Podcasts about google deepmind

In this episode of Campus Technology Insider Podcast Shorts, Rhea Kelly highlights recent developments in higher education technology, including Backslash Security's discovery of vulnerabilities in the Model Context Protocol, a U.S. District Court's ruling on Anthropic's use of copyrighted books, and Google DeepMind's launch of the lightweight AI model, Gemma 3n. Learn about the Neighbor Jack flaw, the OS injection vulnerability, and how these situations impact AI and security. Additionally, stay updated on Anthropic's legal challenges and the features of Google's latest AI innovation designed for mobile and edge devices. 00:00 Introduction to Campus Technology Insider Podcast 00:16 Security Vulnerabilities in Model Context Protocol 00:54 Anthropic's Copyright Ruling and Legal Challenges 01:26 Google DeepMind's Gemma 3n AI Model Launch 02:05 Conclusion and Further Resources Source links: Report: Agentic AI Protocol Is Vulnerable to Cyber Attacks Federal Court Rules AI Training with Copyrighted Books Fair Use Google Launches Lightweight Gemma 3n, Expanding Edge AI Efforts Campus Technology Insider Podcast Shorts are curated by humans and narrated by AI.

The Newcomer Podcast returns just in time to have Eric, Tom, and Madeline weigh in on Meta's audacious AI hiring spree. The tech giant has enticed researchers from OpenAI, Google DeepMind, and Anthropic with huge paydays in the hopes it can bring its Llama models up to par with the competition. Next up, Ramp's report that companies have stopped purchasing AI tools made a lot of buzz this week, but it's still too early to call an AI peak.Later on in the episode, Grok's offensive replies aren't enough to slow down xAI's latest model launch. We close out the episode rehashing Sequoia partner Shaun Maguire's latest inflammatory tweets over New York mayoral candidate Zohran Mamdani.00:35 — Meta poaches top researchers to ail its flailing models11:13 — XAI outperforms despite Grok's offensive replies18:27 — It's too early to call the AI bubble28:50 — Shaun Maguire's tweets bring attention to Sequoia

In this episode, I chat with Samuel Albanie about the Google DeepMind paper he co-authored called "An Approach to Technical AGI Safety and Security". It covers the assumptions made by the approach, as well as the types of mitigations it outlines. Patreon: https://www.patreon.com/axrpodcast Ko-fi: https://ko-fi.com/axrpodcast Transcript: https://axrp.net/episode/2025/07/06/episode-45-samuel-albanie-deepminds-agi-safety-approach.html   Topics we discuss, and timestamps: 0:00:37 DeepMind's Approach to Technical AGI Safety and Security 0:04:29 Current paradigm continuation 0:19:13 No human ceiling 0:21:22 Uncertain timelines 0:23:36 Approximate continuity and the potential for accelerating capability improvement 0:34:29 Misuse and misalignment 0:39:34 Societal readiness 0:43:58 Misuse mitigations 0:52:57 Misalignment mitigations 1:05:20 Samuel's thinking about technical AGI safety 1:14:02 Following Samuel's work   Samuel on Twitter/X: x.com/samuelalbanie   Research we discuss: An Approach to Technical AGI Safety and Security: https://arxiv.org/abs/2504.01849 Levels of AGI for Operationalizing Progress on the Path to AGI: https://arxiv.org/abs/2311.02462 The Checklist: What Succeeding at AI Safety Will Involve: https://sleepinyourhat.github.io/checklist/ Measuring AI Ability to Complete Long Tasks: https://arxiv.org/abs/2503.14499   Episode art by Hamish Doodles: hamishdoodles.com

OpenAI, Meta & Google are fighting over who gets to control the future of superintelligence but what happens when Zuck robs Sam Altman blind? And is Apple about to onboard Anthropic? In the big AI news this week, Meta hires over 10 top OpenAI engineers (for a rumored potential $300 million in compensation), Apple considers replacing its entire AI strategy with Claude or ChatGPT, and Microsoft's new medical model diagnoses diseases 4x better than human doctors. Plus, Google DeepMind's gaming push, a fake band goes viral on Spotify, and OpenAI's secret open-source model might be dropping any day now. Also: Korea's first AI-animated show, Tesla's Optimus robot hits a setback, Google Voice pushes a new update and yes, there's a cowboy robot rizzing people on the street of Austin. US HUMANS AIN'T GOING AWAY. UNLESS THE AI GIVES US ENDLESS TREATS. Join the discord: https://discord.gg/muD2TYgC8f Join our Patreon: https://www.patreon.com/AIForHumansShow AI For Humans Newsletter: https://aiforhumans.beehiiv.com/ Follow us for more on X @AIForHumansShow Join our TikTok @aiforhumansshow To book us for speaking, please visit our website: https://www.aiforhumans.show/   // Show Links // Zuck Has Offered 10 OAI Employees 300m Four Year Packages w/ $100 Total Comp First Year https://x.com/kyliebytes/status/1940123469481758857 Clip from old Y-Combinator Video Sam Talks Facebook Hiring https://x.com/ai_for_success/status/1940323676597232112 Sam Altman Replies To The Poaching https://www.wired.com/story/sam-altman-meta-ai-talent-poaching-spree-leaked-messages/ OpenAI “Re-calibrating Comp” https://x.com/WIRED/status/1939402241279930670 New OpenAI Open Source Model Getting Big Hype https://x.com/Yuchenj_UW/status/1939462191302033757 Apple may partner with either Anthropic or OpenAI For Their Internal AI  https://www.cnbc.com/2025/07/01/apple-weighs-using-anthropic-or-openai-to-power-siri-in-major-reversal-bloomberg-news-.html Demis Hassabis Teases AI Gaming VEO 3 Engine https://x.com/demishassabis/status/1940248521111961988 Microsoft AI 4x Better Than Group of Doctors at Diagnosis https://microsoft.ai/new/the-path-to-medical-superintelligence/ New AI Model Chai-2 Zero Shots Antibody Discovery https://x.com/chaidiscovery/status/1939684680447746050 New Google Audio TTS Models Are Very Good (Demo Live) https://aistudio.google.com/generate-speech ElevenLabs CEO Thinks THIS YEAR will be a massive AI Voice milestone https://www.reddit.com/r/singularity/comments/1lp0tbl/elevenlabs_ceo_mati_staniszewski_says_we_may_pass/ The Velvet Sundown is (Prob) an AI “Hit” Band On Spotify https://futurism.com/indie-rock-band-velvet-sundown-never-use-ai “Their” Twitter Handle Denies They Are AI https://x.com/Velvet_Sundown China's First Robot Soccer Match Is Joybasket of Fails https://x.com/ianbremmer/status/1940088097083203724 https://www.theguardian.com/technology/2025/jun/30/china-hosts-first-fully-autonomous-ai-robot-football-match TESLA Optimus Pause? https://x.com/TheHumanoidHub/status/1940425831907795142 K-Bot: New Open Source American Made Humanoid for $9000 https://x.com/kscalelabs/status/1940108075064865126 Jake the Rizzbot https://www.instagram.com/p/DLQwaWNNYwD/ https://www.tiktok.com/@realjaygroove/video/7518601215547067662?is_from_webapp=1&sender_device=pc&web_id=7439884751341962782 Random Humanoid Running Through Trees https://www.reddit.com/r/singularity/comments/1lprh9b/the_robot_uprising_is_near_give_or_take_a_few_bug/ Polyglot YTer Speaks Binary to ChatGPT & It Kind of Freaks Out https://youtu.be/GiaNp0u_swU?si=c28k2i7gdo0GYmDC  

