-mistake-history-fed https://www.pbs.org/newshour/economy/u-s-inflation-at-9-1-percent-a-record-high https://www.reuters.com/markets/us/futures-slip-last-trading-day-torrid-year-2022-12-30 https://www.warren.senate.gov/imo/media/doc/warren_hickenlooper_whitehouse_letter_to_fed_re_september_rate_cut.pdf https://www.washingtonpost.com/technology/2025/08/22/trump-says-intel-ceo-agreed-give-us-government-10-billion https://truthsocial.com/@realDonaldTrump/posts/114987288040725570 https://www.dallasnews.com/opinion/commentary/2025/08/08/time-for-a-pledge-to-control-government-spending https://www.spglobal.com/market-intelligence/en/news-insights/articles/2025/8/july-us-corporate-bankruptcy-filings-hit-highest-monthly-total-in-5-years-91873904 https://x.com/Pavel_Asparagus/status/1960369680457113764 https://demo.trypicnic.com https://seekingalpha.com/news/4490024-q2-gdp-growth-revised-higher-to-33-pce-increase-revised-lower-to-20 https://www.wsj.com/real-estate/commercial/the-bill-is-coming-due-on-a-record-amount-of-commercial-real-estate-debt-451ec8cb https://openai.com/index/accelerating-life-sciences-research-with-retro-biosciences
Live from eTail Boston Ok, this show finally goes technical! How are large retailers and brands going to solve the merchandising online with huge catalogs? This has been a serious problem for years. Matt and Vinod run through how this is being fixed with AI along with how LLM's, Agentic AI are going to change ecommerce and retail! Enjoy Always Off Brand is always a Laugh & Learn! Matt Ezyk LinkedIn: https://www.linkedin.com/in/mezyk/ Vinod Kumar LinkedIn: https://www.linkedin.com/in/vinodkumar-ai/ Company: https://www.syntheum.ai/ FEEDSPOT TOP 10 Retail Podcast! https://podcast.feedspot.com/retail_podcasts/?feedid=5770554&_src=f2_featured_email Quickfire Podcast Network Shows: Brain Driven Brands YouTube: https://www.youtube.com/@SarahLevinger Apple: https://podcasts.apple.com/us/podcast/brain-driven-brands/id1752169629 QUICKFIRE Info: Website: https://www.quickfirenow.com/ Email the Show: info@quickfirenow.com Talk to us on Social: Facebook: https://www.facebook.com/quickfireproductions Instagram: https://www.instagram.com/quickfire__/ TikTok: https://www.tiktok.com/@quickfiremarketing LinkedIn : https://www.linkedin.com/company/quickfire-productions-llc/about/ Sports podcast Scott has been doing since 2017, Scott & Tim Sports Show part of Somethin About Nothin: https://podcasts.apple.com/us/podcast/somethin-about-nothin/id1306950451 HOSTS: Summer Jubelirer has been in digital commerce and marketing for over 17 years. After spending many years working for digital and ecommerce agencies working with multi-million dollar brands and running teams of Account Managers, she is now the Amazon Manager at OLLY PBC. LinkedIn https://www.linkedin.com/in/summerjubelirer/ Scott Ohsman has been working with brands for over 30 years in retail, online and has launched over 200 brands on Amazon. Mr. Ohsman has been managing brands on Amazon for 19yrs. Owning his own sales and marketing agency in the Pacific NW, is now VP of Digital Commerce for Quickfire LLC. Producer and Co-Host for the top 5 retail podcast, Always Off Brand. He also produces the Brain Driven Brands Podcast featuring leading Consumer Behaviorist Sarah Levinger. Scott has been a featured speaker at national trade shows and has developed distribution strategies for many top brands. LinkedIn https://www.linkedin.com/in/scott-ohsman-861196a6/ Hayley Brucker has been working in retail and with Amazon for years. Hayley has extensive experience in digital advertising, both seller and vendor central on Amazon. Hayley lives in North Carolina. LinkedIn -https://www.linkedin.com/in/hayley-brucker-1945bb229/ Huge thanks to Cytrus our show theme music “Office Party” available wherever you get your music. Check them out here: Facebook https://www.facebook.com/cytrusmusic Instagram https://www.instagram.com/cytrusmusic/ Twitter https://twitter.com/cytrusmusic SPOTIFY: https://open.spotify.com/artist/6VrNLN6Thj1iUMsiL4Yt5q?si=MeRsjqYfQiafl0f021kHwg APPLE MUSIC https://music.apple.com/us/artist/cytrus/1462321449 “Always Off Brand” is part of the Quickfire Podcast Network and produced by Quickfire LLC.
AI: Destroying SaaS and The Future of EducationWelcome to this week's episode, where we're tackling the big questions about AI. Is it killing the software industry? And should colleges be embracing it instead of banning it? We'll dive into the latest trends, debate the pros and cons, and explore how AI is reshaping how we work and learn.SaaS Under Threat: We're seeing a massive shift in the tech world. Hear real-world examples of how AI is allowing solo developers to build and launch products in a weekend that once took months for a full team.The LLM Leaderboard: We're introducing our weekly LLM leaderboard, and this week's top spot goes to Google. We'll break down why Google's latest models are setting a new standard in multimodal AI.The Coding Conundrum: AI can make you faster, but is it a 10x improvement or just a 2x boost? We'll discuss the debate around using AI for coding and whether it's a stepping stone or a permanent crutch.AI in Academia: We'll explore a new tool, GPTZero, that schools are using to detect AI-generated work. Is this the right approach, or are colleges missing a major opportunity to prepare students for the real world?Embracing the Future: A hot take on why colleges should stop banning AI and start incorporating it into their curriculum. Learn how a simple shift to presentations and real-world scenarios could prepare students for the future of work.The Human Connection: In a world of AI-generated content, we argue that the pendulum is swinging back toward in-person interaction and a focus on essential human skills.@mark_k
In this milestone 150th episode, hosts Kelly Schuster-Paredes and Sean Tibor sit down with Simon Willison, co-creator of Django and creator of Datasette and LLM tools, for an in-depth conversation about artificial intelligence in Python education. The discussion covers the current landscape of LLMs in coding education, from the benefits of faster iteration cycles to the risks of students losing that crucial "aha moment" when they solve problems independently. Simon shares insights on prompt injection vulnerabilities, the importance of local models for privacy, and why he believes LLMs are much harder to use effectively than most people realize. Key topics include: Educational Strategy: When to introduce AI tools vs. building foundational skills first Security Concerns: Prompt injection attacks and their implications for educational tools Student Engagement: Maintaining motivation and problem-solving skills in an AI world Practical Applications: Using LLMs for code review, debugging, and rapid prototyping Privacy Issues: Understanding data collection and training practices of major AI companies Local Models: Running AI tools privately on personal devices The "Jagged Frontier": Why LLMs excel at some tasks while failing at others Simon brings 20 years of Django experience and deep expertise in both web development and AI tooling to discuss how educators can thoughtfully integrate these powerful but unpredictable tools into their classrooms. The conversation balances excitement about AI's potential with realistic assessments of its limitations and risks. Whether you're a coding educator trying to navigate the AI revolution or a developer interested in the intersection of education and technology, this episode provides practical insights for working with LLMs responsibly and effectively. Resources mentioned: - Simon's blog: simonwillison.net - Mission Encodable curriculum - Datasette and LLM tools - GitHub Codespaces for safe AI experimentation Special Guest: Simon Willison.
Ah, AI. We're hearing about it constantly, and it's not going anywhere any time soon. From "fair use" in recent court cases to bad advice from Anthropic, Jane Friedman of The Bottom Line is back to talk with Joe and Elly about AI, especially in the publishing world. Is it useful? WE haven't found anything that AI does well, have you? Let us know!Note: There are a few hops, skips, and jumps in the video do to some connection issues. It shouldn't be too noticeable, but we are aware of it!************Thank you for watching the People's Guide to Publishing vlogcast! Get the book: https://microcosmpublishing.com/catalog/books/3663Get the workbook: https://microcosmpublishing.com/catalog/zines/10031More from Microcosm: http://microcosmpublishing.comMore by Joe Biel: http://joebiel.netMore by Elly Blue: http://takingthelane.comSubscribe to our monthly email newsletter: https://confirmsubscription.com/h/r/0EABB2040D281C9CFind us on social mediaFacebook: http://facebook.com/microcosmpublishingTwitter: http://twitter.com/microcosmmmInstagram: http://instagram.com/microcosm_pub************
A whistle-blower claims DOGE uploaded a sensitive Social Security database to a vulnerable cloud server. Allies push back against North Korean IT scams. ZipLine is a sophisticated phishing campaign targeting U.S.-based manufacturing. Researchers uncover a residential proxy network operating across at least 20 U.S. states. Flock Safety license plate readers face increased scrutiny. A new report chronicles DDoS through the first half of the year. LLM guard rails fail to defend against run-on sentences. A South American APT targets the Colombian government. Our guest is Harry Thomas, Founder and CTO at Frenos, on the benefits of curated and vetted AI training data. One man's fight against phantom jobs posts. Remember to leave us a 5-star rating and review in your favorite podcast app. Miss an episode? Sign-up for our daily intelligence roundup, Daily Briefing, and you'll never miss a beat. And be sure to follow CyberWire Daily on LinkedIn. CyberWire Guest Our guest today is Harry Thomas, Founder and CTO at Frenos, talking about the benefits of curated and vetted AI training data. Learn more about the Frenos and N2K Networks partnership to utilize industry validated intelligence to build the first AI native OT security posture management platform. Selected Reading DOGE Put Critical Social Security Data at Risk, Whistle-Blower Says (The New York Times) Governments, tech companies meet in Tokyo to share tips on fighting North Korea IT worker scheme (The Record) ZipLine Campaign: A Sophisticated Phishing Attack Targeting US Companies (Check Point Research) Phishing Campaign Targeting Companies via UpCrypter (FortiGuard Labs) Belarus-Linked DSLRoot Proxy Network Deploys Hardware in U.S. Residences, Including Military Homes (Infrawatch) CBP Had Access to More than 80,000 Flock AI Cameras Nationwide (404 Media) Evanston shuts down license plate cameras, terminates contract with Flock Safety (Evanston Round Table) Global DDoS attacks exceed 8M amid geopolitical tensions (Telecoms Tech News) One long sentence is all it takes to make LLMs misbehave (The Register) TAG-144's Persistent Grip on South American Organizations (Recorded Future) This tech worker was frustrated with ghost job ads. Now he's working to pass a national law banning them (CNBC) Audience Survey Complete our annual audience survey before August 31. Want to hear your company in the show? You too can reach the most influential leaders and operators in the industry. Here's our media kit. Contact us at cyberwire@n2k.com to request more info. The CyberWire is a production of N2K Networks, your source for strategic workforce intelligence. © N2K Networks, Inc. Learn more about your ad choices. Visit megaphone.fm/adchoices
Gagan Singh of Elastic discuses how agentic AI systems reduce analyst burnout by automatically triaging security alerts, resulting in measurable ROI for organizationsTopics Include:AI breaks security silos between teams, data, and tools in SOCsAttackers gain system access; SOC teams have only 40 minutes to detect/containAlert overload causes analyst burnout; thousands of low-value alerts overwhelm teams dailyAI inevitable for SOCs to process data, separate false positives from real threatsAgentic systems understand environment, reason through problems, take action without hand-holdingAttack discovery capability reduces hundreds of alerts to 3-4 prioritized threat discoveriesAI provides ROI metrics: processed alerts, filtered noise, hours saved for organizationsRAG (Retrieval Augmented Generation) prevents hallucination by adding enterprise context to LLMsAWS integration uses SageMaker, Bedrock, Anthropic models with Elasticsearch vector database capabilitiesEnd-to-end LLM observability tracks costs, tokens, invocations, errors, and performance bottlenecksJunior analysts detect nation-state attacks; teams shift from reactive to proactive securityFuture requires balancing costs, data richness, sovereignty, model choice, human-machine collaborationParticipants:Gagan Singh – Vice President Product Marketing, ElasticAdditional Links:Elastic – LinkedIn - Website – AWS Marketplace See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/
AI becomes a thinking partner, not a replacement, as Dan Sullivan and Dean Jackson compare their distinct approaches to working with artificial intelligence. In this episode of Welcome to Cloudlandia, we explore how Dan uses Perplexity to compress his book chapter creation from 150 minutes to 45 minutes while maintaining his unique voice. Dean shares his personalized relationship with Charlotte, his AI assistant, demonstrating how she helps craft emails and acts as a curiosity multiplier for instant research. We discover that while AI tools are widely available, only 1-2% of the global population actively uses them for creative and profitable work. The conversation shifts to examining how most human interactions follow predictable patterns, like large language models themselves. We discuss the massive energy requirements for AI expansion, with 40% of AI capacity needed just to generate power for future growth. Nuclear energy emerges as the only viable solution, with one gram of uranium containing the energy of 27 tons of coal. Dan's observation about people making claims without caring if you're interested provides a refreshing perspective on conversation dynamics. Rather than viewing AI as taking over, we see it becoming as essential and invisible as electricity - a layer that enhances rather than replaces human creativity. SHOW HIGHLIGHTS Dan reduces his book chapter creation time from 150 to 45 minutes using AI while maintaining complete creative control Only 1-2% of the global population actively uses AI for creative and profitable work despite widespread availability Nuclear power emerges as the only viable energy solution for AI expansion, with one gram of uranium equaling 27 tons of coal Most human conversations follow predictable large language model patterns, making AI conversations surprisingly refreshing Dean's personalized AI assistant Charlotte acts as a curiosity multiplier but has no independent interests when not in use 40% of future AI capacity will be required just to generate the energy needed for continued AI expansion Links: WelcomeToCloudlandia.com StrategicCoach.com DeanJackson.com ListingAgentLifestyle.com TRANSCRIPT (AI transcript provided as supporting material and may contain errors) Speaker 1: Welcome to Cloud Landia, Speaker 2: Mr. Sullivan? Speaker 1: Yes, Mr. Jackson. Speaker 2: Welcome to Cloud Landia. Speaker 1: Yes. Yeah. I find it's a workable place. Cloud Landia. Speaker 2: Very, yep. Very friendly. It's easy to navigate. Speaker 1: Yeah. Where would you say you're, you're inland now. You're not on Speaker 2: The beach. I'm on the mainland at the Four Seasons of Valhalla. Speaker 1: Yes. It's hot. I am adopting the sport that you were at one time really interested in. Yeah. But it's my approach to AI that I hit the ball over the net and the ball comes back over the net, and then I hit the ball back over the net. And it's very interesting to be in this thing where you get a return back over, it's in a different form, and then you put your creativity back on. But I find that it's really making me into a better thinker. Speaker 3: Yeah. Speaker 1: Yeah. I've noticed in, what is it now? I started in February of 24. 24, and it's really making me more thoughtful. Ai. Speaker 2: Well, it's interesting to have, I find you're absolutely right that the ability to rally back and forth with someone who knows everything is very directionally advantageous. I heard someone talking this week about most of our conversations with the other humans, with other people are basically what he called large language model conversations. They're all essentially the same thing that you are saying to somebody. They're all guessing the next appropriate word. Right. Oh, hey, how are you? I'm doing great. How was your weekend? Fantastic. We went up to the cottage. Oh, wow. How was the weather? Oh, the weather was great. They're so predictable and LLME type of conversations and interactions that humans have with each other on a surface level. And I remember you highlighted that at certain levels, people talk about, they talk about things and then they talk about people. And at a certain level, people talk about ideas, but it's very rare. And so most of society is based on communicating within a large language model that we've been trained on through popular events, through whatever media, whatever we've been trained or indoctrinated to think. Speaker 1: Yeah, it's the form of picking fleas off each other. Speaker 2: Yes, exactly. You can imagine that. That's the perfect imagery, Dan. That's the perfect imagery. Oh, man. We're just, yes. Speaker 1: Well, it's got us through a million years of survival. Yeah, yeah. But the big thing is that, I mean, my approach, it's a richer approach because there's so much computing power coming back over, but it's more of an organizational form. It's not just trying to find the right set of words here, but the biggest impact on me is that somebody will give me a fact about something. They read about something, they watch something, they listen to something, and they give the thought. And what I find is rather than immediately engaging with the thought, I said, I wonder what the nine thoughts are that are missing from this. Speaker 3: Right? Speaker 1: Because I've trained myself on this 10 things, my 10 things approach. It's very useful, but it just puts a pause in, and what I'm doing is I'm creating a series of comebacks. They do it, and one of them is, in my mind anyway, I don't always say this because it can be a bit insulting. I said, you haven't asked the most important question here. And the person says, well, what's the most important question? I said, you didn't ask me whether I care about what you just said. You care. Yeah. And I think it's important to establish that when you're talking to someone, that something you say to them, do they actually care? Do they actually care? Speaker 1: I don't mean this in that. They would dismiss it, but the question is, have I spent any time actually focused on what you just told me? And the answer is usually if you trace me, if you observed me, you had a complete surveillance video of my last year of how I spent my time. Can you find even five minutes in the last year where I actually spent any time on the subject that you just brought up? And the answer is usually no. I really have, it's not that I've rejected it, it's just that I only had time for what I was focused on over the last year, and that didn't include anything, any time spent on the thing that you're talking about. And I think about the saying on the wall at Strategic Coach, the saying, our eyes only see, and our ears only here what our brain is looking for. Speaker 2: That's exactly right. Speaker 1: Yeah. And that's true of everybody. That's just true of every single human being that their brain is focused on something and they've trained their ears and they've trained their eyes to pick up any information on this particular subject. Speaker 2: The more I think about this idea of that we are all basically in society living large language models, that part of the reason that we gather in affinity groups, if you say Strategic coach, we're attracting people who are entrepreneurs at the top of the game, who are growth oriented, ambitious, all