Today's show:Grammarly is acquiring the beloved email app Superhuman! In today's extremely timely episode, @alex sits down with Grammarly CEO Shishir Mehrotra and Superhuman founder Rahul Vohra to unpack why they're merging, how they plan to combine apps and AI agents, and what it means for the future of email and work. PLUS they reveal how Grammarly's 40M+ daily users already rely on email—and why this deal is the key to building the ultimate communication assistant. Don't miss this deep dive into one of the most exciting AI acquisitions yet!#AI #Startups #Productivity #Grammarly #Superhuman #VentureCapital #MergersAndAcquisitionsTimestamps:(0:00) Introduction to the future of robotics and AI regulation(1:11) Introduction of hosts and overview of today's topics(4:19) Cloudflare's new pay per crawl product(09:37) Northwest Registered Agent. Form your entire business identity in just 10 clicks and 10 minutes. Get more privacy, more options, and more done—visit northwestregisteredagent.com/twist today!(10:41) Polymarket segment on Apple's acquisition prospects(14:29) Grammarly and Superhuman CEOs interviews(19:42) Retool - Visit https://www.retool.com/twist and try it out today.(24:09) AI in productivity tools and email agents discussion(29:23) AWS Activate - AWS Activate helps startups bring their ideas to life. Apply to AWS Activate today to learn more. Visit aws.amazon.com/startups/credits(30:46) Grammarly's AI platform and the acquisition of Superhuman(41:16) Introduction of Manu Sharma from Labelbox(41:47) The role of data labeling in AI and Labelbox's data factory(53:44) Labelbox's market position and capital efficiency post-ChatGPT(1:03:00) Advances in humanoid robotics with Jeff Cardenas from Apptronik(1:07:09) Market readiness and capabilities of Apollo 2 robots(1:13:27) Humanoid robotics: Google DeepMind partnership and international competition(1:20:54) US federal support for R&D in robotics(1:22:10) The evolution of humanoid robotics and Apptronik's growth in AustinSubscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpFollow Lon:X: https://x.com/lonsFollow Alex:X: https://x.com/alexLinkedIn: ⁠https://www.linkedin.com/in/alexwilhelmFollow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisThank you to our partners:(09:37) Northwest Registered Agent. Form your entire business identity in just 10 clicks and 10 minutes. Get more privacy, more options, and more done—visit northwestregisteredagent.com/twist today!(19:42) Retool - Visit https://www.retool.com/twist and try it out today.(29:23) AWS Activate - AWS Activate helps startups bring their ideas to life. Apply to AWS Activate today to learn more. Visit aws.amazon.com/startups/creditsGreat TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarlandCheck out Jason's suite of newsletters: https://substack.com/@calacanisFollow TWiST:Twitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: https://www.instagram.com/thisweekinstartupsTikTok: https://www.tiktok.com/@thisweekinstartupsSubstack: https://twistartups.substack.comSubscribe to the Founder University Podcast: https://www.youtube.com/@founderuniversity1916

Much of the scientific process involves searching. But rather than continue to rely on the luck of discovery, Google DeepMind has engineered a more efficient AI agent that mines complex spaces to facilitate scientific breakthroughs. Sarah Guo speaks with Pushmeet Kohli, VP of Science and Strategic Initiatives, and research scientist Matej Balog at Google DeepMind about AlphaEvolve, an autonomous coding agent they developed that finds new algorithms through evolutionary search. Pushmeet and Matej talk about how AlphaEvolve tackles the problem of matrix multiplication efficiency, scaling and iteration in problem solving, and whether or not this means we are at self-improving AI. Together, they also explore the implications AlphaEvolve has to other sciences beyond mathematics and computer science. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @pushmeet | @matejbalog Chapters: 00:00 Pushmeet Kohli and Matej Balog Introduction 0:48 Origin of AlphaEvolve 02:31 AlphaEvolve's Progression from AlphaGo and AlphaTensor 08:02 The Open Problem of Matrix Multiplication Efficiency 11:18 How AlphaEvolve Evolves Code 14:43 Scaling and Predicting Iterations 16:52 Implications for Coding Agents 19:42 Overcoming Limits of Automated Evaluators 25:21 Are We At Self-Improving AI? 28:10 Effects on Scientific Discovery and Mathematics 31:50 Role of Human Scientists with AlphaEvolve 38:30 Making AlphaEvolve Broadly Accessible 40:18 Applying AlphaEvolve Within Google 41:39 Conclusion

Robots que aprenden tareas viendo videos... y sin conexión a internet  Por Félix Riaño @LocutorCo  Google DeepMind presentó Gemini Robotics On-Device, un modelo que funciona dentro del robot, sin necesidad de la nube, aprende rápido y se adapta a distintos cuerpos robóticos.  Google DeepMind presentó un modelo de inteligencia artificial que no necesita conexión a internet para funcionar. Se llama Gemini Robotics On-Device y opera dentro del robot. Es rápido, privado y ya puede doblar ropa, abrir cremalleras y adaptarse a varios tipos de robots sin tener que volver a entrenarlo desde cero. Aprende viendo tareas nuevas entre 50 y 100 veces. Se entrena rápido y ejecuta en tiempo real. Es como tener un robot que piensa por su cuenta, sin depender de ningún servidor externo. ¿Ya estamos cerca de tener robots verdaderamente autónomos en nuestras casas y trabajos?  Este robot no necesita nube para pensar. Piensa dentro de sí mismo.  Imagina que tienes un robot en casa. Le dices “dobla esta camiseta” y lo hace sin conectarse a internet. Esa es la idea de Gemini Robotics On-Device. Funciona completamente desde el robot. Google entrenó este modelo en su robot ALOHA y luego lo adaptó al humanoide Apollo y al robot Franka FR3 con dos brazos. Se adapta con rapidez y funciona sin ayuda externa. Lo sorprendente es que aprende nuevas tareas con solo 50 a 100 demostraciones. Puede entender instrucciones como “abre esta cremallera” y ejecutar la acción con precisión. Todo se procesa dentro del robot. Nada se envía a la nube.  Los robots que necesitan internet pueden fallar si la red se cae. Además, enviar todo lo que ven a la nube plantea problemas de privacidad. En entornos sensibles como hospitales, fábricas o casas, eso no es aceptable. Gemini Robotics On-Device elimina ese riesgo. El procesamiento local evita filtraciones y funciona incluso sin señal. Eso permite usarlo en lugares donde antes era impensable. Pero también hay desafíos: los desarrolladores deben encargarse de que el robot no cometa errores peligrosos. Google sugiere usar su API de seguridad o crear mecanismos de protección propios para evitar comportamientos inadecuados o inseguros.  Gemini Robotics On-Device es ideal para tareas cotidianas. Se entrena rápido, se adapta a distintos robots y actúa en tiempo real. No sustituye al modelo más avanzado en la nube, pero lo complementa. Puede operar sin conexión, lo que es útil en lugares con mala señal o donde la privacidad es prioritaria. Google lanzó un SDK que permite entrenar nuevos comportamientos usando el simulador físico MuJoCo. Ya hay testers trabajando con el modelo. En poco tiempo podríamos ver robots que doblan ropa, ensamblan piezas o colaboran en casa sin necesidad de conexión. El futuro robótico, autónomo y local ya llegó.  Otras empresas también trabajan en robótica. Nvidia está desarrollando una plataforma de modelos base para robots humanoides. Hugging Face crea conjuntos de datos abiertos para entrenar robots. La startup coreana RLWRLD también desarrolla modelos fundacionales. Pero Google ya tiene un modelo funcional probado en robots reales. Su equipo ReDI evalúa la seguridad y el impacto social del sistema. Cada nuevo avance pasa por el Consejo de Seguridad y se hacen pruebas para corregir errores. La versión actual está basada en Gemini 2.0, pero vendrán más potentes. La robótica sin internet ya no es futuro. Es presente.  Robots que aprenden sin internet, ejecutan tareas en tiempo real y cuidan tu privacidad. Gemini Robotics On-Device ya está en pruebas reales. ¿Qué tarea le enseñarías tú? Comenta y sigue el pódcast Flash Diario en Spotify.