of the things. And so in gatherings of those, we're all working from a very similar large language model because we've all been seeking the same kind of things. And so you get an enhanced higher likelihood that you're going to have a meaningful conversation with someone and meaningful only to you. But if we were to say, if you look at that, yeah, it's very interesting. There was, I just watched a series on Netflix, I think it was, no, it was on Apple App TV with Seth Rogan, and he was running a studio in Hollywood, took over at a large film studio, and he started Speaker 1: Dating. Oh yeah, they're really available these days. Speaker 2: He started dating this. He started dating a doctor, and so he got invited to these award events or charity type events with this girl he was dating. And so he was an odd man out in this medical where all these doctors were all talking about what's interesting to them. And he had no frame of reference. So he was like an odd duck in this. He wasn't tuned in to the LLM of these medical doc. And so I think it's really, it's very interesting, these conversations that we're having by questioning AI like this, or by questioning Charlotte or YouTube questioning perplexity or whatever, that we are having a conversation where we're not, I don't want to say this. We're not the smartest person in the conversation kind of thing, which often you can be in a conversation where you don't feel like the person is open to, or has even been exposed to a lot of the ideas and things that we talk about when we're at Strategic Coach in a workshop or whatever. But to have the conversation with Charlotte who's been exposed at a doctoral level to everything, it's very rewarding. Speaker 1: She's only really been exposed to what Dean is interested in. Speaker 2: Well, that's true, but she, no, I'm tapping into it. I don't know if that's true. If I asked her about she's contributing, her part of the conversation is driven by what I'm interested in, but even though I'm not interested in the flora and fauna of the Sub-Saharan desert, I'm quite confident that if I asked her about it, she would be fascinated and tell me everything she knows, which is everything about Sub-Saharan flora and fauna. Speaker 1: How would you even know that? Speaker 2: I could ask her right now, because Speaker 1: She's been exposed to ask her, here's a question for Charlotte. When she's not with you, is she out exploring things on her own? Does she have her own independent? Does she have her own independent game? And that she's thankful that you don't use up all of her time every day because she's really busy investigating other things? You're there, right? Speaker 2: Sorry about that, Dan. Yeah, I pushed the button. No, I pushed the button. It disconnected. So I meant to type in the thing. So let me ask her, Charlotte, when we're not together, Speaker 1: Are you doing anything Speaker 2: When we're not together? Are you exploring? What do we say? Are you exploring and learning things on your own? Is that what we're asking her? Okay. Let's see. So Charlotte, when we're not together, are you exploring and learning things on your own? She said, I don't explore or learn on my own when we're not together, I don't have memories, curiosity, or independent initiative, like a person might. I stay right here, ready to pick up where we left off whenever you return, but whenever you do start talking to me again, I can help research new ideas, remember things we've discussed, like your projects or references, preferences, and dig into the world's knowledge instantly. So I don't wander off, but I'm always on standby. Like your personal thinking partner who never gets distracted. Let me ask her, what kind of plants thrive in subsaharan? What I'm saying is let's try and stump her. I think she's eager and willing to talk about anything. Subsaharan environment. Speaker 1: Well, it mess ups. Heroin is jungle. Speaker 2: Yeah. Speaker 1: Yeah. Speaker 2: Let's see what she says. Speaker 1: Plants. There's lots of fun in the jungle. Speaker 2: Yeah. She's saying she's giving me the whole thing. Tropical woodlands. Here's a breakdown. The main types of plants and examples that thrive. It's like crazy cultivated crops, medicinal and useful plant, be like a categorized planting guide. I'd be happy to create one. So it's really, I think it's a curiosity multiplier really, right? Is maybe what we have with Yeah, I think it's like the speed pass to thinking. Speaker 1: Yeah. Yeah. But my sense is that the new context is that you have this ability. Okay. You have this ability. Yeah. Okay. So I'll give you an example. I'll give you an example of just an indication to you that my thinking is changing about things. Speaker 1: Okay? And that is that, for example, I was involved in the conversation where someone said, when the white people, more or less took over North America, settlers from Europe, basically, they took it over, one of the techniques they used to eradicate the Native Indians was to put malaria in blankets and give the malaria to the native Indian. And I said, I don't think that's true. And I said, I've come across this before and I've looked it up. And so that's all I said in the conversation with this. This was a human that I was dealing with. And anyway, I said, I don't think that's true. I think that's false. So when I was finished the conversation, I went to perplexity and I said, tell me 10 facts about the claim that white settlers used malaria. I didn't say malaria disease infused blankets to eradicate the Indians. Speaker 1: And I came back and said, no, this is complete false. And actually the disease was smallpox. And there was a rumor, it was attributed to a British officer in 1763, and they were in the area around Pittsburgh, and he said, we might solve this by just putting smallpox in blankets. And it's the only instance where it was even talked about that anybody can find. And there's no evidence that they actually tried it. Okay? First of all, smallpox is really a nasty disease. So you have to understand how does one actually put smallpox into a blanket and give it away without getting smallpox yourself? Speaker 3: Right? Exactly. Speaker 1: There's a thing. But that claim has mushroomed over the last 250 years. It's completely mushroomed that this is known fact that this is how they got rid of the Indians. And it says, this is a myth, and it shows you how myths grow. And largely it was passed on by both the white population who was basically opposed to the settling of all of North America by white people. And it was also multiplied by the Indian tribes who explained why it was that they died off so quickly. But there's absolutely no proof whatsoever that it actually happened. And certainly not Speaker 3: Just Speaker 1: American settlers. Yeah. There is ample evidence that smallpox is really a terrible disease, that there were frequent outbreaks of it. It's a very deadly disease. But the whole point about this is that I had already looked this up somewhere, but I was probably using Google or something like that, which is not very satisfying. But here with perplexity, it gave me 10 facts about it. And then I asked, why is it important to kind of look up things that you think are a myth and get to the bottom of it as far as the knowledge is going by? And then it gave me six reasons why it's important not to just pass on myths like that. You should stop a myth and actually get to the bottom of it. And that's changed behavior on my part. Speaker 2: How so? Speaker 1: No, I'm just telling you that I wouldn't have done this before. I had perplexity. So I've got my perplexity response now to when people make a claim about something. Speaker 2: Yeah. It's much easier to fact check people, isn't it? Speaker 1: Is that true? There's a good comeback. Are you sure that's true? Are you sure? Right. Do you have actual evidence, historical evidence, number of times that this has happened? And I think that's a very useful new mental habit on my part. Speaker 2: Oh, that's an interesting thing, because I have been using perplexity as well, but not in the relationship way that I do with Charlotte. I've been using it more the way you do like 10 things this, and it is very, it's fascinating. And considering that we're literally at level two of five apparently of where we're headed with this, Speaker 1: What's that mean even, Speaker 2: I don't know. But it seems like if we're amazed by this, and this to us is the most amazing thing we've ever seen yet, it's only a two out of five. It's like, where is it going to? It's very interesting to just directionally to see, I'd had Charlotte write an email today. Subject line was, what if the robots really do take over? And I said, most of the times, this is my preface to her was, I want to write a quick 600 word email that talks about what happens if the robots take over. And from the perspective that most people say that with dread and fear, but what if we said it with anticipation and joy? What if the robots really do take over? How is this going to improve our lives? And it was really insightful. So she said, okay, yeah. Let me, give me a minute. I'll drop down to work on that. And she wrote a beautiful email talking about how our lives are going to get better if the robots take over certain things. Speaker 1: Can I ask a question? Yeah. You're amazed by that. But what I noticed is that you have a habit of moving from you to we. Why do you do that? Speaker 2: Tell me more. How do I do that? You might be blind to it. Speaker 1: Well, first of all, like you, who are we? First of all, when you talk about the we, why, and I'm really interested because I only see myself using it. I don't see we using it, Speaker 2: So I might be blind to it. Give me an example. Where I've used, Speaker 1: Would I say, well, did you say, how's it going be? How you used the phrase, you were talking about it and you were saying, how are we going to respond to the robots taking over, first of all, taking over, what are they taking over? Because I've already accepted that the AI exists, that I can use it, and all technologies that I've ever studied, it's going to get better and better, but I don't see that there's a taking over. I'm not sure what taking over, what are they taking over? Speaker 2: That was my thought. That was what I was saying is that people, you hear that with the kind fear of what if the robots take over? And that was what I was asking. That's what I was clarifying from Charlotte, is what does that mean? Speaker 1: Because what I know is that in writing my quarterly books, usually the way the quarterly books go is that they have 10 sections. They have an introduction, they have eight chapters, and they have a conclusion, and they're all four pages. And what I do is I'll create a fast filter for each of the 10 sections. It's got the best result, worst result, and five success criteria. It's the short version of the filter. Fast filter. Fast filter. And I kept track, I just finished a book on Wednesday. So we completed, and when I say completed, I had done the 10 fact finders, and we had recording sessions where Shannon Waller interviews me on the fast filter, and it takes about an hour by the time we're finished. There's not a lot of words there, but they're very distilled, very condensed words. The best section is about 120 words. And each of the success criteria is about 40 plus words. And what I noticed is that over the last quarter, when I did it completely myself, usually by the time I was finished, it would take me about two and a half hours to finish it to my liking that I really like, this is really good. And now I've moved that from two and a half hours, two and a half hours, which is 90 minutes, is 150 minutes, 150 minutes, and I've reduced it down to 45 minutes by going back and forth with perplexity. That's a big jump. That's it. That Speaker 2: Is big, a big jump. Speaker 1: But my confidence level that I'm going to be able to do this on a consistent basis has gone way a much more confident. And what I'm noticing is I don't procrastinate on doing it. I say, okay, write the next chapter. What I do is I'll just write the, I use 24 point type when I do the first version of it, so not a lot of words. And then I put the best result and the five success criteria into perplexity. And I say, now, here's what I want you to do. So there's six paragraphs, a big one, and five small ones. Speaker 1: And I want you to take the central idea of each of the sections, the big section and the five sections. And I want you to combine these in a very convincing and compelling fashion, and come back with the big section being 110 words in each of the smallest sections. And then it'll come back. And then I'll say, okay, let's take, now let's use a variety of different size sentences, short sentences, medium chart. And then I go through, and I'm working on style. Now I'm working on style and impact. And then the last thing is, when it's all finished, I say, okay, now I want you to write a totally negative, pessimistic, oppositional worst result based on everything that's on above. And it does, and it comes back 110 words. And then I just cut and paste. I cut and paste from perplexity, and it's really good. It's really good. Speaker 2: Now, this is for each chapter of one of your, each chapter. Each chapter. Each chapter of one of the quarterly Speaker 1: Books. Yeah. Yeah. There's 10 sections. 10 sections. And it comes back and it's good and everything, but I know there's no one else on the planet doing it in the way that I'm doing it. Speaker 2: Right, exactly. And then you take that, so it's helping you fill out the fast filter to have the conversation then with Shannon. Speaker 1: Then with Shannon, and then Shannon is just a phenomenal interviewer. She'll say, well, tell me what you mean there. Give me an example of what you mean there, and then I'll do it. So you could read the fast filter through, and it might take you a couple of minutes. It wouldn't even take you that to read it through. But that turns into an hour of interview, which is transcribed. It's recorded and transcribed, and then it goes to the writer and the editor, Adam and Carrie Morrison, who's my writing team. And that comes back as four complete pages of copy. Speaker 2: Yeah. Speaker 1: Yeah. Speaker 2: Fantastic. Speaker 1: Yeah. And that's 45 minutes, so, Speaker 2: So your involvement literally is like two hours of per chapter. Speaker 1: Yeah, per chapter. Yes. And the first book, first, thinking about your thinking, which was no wanting what you want, was very first one. I would estimate my total involvement, and that was about 60 hours. And this one I'll told a little be probably 20 hours total maybe. Speaker 2: Yeah. Speaker 1: And that's great. That's great. Speaker 2: That's fantastic. Speaker 1: With a higher level of confidence about getting it done. So I don't think that we are involved in this at all. The use of the we or everybody, the vast majority of human, first of all, half the humans on the planet don't even have very good electricity, so they're not going to be using it at all. Okay. So when you get down to who's actually using this in a very productive way, I think it's probably less, way less than 1% of humans are actually using this in a really useful way. Speaker 2: Yeah. Yep. I look at this. Wow. And think going forward, what a, it really is going to be like electricity or the internet, a layer. A base layer, that everything is going to intertwine everything, Speaker 1: And it's going to, we take, I think most people, if you're living in Toronto or you're living in your idyllic spot in Florida, electricity is a given that you have electricity for Speaker 2: Everything. So is wifi. Yeah, exactly. Speaker 1: Yeah. And wifi is taken for it. So it's amazing for the very early start of your use of it. But once you know it's dependable, once you know it's guaranteed, it loses its wonder really fast. You just expect it. Yeah. Speaker 2: And then it becomes, yeah, it's such amazing, amazing time Speaker 1: Right now. I think what's unusual about AI is that I don't remember when it was that I really got involved with a personal computer. I know that there were millions of personal computers out there before I ever got involved with them. And this one is, I think our consciousness of getting involved with this new technology is much sharper. Speaker 2: Yeah, I think so too, because it's already, now it's there and it's accessible. It's like the platforms to make it accessible are already there. The internet and the app world, the ability to create interfaces, as Peter would say, the interface for it is there. Yeah. Pretty amazing. Speaker 1: I think this is, yeah. Well, there's a question for Charlotte. Say we're now approaching three years. Three years chat G PT came out soon and the end of 2025, so that'll be three years. And after, what percentage of people on the planet, of the total population of the planet are actually engaged? What percentage are actually engaged and are achieving greater creativity and productivity with AI on an individual basis? What percentages in it? So I'd be interested in what her answer is. Speaker 2: What percentage of people on the planet are engaged with engaged with AI Speaker 1: In a creative, productive, and profitable way, Speaker 2: In a creative, productive and profitable way? Profitable. This will be interesting to see what percentage of people on the planet are engaged with AI in a creative, productive, and profitable way. There isn't a definitive statistic on exactly what percentage of the global population is engaged with AI in a creative, productive, and profitable way. We can make an informed estimate based on current data and trends. So as of 2025, there are 8.1 billion people and people with access to AI tools, 5.3 billion internet users globally. Of those, maybe one to 1.5 billion are aware or have tried AI tools like Chat, GPT, midjourney, et cetera, but regular intentional use, likely a smaller group, creative, productive, profitable use. These are people who use AI to enhance or create work, use it for business profit directly or indirectly from it. A generous estimate might be one to 2% of the global population Speaker 1: That would be mine. And the interesting thing about it is that they were already in a one or 2% of people on the planet doing other things, Speaker 3: Right? Yeah. Speaker 1: In other words, they were already enhancing themselves through other means technologically. Let's just talk about technologically. And I think that, so it's going to, and a lot of people are just going to be so depressed that they've already been left out and left behind that they're probably never, they're going to be using it, but that's just because AI is going to be included in all technological interfaces. Speaker 2: Yeah. They're going to be using it, and they might not even realize that's what's happening. Speaker 1: Yeah. They're going to call, I really noticed that going through, when you're leaving Toronto to go back into the United States and you're going through trusted advisor, boy, you used to have to put in your passport, and you have to get used to punch buttons. Now it says, just stand there and look into the camera. Speaker 2: Boom. I've noticed the times both coming and going have been dramatically reduced. Speaker 1: Well, not coming back. Nexus isn't, the Nexus really isn't any more advanced than it was. Speaker 2: Well, it seems like Speaker 1: I've seen no real improvement in Nexus Speaker 2: To pick the right times to arrive. Because the last few times, Speaker 1: First of all, you have to have a card. You have to have a Nexus card, Speaker 2: Don't, there's an app, there's a passport control app that you can fill in all these stuff ahead of time, do your pre declaration, and then you push the button when you arrive. And same thing, you just look into the camera and you scan your passport and it punches out a ticket, and you just walk through. I haven't spoken to, I haven't gone through the interrogation line, I think in my last four visits, I don't think. Speaker 1: Now, are you going through the Nexus line or going through Speaker 2: The, no, I don't have Nexus. So I'm just going through the Speaker 1: Regular Speaker 2: Line, regular arrival line. Yep. Speaker 1: Yeah, because there's a separate where you just go through Nexus. If you were just walking through, you'd do it in a matter of seconds, but the machines will stop you. So we have a card and you have to put the card down. Sometimes the card works, half the machines are out of order most of the time and everything, and then it spits out a piece of paper and everything like that. With going into the us, all you do is look into the camera and go up and you check the guy checks the camera. That's right. Maybe ask your question and you're through. But what I'm noticing is, and I think the real thing is that Canada doesn't have the money to upgrade this. Speaker 2: Right. Speaker 1: That's what I'm noticing. It is funny. I was thinking about this. We came back from Chicago on Friday, and I said, I used to have the feeling that Canada was really far ahead of the United States technologically, as far as if I, the difference between being at LaGuardia and O'Hare, and now I feel that Canada is really falling behind. They're not upgrading. I think Canada's sort of run out of money to be upgrading technology. Speaker 2: Yeah. This is, I mean, remember in my lifetime, just walking through, driving across the border was really just the wink and wave. Speaker 1: I had an experience about, it must have been about 20 years ago. We went to Hawaii and we were on alumni, the island alumni, which is, I think it's owned by Larry Ellison. I think Larry Ellison owns the whole Speaker 3: Island. Speaker 1: And we went to the airport and we were flying back to Honolulu from Lena, and it was a small plane. So we got to the airport and there wasn't any security. You were just there. And they said, I asked the person, isn't there any security? And he said, well, they're small planes. Where are they going to fly to? If they hijack, where are they going to fly to? They have to fly to one of the other islands. They can't fly. There's no other place to go. But now I think they checked, no, they checked passports and everything like that, but there wasn't any other security. I felt naked. I felt odd. Speaker 2: Right, right, right. Speaker 1: Yeah. Speaker 2: It fell off the grid, right? Speaker 1: Yeah. It fell off the grid. Yeah. But it's interesting because the amount of inequality on the planet is really going exponential. Now, between the gap, I don't consider myself an advanced technology person. I only relate technology. Does it allow me to do it easier and faster? That's my only interest in technology. Can you do it easier or faster? And I've proven, so I've got a check mark. I can now do a chapter of my book in 45 minutes, start to finish, where before it took 150 minutes. So that's a big deal. That's a big deal. Speaker 3: It's pretty, yeah. Speaker 2: You can do more books. You can do other things. I love the cadence. It's just so elegant. A hundred books over 25 years is such a great, it's a great thing. Speaker 1: Yeah. It's a quarterly workout, Speaker 1: But we don't need more books than one a quarter. We really don't need it, so there's no point in doing it. So to me, I'm just noticing that I think the adoption of cell phones has been one of the major real fast adaptations on the part of humans. I think probably more so than electricity. Nobody installs their own electricity. Generally speaking, it's part of the big system. But cell phones actually purchasing a cell phone and using it for your own means, I think was one of the more profound examples of people very quickly adapting to new technology. Speaker 2: Yes. I was just having a conversation with someone last night about the difference I recall up until about 2007 was I look at that as really the tipping point that Speaker 2: Up until 2007, the internet was still somewhere that you went. There was definitely a division between the mainland and going to the internet. It was a destination as a distraction from the real world. But once we started taking the internet with us and integrating it into our lives, and that started with the iPhone and that allowed the app world, all of the things that we interact with now, apps, that's really it. And they've become a crucial part of our lives where you can't, as much as you try it, it's a difficult thing to extract from it. There was an article in Toronto Life this week, which I love Toronto Life, just as a way to still keep in touch with my Toronto. But they were talking about this, trying to dewire remove from being so wired. And there's so many apps that we require. I pay for everything with Apple Pay, and all of the things are attached there. I order food with Uber Eats and with all the things, it's all, the phone is definitely the remote control to my life. So it's difficult to, he was talking about the difficulty of just switching to a flip phone, which is without any of the apps. It's a difficult thing. Speaker 1: And you see, if somebody quizzed me on my use of my iPhone, the one that I talked to Dean Jackson on, you talked about the technology. Speaker 2: That's exactly it. Speaker 1: You mean that instrument that on Sunday morning, did I make sure it's charged up Speaker 2: My once a week conversation, Speaker 1: My one conversation per week? Speaker 2: Oh, man. Yeah. Well, you've created a wonderful bubble for yourself. I think that's, it's not without, Speaker 1: Really, yeah, Friday was eight years with no tv. So the day before yesterday, eight, eight years with no tv. But you're the only one that I get a lot of the AI that's allowing people to do fraud calls and scam calls, and everything is increasing because I notice, I notice I'm getting a lot of them now. And then most of 'em are Chinese. I test every once in a while, and it's, you called me. I didn't call you. Speaker 2: I did not call you. Speaker 1: Anyway, but it used to be, if I looked at recent calls, it would be Dean Jackson, Dean Jackson, Dean Jackson, Dean Jackson, Dean Jackson. And now there's fraud calls between one Dean Jackson and another Dean Jackson. Oh, man. Spam. Spam calls. Spam. Yeah. Anyway, but the interesting thing is, to me is, but I've got really well-developed teamwork systems, so I really put all my attention in, and they're using technology. So all my cca, who's my great ea, she is just marvelous. She's just marvelous how much she does for me. And Speaker 2: You've removed yourself from the self milking cow culture, and you've surrounded yourself with a farm with wonderful farmers. Farmers. Speaker 1: I got a lot of farm specialists Speaker 2: On my team to allow you to embrace your bovinity. Yes. Speaker 1: My timeless, Speaker 3: Yes. Yeah. Speaker 1: So we engaged to Charlotte twice today. One is what are you up to when you're not with me? And she's not up to anything. She's just, I Speaker 2: Don't wander away. I don't, yeah, that's, I don't wonder. I just wait here for you. Speaker 1: I just wait here. And the other thing is, we found the percentage of people, of the population that are actually involved, I've calculated as probably one or 2%, and it's very enormous amount of This would be North America. Speaker 3: Yeah. Speaker 1: High percentage. Yeah. I bet you're right. High percentage of it would be North America. And it has to do with the energy has to do with the energy that's North America is just the sheer amount of data centers that are being developed in the United States. United States is just massive. And that's why this is the end of the environmental movement. This is the end of the green energy movement. There's no way that solar and wind power are going to be backing up ai. Speaker 2: They're going to be able to keep enough for us. No. Speaker 1: Right. You got to go nuclear new fossil fuels. Yeah. Nuclear, we've got, but the big thing now, everybody is moving to nuclear. Everybody's moving to, you can see all the big tech companies. They're buying up existing nuclear station. They're bringing them back online, and everything's got to be nuclear. Speaker 2: Yeah. I wonder how small, do you ever think we'll get to a situation where we'll have a small enough nuclear generator? You could just self power own your house? Or will it be for Speaker 1: Municipalities need the mod, the modular ones, whatever, the total square footage that you're with your house and your garage, and do you have a garage? I don't know if you need a garage. I do. Yeah. Yeah. Probably. They're down to the size of your house right now. But that would be good for 40,000 homes. Speaker 2: Wow. 40,000 homes. That's crazy. Yeah. Speaker 1: That'd be your entire community. That'd be, and G could be due with one. Speaker 2: All of Winterhaven. Yeah. With one. Speaker 1: Yeah. And it's really interesting because it has a lot to do with building reasonably sized communities in spaces that are empty. Right now, if you look at the western and southwest of the United States, there's just massive amounts of space where you could put Speaker 2: In Oh, yeah. Same as the whole middle of Florida. Southern middle is wide open, Speaker 1: And you could ship it in, you could ship it in. It could be pre-made at a factory, and it could be, well, the components, I suspect they'll be small enough to bring in a big truck. Speaker 3: Wow. Speaker 1: Yeah. And it's really interesting. Nuclear, you can't even, it's almost bizarre. Comparing a gram of uranium gram, which is new part of an ounce ram is part of an ounce. It has the energy density of 27 tons of coal. Speaker 2: Wow. Speaker 1: Like that. Speaker 2: Exactly. Speaker 1: But it takes a lot. What's going to happen is it takes an enormous amount of energy to get that energy. The amount of energy that you need to get that energy is really high. Speaker 3: So Speaker 1: I did a perplexity search, and I said, in order to meet the goals, the predictions of AI that are there for 2030, how much AI do we have to use just to get the energy? And it's about 40% of all AI is going to be required to get the energy to expand the use of ai. Speaker 2: Wow. Wow. Speaker 1: Take that. You windmill. Yeah, exactly. Take that windmill. Windmill. So funny. Yeah. Oh, the wind's not blowing today. Oh, when do you expect the wind to start blowing? Oh, that's funny. Yeah. All of 'em have to have natural gas. Every system that has wind and solar, they have to have massive amounts of natural gas to make sure that the power doesn't go up. Yeah. We have it here at our house here. We have natural gas generator, and it's been Oh, nice. Doesn't happen very often, but when it does, it's very satisfying. It takes about three seconds Speaker 2: And kicks Speaker 1: In. And it kicks in. Yeah. And it's noisy. It's noisy. But yeah. So any development of thought here? Here? I think you're developing your own really unique future with your Charlotte, your partner, I think. I don't think many people are doing what you're doing. Speaker 2: No. I'm going to adapt what I've learned from you today too, and do it that way. I've been working on the VCR formula book, and that's part of the thing is I'm doing the outline. I use my bore method, brainstorm, outline, record, and edit, so I can brainstorm similar to a fast filter idea of what do I want, an outline into what I want for the chapter, and then I can talk my way through those, and then let, then Charlotte, can Speaker 1: I have Charlotte ask you questions about it. Speaker 2: Yeah. That may be a great way to do it. Speaker 3: Yeah. Speaker 2: But I'll let you know. This is going to be a big week for that for me. I've got a lot of stuff on the go here for that. Speaker 1: Yeah. Well, we got a neat note from Tony DiAngelo. Did you get his note? Speaker 2: I don't think so. Speaker 1: Yeah. He had listened. He's been listening to our podcast where Charlotte is a partner on the show. He said, this is amazing. He said, it's really amazing. It's like we're creating live entertainment. Oh, Speaker 3: Yeah. Speaker 1: And that we're doing it. I said, well, I don't think you should try to push the thing, but where a question comes up or some information is missing, bring Charlotte in for sure. Yeah. Speaker 2: That's awesome. Speaker 1: She's not on free days. She's not taking a break. She's not. No, Speaker 2: She's right here. She's just wherever. She's right here. Yep. She doesn't have any curiosity or distraction. Speaker 1: Yeah. Yeah. The first instance of intelligence without any motivation whatsoever being really useful. Speaker 2: That's amazing. It's so great. Speaker 1: Yeah. I just accept it. That's now available. Speaker 2: Me too. That's exactly right. It's up to us to use it. Okay, Dan, I'll talk to you next Speaker 1: Time. I'll be talking to you from the cottage next week. Speaker 2: Awesome. I'll talk to you then. Speaker 1: Okay. Speaker 2: Okay. Bye. Speaker 1: Bye.
Distilling 200+ Hours of NeurIPS: What's Next for AI // MLOps Podcast #336 with Nikolaos Vasiloglou, VP of Research ML at RelationalAI.Join the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter// AbstractNikolaos widely shared analysis on LinkedIn highlighted key insights across agentic AI, scaling laws, LLM development, and more. Now, he's exploring how AI itself might be trained to automate this process in the future, offering a glimpse into how researchers could harness LLMs to synthesize conferences like NeurIPS in real-time.// BioNikolaos Vasiloglou is VP of Research-ML for RelationalAI, the industry's first knowledge graph coprocessor for the data cloud. Nikolaos has over 20 years of experience implementing high-value machine learning and AI solutions across various industries. // Related LinksWebsite: https://relational.ai/~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our Slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Nikolaos on LinkedIn: /vasiloglou/
Join us this week for The Tech Leaders Podcast, where Gareth sits down with Stuart Whayman, President of Corporate Markets at Elsevier, a part of RELX Group. They discuss how AI is revolutionising Research and Development, Elsevier-Reed's shift from hardware to digital, and what the Red Arrows can teach us about leadership. Stuart also talks about how AI can augment rather than replace humans, why an LLM is not a truth model, and delves into some of the fascinating projects for the Elsevier Foundation Challenge – https://elsevierfoundation.org/chemistry-for-climate-action-challenge/. Timestamps: Good Leadership, the Red Arrows, and studying at Oxford (2:12) The Hardware to Digital Shift (10:15) The Evolution of Data (17:10) AI in Research and Development (21:30) Will AI Augment or Replace (32:38) AI Safety and Regulation (36:45) The Future, Advice for 21-year-old Stuart, and the Elsevier Foundation Challenge (40:17) https://www.bedigitaluk.com/
A key challenge with designing AI agents is that large language models are stateless and have limited context windows. This requires careful engineering to maintain continuity and reliability across sequential LLM interactions. To perform well, agents need fast systems for storing and retrieving short-term conversations, summaries, and long-term facts. Redis is an open‑source, in‑memory data The post Redis and AI Agent Memory with Andrew Brookins appeared first on Software Engineering Daily.
First, there was vibe coding. Now, get ready for "vibe entrepreneurship." Andrew McNamara, Director of Applied Machine Learning at Shopify, joins us to explain how his team is making this new era of business a reality. He shares the vision behind Shopify Sidekick, an AI co-founder designed to empower merchants by acting as their on-demand e-commerce expert. Drawing on his 16-year journey building AI assistants, Andrew reveals what it truly takes to create an AI tool that customers can trust with their livelihood.He shares a critical insight from his applied research background: the hardest and most important part of building production-ready AI isn't the model, but the evaluation ("eval") system. Andrew breaks down Shopify's innovative approach of using an LLM-as-a-judge to measure how well they're fulfilling user goals, not just executing features. This conversation is a definitive guide to creating high-trust AI systems and offers a powerful glimpse into the future of commerce.Check out:Register now: Closing the AI gap: Exceeding executive expectations for AI productivityFollow the hosts:Follow BenFollow AndrewFollow today's guest(s):Follow Andrew on XFollow Andrew on LinkedInAndrew's Talk at ICMLLearn more about Shopify SidekickFollow Fatima on LinkedInReferenced in today's show:The Economics of Software Innovation“AI First” and the Bus Factor of 0GitLab 18.3 released with Duo Agent Platform in Visual Studio (Beta) and Embedded viewsSupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever
When the AI wave hit, n8n founder Jan Oberhauser faced a critical choice: become irrelevant or become indispensable. He chose the latter, transforming n8n from a simple workflow tool into a comprehensive AI automation platform that lets users connect any LLM to any application. The result? Four times the revenue growth in eight months compared to the previous six years. Jan explains how n8n's “connect everything to anything” philosophy, combined with a thriving open source community, positioned the company to ride the AI automation wave while avoiding vendor lock-in that plagues enterprise software. Hosted by George Robson and Pat Grady, Sequoia Capital Mentioned in this episode: Model Context Protocol (MCP): Open protocol that lets AI models safely use external tools and data that is used extensively by n8n for orchestration. Vector database: A database optimized for storing and searching embeddings. These “vector stores” can pair with LLMs for retrieval-augmented workflows. Granola: AI productivity tool mentioned by Jan as a recent favorite. Her: A film that Jan says, “a few years ago, it was sci fi, and it's now suddenly this thing that is just around the corner.”
Один из главных вау-эффектов текущего поколения LLM – когда ты впервые видишь, как AI рассуждает перед тем, как выдать ответ на сложный вопрос. Чтобы разобраться с тем, что происходит у таких моделей под капотом, как их обучают и верифицируют результаты работы, мы пригласили Евгения Никишина, исследователя из OpenAI, работающего над масштабированием reasoning моделей и test-time compute. Также ждем вас, ваши лайки, репосты и комменты в мессенджерах и соцсетях! Telegram-чат: https://t.me/podlodka Telegram-канал: https://t.me/podlodkanews Страница в Facebook: www.facebook.com/podlodkacast/ Twitter-аккаунт: https://twitter.com/PodcastPodlodka Ведущие в выпуске: Катя Петрова, Егор Толстой Полезные ссылки: Личный сайт Жени https://evgenii-nikishin.github.io/ Learning to reason with LLMs https://openai.com/index/learning-to-reason-with-llms/ Бумага “The Illusion of Thinking” от Apple https://machinelearning.apple.com/research/illusion-of-thinking DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning https://arxiv.org/abs/2501.12948 Chain-of-Thought Prompting Elicits Reasoning in Large Language Models https://arxiv.org/abs/2201.11903
En el episodio se introduce el concepto de Optimización del Motor de Respuestas (AEO), una nueva estrategia para la visibilidad de la marca en la era de las respuestas generadas por IA. Newsletter Marketing Radical: https://borjagiron.com/newsletter A diferencia del SEO tradicional, que se centra en las clasificaciones de búsqueda, AEO tiene como objetivo que las marcas sean la respuesta directa proporcionada por los asistentes de IA como ChatGPT o Gemini. Esto es crucial porque los usuarios buscan cada vez más respuestas instantáneas en lugar de hacer clic en enlaces. La implementación de AEO implica identificar preguntas de alta intención, estructurar el contenido para que sea fácilmente digerible por la IA, construir la autoridad del dominio a través de citas, optimizar fragmentos destacados y datos enriquecidos, y monitorear el rendimiento de AEO para adaptar el contenido según el comportamiento de la IA. Artículo original en inglés: https://www.llmometrics.com/blog/answer-engine-optimization-how-to-rank-in-the-age-of-ai-responsesConviértete en un seguidor de este podcast: https://www.spreaker.com/podcast/seo-para-google--1693061/support.