Anthropic kocht fysiek duizenden boeken, scheurde de ruggen eraf en scande ze voor hun AI-modellen. Een Amerikaanse rechter oordeelde deze week dat dit prima is - drie rechtszaken die bepalen dat AI-bedrijven mogen trainen op legaal verkregen content. Ondertussen infiltreren chatbots van OpenAI en Perplexity stilletjes WhatsApp met 3 miljard gebruikers. Terwijl Meta haar eigen AI pusht, gebruiken concurrenten WhatsApp Business als distributiekanaal. Het wordt een strijd om de messaging-app als AI-toegang.In de recruitingwereld een absurde wapenwetloop: sollicitanten gebruiken AI voor 1200 sollicitaties per dag, werkgevers zetten AI-chatbots in om te screenen, kandidaten gebruiken weer AI om die testen te verslaan. Tenslotte maakte Google DeepMind een doorbraak met Vision Language Action modellen die volledig lokaal op robots draaien - geen internet nodig om je t-shirt te vouwen. Van cloud-robots naar lokale AI-zwermen.Als je een lezing wil over AI van Wietse of Alexander dan kan dat. Mail ons op lezing@aireport.emailOp de hoogte blijven van het laatste AI-nieuws en 2x per week tips & tools ontvangen om het meeste uit AI te halen (en bij de webinar te zijn). Abonneer je dan op onze nieuwsbrief via aireport.emailVandaag nog beginnen met AI binnen jouw bedrijf? Ga dan naar deptagency.com/aireport This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.aireport.email/subscribe

Professor Satinder Singh of Google DeepMind and U of Michigan is co-founder of RLDM.  Here he narrates the origin story of the Reinforcement Learning and Decision Making meeting (not conference).Recorded on location at Trinity College Dublin, Ireland during RLDM 2025.Featured ReferencesRLDM 2025: Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM)June 11-14, 2025 at Trinity College Dublin, IrelandSatinder Singh on Google Scholar

What does it take to build AI-powered products that scale? In this episode, we are joined by Jonathan Evens, Product Lead at Google DeepMind, to explore the evolving role of product management in the AI era. Jonathan draws from experience across startups and Big Tech, ranging from smart grid systems to LLM-powered search, to reveal how high-impact AI products come to life. He breaks down DeepMind's journey launching “AI Overviews” in Search, from beta testing in May 2023 to worldwide rollout just six months later. Jonathan also shares frameworks for balancing problem-led versus technology-led thinking, future-proofing AI roadmaps, and making intelligent experiences (not just features) the north star. He's here to help product teams demystify LLMs and launch bold AI functionality with nimble development cycles. Tune in to gain practical advice for integrating AI thoughtfully, iterating quickly, and delivering real value.

Logan Kilpatrick from Google DeepMind talks about the latest developments in the Gemini 2.5 model family, including Gemini 2.5 Pro, Flash, and the newly introduced Flashlight. Logan also offers insight into AI development workflows, model performance, and the future of proactive AI assistants. Links Website: https://logank.ai LinkedIn: https://www.linkedin.com/in/logankilpatrick X: https://x.com/officiallogank YouTube: https://www.youtube.com/@LoganKilpatrickYT Google AI Studio: https://aistudio.google.com Resources Gemini 2.5 Pro Preview: even better coding performance (https://developers.googleblog.com/en/gemini-2-5-pro-io-improved-coding-performance) Building with AI: highlights for developers at Google I/O (https://blog.google/technology/developers/google-ai-developer-updates-io-2025) We want to hear from you! How did you find us? Did you see us on Twitter? In a newsletter? Or maybe we were recommended by a friend? Let us know by sending an email to our producer, Em, at emily.kochanek@logrocket.com (mailto:emily.kochanek@logrocket.com), or tweet at us at PodRocketPod (https://twitter.com/PodRocketpod). Follow us. Get free stickers. Follow us on Apple Podcasts, fill out this form (https://podrocket.logrocket.com/get-podrocket-stickers), and we'll send you free PodRocket stickers! What does LogRocket do? LogRocket provides AI-first session replay and analytics that surfaces the UX and technical issues impacting user experiences. Start understanding where your users are struggling by trying it for free at LogRocket.com. Try LogRocket for free today. (https://logrocket.com/signup/?pdr) Special Guest: Logan Kilpatrick.

What if the traditional engineering career path is being fundamentally rewritten by AI? We're joined by Philipp Schmid, Senior AI Developer Relations Engineer at Google DeepMind, to explore how artificial intelligence is not just a tool, but a force reshaping engineering roles, team dynamics, and the foundational methods of skill development. Philipp, with his background at Hugging Face and now at the cutting edge with Google DeepMind, offers a unique perspective on the rise of AI-native teams and engineers who learn faster, work more broadly, and drive innovation at an unprecedented scale.Philipp offers an inside look at Google DeepMind's engine of AI innovation and breaks down the key differences between Google's flagship Gemini models and the versatile Gemma family of open models, detailing their distinct purposes.We also touch upon exciting takeaways from the recent Google I/O event, including powerful new on-device capabilities and the mind-blowing text-to-video generation with Veo.Finally, Philipp shares practical advice for engineers and their organizations on navigating this AI-driven landscape, emphasizing continuous learning, an adaptable mindset, and how to effectively leverage a diverse AI toolkit to thrive.Check out:Download: The 6 trends shaping the future of AI-driven development Follow the hosts:Follow BenFollow AndrewFollow today's guest:Twitter: @philschmidLinkedInGitHub (philschmid)Learn more about Google DeepMind's models: Google AI StudioReferenced in today's show:OpenAI's latest partner: Mattel | LinkedIn I Read All Of Cloudflare's Claude-Generated Commits AI coding assistants aren't really making devs feel more productive - LeadDev Congratulations on creating the one billionth repository on GitHubSupport 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

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Emily Forlini is here to give us an update on the state of brain computer interfaces. Google DeepMind and Google Research launched a new AI-based tropical cyclone forecasting model. NYU and UC Berkeley researchers have come up with a way to train robots by watching people perform tasks from their own perspectives. And Amazon Prime Video pads out their streaming non-ad free subscription with more ads. Starring Sarah Lane, Robb Dunewood, Emily Forlini, Roger Chang, Joe. To read the show notes in a separate page click here! Support the show on Patreon by becoming a supporter!

AI models have a defined memory ceiling, which is reshaping the ongoing debates surrounding copyright and data privacy. Recent research from Meta, Google DeepMind, Cornell, and NVIDIA reveals that large language models have a fixed memorization capacity of approximately 8.6 bits per parameter. This finding clarifies the distinction between memorized data and generalized knowledge, indicating that larger datasets do not necessarily lead to increased memorization of specific data points. This understanding is crucial as it informs the operational mechanisms of AI models and addresses concerns related to copyright infringement.Sundar Pichai, CEO of Google, has introduced the term "artificial jagged intelligence" to describe the current phase of AI development, highlighting the non-linear progress and the challenges faced by researchers despite significant advancements. Pichai's perspective reflects the mixed performance of AI models, which can exhibit extraordinary capabilities alongside notable errors. This sentiment is echoed by deep learning researcher Andrej Karpathy, emphasizing the unpredictability of AI performance and the need for a more nuanced understanding of its capabilities.The rise of AI retrieval bots is transforming how users access information online, with a significant increase in traffic from these bots. Companies like OpenAI and Anthropic are deploying these bots to summarize content in real-time, moving away from traditional search methods that provide links to multiple sources. This shift poses challenges for content publishers, as the growth of retrieval bots indicates a changing economic landscape where content is increasingly consumed by AI first, with human users following. Publishers may need to rethink their engagement strategies to adapt to this new reality.In the broader context of technology and cybersecurity, WhatsApp's intervention in a legal case concerning encryption and privacy rights highlights the growing role of platforms in surveillance debates. Additionally, the U.S. Cybersecurity and Infrastructure Security Agency faces leadership challenges amid a talent exodus, raising concerns about its operational effectiveness. As the IT services industry evolves, the integration of AI into various sectors, including hiring and cybersecurity, underscores the importance of execution, interoperability, and trust in automation. The future of technology will depend on how well businesses can navigate these changes and support their clients in making informed decisions.  Four things to know today  00:00 AI's Jagged Reality: Study Reveals Limits to Model Memory as Bots Redefine the Web Economy05:35 Cybersecurity Crossroads: WhatsApp Joins Apple in Legal Fight as U.S. Agency Leadership Crumbles08:29 AI Matures Into Infrastructure Layer as IT Vendors Shift Focus to Outcomes and Execution11:51 Legal Tech, GenAI, and Fast Food Bots All Show One Thing: Hype Doesn't Equal Success  This is the Business of Tech.    Supported by:  All our Sponsors: https://businessof.tech/sponsors/ Do you want the show on your podcast app or the written versions of the stories? Subscribe to the Business of Tech: https://www.businessof.tech/subscribe/Looking for a link from the stories? The entire script of the show, with links to articles, are posted in each story on https://www.businessof.tech/ Support the show on Patreon: https://patreon.com/mspradio/ Want to be a guest on Business of Tech: Daily 10-Minute IT Services Insights? Send Dave Sobel a message on PodMatch, here: https://www.podmatch.com/hostdetailpreview/businessoftech Want our stuff? Cool Merch? Wear “Why Do We Care?” - Visit https://mspradio.myspreadshop.com Follow us on:LinkedIn: https://www.linkedin.com/company/28908079/YouTube: https://youtube.com/mspradio/Facebook: https://www.facebook.com/mspradionews/Instagram: https://www.instagram.com/mspradio/TikTok: https://www.tiktok.com/@businessoftechBluesky: https://bsky.app/profile/businessof.tech

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Logan Kilpatrick from Google DeepMind returns for his fifth appearance to discuss Google's transformation from "sleeping giant" to AI powerhouse, sharing insights from his year at the company as AI usage grew 50 times to 500 trillion tokens per month. He examines Google's strengths, including superior compute infrastructure, frontier models like Gemini 2.5 Pro, viral products like NotebookLM, and the deepest AI research talent in the industry. The conversation covers whether leading AI companies will become more similar or different as easy opportunities disappear, why startups still have unique chances, and the potential impact of Google's ultra-fast diffusion language models. Logan also shares practical advice for joining early access programs and getting noticed by industry insiders, including his personal email and an open invitation to reach out. SPONSORS: Oracle Cloud Infrastructure: Oracle Cloud Infrastructure (OCI) is the next-generation cloud that delivers better performance, faster speeds, and significantly lower costs, including up to 50% less for compute, 70% for storage, and 80% for networking. Run any workload, from infrastructure to AI, in a high-availability environment and try OCI for free with zero commitment at https://oracle.com/cognitive The AGNTCY: The AGNTCY is an open-source collective dedicated to building the Internet of Agents, enabling AI agents to communicate and collaborate seamlessly across frameworks. Join a community of engineers focused on high-quality multi-agent software and support the initiative at https://agntcy.org/?utmcampaign=fy25q4agntcyamerpaid-mediaagntcy-cognitiverevolutionpodcast&utmchannel=podcast&utmsource=podcast NetSuite by Oracle: NetSuite by Oracle is the AI-powered business management suite trusted by over 41,000 businesses, offering a unified platform for accounting, financial management, inventory, and HR. Gain total visibility and control to make quick decisions and automate everyday tasks—download the free ebook, Navigating Global Trade: Three Insights for Leaders, at https://netsuite.com/cognitive PRODUCED BY: https://aipodcast.ing SOCIAL LINKS: Website: https://www.cognitiverevolution.ai Twitter (Podcast): https://x.com/cogrev_podcast Twitter (Nathan): https://x.com/labenz LinkedIn: https://linkedin.com/in/nathanlabenz/ Youtube: https://youtube.com/@CognitiveRevolutionPodcast Apple: https://podcasts.apple.com/de/podcast/the-cognitive-revolution-ai-builders-researchers-and/id1669813431 Spotify: https://open.spotify.com/show/6yHyok3M3BjqzR0VB5MSyk