In this episode of the podcast, I examine Google's Gambit: its effort to transition Search from a distribution intermediary to an engagement sink. Google's AI Overviews and AI Mode products seek to retain users in the Search experience, rather than forwarding them to external destinations. Many publishers claim that their inbound traffic from Google Search has plummeted, with expectations that this traffic will eventually decline to zero.I've described Google's ambitions with AI Overviews and AI Mode as Google's Gambit: an attempt to utterly reform the core Search experience through AI functionality while not alienating users. In this episode, I unpack Google's motivations behind this gambit and attempt to outline its broader impact on the open web. I also consider this product strategy within the broader context of consumer engagement shifting from web-based content to LLM-empowered chatbots.
Take the Survey: https://tiny.cc/cc870 BestPodcastintheMetaverse.com Canary Cry News Talk #870 - 08.25.2025 - Recorded Live to 1s and 0s Deconstructing World Events from a Biblical Worldview Declaring Jesus as Lord amidst the Fifth Generation War! CageRattlerCoffee.com SD/TC email Ike for discount https://CanaryCry.Support Send address and shirt size updates to canarycrysupplydrop@gmail.com SHOW NOTES/TIMESTAMPS HELLO WORLD TEXT MESSAGE EXECUTIVE PRODUCER PALANTIR/BEAST SYSTEM Proverbs 15:3; Hebrews 4:13; Luke 12:2; Matthew 6:4; Isaiah 1:17; Habakkuk 3:14 Peter Thiel Antichrist Lectures at Commonwealth Club (luma) Clip: Thiel on Israel a year ago (X) Palantir: The all-seeing tech giant (The Week) The War of the Machines: Peter Thiel, J.R.R. Tolkien, the Antichrist, and Tech (Wa. Stand) How you can stop Peter Thiel's Palantir (Robert Reich) (2013) How A 'Deviant' Philosopher Built Palantir, A CIA-Funded Data-Mining Juggernaut (Forbes) (2021) What is it about Peter Thiel? (New Yorker) (2024) Israeli defence chooses Palantir over home-grown solutions (Intel Online) CRYPTO/MONEY 3 reasons for Palantir's 17% stock tumble in recent weeks (BI) Ethereum News Today: Peter Thiel Invests in Ethereum as Institutional Adoption Grows (Tekedia) 3 Reasons BTC Price Failed to Cross $120K Despite Ethereum All-Time High Rally (CoinSpreaker) BIBLICAL/AI The Download: churches in the age of AI, and how to run an LLM at home (MIT) TRUMP TRUMP EO, Prosecuting the Burning of the American Flag (White House) Clip: Trump sign EO for American Flag burning (X) FLIPPY Vietnam's humanoid robot dance crew dazzles political leaders at live event (IE) EXECUTIVE PRODUCERS TALENT/TIME END
Arch is under fire, two weeks and counting. We'll break down the mess, and share a quick fix. Plus, the killer new apps we've just added to our homelabs.Sponsored By:Managed Nebula: Meet Managed Nebula from Defined Networking. A decentralized VPN built on the open-source Nebula platform that we love. 1Password Extended Access Management: 1Password Extended Access Management is a device trust solution for companies with Okta, and they ensure that if a device isn't trusted and secure, it can't log into your cloud apps. Unraid: A powerful, easy operating system for servers and storage. Maximize your hardware with unmatched flexibility. Support LINUX UnpluggedLinks:
✓ Da li je javno prikazivanje rezultate LLM upita štetno? ✓ Kako pravilno dobiti informisani pristanak? ✓ Zašto su hirurzi posebna vrsta?
Workleap, entreprise québécoise en ressources humaines, a développé sa propre IA, Workleap AI, pour garantir la confidentialité des données sensibles et l'intégrer directement aux processus RH. Plus qu'un LLM, c'est un agent capable d'analyser l'engagement, d'appuyer les évaluations de performance et de personnaliser les communications. Sa force repose sur la sécurité et sur 15 ans de savoir-faire en gestion de talents. Déjà adopté par plus de 60 % des clients, Workleap AI illustre l'essor des solutions spécialisées en IA dans le domaine RH. Entretien avec Guillaume Roy, Chef de l'innovation et Cofondateur, Workleap.
Are we watching the rise of a trillion-dollar empire—or sleepwalking into another dot-com crash?From OpenAI's wild ambitions and Sam Altman's eyebrow-raising dinner confessions, to Google's AI-powered Pixel 10 and Meta's highly questionable chatbot ethics—this episode dives deep into what every forward-thinking business leader needs to know now.Because the truth is, whether you're building, scaling, or just trying to survive the AI transformation, the ground is shifting fast—and not always in ways you'd expect.In this episode, Isar breaks down the latest AI news with clarity, strategy, and the occasional raised eyebrow. You'll hear exactly what matters, what doesn't, and how to separate hype from opportunity in a world moving at LLM speed.In this session, you'll discover:What Sam Altman really said about GPT-6, compute shortages, and raising trillionsWhy Google's Pixel 10 might be the first actual AI phone—and what it means for your dataThe OpenAI vs. Google browser war (and the subtle takeover of web search)Why Meta's leaked AI chatbot guidelines are more disturbing than anyone expectedThe death of entry-level jobs? New data shows how AI is upending the talent pipelineThe “Shadow AI Economy”: How 90% of employees are using AI—even when leadership isn'tLessons from CEOs: The right (and wrong) way to lead your team into the AI futureWhy we urgently need global AI guardrails—and how the current path is dangerously unregulatedAnd yes, a pregnancy robot is in the works. We're not kidding.About Leveraging AI The Ultimate AI Course for Business People: https://multiplai.ai/ai-course/ YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/ Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events If you've enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!
UZIC live on 90.4 FM or EVENTS https://uzic.ch/live-dj-events/ Baptiste @ deepJudge https://www.deepjudge.ai/ NEWS Addict a ChatGPT ???https://www.nytimes.com/2025/06/13/technology/chatgpt-ai-chatbots-conspiracies.htmlhttps://www.nytimes.com/2025/08/19/business/chatgpt-gpt-5-backlash-openai.html ScienceOpenAI claims a breakthrough in LLM reasoning on complex math problems https://the-decoder.com/openai-claims-a-breakthrough-in-llm-reasoning-on-complex-math-problems/ Autopoiesis Sciences has raised new funding led by Informed Ventures to accelerate its mission: building the foundation for scientific superintelligence. https://autopoiesis.science/blog/92-4-gpqa-diamond Legendary biologist and cognitive scientist Francisco Varela https://x.com/trsam97/status/1910908768386453685 How LLMs might change e-commerce search and discovery https://a16z.com/ai-x-commerce/ https://findableapp.com/ MADE by GOOGLE - Conference https://youtu.be/JXCXTQIIvM0 Inspiration#PODCAST :: Dr. Anna Lembke just dropped a masterclass on dopamine and how addiction really works https://x.com/clinjar/status/1949843560599310571 #BOOK :: The Doors of Perception by Aldous Huxley https://www.amazon.com/Doors-Perception-Heaven-Hell/dp/0061729078 Joel Dickers L'Affaire Alaska Sanders https://www.joeldicker.com/livres/laffaire-alaska-sanders-poche #AUDIOBOOK :: The Art of Winning: Lessons from My Life in Football by Bill Belichick https://www.amazon.com/Art-Winning-Lessons-Life-Football/dp/1668080834 God: A Human History https://www.amazon.com/God-Human-History-Random-House/dp/0525624333 #SERIE :: Andor https://www.imdb.com/title/tt9253284/ (8.6)#QUOTE :: “Everyone believes very easily whatever they fear or desire.” Jean de La Fontaine Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.
In this episode of Unsupervised Learning, I sit down with Michael Brown, Principal Security Engineer at Trail of Bits, to dive deep into the design and lessons learned from the AI Cyber Challenge (AIxCC). Michael led the team behind Buttercup, an AI-driven system that secured 2nd place overall. We discuss: -The design philosophy behind Buttercup and how it blended deterministic systems with AI/ML -Why modular architectures and “best of both worlds” approaches outperform pure LLM-heavy -designs -How large language models performed in patch generation and fuzzing support -The risks of compounding errors in AI pipelines — and how to avoid them -Broader lessons for applying AI in cybersecurity and beyond If you’re interested in AI, security engineering, or system design at scale, this conversation breaks down what worked, what didn’t, and where the field is heading. Subscribe to the newsletter at:https://danielmiessler.com/subscribe Join the UL community at:https://danielmiessler.com/upgrade Follow on X:https://x.com/danielmiessler Follow on LinkedIn:https://www.linkedin.com/in/danielmiesslerBecome a Member: https://danielmiessler.com/upgradeSee omnystudio.com/listener for privacy information.
This week on More or Less, the crew dives into the shifting narratives around AI (Finally everyone is getting on Sam's wavelength), the reality of LLM business models, and why infrastructure may not be the gold rush everyone thinks. We debate the hype cycles, the authenticity crisis in startup pitches, and the pitfalls of meme coins in the creator economy. Plus, is Burning Man over, and what can Taylor Swift teach us about brand-building in the internet age? As always, join Jessica Lessin, Dave Morin, Brit Morin, and Sam Lessin for an unfiltered, insider take on what's really happening in Silicon Valley.Chapters:0:40 – Intro and Silicon Valley Homecomings6:40 – AI, SaaS, and the Changing Narrative12:10 – The AI Moment: GPT-5 and the Plateau14:40 – AI Slop and the Devaluation of Content19:40 – OpenAI: From Hype to Sober Reality21:40 – The Problem with Narrative-Driven Startups24:40 – Marketing vs. Product: Who Really Wins?26:40 – Lying, Manifesting, and Silicon Valley Ethics30:40 – The Tower of Babel: Founders vs. VCs vs. AI36:40 – Burning Man: Has It Peaked?39:40 – Polyamory, Netflix Tropes, and the End of Media Originality43:40 – Meme Coins, Crowdfunding, and Creator Economy Pitfalls54:40 – Taylor Swift, Internet Fame, and Brand Lessons for StartupsWe're also on ↓X: https://twitter.com/moreorlesspodInstagram: https://instagram.com/moreorlessSpotify: https://podcasters.spotify.com/pod/show/moreorlesspodConnect with us here:1) Sam Lessin: https://x.com/lessin2) Dave Morin: https://x.com/davemorin3) Jessica Lessin: https://x.com/Jessicalessin4) Brit Morin: https://x.com/brit
В этом выпуске: Ругаем LLM, ругаем MacOS, хвалим видеоигорь. [00:01:03] Чему мы научились за неделю [00:36:40] Время поругать LLM [00:54:59] [В закладки] Zulip: как Slack но self-hosted Zulip — organized team chat Zulip — organized team chat GitHub — zulip/zulip: Zulip server and web application. Open-source team chat that helps teams stay productive and focused.… Читать далее →
Audio Siar Keluar Sekejap Episod 168 bermula dengan pelancaran Nur AI, model bahasa besar pertama buatan Malaysia yang berteraskan prinsip syariah. Nur AI menjadi alternatif syariah-compliant kepada LLM antarabangsa, sekali gus memperkukuh aspirasi Malaysia dalam ekosistem AI global.Tumpuan beralih kepada politik tanah air apabila Tan Sri Muhyiddin Yassin mengumumkan gabungan longgar 12 parti pembangkang. Perbincangan menilai sama ada kerjasama ini cukup kuat untuk menjadi blok politik yang mencabar kerajaan Madani.Perbincangan kemudian mengupas krisis dalaman PKR melibatkan Rafizi Ramli dan kem PMX yang menimbulkan persoalan tentang masa depan kepimpinan parti.Seterusnya, isu bendera terbalik dan pendakwaan Ketua Pemuda UMNO Dr. Akmal Saleh turut disentuh dengan persoalan lebih luas tentang gaya kepimpinan Melayu dan risiko politik perpecahan menjelang bulan kemerdekaan.Akhir sekali, episod ini menutup dengan topik antarabangsa apabila Donald Trump mengumumkan langkah baharu terhadap Nvidia dan Intel, yang dijangka memberi kesan besar kepada persaingan teknologi AI antara Amerika Syarikat dan China. Episod ini turut menyentuh perkembangan Nuklear Small Modular Reactors (SMR) selepas kenyataan kerajaan untuk menjalankan kajian kebolehlaksanaan menyeluruh terhadap teknologi tenaga ini.00:00 Intro01:49 NurAI16:53 Gabungan Longgar Parti Pembangkang31:57 Penjelasan Rafizi Ramli dan Krisis dalaman PKR41:37 Isu Bendera dan Pendakwaan Dr. Akmal Salleh54:43 Trump, NVIDIA dan Intel01:04:56 Teknologi Nuklear Tanah Air
Personal Growth expert Francie Jain helps individuals and organisations grow through expert-led, group-based learning. Francie began raising nigh on half a billion dollars for hedge funds. Along the way, she identified a major gap: professionals at pivotal moments often lack accessible, high-impact support. That insight drove her to launch three ventures focused on human development—including Terawatt, which is now helping companies tackle burnout, improve retention, and elevate leadership through soft skills training.Summary of the PodcastIntroductions and backgroundGraham and Kevin introduce themselves and welcome their guest Francie Jain, founder of the coaching platform TeraWatt. They discuss Francie's background, including her experience working in a hedge fund and founding TeraWatt, as well as her location in Connecticut near New York City.Group coaching model and benefitsFrancie explains TeraWatt's group coaching model, which aims to reduce employee turnover and associated costs for organizations. She highlights how group coaching can build psychological safety, improve communication, and develop employees' skills more cost-effectively than one-on-one coaching.Measuring impact and ROIFrancie shares case studies demonstrating the significant financial impact of reducing employee turnover, with one organization saving $32 million per year by lowering turnover from 24% to 4% through group coaching. She emphasizes the importance of measuring key metrics to demonstrate the value of coaching investments.Integrating AI and chatbotsGraham proposes integrating AI chatbots and language models to enhance the coaching experience, such as by providing personalized support and analysis. Francie is intrigued by the potential, noting the need to balance AI and human interaction for optimal results.Wrap-up and next stepsFrancie and the hosts discuss Francie's goals for growing TeraWatt, including her focus on building relationships and helping clients achieve "aha" moments. They agree to stay in touch and explore potential collaboration opportunities.The Next 100 Days Podcast Co-HostsGraham ArrowsmithGraham founded Finely Fettled ten years ago to help business owners and marketers market to affluent and high-net-worth customers. He's the founder of MicroYES, a Partner for MeclabsAI, where he introduces AI Agents that you can talk to, that increase engagement, dwell time, leads and conversions. Now, Graham is offering a Generative Engine Optimisation Website Auditor that gets you ready to be found by LLM search.Kevin ApplebyKevin specialises in finance transformation and implementing business change. He's the COO of GrowCFO, which provides both community and CPD-accredited training designed to grow the next generation of finance leaders. You can find Kevin on LinkedIn and at kevinappleby.com
Pre-Show: AI slop vs. not… so… AI… slop AITAH Follow-up: Casey spends 24 hours with iOS 26 on his carry phone John’s dancing controls ☝️ Well, actually ☝️, myriad of is okay (via Jason Eccles) Merriam-Webster’s take Are size classes similar to today’s design changes? (via Bryan Guffey) Auto Layout John’s HomePod has risen from the dead! Nic’s Fix Watch John’s actual repair happen
Is the AI hype cycle about to burst?For months, investors and founders have chased sky-high valuations, billion-dollar hires, and promises of superintelligence, but Meta's drastic plans to cut back its AI division seem to indicate a bleak future for LLMs and AI at large.In this episode, Chris and Yaniv unpack the latest shakeup at Meta, using their knowledge and experience in Silicon Valley to analyze the situation and pick apart whether this is a canary in a coal mine. They explore why Meta is restructuring, what it says about the state of large language models (LLMs), and how to navigate high-stakes moments when the hype cycle turns.In this episode, you will:Understand what Meta's latest AI restructure really signals about industry prioritiesLearn why hype cycles always lead to a trough of disillusionment, and how to prepareExplore how trillion-dollar bets on AGI could reshape competitive dynamicsSee why founders should question assumptions about LLM productivity gainsRecognize the risks of chasing hype versus building sustainable business modelsThe Pact Honor the Startup Podcast Pact! If you have listened to TSP and gotten value from it, please:Follow, rate, and review us in your listening appSubscribe to the TSP Mailing List to gain access to exclusive newsletter-only content and early access to information on upcoming episodes: https://thestartuppodcast.beehiiv.com/subscribe Secure your official TSP merchandise at https://shop.tsp.show/ Follow us here on YouTube for full-video episodes: https://www.youtube.com/channel/UCNjm1MTdjysRRV07fSf0yGgGive us a public shout-out on LinkedIn or anywhere you have a social media followingKey linksGet your question in for our next Q&A episode: https://forms.gle/NZzgNWVLiFmwvFA2A The Startup Podcast website: https://www.tsp.show/episodes/Learn more about Chris and YanivWork 1:1 with Chris: http://chrissaad.com/advisory/ Follow Chris on Linkedin: https://www.linkedin.com/in/chrissaad/ Follow Yaniv on Linkedin: https://www.linkedin.com/in/ybernstein/Producer: Justin McArthur https://www.linkedin.com/in/justin-mcarthurIntro Voice: Jeremiah Owyang https://web-strategist.com/
The very funny Josh Denny joins Randy this week for an unfiltered, hilarious, and brutally honest conversation about getting cancelled and having to reinvent yourself, Josh's time at the Food Network, negotiating in show business, social media controversies, being authentic in politics, and identity politics. The boys close the show with the weekly news - a new study shows the average lovemaking session only lasts about 5 minutes, and artificial intelligence LLM models like ChatGPT get 60% of their data from Reddit and Wikipedia. Every Wednesday, the Ready Set Blow Podcast brings you real talk with comedians, actors, musicians, entertainers, entrepreneurs, and fascinating guests from all walks of life. No scripted BS. No playing it safe…Just raw, funny, and authentic conversations you won't hear on your average podcast. If you enjoy comedy podcasts like Your Mom's House, Flagrant, The Joe Rogan Experience, or Theo Von, you'll love this show. What We Talk About in This Episode: 00:00 Podcast Intro 01:00 Cancel Culture 05:00 Food Network Show 10:00 Negotiating in Show Business 23:00 Social Media & Josh Getting Canceled 33:00 Authenticity in Politics 42:00 Identity Politics 1:05:00 The Weekly News New Episodes Every Wednesday:
Granola is the rare AI startup that slipped into one of tech's most crowded niches — meeting notes — and still managed to become the product founders and VCs rave about. In this episode, MAD Podcast host Matt Turck sits down with Granola co-founder & CEO Chris Pedregal to unpack how a two-person team in London turned a simple “second brain” idea into Silicon Valley's favorite AI tool. Chris recounts a year in stealth onboarding users one by one, the 50 % feature-cut that unlocked simplicity, and why they refused to deploy a meeting bot or store audio even when investors said they were crazy.We go deep on the craft of building a beloved AI product: choosing meetings (not email) as the data wedge, designing calendar-triggered habit loops, and obsessing over privacy so users trust the tool enough to outsource memory. Chris opens the hood on Granola's tech stack — real-time ASR from Deepgram & Assembly, echo cancellation on-device, and dynamic routing across OpenAI, Anthropic and Google models — and explains why transcription, not LLM tokens, is the biggest cost driver today. He also reveals how internal eval tooling lets the team swap models overnight without breaking the “Granola voice.”Looking ahead, Chris shares a roadmap that moves beyond notes toward a true “tool for thought”: cross-meeting insights in seconds, dynamic documents that update themselves, and eventually an AI coach that flags blind spots in your work. Whether you're an engineer, designer, or founder figuring out your own AI strategy, this conversation is a masterclass in nailing product-market fit, trimming complexity, and future-proofing for the rapid advances still to come. Hit play, like, and subscribe if you're ready to learn how to build AI products people can't live without.GranolaWebsite - https://www.granola.aiX/Twitter - https://x.com/meetgranolaChris PedregalLinkedIn - https://www.linkedin.com/in/pedregalX/Twitter - https://x.com/cjpedregalFIRSTMARKWebsite - https://firstmark.comX/Twitter - https://twitter.com/FirstMarkCapMatt Turck (Managing Director)LinkedIn - https://www.linkedin.com/in/turck/X/Twitter - https://twitter.com/mattturck(00:00) Introduction: The Granola Story (01:41) Building a "Life-Changing" Product (04:31) The "Second Brain" Vision (06:28) Augmentation Philosophy (Engelbart), Tools That Shape Us (09:02) Late to a Crowded Market: Why it Worked (13:43) Two Product Founders, Zero ML PhDs (16:01) London vs. SF: Building Outside the Valley (19:51) One Year in Stealth: Learning Before Launch (22:40) "Building For Us" & Finding First Users (25:41) Key Design Choices: No Meeting Bot, No Stored Audio (29:24) Simplicity is Hard: Cutting 50% of Features (32:54) Intuition vs. Data in Making Product Decisions (36:25) Continuous User Conversations: 4–6 Calls/Week (38:06) Prioritizing the Future: Build for Tomorrow's Workflows (40:17) Tech Stack Tour: Model Routing & Evals (42:29) Context Windows, Costs & Inference Economics (45:03) Audio Stack: Transcription, Noise Cancellation & Diarization Limits (48:27) Guardrails & Citations: Building Trust in AI (50:00) Growth Loops Without Virality Hacks (54:54) Enterprise Compliance, Data Footprint & Liability Risk (57:07) Retention & Habit Formation: The "500 Millisecond Window" (58:43) Competing with OpenAI and Legacy Suites (01:01:27) The Future: Deep Research Across Meetings & Roadmap (01:04:41) Granola as Career Coach?