As artificial intelligence seeps into some realms of society, it rushes into others. One area it's making a big difference is protein science — as in the "building blocks of life," proteins! Producer Berly McCoy talks to host Emily Kwong about the newest advance in protein science: AlphaFold3, an AI program from Google DeepMind. Plus, they talk about the wider field of AI protein science and why researchers hope it will solve a range of problems, from disease to the climate.Have other aspects of AI you want us to cover? Email us at shortwave@npr.org.Learn more about sponsor message choices: podcastchoices.com/adchoicesNPR Privacy Policy

Finally, the long-anticipated new Sony FX2 cinema camera has arrived at the CineD headquarters for a full stress test — and that's exactly what we did. Johnnie has already spent some time with the camera, produced a short documentary, and shares insights on what worked for him and what didn't. Additionally, we cover new updates on the latest version of Google's AI video generator, Neo, along with the usual gear updates for the week. Join us to discover all the details in this "Sony FX2 podcast". Sponsor: This episode is sponsored by FUJIFILM. Check it out at 29:04 Chapters & Articles Mentioned in This Episode: (00:00) -  Intro (03:26) - Sony FX2 Review – An Entry-Level, Full-Frame, Cinema Line Camera. Is the Price Right? https://www.cined.com/sony-fx2-review-an-entry-level-full-frame-cinema-line-camera-is-the-price-right/   (30:05) - Google DeepMind Veo 3 and Flow Unveiled for AI “Filmmaking” https://www.cined.com/google-deepmind-unveils-veo-3-and-flow-for-ai-filmmaking/   (39.26) - AI Flood on Adobe Stock: Nearly Half of All Images Now AI-Generated https://www.cined.com/ai-flood-on-adobe-stock-nearly-half-of-all-images-now-ai-generated/    (42:45) - Darren Aronofsky Partners with Google DeepMind on Generative AI Short Film Initiative https://www.cined.com/darren-aronofsky-partners-with-google-deepmind-on-generative-ai-short-film-initiative/   (48:11) - B&H BILD Expo Returns to New York City in June, with CineD Talk – Free Registration Now Open https://www.cined.com/bh-bild-expo-returns-to-new-york-city-in-june-with-cined-talk-free-registration-now-open/   (50:06) - Poll: What is the Most Innovative Camera Brand? https://www.cined.com/poll-innovation-in-cameras-which-is-your-favorite-brand/   (53:19) - RØDE Wireless Micro Bluetooth iOS Update Adds Direct Pairing with iPhones https://www.cined.com/rode-wireless-micro-bluetooth-ios-update-adds-direct-pairing-with-iphones/   (55:43) - Hollyland LARK MAX 2 Officially Launched – 32-bit Float, On-board TC & Four-TX Support https://www.cined.com/hollyland-lark-max-2-officially-launched-32-bit-float-on-board-tc-four-tx-support/ (1:00:35) - Mandy Walker Makes History as ASC's First Female President https://www.cined.com/mandy-walker-makes-history-as-ascs-first-female-president/   (01:02:48) - Pro Tip: Sensor Crop Feature in CineD Lens Coverage Tool https://www.cined.com/pro-tip-sensor-crop-feature-in-lens-coverage-tool/   We hope you enjoyed this episode! You have feedback, comments, or suggestions? Write us at podcast@cined.com   

Today, I'm excited to share a special crossover edition of the podcast recorded live from Google I/O 2025! In this episode, I join Shawn Wang aka Swyx from the Latent Space Podcast, to interview Logan Kilpatrick and Shrestha Basu Mallick, PMs at Google DeepMind working on AI Studio and the Gemini API, along with Kwindla Kramer, CEO of Daily and creator of the Pipecat open source project. We cover all the highlights from the event, including enhancements to the Gemini models like thinking budgets and thought summaries, native audio output for expressive voice AI, and the new URL Context tool for research agents. The discussion also digs into the Gemini Live API, covering its architecture, the challenges of building real-time voice applications (such as latency and voice activity detection), and new features like proactive audio and asynchronous function calling. Finally, don't miss our guests' wish lists for next year's I/O! The complete show notes for this episode can be found at https://twimlai.com/go/733.