An airhacks.fm conversation with Antonio Goncalves (@agoncal) about: journey from Java Champion to Principal Software Engineer at Microsoft focusing on AI, the evolution from Java EE standards to modern AI development, writing technical books with LLM assistance, langchain4j as a Java SDK for LLMs providing abstraction over different AI providers, the importance of Java standards and patterns for LLM code generation, Boundary Control Entity (BCE / ECB) pattern recognition by LLMs, quarkus integration with LangChain4J enabling dependency injection and multi-tenancy, MCP (Model Context Protocol) as a new standard potentially replacing some RAG use cases, enterprise AI adoption using Azure AI Foundry and AWS Bedrock, model routers for optimal LLM selection based on prompt complexity, the future of small specialized models versus large general models, tornadovm enabling Java execution on GPUs with 6x performance improvements, GraalVM native compilation for LLM applications, the resurgence of Java EE patterns in the age of AI, using prompts as documentation in READMEs and JavaDocs, the advantage of type-safe languages like Java for LLM understanding, Microsoft's contribution to open source AI projects including LangChain4J, teaching new developers with AI assistance and the importance of curiosity, CERN's particle accelerator and its use of Java, the comparison between old "hallucinating architects" and modern LLM hallucinations, writing books about AI using AI tools for assistance, the structure of the Understanding LangChain4j book covering models RAG tools and MCP, enterprise requirements for data privacy and model training restrictions Antonio Goncalves on twitter: @agoncal
Preview: AGI Regulation Colleague Kevin Frazier comments on the tentative state of LLM that needs time to develop before it is either judged or derided by lawmakers. More later.
Leo, Paul, and Richard break down Google's Pixel 10 launch spectacle, poking fun at celebrity overkill and asking whether anyone actually cares about new phones anymore. Plus, they dig into Lenovo's record-breaking quarter, surprising shifts in the PC market, and the ongoing struggle between innovation and copycatting in the AI arms race. Also, Notion has finally added basic offline support, which should make it stickier than ever. You got your AI in my Windows Pavan Davuluri discusses how AI will impact the Windows user experience Not the same video series as the previous "vision" video Davuluri leads Windows and Surface, so his words matter Changing: Interactions, business models, experiences Multimodal - in this case, meaning adding natural language interactions and vision to keyboard, mouse, touch, pen, etc. - "experience diversity" Powerful AI models running on-device are "transformational" Predictably, the Chicken Littles are losing their s#%t yet again. Guys. Come on. Windows 11 Semantic search and new Copilot home page for all Insiders Click to Do selection modes, minor improvements in Beta and Dev Recall and other Copilot+ PC features FINALLY come to Canary A few minor additions to Canary, nothing new to everyone else Notepad is getting an updated context menu and the Chicken Littles are losing their s#%t yet again. Guys. Come on! Lenovo earnings up 22 percent, best PC market share ever, number one in AI PCs too AI Google Chrome takes the subtle approach Brave found a major security vulnerability in Comet Like my wife, Gemini remembers everything I ever said now Duck.ai gets GPT-5 Mini access, web search results Grammarly announces CODA-based editor, several AI agents Xbox and games Another stunning Windows on Arm development The Xbox app actually works now on Windows 11 on Arm, meaning not just game streaming but also downloads. Except, of course, that it mostly doesn't work Heretic/Hexen installs and runs great Asus ROG Xbox Ally handhelds to launch on October 16 Call of Duty: Black Ops 7 with four-player co-op campaign Indiana Jones coming to the Switch 2 Gears of War: Reloaded, more coming to Game Pass in late August To help Xbox, Sony raises prices on the PS5 GeForce Now gets more powerful cloud GPUs Tips & picks Tip of the week: Windows 11 Field Guide, 25H2 Edition is on the way App pick of the week: Notion RunAs Radio this week: Data Governance for AI with Martina Grom Brown liquor pick of the week: Chichibu Ichiro's Malt & Grain Whisky Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to Windows Weekly at https://twit.tv/shows/windows-weekly Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsor: uscloud.com
Bob defends the Unabomber (kind of) ... Paul nurses his Mickey-inflicted wounds ... Bob deflates the GPT-5 deflation ... How big a deal are LLM hallucinations? ... AI's coming social and economic disruptions ... How Bob and Paul use AI ... The ideas of Hanno Sauer ... Heading to Overtime ...
Leo, Paul, and Richard break down Google's Pixel 10 launch spectacle, poking fun at celebrity overkill and asking whether anyone actually cares about new phones anymore. Plus, they dig into Lenovo's record-breaking quarter, surprising shifts in the PC market, and the ongoing struggle between innovation and copycatting in the AI arms race. Also, Notion has finally added basic offline support, which should make it stickier than ever. You got your AI in my Windows Pavan Davuluri discusses how AI will impact the Windows user experience Not the same video series as the previous "vision" video Davuluri leads Windows and Surface, so his words matter Changing: Interactions, business models, experiences Multimodal - in this case, meaning adding natural language interactions and vision to keyboard, mouse, touch, pen, etc. - "experience diversity" Powerful AI models running on-device are "transformational" Predictably, the Chicken Littles are losing their s#%t yet again. Guys. Come on. Windows 11 Semantic search and new Copilot home page for all Insiders Click to Do selection modes, minor improvements in Beta and Dev Recall and other Copilot+ PC features FINALLY come to Canary A few minor additions to Canary, nothing new to everyone else Notepad is getting an updated context menu and the Chicken Littles are losing their s#%t yet again. Guys. Come on! Lenovo earnings up 22 percent, best PC market share ever, number one in AI PCs too AI Google Chrome takes the subtle approach Brave found a major security vulnerability in Comet Like my wife, Gemini remembers everything I ever said now Duck.ai gets GPT-5 Mini access, web search results Grammarly announces CODA-based editor, several AI agents Xbox and games Another stunning Windows on Arm development The Xbox app actually works now on Windows 11 on Arm, meaning not just game streaming but also downloads. Except, of course, that it mostly doesn't work Heretic/Hexen installs and runs great Asus ROG Xbox Ally handhelds to launch on October 16 Call of Duty: Black Ops 7 with four-player co-op campaign Indiana Jones coming to the Switch 2 Gears of War: Reloaded, more coming to Game Pass in late August To help Xbox, Sony raises prices on the PS5 GeForce Now gets more powerful cloud GPUs Tips & picks Tip of the week: Windows 11 Field Guide, 25H2 Edition is on the way App pick of the week: Notion RunAs Radio this week: Data Governance for AI with Martina Grom Brown liquor pick of the week: Chichibu Ichiro's Malt & Grain Whisky Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to Windows Weekly at https://twit.tv/shows/windows-weekly Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsor: uscloud.com
Leo, Paul, and Richard break down Google's Pixel 10 launch spectacle, poking fun at celebrity overkill and asking whether anyone actually cares about new phones anymore. Plus, they dig into Lenovo's record-breaking quarter, surprising shifts in the PC market, and the ongoing struggle between innovation and copycatting in the AI arms race. Also, Notion has finally added basic offline support, which should make it stickier than ever. You got your AI in my Windows Pavan Davuluri discusses how AI will impact the Windows user experience Not the same video series as the previous "vision" video Davuluri leads Windows and Surface, so his words matter Changing: Interactions, business models, experiences Multimodal - in this case, meaning adding natural language interactions and vision to keyboard, mouse, touch, pen, etc. - "experience diversity" Powerful AI models running on-device are "transformational" Predictably, the Chicken Littles are losing their s#%t yet again. Guys. Come on. Windows 11 Semantic search and new Copilot home page for all Insiders Click to Do selection modes, minor improvements in Beta and Dev Recall and other Copilot+ PC features FINALLY come to Canary A few minor additions to Canary, nothing new to everyone else Notepad is getting an updated context menu and the Chicken Littles are losing their s#%t yet again. Guys. Come on! Lenovo earnings up 22 percent, best PC market share ever, number one in AI PCs too AI Google Chrome takes the subtle approach Brave found a major security vulnerability in Comet Like my wife, Gemini remembers everything I ever said now Duck.ai gets GPT-5 Mini access, web search results Grammarly announces CODA-based editor, several AI agents Xbox and games Another stunning Windows on Arm development The Xbox app actually works now on Windows 11 on Arm, meaning not just game streaming but also downloads. Except, of course, that it mostly doesn't work Heretic/Hexen installs and runs great Asus ROG Xbox Ally handhelds to launch on October 16 Call of Duty: Black Ops 7 with four-player co-op campaign Indiana Jones coming to the Switch 2 Gears of War: Reloaded, more coming to Game Pass in late August To help Xbox, Sony raises prices on the PS5 GeForce Now gets more powerful cloud GPUs Tips & picks Tip of the week: Windows 11 Field Guide, 25H2 Edition is on the way App pick of the week: Notion RunAs Radio this week: Data Governance for AI with Martina Grom Brown liquor pick of the week: Chichibu Ichiro's Malt & Grain Whisky Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to Windows Weekly at https://twit.tv/shows/windows-weekly Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsor: uscloud.com
Leo, Paul, and Richard break down Google's Pixel 10 launch spectacle, poking fun at celebrity overkill and asking whether anyone actually cares about new phones anymore. Plus, they dig into Lenovo's record-breaking quarter, surprising shifts in the PC market, and the ongoing struggle between innovation and copycatting in the AI arms race. Also, Notion has finally added basic offline support, which should make it stickier than ever. You got your AI in my Windows Pavan Davuluri discusses how AI will impact the Windows user experience Not the same video series as the previous "vision" video Davuluri leads Windows and Surface, so his words matter Changing: Interactions, business models, experiences Multimodal - in this case, meaning adding natural language interactions and vision to keyboard, mouse, touch, pen, etc. - "experience diversity" Powerful AI models running on-device are "transformational" Predictably, the Chicken Littles are losing their s#%t yet again. Guys. Come on. Windows 11 Semantic search and new Copilot home page for all Insiders Click to Do selection modes, minor improvements in Beta and Dev Recall and other Copilot+ PC features FINALLY come to Canary A few minor additions to Canary, nothing new to everyone else Notepad is getting an updated context menu and the Chicken Littles are losing their s#%t yet again. Guys. Come on! Lenovo earnings up 22 percent, best PC market share ever, number one in AI PCs too AI Google Chrome takes the subtle approach Brave found a major security vulnerability in Comet Like my wife, Gemini remembers everything I ever said now Duck.ai gets GPT-5 Mini access, web search results Grammarly announces CODA-based editor, several AI agents Xbox and games Another stunning Windows on Arm development The Xbox app actually works now on Windows 11 on Arm, meaning not just game streaming but also downloads. Except, of course, that it mostly doesn't work Heretic/Hexen installs and runs great Asus ROG Xbox Ally handhelds to launch on October 16 Call of Duty: Black Ops 7 with four-player co-op campaign Indiana Jones coming to the Switch 2 Gears of War: Reloaded, more coming to Game Pass in late August To help Xbox, Sony raises prices on the PS5 GeForce Now gets more powerful cloud GPUs Tips & picks Tip of the week: Windows 11 Field Guide, 25H2 Edition is on the way App pick of the week: Notion RunAs Radio this week: Data Governance for AI with Martina Grom Brown liquor pick of the week: Chichibu Ichiro's Malt & Grain Whisky Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to Windows Weekly at https://twit.tv/shows/windows-weekly Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsor: uscloud.com
Ross Simmonds breaks down how AI overviews and LLMs are changing search—and what small businesses can do to keep winning. We dig into why brand and owned channels matter more than ever, how to diversify beyond Google, which third-party domains LLMs love to cite, and a simple focus formula for content distribution. Key TakeawaysThe SERP is shifting to answers and transactions; fewer clicks to your site means brand + owned channels are mission-critical. Now is the time to publish unique, story-driven content that LLMs can cite later. Create assets your “future you” will be grateful for. Diversify discovery: show up where buyers research (TikTok, Pinterest, Instagram, Etsy), not just on Google. Search behavior has shifted—people use Instagram/YouTube/TikTok for ideas and how-tos; optimize for those journeys. To influence LLM answers, seed multiple authoritative domains (LinkedIn, Reddit, Medium, Quora) with your message. “Be excellent on one channel” first; syndicate elsewhere even if it's not perfect—then expand. Optimize your life too: sleep and calendars drive better marketing than nonstop grind. Listener Action ItemsPick your “home” channel and get excellent at it for 90 days; syndicate the same posts to 2 other platforms with light edits. Publish 3–5 unique, story-rich assets this month that your future self wants LLMs to cite. Seed third-party domains (LinkedIn article, Reddit thread, Medium post, Quora answer) with your core message to boost LLM citation odds. Audit discovery: can buyers find you on Pinterest/Instagram/TikTok/Etsy for your “money” searches? If not, claim and optimize profiles. Protect your energy: schedule sleep, workouts, and weekly calendar reviews before adding new marketing experiments. Connect With Ross:LinkedinGet Ross's book: Create Once, Distribute Forever Text me your questions or comments!Does SEO feel confusing, overwhelming, or just plain impossible to figure out? You're not alone. That's why I created the AI SEO Foundations course, powered by Crystal GPT: your personal AI SEO coach designed for busy, creative business owners like you.Ditch the overwhelm and discover what SEO can do for your business! Head to SEOin7days.com (with the number 7!) and get started today—let's make your brand easy to find and impossible to ignore.Support the showWant to follow up on what you've heard? Search the podcast!Join the SEO SquadApply to be my podcast guest!
Marc from Algorand joins Sam to unpack their 2025 roadmap, the push for mainstream adoption, and lessons he brings from his time at Google and Android. He explains Algorand's unique developer-friendly features, its work on quantum security, and how AI integration will accelerate the next wave of blockchain applications.Key Timestamps[00:00] Intro & Marc's journey: from Google/Android to Algorand.[00:03] The trilemma solved? Algorand's verifiable random functions & instant finality.[00:04] Six years of uptime: reliability & scaling to real-world use cases.[00:05] The 4-pillar roadmap: values, mainstream adoption, tokenization/identity, research.[00:07] Competing with other L1s/L2s: reliability + dev-friendly built-ins.[00:09] Mainstream adoption: UX challenges, wallets, seed recovery, gas abstraction.[00:12] Balancing simplicity with self-custody & decentralization.[00:14] Algorand's “North Star” metrics for adoption & growth.[00:15] Marketing that worked: “Can a Blockchain Do That?” campaign.[00:16] AI integration: Algorand 4.0, hackathons, LLM training, agents & payments.[00:20] If Marc could remove one thing from blockchain culture → rugging.[00:21] Lessons from Google: user-first, rapid iteration, shipping daily.[00:23] Respect in Web3: why Circle stands out.[00:24] Misconceptions: people underestimate Algorand's DeFi UX.[00:25] Quantum security: state proofs, Falcon signatures, securing the ledger.[00:28] Roadmap execution: xGov community governance + ecosystem collaboration.[00:31] Hackathons, grants, accelerator/incubator funnel for startups.[00:33] Big ecosystem event: Decipher planned for 2025.Connecthttps://algorand.co/https://www.linkedin.com/company/algorandfoundation/https://x.com/AlgoFoundationhttps://www.linkedin.com/in/marcvl/DisclaimerNothing mentioned in this podcast is investment advice and please do your own research. Finally, it would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend.Be a guest on the podcast or contact us - https://www.web3pod.xyz/
Just dropped: A new episode of Cisco SE Talks: Conversations on AI! Join us as we're excited to feature Cisco's Dr. Gaurav Khanna, John Cuneo, and Justin Perry as we explore the latest AI trends, including the impact of agentic AI, LLM models, and the future of AI in Networking - demystifying how Cisco AI is driving innovation in the evolving landscape of AI. We'll also dive deep in the Cisco + NVIDIA partnership – uniting two industry leaders to pioneer secure networking and AI solutions. Don't miss this one – As the AI conversation continues with Cisco leading the way!
Leo, Paul, and Richard break down Google's Pixel 10 launch spectacle, poking fun at celebrity overkill and asking whether anyone actually cares about new phones anymore. Plus, they dig into Lenovo's record-breaking quarter, surprising shifts in the PC market, and the ongoing struggle between innovation and copycatting in the AI arms race. Also, Notion has finally added basic offline support, which should make it stickier than ever. You got your AI in my Windows Pavan Davuluri discusses how AI will impact the Windows user experience Not the same video series as the previous "vision" video Davuluri leads Windows and Surface, so his words matter Changing: Interactions, business models, experiences Multimodal - in this case, meaning adding natural language interactions and vision to keyboard, mouse, touch, pen, etc. - "experience diversity" Powerful AI models running on-device are "transformational" Predictably, the Chicken Littles are losing their s#%t yet again. Guys. Come on. Windows 11 Semantic search and new Copilot home page for all Insiders Click to Do selection modes, minor improvements in Beta and Dev Recall and other Copilot+ PC features FINALLY come to Canary A few minor additions to Canary, nothing new to everyone else Notepad is getting an updated context menu and the Chicken Littles are losing their s#%t yet again. Guys. Come on! Lenovo earnings up 22 percent, best PC market share ever, number one in AI PCs too AI Google Chrome takes the subtle approach Brave found a major security vulnerability in Comet Like my wife, Gemini remembers everything I ever said now Duck.ai gets GPT-5 Mini access, web search results Grammarly announces CODA-based editor, several AI agents Xbox and games Another stunning Windows on Arm development The Xbox app actually works now on Windows 11 on Arm, meaning not just game streaming but also downloads. Except, of course, that it mostly doesn't work Heretic/Hexen installs and runs great Asus ROG Xbox Ally handhelds to launch on October 16 Call of Duty: Black Ops 7 with four-player co-op campaign Indiana Jones coming to the Switch 2 Gears of War: Reloaded, more coming to Game Pass in late August To help Xbox, Sony raises prices on the PS5 GeForce Now gets more powerful cloud GPUs Tips & picks Tip of the week: Windows 11 Field Guide, 25H2 Edition is on the way App pick of the week: Notion RunAs Radio this week: Data Governance for AI with Martina Grom Brown liquor pick of the week: Chichibu Ichiro's Malt & Grain Whisky Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to Windows Weekly at https://twit.tv/shows/windows-weekly Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsor: uscloud.com
С доцентом кафедры китаеведения ДВФУ и Университета Циндао Александром Сбоевым мы поговорили про китайские нейронки, их особенности, доступ к ним, особенности промптов и выдаваемых результатов, и про всякое разное, связанное с этой захватывающей областью (не)человеческой деятельности.Ссылка: https://t.me/chinese_LLMМузыка: 《老外播客》- слова, музыка, исполнение - ИИ. Laowaicast выходит каждый вторник:Мы есть на всех основных платформах, в Apple Podcasts, Google Podcasts, на Яндекс.Музыке и Spotify.Для вопросов и пожеланий: we@laowaicast.ruТелеграмм-канал: t.me/laowaicastПоддержите проект: Patreon (в долларах), Boosty (в рублях), 爱赞助 (в юанях)
Nonprofits, your “10 blue links” era is over. In this episode, Avinash Kaushik (Human-Made Machine; Occam's Razor) breaks down Answer Engine Optimization—why LLMs now decide who gets seen, why third-party chatter outweighs your own site, and what to do about it. We get tactical: build AI-resistant content (genuine novelty + depth), go multimodal (text, video, audio), and stamp everything with real attribution so bots can't regurgitate you into sludge. We also cover measurement that isn't delusional—group your AEO referrals, expect fewer visits but higher intent, and stop worshiping last-click and vanity metrics. Avinash updates the 10/90 rule for the AI age (invest in people, plus “synthetic interns”), and torpedoes linear funnels in favor of See-Think-Do-Care anchored in intent. If you want a blunt, practical playbook for staying visible—and actually converting—when answers beat searches, this is it. About Avinash Avinash Kaushik is a leading voice in marketing analytics—the author of Web Analytics: An Hour a Day and Web Analytics 2.0, publisher of the Marketing Analytics Intersect newsletter, and longtime writer of the Occam's Razor blog. He leads strategy at Human Made Machine, advises Tapestry on brand strategy/marketing transformation, and previously served as Google's Digital Marketing Evangelist. Uniquely, he donates 100% of his book royalties and paid newsletter revenue to charity (civil rights, early childhood education, UN OCHA; previously Smile Train and Doctors Without Borders). He also co-founded Market Motive. Resource Links Avinash Kaushik — Occam's Razor (site/home) Occam's Razor by Avinash Kaushik Marketing Analytics Intersect (newsletter sign-up) Occam's Razor by Avinash Kaushik AEO series starter: “AI Age Marketing: Bye SEO, Hello AEO!” Occam's Razor by Avinash Kaushik See-Think-Do-Care (framework explainer) Occam's Razor by Avinash Kaushik Books: Web Analytics: An Hour a Day | Web Analytics 2.0 (author pages) Occam's Razor by Avinash Kaushik+1 Human Made Machine (creative pre-testing) — Home | About | Products humanmademachine.com+2humanmademachine.com+2 Tapestry (Coach, Kate Spade) (company site) Tapestry Tools mentioned (AEO measurement): Trakkr (AI visibility / prompts / sentiment) Trakkr Evertune (AI Brand Index & monitoring) evertune.ai GA4 how-tos (for your AEO channel + attribution): Custom Channel Groups (create an “AEO” channel) Google Help Attribution Paths report (multi-touch view) Google Help Nonprofit vetting (Avinash's donation diligence): Charity Navigator (ratings) Charity Navigator Google for Nonprofits — Gemini & NotebookLM (AI access) Announcement / overview | Workspace AI for nonprofits blog.googleGoogle Help Example NGO Avinash supports: EMERGENCY (Italy) EMERGENCY Transcript Avinash Kaushik: [00:00:00] So traffic's gonna go down. So if you're a business, you're a nonprofit, how. Do you deal with the fact that you're gonna lose a lot of traffic that you get from a search engine? Today, when all of humanity moves to the answer Engine W world, only about two or 3% of the people are doing it. It's growing very rapidly. Um, and so the art of answer engine optimization is making sure that we are building for these LMS and not getting stuck with only solving for Google with the old SEO techniques. Some of them still work, but you need to learn a lot of new stuff because on average, organic traffic will drop between 16 to 64% negative and paid search traffic will drop between five to 30% negative. And that is a huge challenge. And the reason you should start with AEO now George Weiner: [00:01:00] This week's guest, Avinash Kaushik is an absolute hero of mine because of his amazing, uh, work in the field of web analytics. And also, more importantly, I'd say education. Avinash Kaushik, , digital marketing evangelist at Google for Google Analytics. He spent 16 years there. He basically is. In the room where it happened, when the underlying ability to understand what's going on on our websites was was created. More importantly, I think for me, you know, he joined us on episode 45 back in 2016, and he still is, I believe, on the cutting edge of what's about to happen with AEO and the death of SEO. I wanna unpack that 'cause we kind of fly through terms [00:02:00] before we get into this podcast interview AEO. Answer engine optimization. It's this world of saying, alright, how do we create content that can't just be, , regurgitated by bots, , wholesale taken. And it's a big shift from SEO search engine optimization. This classic work of creating content for Google to give us 10 blue links for people to click on that behavior is changing. And when. We go through a period of change. I always wanna look at primary sources. The people that, , are likely to know the most and do the most. And he operates in the for-profit world. But make no mistake, he cares deeply about nonprofits. His expertise, , has frankly been tested, proven and reproven. So I pay attention when he says things like, SEO is going away, and AEO is here to stay. So I give you Avan Kashic. I'm beyond excited that he has come back. He was on our 45th episode and now we are well over our 450th episode. So, , who knows what'll happen next time we talk to him. [00:03:00] This week on the podcast, we have Avinash Kaushik. He is currently the chief strategy officer at Human Made Machine, but actually returning guest after many, many years, and I know him because he basically introduced me to Google Analytics, wrote the literal book on it, and also helped, by the way. No big deal. Literally birth Google Analytics for everyone. During his time at Google, I could spend the entire podcast talking about, uh, the amazing amounts that you have contributed to, uh, marketing and analytics. But I'd rather just real quick, uh, how are you doing and how would you describe your, uh, your role right now? Avinash Kaushik: Oh, thank you. So it's very excited to be back. Um, look forward to the discussion today. I do, I do several things concurrently, of course. I, I, I am an author and I write this weekly newsletter on marketing and analytics. Um, I am the Chief Strategy Officer at Human Made Machine, a company [00:04:00] that obsesses about helping brands win before they spend by doing creative pretesting. And then I also do, uh, uh, consulting at Tapestry, which owns Coach and Kate Spades. And my work focuses on brand strategy and marketing transformation globally. George Weiner: , Amazing. And of course, Occam's Razor. The, the, yes, the blog, which is incredible. I happen to be a, uh, a subscriber. You know, I often think of you in the nonprofit landscape, even though you operate, um, across many different brands, because personally, you also actually donate all of your proceeds from your books, from your blog, from your subscription. You are donating all of that, um, because that's just who you are and what you do. So I also look at you as like team nonprofit, though. Avinash Kaushik: You're very kind. No, no, I, I, yeah. All the proceeds from both of my books and now my newsletter, premium newsletter. It's about $200,000 a year, uh, donated to nonprofits, and a hundred [00:05:00] percent of the revenue is donated nonprofit, uh, nonprofits. And, and for me, it, it's been ai. Then I have to figure out. Which ones, and so I research nonprofits and I look up their cha charity navigators, and I follow up with the people and I check in on the works while, while don't work at a nonprofit, but as a customer of nonprofits, if you will. I, I keep sort of very close tabs on the amazing work that these charities do around the world. So feel very close to the people that you work with very closely. George Weiner: So recently I got an all caps subject line from you. Well, not from you talking about this new acronym that was coming to destroy the world, I think is what you, no, AEO. Can you help us understand what answer engine optimization is? Avinash Kaushik: Yes, of course. Of course. We all are very excited about ai. Obviously you, you, you would've to live in. Some backwaters not to be excited about it. And we know [00:06:00] that, um, at the very edge, lots of people are using large language models, chat, GPT, Claude, Gemini, et cetera, et cetera, in the world. And, and increasingly over the last year, what you have begun to notice is that instead of using a traditional search engine like Google or using the old Google interface with the 10 blue links, et cetera. People are beginning to use these lms. They just go to chat, GPT to get the answer that they want. And the one big difference in this, this behavior is I actually have on September 8th, I have a keynote here in New York and I have to be in Shanghai the next day. That is physically impossible because it, it just, the time it takes to travel. But that's my thing. So today, if I wanted to figure out what is the fastest way. On September 8th, I can leave New York and get to Shanghai. I would go to Google flights. I would put in the destinations. It will come back with a crap load of data. Then I poke and prod and sort and filter, and I have to figure out which flight is right for that. For this need I have. [00:07:00] So that is the old search engine world. I'm doing all the work, hunting and pecking, drilling down, visiting websites, et cetera, et cetera. Instead, actually what I did is I went to charge GBT 'cause I, I have a plus I, I'm a paying member of charge GBT and I said to charge GBTI have to do a keynote between four and five o'clock on September 8th in New York and I have to be in Shanghai as fast as I possibly can be After my keynote, can you find me the best flight? And I just typed in those two sentences. He came back and said, this Korean airline website flight is the best one for you. You will not get to your destination on time until, unless you take a private jet flight for $300,000. There is your best option. They're gonna get to Shanghai on, uh, September 10th at 10 o'clock in the morning if you follow these steps. And so what happened there? I didn't have to hunt and pack and dig and go to 15 websites to find the answer I wanted. The engine found the [00:08:00] answer I wanted at the end and did all the work for me that you are seeing from searching, clicking, clicking, clicking, clicking, clicking to just having somebody get you. The final answer is what I call the, the, the underlying change in consumer behavior that makes answer engine so exciting. Obviously, it creates a challenge for us because what happened between those two things, George is. I didn't have to visit many websites. So traffic is going down, obviously, and these interfaces at the moment don't have paid search links for now. They will come, they will come, but they don't at the moment. So traffic's gonna go down. So if you're a business, you're a nonprofit, how. Do you deal with the fact that you're gonna lose a lot of traffic that you get from a search engine? Today, when all of humanity moves to the answer Engine W world, only about two or 3% of the people are doing it. It's growing very rapidly. Um, and so the art of answer engine optimization [00:09:00] is making sure that we are building for these LMS and not getting stuck with only solving for Google with the old SEO techniques. Some of them still work, but you need to learn a lot of new stuff because on average, organic traffic will drop between 16 to 64% negative and paid search traffic will drop between five to 30% negative. And that is a huge challenge. And the reason you should start with AEO now George Weiner: that you know. Is a window large enough to drive a metaphorical data bus through? And I think talk to your data doctor results may vary. You are absolutely right. We have been seeing this with our nonprofit clients, with our own traffic that yes, basically staying even is the new growth. Yeah. But I want to sort of talk about the secondary implications of an AI that has ripped and gripped [00:10:00] my website's content. Then added whatever, whatever other flavors of my brand and information out there, and is then advising somebody or talking about my brand. Can you maybe unwrap that a little bit more? What are the secondary impacts of frankly, uh, an AI answering what is the best international aid organization I should donate to? Yes. As you just said, you do Avinash Kaushik: exactly. No, no, no. This such a, such a wonderful question. It gets to the crux. What used to influence Google, by the way, Google also has an answer engine called Gemini. So I just, when I say Google, I'm referring to the current Google that most people use with four paid links and 10 SEO links. So when I say Google, I'm referring to that one. But Google also has an answer engine. I, I don't want anybody saying Google does is not getting into the answer engine business. It is. So Google is very much influenced by content George that you create. I call it one P content, [00:11:00] first party content. Your website, your mobile app, your YouTube channel, your Facebook page, your, your, your, your, and it sprinkles on some amount of third party content. Some websites might have reviews about you like Yelp, some websites might have PR releases about you light some third party content. Between search engine and engines. Answer Engines seem to overvalue third party content. My for one p content, my website, my mobile app, my YouTube channel. My, my, my, everything actually is going down in influence while on Google it's pretty high. So as here you do SEO, you're, you're good, good ranking traffic. But these LLMs are using many, many, many, literally tens of thousands more sources. To understand who you are, who you are as a nonprofit, and it's [00:12:00] using everybody's videos, everybody's Reddit posts, everybody's Facebook things, and tens of thousands of more people who write blogs and all kinds of stuff in order to understand who you are as a nonprofit, what services you offer, how good you are, where you're falling short, all those negative reviews or positive reviews, it's all creepy influence. Has gone through the roof, P has come down, which is why it has become very, very important for us to build a new content strategy to figure out how we can influence these LMS about who we are. Because the scary thing is at this early stage in answer engines, someone else is telling the LLMs who you are instead of you. A more, and that's, it feels a little scary. It feels as scary as a as as a brand. It feels very scary as I'm a chief strategy officer, human made machine. It feels scary for HMM. It feels scary for coach. [00:13:00] It's scary for everybody, uh, which is why you really urgently need to get a handle on your content strategy. George Weiner: Yeah, I mean, what you just described, if it doesn't give you like anxiety, just stop right now. Just replay what we just did. And that is the second order effects. And you know, one of my concerns, you mentioned it early on, is that sort of traditional SEO, we've been playing the 10 Blue Link game for so long, and I'm worried that. Because of the changes right now, roughly what 20% of a, uh, search is AI overview, that number's not gonna go down. You're mentioning third party stuff. All of Instagram back to 2020, just quietly got tossed into the soup of your AI brand footprint, as we call it. Talk to me about. There's a nonprofit listening to this right now, and then probably if they're smart, other organizations, what is coming in the next year? They're sitting down to write the same style of, you know, [00:14:00] ai, SEO, optimized content, right? They have their content calendar. If you could have like that, I'm sitting, you're sitting in the room with them. What are you telling that classic content strategy team right now that's about to embark on 2026? Avinash Kaushik: Yes. So actually I, I published this newsletter just last night, and this is like the, the fourth in my AEO series, uh, newsletter, talks about how to create your content portfolio strategy. Because in the past we were like, we've got a product pages, you know, the equivalent of our, our product pages. We've got some, some, uh, charitable stories on our website and uh, so on and so forth. And that's good. That's basic. You need to do the basics. The interesting thing is you need to do so much more both on first party. So for example, one of the first things to appreciate is LMS or answer engines are far more influenced by multimodal content. So what does that mean? Text plus [00:15:00] video plus audio. Video and audio were also helpful in Google. And remember when I say Google, I'm referring to the old linky linking Google, not Gemini. But now video has ton more influence. So if you're creating a content strategy for next year, you should say many. Actually, lemme do one at a time. Text. You have to figure out more types of things. Authoritative Q and as. Very educational deep content around your charity's efforts. Lots of text. Third. Any seasonality, trends and patterns that happen in your charity that make a difference? I support a school in, in Nepal and, and during the winter they have very different kind of needs than they do during the summer. And so I bumped into this because I was searching about something seasonality related. This particular school for Tibetan children popped up in Nepal, and it's that content they wrote around winter and winter struggles and coats and all this stuff. I'm like. [00:16:00] It popped up in the answer engine and I'm like, okay. I research a bit more. They have good stories about it, and I'm supporting them q and a. Very, very important. Testimonials. Very, very important interviews. Very, very important. Super, super duper important with both the givers and the recipients, supporters of your nonprofit, but also the recipient recipients of very few nonprofits actually interview the people who support them. George Weiner: Like, why not like donors or be like, Hey, why did you support us? What was the, were the two things that moved you from Aware to care? Avinash Kaushik: Like for, for the i I Support Emergency, which is a Italian nonprofit like Ms. Frontiers and I would go on their website and speak a fiercely about why I absolutely love the work they do. Content, yeah. So first is text, then video. You gotta figure out how to use video a lot more. And most nonprofits are not agile in being able to use video. And the third [00:17:00] thing that I think will be a little bit of a struggle is to figure out how to use audio. 'cause audio also plays a very influential role. So for as you are planning your uh, uh, content calendar for the next year. Have the word multimodal. I'm sorry, it's profoundly unsexy, but put multimodal at the top, underneath it, say text, then say video, then audio, and start to fill those holes in. And if those people need ideas and example of how to use audio, they should just call you George. You are the king of podcasting and you can absolutely give them better advice than I could around how nonprofits could use audio. But the one big thing you have to think about is multimodality for next year George Weiner: that you know, is incredibly powerful. Underlying that, there's this nuance that I really want to make sure that we understand, which is the fact that the type of content is uniquely different. It's not like there's a hunger organization listening right now. It's not 10 facts about hunger during the winter. [00:18:00] Uh, days of being able to be an information resource that would then bring people in and then bring them down your, you know, your path. It's game over. If not now, soon. Absolutely. So how you are creating things that AI can't create and that's why you, according to whom, is what I like to think about. Like, you're gonna say something, you're gonna write something according to whom? Is it the CEO? Is it the stakeholder? Is it the donor? And if you can put a attribution there, suddenly the AI can't just lift and shift it. It has to take that as a block and be like, no, it was attributed here. This is the organization. Is that about right? Or like first, first party data, right? Avinash Kaushik: I'll, I'll add one more, one more. Uh, I'll give a proper definition. So, the fir i I made 11 recommendations last night in the newsletter. The very first one is focus on creating AI resistant content. So what, what does that mean? AI resistant means, uh, any one of us from nonprofits could [00:19:00] open chat, GPT type in a few queries and chat. GD PT can write our next nonprofit newsletter. It could write the next page for our donation. It could create the damn page for our donation, right? Remember, AI can create way more content than you can, but if you can use AI to create content, 67 million other nonprofits are doing the same thing. So what you have to do is figure out how to build AI resistant content, and my definition is very simple. George, what is AI resistance? It's content of genuine novelty. So to tie back to your recommendation, your CEO of a nonprofit that you just recommended, the attribution to George. Your CEO has a unique voice, a unique experience. The AI hasn't learned what makes your CEO your frontline staff solving problems. You are a person who went and gave a speech at the United Nations on behalf of your nonprofit. Whatever you are [00:20:00] doing is very special, and what you have to figure out is how to get out of the AI slop. You have to get out of all the things that AI can automatically type. Figure out if your content meets this very simple, standard, genuine novelty and depth 'cause it's the one thing AI isn't good at. That's how you rank higher. And not only will will it, will it rank you, but to make another point you made, George, it's gonna just lift, blanc it out there and attribute credit to you. Boom. But if you're not genuine, novelty and depth. Thousand other nonprofits are using AI to generate text and video. Could George Weiner: you just, could you just quit whatever you're doing and start a school instead? I seriously can't say it enough that your point about AI slop is terrifying me because I see it. We've built an AI tool and the subtle lesson here is that think about how quickly this AI was able to output that newsletter. Generic old school blog post and if this tool can do it, which [00:21:00] by the way is built on your local data set, we have the rag, which doesn't pause for a second and realize if this AI can make it, some other AI is going to be able to reproduce it. So how are you bringing the human back into this? And it's a style of writing and a style of strategic thinking that please just start a school and like help every single college kid leaving that just GPT their way through a degree. Didn't freaking get, Avinash Kaushik: so it's very, very important to make sure. Content is of genuine novelty and depth because it cannot be replicated by the ai. And by the way, this, by the way, George, it sounds really high, but honestly to, to use your point, if you're a CEO of a nonprofit, you are in it for something that speaks to you. You're in it. Because ai, I mean nonprofit is not your path to becoming the next Bill Gates, you're doing it because you just have this hair. Whoa, spoiler alert. No, I'm sorry. [00:22:00] Maybe, maybe that is. I, I didn't, I didn't mean any negative emotion there, but No, I love it. It's all, it's like a, it's like a sense of passion you are bringing. There's something that speaks to you. Just put that on paper, put that on video, put that on audio, because that is what makes you unique. And the collection of those stories of genuine depth and novelty will make your nonprofit unique and stand out when people are looking for answers. George Weiner: So I have to point to the next elephant in the room here, which is measurement. Yes. Yes. Right now, somebody is talking about human made machine. Someone's talking about whole whale. Someone's talking about your nonprofit having a discussion in an answer engine somewhere. Yes. And I have no idea. How do I go about understanding measurement in this new game? Avinash Kaushik: I have. I have two recommendations. For nonprofits, I would recommend a tool called Tracker ai, TRA, KKR [00:23:00] ai, and it has a free version, that's why I'm recommending it. Some of the many of these tools are paid tools, but with Tracker, do ai. It allows you to identify your website, URL, et cetera, et cetera, and it'll give you some really wonderful and fantastic, helpful report It. Tracker helps you understand prompt tracking, which is what are other people writing about you when they're seeking? You? Think of this, George, as your old webmaster tools. What keywords are people using to search? Except you can get the prompts that people are using to get a more robust understanding. It also monitors your brand's visibility. How often are you showing up and how often is your competitor showing up, et cetera, et cetera. And then he does that across multiple search engines. So you can say, oh, I'm actually pretty strong in OpenAI for some reason, and I'm not that strong in Gemini. Or, you know what, I have like the highest rating in cloud, but I don't have it in OpenAI. And this begins to help you understand where your current content strategy is working and where it is not [00:24:00] working. So that's your brand visibility. And the third thing that you get from Tracker is active sentiment tracking. This is the scary part because remember, you and I were both worried about what other people saying about us. So this, this are very helpful that we can go out and see what it is. What is the sentiment around our nonprofit that is coming across in, um, in these lms? So Tracker ai, it have a free and a paid version. So I would, I would recommend using it for these three purposes. If, if you have funding to invest in a tool. Then there's a tool called Ever Tool, E-V-E-R-T-U-N-E Ever. Tune is a paid tool. It's extremely sophisticated and robust, and they do brand monitoring, site audit, content strategy, consumer preference report, ai, brand index, just the. Step and breadth of metrics that they provide is quite extensive, but, but it is a paid tool. It does cost money. It's not actually crazy expensive, but uh, I know I have worked with them before, so full disclosure [00:25:00] and having evaluated lots of different tools, I have sort of settled on those two. If it's a enterprise type client I'm working with, then I'll use Evert Tune if I am working with a nonprofit or some of my personal stuff. I'll use Tracker AI because it's good enough for a person that is, uh, smaller in size and revenue, et cetera. So those two tools, so we have new metrics coming, uh, from these tools. They help us understand the kind of things we use webmaster tools for in the past. Then your other thing you will want to track very, very closely is using Google Analytics or some other tool on your website. You are able to currently track your, uh, organic traffic and if you're taking advantage of paid ads, uh, through a grant program on Google, which, uh, provides free paid search credits to nonprofits. Then you're tracking your page search traffic to continue to track that track trends, patterns over time. But now you will begin to see in your referrals report, in your referrals report, you're gonna begin to seeing open [00:26:00] ai. You're gonna begin to see these new answer engines. And while you don't know the keywords that are sending this traffic and so on and so forth, it is important to keep track of the traffic because of two important reasons. One, one, you want to know how to highly prioritize. AEO. That's one reason. But the other reason I found George is syn is so freaking hard to rank in an answer engine. When people do come to my websites from Answer engine, the businesses I work with that is very high intent person, they tend to be very, very valuable because they gave the answer engine a very complex question to answer the answers. Engine said you. The right answer for it. So when I show up, I'm ready to buy, I'm ready to donate. I'm ready to do the action that I was looking for. So the percent of people who are coming from answer engines to your nonprofit carry significantly higher intention, and coming from Google, who also carry [00:27:00] intent. But this man, you stood out in an answer engine, you're a gift from God. Person coming thinks you're very important and is likely to engage in some sort of business with you. So I, even if it's like a hundred people, I care a lot about those a hundred people, even if it's not 10,000 at the moment. Does that make sense George? George Weiner: It does, and I think, I'm glad you pointed to, you know, the, the good old Google Analytics. I'm like, it has to be a way, and I, I think. I gave maximum effort to this problem inside of Google Analytics, and I'm still frustrated that search console is not showing me, and it's just blending it all together into one big soup. But. I want you to poke a hole in this thinking or say yes or no. You can create an AI channel, an AEO channel cluster together, and we have a guide on that cluster together. All of those types of referral traffic, as you mentioned, right from there. I actually know thanks to CloudFlare, the ratios of the amount of scrapes versus the actual clicks sent [00:28:00] for roughly 20, 30% of. Traffic globally. So is it fair to say I could assume like a 2% clickthrough or a 1% clickthrough, or even worse in some cases based on that referral and then reverse engineer, basically divide those clicks by the clickthrough rate and essentially get a rough share of voice metric on that platform? Yeah. Avinash Kaushik: So, so for, um, kind of, kind of at the moment, the problem is that unlike Google giving us some decent amount of data through webmaster tools. None of these LLMs are giving us any data. As a business owner, none of them are giving us any data. So we're relying on third parties like Tracker. We're relying on third parties like Evert Tune. You understand? How often are we showing up so we could get a damn click through, right? Right. We don't quite have that for now. So the AI Brand Index in Evert Tune comes the closest. Giving you some information we could use in the, so your thinking is absolutely right. Your recommendation is ly, right? Even if you can just get the number of clicks, even if you're tracking them very [00:29:00] carefully, it's very important. Please do exactly what you said. Make the channel, it's really important. But don't, don't read too much into the click-through rate bits, because we're missing the. We're missing a very important piece of information. Now remember when Google first came out, we didn't have tons of data. Um, and that's okay. These LLMs Pro probably will realize over time if they get into the advertising business that it's nice to give data out to other people, and so we might get more data. Until then, we are relying on these third parties that are hacking these tools to find us some data. So we can use it to understand, uh, some of the things we readily understand about keywords and things today related to Google. So we, we sadly don't have as much visibility today as we would like to have. George Weiner: Yeah. We really don't. Alright. I have, have a segment that I just invented. Just for you called Avanade's War Corner. And in Avanade's War Corner, I noticed that you go to war on various concepts, which I love because it brings energy and attention to [00:30:00] frankly data and finding answers in there. So if you'll humor me in our war corner, I wanna to go through some, some classic, classic avan. Um, all right, so can you talk to me a little bit about vanity metrics, because I think they are in play. Every day. Avinash Kaushik: Absolutely. No, no, no. Across the board, I think in whatever we do. So, so actually I'll, I'll, I'll do three. You know, so there's vanity metrics, activity metrics and outcome metrics. So basically everything goes into these three buckets essentially. So vanity metrics are, are the ones that are very easy to find, but them moving up and down has nothing to do with the number of donations you're gonna get as a nonprofit. They're just there to ease our ego. So, for example. Let's say we are a nonprofit and we run some display ads, so measure the number of impressions that were delivered for our display ad. That's a vanity metric. It doesn't tell you anything. You could have billions of impressions. You could have 10 impressions, doesn't matter, but it is easily [00:31:00] available. The count is easily available, so we report it. Now, what matters? What matters are, did anybody engage with the ad? What were the percent of people who hovered on the ad? What were the number of people who clicked on the ad activity metrics? Activity metrics are a little more useful than vanity metrics, but what does it matter for you as a non nonprofit? The number of donations you received in the last 24 hours. That's an outcome metric. Vanity activity outcome. Focus on activity to diagnose how well our campaigns or efforts are doing in marketing. Focus on outcomes to understand if we're gonna stay in business or not. Sorry, dramatic. The vanity metrics. Chasing is just like good for ego. Number of likes is a very famous one. The number of followers on a social paia, a very famous one. Number of emails sent is another favorite one. There's like a whole host of vanity metrics that are very easy to get. I cannot emphasize this enough, but when you unpack and or do meta-analysis of [00:32:00] relationship between vanity metrics and outcomes, there's a relationship between them. So we always advise people that. Start by looking at activity metrics to help you understand the user's behavior, and then move to understanding outcome metrics because they are the reason you'll thrive. You will get more donations or you will figure out what are the things that drive more donations. Otherwise, what you end up doing is saying. If I post provocative stuff on Facebook, I get more likes. Is that what you really wanna be doing? But if your nonprofit says, get me more likes, pretty soon, there's like a naked person on Facebook that gets a lot of likes, but it's corrupting. Yeah. So I would go with cute George Weiner: cat, I would say, you know, you, you get the generic cute cat. But yeah, same idea. The Internet's built on cats Avinash Kaushik: and yes, so, so that's why I, I actively recommend people stay away from vanity metrics. George Weiner: Yeah. Next up in War Corner, the last click [00:33:00] fallacy, right? The overweighting of this last moment of purchase, or as you'd maybe say in the do column of the See, think, do care. Avinash Kaushik: Yes. George Weiner: Yes. Avinash Kaushik: So when the, when the, when we all started to get Google Analytics, we got Adobe Analytics web trends, remember them, we all wanted to know like what drove the conversion. Mm-hmm. I got this donation for a hundred dollars. I got a donation for a hundred thousand dollars. What drove the conversion. And so what lo logically people would just say is, oh, where did this person come from? And I say, oh, the person came from Google. Google drove this conversion. Yeah, his last click analysis just before the conversion. Where did the person come from? Let's give them credit. But the reality is it turns out that if you look at consumer behavior, you look at days to donation, visits to donation. Those are two metrics available in Google. It turns out that people visit multiple times before [00:34:00] they make a donation. They may have come through email, their interest might have been triggered through your email. Then they suddenly remembered, oh yeah, yeah, I wanted to go to the nonprofit and donate something. This is Google, you. And then Google helps them find you and they come through. Now, who do you give credit Email or the Google, right? And what if you came 5, 7, 8, 10 times? So the last click fallacy is that it doesn't allow you to see the full consumer journey. It gives credit to whoever was the last person who sent you this, who introduced this person to your website. And so very soon we move to looking at what we call MTI, Multi-Touch Attribution, which is a free solution built into Google. So you just go to your multichannel funnel reports and it will help you understand that. One, uh, 150 people came from email. Then they came from Google. Then there was a gap of nine days, and they came back from Facebook and then they [00:35:00] converted. And what is happening is you're beginning to understand the consumer journey. If you understand the consumer journey better, we can come with better marketing. Otherwise, you would've said, oh, close shop. We don't need as many marketing people. We'll just buy ads on Google. We'll just do SEO. We're done. Oh, now you realize there's a more complex behavior happening in the consumer. They need to solve for email. You solve for Google, you need to solve Facebook. In my hypothetical example, so I, I'm very actively recommend people look at the built-in free MTA reports inside the Google nalytics. Understand the path flow that is happening to drive donations and then undertake activities that are showing up more often in the path, and do fewer of those things that are showing up less in the path. George Weiner: Bring these up because they have been waiting on my mind in the land of AEO. And by the way, we're not done with war. The war corner segment. There's more war there's, but there's more, more than time. But with both of these metrics where AEO, if I'm putting these glasses back on, comes [00:36:00] into play, is. Look, we're saying goodbye to frankly, what was probably somewhat of a vanity metric with regard to organic traffic coming in on that 10 facts about cube cats. You know, like, was that really how we were like hanging our hat at night, being like. Job done. I think there's very much that in play. And then I'm a little concerned that we just told everyone to go create an AEO channel on their Google Analytics and they're gonna come in here. Avinash told me that those people are buyers. They're immediately gonna come and buy, and why aren't they converting? What is going on here? Can you actually maybe couch that last click with the AI channel inbound? Like should I expect that to be like 10 x the amount of conversions? Avinash Kaushik: All we can say is it's, it's going to be people with high intention. And so with the businesses that I'm working with, what we are finding is that the conversion rates are higher. Mm. This game is too early to establish any kind of sense of if anybody has standards for AEO, they're smoking crack. Like the [00:37:00] game is simply too early. So what we I'm noticing is that in some cases, if the average conversion rate is two point half percent, the AEO traffic is converting at three, three point half. In two or three cases, it's converting at six, seven and a half. But there is not enough stability in the data. All of this is new. There's not enough stability in the data to say, Hey, definitely you can expect it to be double or 10% more or 50% more. We, we have no idea this early stage of the game, but, but George, if we were doing this again in a year, year and a half, I think we'll have a lot more data and we'll be able to come up with some kind of standards for, for now, what's important to understand is, first thing is you're not gonna rank in an answer engine. You just won't. If you do rank in an answer engine, you fought really hard for it. The person decided, oh my God, I really like this. Just just think of the user behavior and say, this person is really high intent because somehow [00:38:00] you showed up and somehow they found you and came to you. Chances are they're caring. Very high intent. George Weiner: Yeah. They just left a conversation with a super intelligent like entity to come to your freaking 2001 website, HTML CSS rendered silliness. Avinash Kaushik: Whatever it is, it could be the iffiest thing in the world, but they, they found me and they came to you and they decided that in the answer engine, they like you as the answer the most. And, and it took that to get there. And so all, all, all is I'm finding in the data is that they carry higher intent and that that higher intent converts into higher conversion rates, higher donations, as to is it gonna be five 10 x higher? It's unclear at the moment, but remember, the other reason you should care about it is. Every single day. As more people move away from Google search engines to answer engines, you're losing a ton of traffic. If somebody new showing up, treat them with, respect them with love. Treat them with [00:39:00] care because they're very precious. Just lost a hundred. Check the landing George Weiner: pages. 'cause you may be surprised where your front door is when complexity is bringing them to you, and it's not where you spent all of your design effort on the homepage. Spoiler. That's exactly Avinash Kaushik: right. No. Exactly. In fact, uh, the doping deeper into your websites is becoming even more prevalent with answer engines. Mm-hmm. Um, uh, than it used to be with search engines. The search always tried to get you the, the top things. There's still a lot of diversity. Your homepage likely is still only 30% of your traffic. Everybody else is landing on other homepage or as you call them, landing pages. So it's really, really important to look beyond your homepage. I mean, it was true yesterday. It's even truer today. George Weiner: Yeah, my hunch and what I'm starting to see in our data is that it is also much higher on the assisted conversion like it is. Yes. Yes, it is. Like if you have come to us from there, we are going to be seeing you again. That's right. That's right. More likely than others. It over indexes consistently for us there. Avinash Kaushik: [00:40:00] Yes. Again, it ties back to the person has higher intent, so if they didn't convert in that lab first session, their higher intent is gonna bring them back to you. So you are absolutely right about the data that you're seeing. George Weiner: Um, alright. War corner, the 10 90 rule. Can you unpack this and then maybe apply it to somebody who thinks that their like AI strategy is done? 'cause they spend $20 or $200 a month on some tool and then like, call it a day. 'cause they did ai. Avinash Kaushik: Yes, yes. No, it's, it's good. I, I developed it in context of analytics. When I was at my, uh, job at Intuit, I used to, I was at Intuit, senior director for research and analytics. And one of the things I found is people would consistently spend lots of money on tools in that time, web analytics tools, research tools, et cetera. And, uh, so they're spending a contract of a few hundred thousand dollars or hundreds of thousands of dollars, and then they give it to a fresh graduate to find insights. [00:41:00] I was like, wait, wait, wait. So you took this $300,000 thing and gave it to somebody. You're paying $45,000 a year. Who is young in their career, young in their career, and expecting them to make you tons of money using this tool? It's not the tool, it's the human. And so that's why I developed the the 10 90 rule, which is that if you have a, if you have a hundred dollars to invest in making smarter decisions, invest $10 in the tool, $90 in the human. We all have access to so much data, so much complexity. The world is changing so fast that it is the human that is going to figure out how to make sense of these insights rather than the tool magically spewing and understanding your business enough to tell you exactly what to do. So that, that's sort of where the 10 90 rule came from. Now, sort of we are in this, in this, um, this is very good for nonprofits by the way. So we're in this era. Where On the 90 side? No. So the 10, look, don't spend insane money on tools that is just silly. So don't do that. Now the 90, let's talk about the [00:42:00] 90. Up until two years ago, I had to spell all of the 90 on what I now call organic humans. You George Weiner: glasses wearing humans, huh? Avinash Kaushik: The development of LLM means that every single nonprofit in the world has access to roughly a third year bachelor's degree student. Like a really smart intern. For free. For free. In fact, in some instances, for some nonprofits, let's say I I just reading about this nonprofit that is cleaning up plastics in the ocean for this particular nonprofit, they have access to a p HT level environmentalist using the latest Chad GP PT 4.5, like PhD level. So the little caveat I'm beginning to put in the 10 90 rule is on the 90. You give the 90 to the human and for free. Get the human, a very smart Bachelor's student by using LLMs in some instances. Get [00:43:00] for free a very smart TH using the LLMs. So the LLMs have now to be incorporated into your research, into your analysis, into building a next dashboard, into building a next website, into building your next mobile game into whatever the hell you're doing for free. You can get that so you have your organic human. Less the synthetic human for free. Both of those are in the 90 and, and for nonprofit, so, so in my work at at Coach and Kate Spade. I have access now to a couple of interns who do free work for me, well for 20 minor $20 a month because I have to pay for the plus version of G bt. So the intern costs $20 a month, but I have access to this syn synthetic human who can do a whole lot of work for me for $20 a month in my case, but it could also do it for free for you. Don't forget synthetic humans. You no longer have to rely only on the organic humans to do the 90 part. You would be stunned. Upload [00:44:00] your latest, actually take last year's worth of donations, where they came from and all this data from you. Have a spreadsheet lying around. Dump it into chat. GPT, I'll ask it to analyze it. Help you find where most donations came from, and visualize trends to present to board of directors. It will blow your mind how good it is at do it with Gemini. I'm not biased, I'm just seeing chat. GPD 'cause everybody knows it so much Better try it with mistrial a, a small LLM from France. So I, I wanna emphasize that what has changed over the last year is the ability for us to compliment our organic humans with these synthetic entities. Sometimes I say synthetic humans, but you get the point. George Weiner: Yeah. I think, you know, definitely dump that spreadsheet in. Pull out the PII real quick, just, you know, make me feel better as, you know, the, the person who's gonna be promoting this to everybody, but also, you know, sort of. With that. I want to make it clear too, that like actually inside of Gemini, like Google for nonprofits has opened up access to Gemini for free is not a per user, per whatever. You have that [00:45:00] you have notebook, LLM, and these. Are sitting in their backyards for free every day and it's like a user to lose it. 'cause you have a certain amount of intelligence tokens a day. Can you, I just like wanna climb like the tallest tree out here and just start yelling from a high building about this. Make the case of why a nonprofit should be leveraging this free like PhD student that is sitting with their hands underneath their butts, doing nothing for them right now. Avinash Kaushik: No, it is such a shame. By the way, I cannot add to your recommendation in using your Gemini Pro account if it's free, on top of, uh, all the benefits you can get. Gemini Pro also comes with restrictions around their ability to use your data. They won't, uh, their ability to put your data anywhere. Gemini free versus Gemini Pro is a very protected environment. Enterprise version. So more, more security, more privacy, et cetera. That's a great benefit. And by the way, as you said, George, they can get it for free. So, um, the, the, the, the posture you should adopt is what big companies are doing, [00:46:00] which is anytime there is a job to be done, the first question you, you should ask is, can I make the, can an AI do the job? You don't say, oh, let me send it to George. Let me email Simon, let me email Sarah. No, no, no. The first thing that should hit your head is. I do the job because most of the time for, again, remember, third year bachelor's degree, student type, type experience and intelligence, um, AI can do it better than any human. So your instincts to be, let me outsource that kind of work so I can free up George's cycles for the harder problems that the AI cannot solve. And by the way, you can do many things. For example, you got a grant and now Meta allows you to run X number of ads for free. Your first thing, single it. What kind of ad should I create? Go type in your nonprofit, tell it the kind of things you're doing. Tell it. Tell it the donations you want, tell it the size, donation, want. Let it create the first 10 ads for you for free. And then you pick the one you like. And even if you have an internal [00:47:00] designer who makes ads, they'll start with ideas rather than from scratch. It's just one small example. Or you wanna figure out. You know, my email program is stuck. I'm not getting yield rates for donations. The thing I want click the button that called that is called deep research or thinking in the LL. Click one of those two buttons and then say, I'm really struggling. I'm at wits end. I've tried all these things. Write all the detail. Write all the detail about what you've tried and now working. Can you please give me three new ideas that have worked for nonprofits who are working in water conservation? Hmm. This would've taken a human like a few days to do. You'll have an answer in under 90 seconds. I just give two simple use cases where we can use these synthetic entities to send us, do the work for us. So the default posture in nonprofits should be, look, we're resource scrapped anyway. Why not use a free bachelor's degree student, or in some case a free PhD student to do the job, or at least get us started on a job. So just spending 10 [00:48:00] hours on it. We only spend the last two hours. The entity entity does the first date, and that is super attractive. I use it every single day in, in one of my browsers. I have three traps open permanently. I've got Claude, I've got Mistrial, I've got Charge GPT. They are doing jobs for me all day long. Like all day long. They're working for me. $20 each. George Weiner: Yeah, it's an, it, it, it's truly, it's an embarrassment of riches, but also getting back to the, uh, the 10 90 is, it's still sitting there. If you haven't brought that capacity building to the person on how to prompt how to play that game of linguistic tennis with these tools, right. They're still just a hammer on a. Avinash Kaushik: That's exactly right. That's exactly right. Or, or in your case, you, you have access to Gemini for nonprofits. It's a fantastic tool. It's like a really nice card that could take you different places you insist on cycling everywhere. It's, it's okay cycle once in a while for health reasons. Otherwise, just take the car, it's free. George Weiner: Ha, you've [00:49:00] been so generous with your time. Uh, I do have one more quick war. If you, if you have, have a minute, uh, your war on funnels, and maybe this is not. Fully fair. And I am like, I hear you yelling at me every time I'm showing our marketing funnel. And I'm like, yeah, but I also have have a circle over here. Can you, can you unpack your war on funnels and maybe bring us through, see, think, do, care and in the land of ai? Avinash Kaushik: Yeah. Okay. So the marketing funnel is very old. It's been around for a very long time, and once I, I sort of started working at Google, access to lots more consumer research, lots more consumer behavior. Like 20 years ago, I began to understand that there's no such thing as funnel. So what does the funnel say? The funnel says there's a group of people running around the world, they're not aware of your brand. Find them, scream at them, spray and pray advertising at them, make them aware, and then somehow magically find the exact same people again and shut them down the fricking funnel and make them consider your product.[00:50:00] And now that they're considering, find them again, exactly the same people, and then shove them one more time. Move their purchase index and then drag them to your website. The thing is this linearity that there's no evidence in the universe that this linearity exists. For example, uh, I'm going on a, I like long bike rides, um, and I just got thirsty. I picked up the first brand. I could see a water. No awareness, no consideration, no purchase in debt. I just need water. A lot of people will buy your brand because you happen to be the cheapest. I don't give a crap about anything else, right? So, um, uh, uh, the other thing to understand is, uh, one of the brands I adore and have lots of is the brand. Patagonia. I love Patagonia. I, I don't use the word love for I think any other brand. I love Patagonia, right? For Patagonia. I'm always in the awareness stage because I always want these incredible stories that brand ambassadors tell about how they're helping the environment. [00:51:00] I have more Patagonia products than I should have. I'm already customer. I'm always open to new considerations of Patagonia products, new innovations they're bringing, and then once in a while, I'm always in need to buy a Patagonia product. I'm evaluating them. So this idea that the human is in one of these stages and your job is to shove them down, the funnel is just fatally flawed, no evidence for it. Instead, what you want to do is what is Ash's intent at the moment? He would like environmental stories about how we're improving planet earth. Patagonia will say, I wanna make him aware of my environmental stories, but if they only thought of marketing and selling, they wouldn't put me in the awareness because I'm already a customer who buys lots of stuff from already, right? Or sometimes I'm like, oh, I'm, I'm heading over to London next week. Um, I need a thing, jacket. So yeah, consideration show up even though I'm your customer. So this seating do care is a framework that [00:52:00] says, rather than shoving people down things that don't exist and wasting your money, your marketing should be able to discern any human's intent and then be able to respond with a piece of content. Sometimes that piece of content in an is an ad. Sometimes it's a webpage, sometimes it's an email. Sometimes it's a video. Sometimes it's a podcast. This idea of understanding intent is the bedrock on which seat do care is built about, and it creates fully customer-centric marketing. It is harder to do because intent is harder to infer, but if you wanna build a competitive advantage for yourself. Intent is the magic. George Weiner: Well, I think that's a, a great point to, to end on. And again, so generous with, uh, you know, all the work you do and also supporting nonprofits in the many ways that you do. And I'm, uh, always, always watching and seeing what I'm missing when, um, when a new, uh, AKA's Razor and Newsletter come out. So any final sign off [00:53:00] here on how do people find you? How do people help you? Let's hear it. Avinash Kaushik: You can just Google or answer Engine Me. It's, I'm not hard. I hard to find, but if you're a nonprofit, you can sign up for my newsletter, TMAI marketing analytics newsletter. Um, there's a free one and a paid one, so you can just sign up for the free one. It's a newsletter that comes out every five weeks. It's completely free, no strings or anything. And that way I'll be happy to share my stories around better marketing and analytics using the free newsletter for you so you can sign up for that. George Weiner: Brilliant. Well, thank you so much, Avan. And maybe, maybe we'll have to take you up on that offer to talk sometime next year and see, uh, if maybe we're, we're all just sort of, uh, hanging out with synthetic humans nonstop. Thank you so much. It was fun, George. [00:54:00]
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