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the critical considerations when deciding whether to hire an external AI expert or develop internal AI capabilities. You’ll learn why it is essential to first define your organization’s specific AI needs and goals before seeking any AI expertise. You’ll discover the diverse skill sets that comprise true AI expertise, beyond just technology, and how to effectively vet potential candidates. You’ll understand how AI can magnify existing organizational challenges and why foundational strategy must precede any AI solution. You’ll gain insight into how to strategically approach AI implementation to avoid costly mistakes and ensure long-term success for your organization. Watch now to learn how to make the right choice for your organization’s AI future. Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-should-you-hire-ai-expert.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn – 00:00 In this week’s In-Ear Insights, a few people have asked us the question, should I hire an AI expert—a person, an AI expert on my team—or should I try to grow AI expertise, someone as an AI leader within my company? I can see there being pros and cons to both, but, Katie, you are the people expert. You are the organizational behavior expert. I know the answer is it depends. But at first blush, when someone comes to you and says, hey, should I be hiring an AI expert, somebody who can help shepherd my organization through the crazy mazes of AI, or should I grow my own experts? What is your take on that question? Katie Robbert – 00:47 Well, it definitely comes down to it depends. It depends on what you mean by an AI expert. So, what is it about AI that they are an expert in? Are you looking for someone who is staying up to date on all of the changes in AI? Are you looking for someone who can actually develop with AI tools? Or are you looking for someone to guide your team through the process of integrating AI tools? Or are you looking for all of the above? Which is a totally reasonable response, but that doesn’t mean you’ll get one person who can do all three. So, I think first and foremost, it comes down to what is your goal? And by that I mean, what is the AI expertise that your team is lacking? Katie Robbert – 01:41 Or what is the purpose of introducing AI into your organization? So, unsurprisingly, starting with the 5P framework, the 5Ps are purpose, people, process, platform, performance, because marketers like alliteration. So, purpose. You want to define clearly what AI means to the company, so not your ‘what I did over summer vacation’ essay, but what AI means to me. What do you want to do with AI? Why are you bringing AI in? Is it because I want to keep up with my competitors? Bad answer. Is it because you want to find efficiencies? Okay, that’s a little bit better. But if you’re finding efficiencies, first you need to know what’s not working. So before you jump into getting an AI expert, you probably need someone who’s a process expert or an expert in the technologies that you feel like are inefficient. Katie Robbert – 02:39 So my personal stance is that there’s a lot of foundational work to do before you figure out if you can have an AI expert. An AI expert is like bringing in an AI piece of software. It’s one more thing in your tech stack. This is one more person in your organization fighting to be heard. What are your thoughts, Chris? Christopher S. Penn – 03:02 AI expert is kind of like saying, I want to hire a business expert. It’s a very umbrella term. Okay, are your finances bad? Is your hiring bad? Is your sales process bad? To your point, being very specific about your purpose and the performance—which are the bookends of the 5Ps—is really important because otherwise AI is a big area. You have regression, you have classification, you have generative AI. Even within generative AI, you have coding, media generation. There’s so many things. We were having a discussion internally in our own organization this morning about some ideas about internationalization using AI. It’s a big planet. Katie Robbert – 03:46 Yeah, you’ve got to give me some direction. What does that mean? I think you and I, Chris, are aligned. If you’re saying, ‘I want to bring in an AI expert,’ you don’t actually know what you’re looking for because there are so many different facets of expertise within the AI umbrella that you want to be really specific about what that actually means and how you’re going to measure their performance. So if you’re looking for someone to help you make things more efficient, that’s not necessarily an AI expert. If you’re concerned that your team is not on board, that’s not an AI expert. If you are thinking that you’re not getting the most out of the platforms that you’re using, that’s not an AI expert. Those are very different skill sets. Katie Robbert – 04:38 An AI expert, if we’re talking—let’s just say we could come up with a definition of an AI expert—Chris, you are someone who I would consider an AI expert, and I would list those qualifications as: someone who stays up to date. Someone who knows enough that you can put pretty much any model in front of them and they know how to build a prompt, and someone who can speak to how these tools would integrate into your existing tech stack. My guess is that’s the kind of person that everybody’s looking for: someone to bring AI into my organization, do some light education, and give us a tool to play with. Christopher S. Penn – 05:20 We often talk about things like strategy, tactics, execution, and measurement. So, sort of four layers: why are you doing this thing? What are you going to do? How are you going to do it, and did it work? An actual AI expert has to be able to do all four of those things to say, here’s why we’re doing this thing—AI or not. But here’s why you’d use AI, here’s what AI tools and technologies you use, here’s how you do them, and here’s the proof that what you did worked. So when someone says, ‘I want an AI expert for my company,’ even then, they have to be clear: do we want someone who’s going to help us set our strategy or do we want someone who’s going to build stuff and make stuff for us? It’s very unclear. Christopher S. Penn – 06:03 I think that narrowing down the focus, even if you do narrow down the focus, you still have to restart the 5Ps. So let’s say we got this question from another colleague of ours: ‘I want to do AI lead generation.’ Was the remit to help me segment and use AI to do better lead generation? Well, that’s not an AI problem. As you always say, new technology does not solve all problems. This is not an AI problem; this is a lead generation problem. So the purpose is pretty clear. You want more leads, but it’s not a platform issue with AI. It is actually a people problem. How are people buying in the age of AI? And that’s what you need to solve. Christopher S. Penn – 06:45 And from there you can then go through the 5Ps and user stories and things to say, ‘yeah, this is not an AI expert problem. This is an attention problem.’ You are no longer getting awareness because AI has eaten it. How are you going to get attention to generate audience that becomes prospects that eventually becomes leads? Katie Robbert – 07:05 Yeah, that to me is an ideal customer profile, sales playbook, marketing planning and measurement problem. And sure, you can use AI tools to help with all of those things, but those are not the core problems you’re trying to solve. You don’t need AI to solve any of those problems. You can do it all without it. It might take a little longer or it might not. It really depends. I think that’s—So, Chris, I guess we’re not saying, ‘no, you can’t bring in an AI expert.’ We’re saying there’s a lot of different flavors of AI expertise. And especially now where AI is the topic, the thing—it was NFTs and it was crypto and it was Bitcoin and it was Web three, whatever the heck that was. And it was, pick a thing—Clubhouse. Katie Robbert – 07:57 All of a sudden, everybody was an expert. Right now everybody’s a freaking expert in AI. You can’t sneeze and not have someone be like, ‘I’m an AI expert. I can fix that problem for you.’ Cool. I’ve literally never seen you in the space, but congratulations, you’re an AI expert. The point I’m making here is that if you are not hyper specific about the kind of expertise you’re looking for, you are likely going to end up with a dud. You are likely going to end up with someone who is willing to come in at a lower price just to get their foot in the door. Christopher S. Penn – 08:40 Yep. Katie Robbert – 08:40 Or charge you a lot of money. You won’t know that it’s not working until it doesn’t work and they’ve already moved on. We talked about this on the livestream yesterday about people who come in as AI experts to fix your sales process or something like that. And you don’t know it’s not working until you’ve spent a lot of money on this expert, but you’re not bringing in any more revenue. But by then they’re gone. They’re already down the street selling their snake oil to the next guy. Christopher S. Penn – 09:07 Exactly. Now, to the question of should you grow your own? That’s a big question because again, what level of expertise are you looking for? Strategy, tactics, or execution? Do you want someone who can build? Do you want someone who can choose tools and tactics? Do you want someone who can set the strategy? And then within your organization, who are those people? And this is very much a people issue, which is: do they have the aptitudes to do that? I don’t mean AI aptitude; I mean, are they a curious person? Do they learn quickly? Do they learn well outside their domain? Because a lot of people can learn in their domain with what’s familiar to them. But a whole bunch of other people are really uncomfortable learning something outside their domain. Christopher S. Penn – 09:53 And for one reason or another, they may not be suited as humans to become that internal AI champion. Katie Robbert – 10:02 I would add to that not only the curiosity, but also the communication, because it’s one thing to be able to learn it, but then you have to, if you’re part of a larger team, explain what you learned, explain why you think this is a good idea. You don’t have to be a professional speaker, be able to give a TED talk, but you need to be able to say, ‘hey, Chris, I found this tool. Here’s what it does, here’s why I think we should use it,’ and be able to do that in a way that Chris is like, ‘oh, yeah! That is a really good idea. Let’s go ahead and explore it.’ But if you just say, ‘I found this thing,’ okay, and congratulations, here’s your sticker, that’s not helpful. Katie Robbert – 10:44 So communication, the people part of it, is essential. Right now, a lot of companies—we talked about this on last week’s podcast—a lot of leaders, a lot of CEOs, are disregarding the people in favor of ‘AI is going to do it,’ ‘technology is going to take it over,’ and that’s just not how that’s going to work. You can go ahead and alienate all of your people, but then you don’t have anyone to actually do the work. Because AI doesn’t just set itself up; it doesn’t just run itself without you telling it what it is you need it to do. And you need people to do that. Christopher S. Penn – 11:27 Yep. Really important AI models—we just had a raft of new announcements. So the new version of Gemini 2.5, the new version of OpenAI’s Codex, Claude 4 from Anthropic just came out. These models have gotten insanely smart, which, as Ethan Mollock from Wharton says, is a problem, because the smarter AI gets, the smarter its mistakes get and the harder it is for non-experts to pick up that expert AI is making expert-level mistakes that can still steer the ship in the wrong direction, but you no longer know if you’re not a domain expert in that area. So part of ‘do we grow an AI expert internally’ is: does this person that we’re thinking of have the ability to become an AI expert but also have domain expertise in our business to know when the AI is wrong? Katie Robbert – 12:26 At the end of the day, it’s software development. So if you understand the software development lifecycle, or even if you don’t, here’s a very basic example. Software engineers, developers, who don’t have a QA process, yes, they can get you from point A to point B, but it may be breaking things in the background. It might be, if their code is touching other things, something else that you rely on may have been broken. But listen, that thing you asked for—it’s right here. They did it. Or it may be using a lot of API tokens or server space or memory, whatever it is. Katie Robbert – 13:06 So if you don’t also have a QA process to find out if that software is working as expected, then yes, they got you from point A to point B, but there are all of these other things in the background that aren’t working. So, Chris, to your point about ‘as AI gets smarter, the mistakes get smarter’—unless you’re building people and process into these AI technologies, you’re not going to know until you get slapped with that thousand-dollar bill for all those tokens that you used. But hey, great! Three of your prospects now have really solid lead scores. Cool. Christopher S. Penn – 13:44 So I think we’re sort of triangulating on what the skills are that you should be looking for, which is someone who’s a good critical thinker, someone who’s an amazing communicator who can explain things, someone who is phenomenal at doing requirements gathering and being able to say, ‘this is what the thing is.’ Someone who is good at QA to be able to say the output of this thing—human or machine—is not good, and here’s why, and here’s what we should do to fix it. Someone who has domain expertise in your business and can explain, ‘okay, this is how AI does or does not fit into these things.’ And then someone who knows the technology—strategy, tactics, and execution. Why are we using this technology? What does the technology do? How do we deploy it? Christopher S. Penn – 14:30 For example, Mistral, the French company, just came up with a new model Dev Stroll, which is apparently doing very well on software benchmarks. Knowing that it exists is important. But then that AI expert who has to have all those other areas of expertise also has to know why you would use this, what you would use it for, and how you would use it. So I almost feel that’s a lot to cram into one human being. Katie Robbert – 14:56 It’s funny, I was just gonna say I feel that’s where—and obviously dating ourselves—that’s where things, the example of Voltron, where five mini-lion bots come together to make one giant lion bot, is an appropriate example because no one person—I don’t care who they are—no one person is going to be all of those things for you. But congratulations: together Chris and I are. That Voltron machine—just a quick plug. Because it’s funny, as you’re going through, I’m like, ‘you’re describing the things that we pride ourselves on, Chris,’ but neither of us alone make up that person. But together we do cover the majority. I would say 95% of those things that you just listed we can cover, we can tackle, but we have to do it together. Katie Robbert – 15:47 Because being an expert in the people side of things doesn’t always coincide with being an expert in the technology side of things. You tend to get one or the other. Christopher S. Penn – 15:59 Exactly. And in our case as an agency, the client provides the domain expertise to say, ‘hey, here’s what our business is.’ We can look at it and go, ‘okay, now I understand your business and I can apply AI technology and AI processes and things to it.’ But yeah, we were having that discussion not too long ago about, should we claim that AI expertise in healthcare technologies? Well, we know AI really well. Do we know healthcare—DSM codes—really well? Not really, no. So could we adapt and learn fast? Yes. But are we practitioners day to day working in an ER? No. Katie Robbert – 16:43 So in that case, our best bet is to bring on a healthcare domain expert to work alongside both of us, which adds another person to the conversation. But that’s what that starts to look like. If you say, ‘I want an AI expert in healthcare,’ you’re likely talking about a few different people. Someone who knows healthcare, someone who knows the organizational behavior side of things, and someone who knows the technology side of things. And together that gives your quote-unquote AI expert. Christopher S. Penn – 17:13 So one of the red flags for the AI expert side of things, if you’re looking to bring in someone externally, is someone who claims that with AI, they can know everything because the machines, even with great research tools, will still make mistakes. And just because someone’s an AI expert does not mean they have the sense to understand the subtle mistakes that were made. Not too long ago, we were using some of the deep research tools to pull together potential sponsors for our podcast, using it as a sales prospecting tool. And we were looking at it, looking at who we know to be in the market: ‘yeah, some of these are not good fits.’ Even though it’s plausible, it’s still not a good fit. Christopher S. Penn – 18:01 One of them was the Athletic Greens company, which, yes, for a podcast, they advertise on every podcast in the world. I know from listening to other shows and listening to actual experts that there’s some issues with that particular sponsorship. So it’s not a good fit. Even though the machine said, ‘yeah, this is because they advertise on every other podcast, they’re clearly just wanting to hand out money to podcasters.’ I have the domain expertise in our show to know, ‘yeah, that’s not a good fit.’ But as someone who is an AI expert who claimed that they understood everything because AI understands everything, doesn’t know that the machine’s wrong. So as you’re thinking about, should I bring an AI expert on externally, vet them on the level, vet them on how willing they are to say, ‘I don’t know.’ Katie Robbert – 18:58 But that’s true of really any job interview. Christopher S. Penn – 19:01 Yes. Katie Robbert – 19:02 Again, new tech doesn’t solve old problems, and AI is, at least from my perspective, exacerbating existing problems. So suddenly you’re an expert in everything. Suddenly it’s okay to be a bad manager because ‘AI is going to do it.’ Suddenly the machines are all. And that’s not an AI thing. Those are existing problems within your organization that AI is just going to magnify. So go ahead and hire that quote-unquote AI expert who on their LinkedIn profile says they have 20 years of generative AI expertise. Good luck with that person, because that’s actually not a thing now. Christopher S. Penn – 19:48 At most it would have to be 8 years and you would have to have credentials from Google DeepMind, because that’s where it was invented. You cannot say it’s anything older than that. Katie Robbert – 20:00 But I think that’s also a really good screening question is: do you know what Google DeepMind is? And do you know how long it’s been around? Christopher S. Penn – 20:09 Yep. If someone is an actual AI expert—not ‘AI and marketing,’ but an actual AI expert itself—can you explain the Transformers architecture? Can you explain the diffuser architecture? Can you explain how they’re different? Can you explain how one becomes the other? Because that was a big thing that was announced this week by Google DeepMind. No surprise about how they’re crossing over into each other, which is a topic for another time. But to your point, I feel AI is making Dunning-Kruger much worse. At the risk of being insensitive, it’s very much along gender lines. There are a bunch of dudes who are now making wild claims: ‘no, you really don’t know what you’re talking about.’ Katie Robbert – 21:18 I hadn’t planned on putting on my ranty pants today, but no, I feel that’s. Again, that’s a topic for another time. Okay. So here’s the thing: you’re not wrong. To keep this podcast and this topic productive, you just talked about a lot of things that people should be able to explain if they are an AI expert. The challenge on the other side of that table is people hiring that AI expert aren’t experts in AI. So, Chris, you could be explaining to me how Transformers turn into Voltron, bots turn into Decepticons, and I’m like, ‘yeah, that sounds good’ because you said all the right words. So therefore, you must be an expert. So I guess my question to you is, how can a non-AI expert vet and hire an AI expert without losing their mind? Is that possible? Christopher S. Penn – 22:15 Change the words. How would you hire a medical doctor when you’re not a doctor? How would you hire a plumber when you’re not a plumber? What are the things that you care about? And that goes back to the 5Ps, which is: and we say this with job interviews all the time. Walk me through, step by step, how you would solve this specific problem. Katie, I have a lead generation problem. My leads are—I’m not getting enough leads. The ones I get are not qualified. Tell me as an AI expert exactly what you would do to solve this specific problem. Because if I know my business, I should be able to listen to you go, ‘yeah, but you’re not understanding the problem, which is, I don’t get enough qualified leads. I get plenty of leads, but they’re crap.’ Christopher S. Penn – 23:02 It’s the old Glengarry Glen Ross: ‘The leads are weak.’ Whereas if the person is an actual AI expert, they can say, ‘okay, let me ask you a bunch of questions. Tell me about your marketing automation software. Tell me about your CRM. Tell me how you have set up the flow to go from your website to your marketing automation to your sales CRM. Tell me about your lead scoring. How do you do your lead scoring? Because your leads are weak, but you’re still collecting tons of them. That means you’re not using your lead scoring properly. Oh, there’s an opportunity where I can show AI’s benefit to improve your lead scoring using generative AI.’ Christopher S. Penn – 23:40 So even in that, we haven’t talked about a single model or a single ‘this’ or ‘that,’ but we have said, ‘let me understand your process and what’s going on.’ That’s what I would listen for. If I was hiring an AI expert to diagnose anything and say, I want to hear, and where we started: this person’s a great communicator. They’re a critical thinker. They can explain things. They understand the why, the what, and the how. They can ask good questions. Katie Robbert – 24:12 If I was the one being interviewed and you said, ‘how can I use AI to improve my lead score? I’m getting terrible leads.’ My first statement would be, ‘let’s put AI aside for a minute because that’s not a problem AI is going to solve immediately without having a lot of background information.’ So, where does your marketing team fit into your sales funnel? Are they driving awareness or are you doing all pure cold calling or outbound marketing—whatever it is you’re doing? How clear is your ideal customer profile? Is it segmented? Are you creating different marketing materials for those different segments? Or are you just saying, ‘hi, we’re Trust Insights, we’re here, please hire us,’ which is way too generic. Katie Robbert – 24:54 So there’s a lot of things that you would want to know before even getting into the technology. I think that, Chris, to your point, an AI expert, before they say, ‘I’m the expert, here’s what AI is going to fix,’ they’re going to know that there are a lot of things you probably need to do before you even get to AI. Anyone who jumps immediately to AI is going to solve this problem is likely not a true expert. They are probably just jumping on the bandwagon looking for a dollar. Christopher S. Penn – 25:21 Our friend Andy Crestedine has a phenomenal phrase that I love so much, which is ‘prescription before diagnosis is malpractice.’ That completely applies here. If you’re saying ‘AI is the thing, here’s the AI solution,’ yeah, but we haven’t talked about what the problem is. So to your point about if you’re doing these interviews, the person’s ‘oh yeah, all things AI. Let’s go.’ I get that as a technologist at heart, I’m like, ‘yeah, look at all the cool things we can do.’ But it doesn’t solve. Probably on the 5Ps here—down to performance—it doesn’t solve: ‘Here’s how we’re going to improve that performance.’ Katie Robbert – 26:00 To your point about how do you hire a doctor? How do you hire a plumber? We’ve all had that experience where we go to a doctor and they’re like, ‘here’s a list of medications you can take.’ And you’re like, ‘but you haven’t even heard me. You’re not listening to what I’m telling you is the problem.’ The doctor’s saying, ‘no, you’re totally normal, everything’s fine, you don’t need treatment. Maybe just move more and eat less.’ Think about it in those terms. Are you being listened to? Are they really understanding your problem? If a plumber comes into your house and you’re like, ‘I really think there’s a leak somewhere. But we hear this over here,’ and they’re like, ‘okay, here’s a cost estimate for all brand new copper piping.’ You’re like, ‘no, that’s not what I’m asking you for.’ Katie Robbert – 26:42 The key in these interviews, if you’re looking to bring on an AI expert, is: are they really listening to you and are they really understanding the problem that’s going to demonstrate their level of expertise? Christopher S. Penn – 26:54 Yep. And if you’re growing your own experts, sit down with the people that you want to become experts and A) ask them if they want to do it—that part does matter. And then B) ask them. You can use AI for this. It’s a phenomenal use case for it, of course. What is your learning journey going to be? How are you going to focus your learning so that you solve the problems? The purpose that we’ve outlined: ‘yeah, our organization, we know that our sales is our biggest blockage or finance is our biggest blockage or whatever.’ Start there and say, ‘okay, now your learning journey is going to be focused on how is AI being used to solve these kinds of problems. Dig into the technologies, dig into best practices and things.’ Christopher S. Penn – 27:42 But just saying, ‘go learn AI’ is also a recipe for disaster. Katie Robbert – 27:47 Yeah. Because, what about AI? Do you need to learn prompt engineering? Do you need to learn the different use cases? Do you need to learn the actual how the models work, any algorithms? Or, pick a thing—pick a Decepticon and go learn it. But you need to be specific. Are you a Transformer or are you a Decepticon? And which one do you need to learn? That’s going to be my example from now on, Chris, to try to explain AI because they sound like technical terms, and in the wrong audience, someone’s going to think I’m an AI expert. So I think that’s going to be my test. Christopher S. Penn – 28:23 Yes. Comment guide on our LinkedIn. Katie Robbert – 28:27 That’s a whole. Christopher S. Penn – 28:29 All right, so, wrapping up whether you buy or build—which is effectively what we’re discussing here—for AI expertise, you’ve got to go through the 5Ps first. You’ve got to build some user stories. You’ve got to think about the skills that are not AI, that the person needs to have: critical thinking, good communication, the ability to ask great questions, the ability to learn quickly inside and outside of their domain, the ability to be essentially great employees or contractors, no matter what—whether it’s a plumber, whether it’s a doctor, whether it’s an AI expert. None of that changes. Any final parting thoughts, Katie? Katie Robbert – 29:15 Take your time. Which sounds counterintuitive because we all feel that AI is changing so rapidly that we’re falling behind. Now is the time to take your time and really think about what it is you’re trying to do with AI. Because if you rush into something, if you hire the wrong people, it’s a lot of money, it’s a lot of headache, and then you end up having to start over. We’ve had talks with prospects and clients who did just that, and it comes from ‘we’re just trying to keep up,’ ‘we’re trying to do it quickly,’ ‘we’re trying to do it faster,’ and that’s when mistakes are made. Christopher S. Penn – 29:50 What’s the expression? ‘Hire slow, fire fast.’ Something along those lines. Take your time to really make good choices with the people. Because your AI strategy—at some point you’re gonna start making investments—and then you get stuck with those investments for potentially quite some time. If you’ve got some thoughts about how you are buying or building AI expertise in your organization you want to share, pop on. Buy our free Slack. Go to trustinsights.ai/analyticsformarketers where you and over 4,200 other marketers are asking and answering each other’s questions every single day. And wherever it is you watch or listen to the show, if there’s a channel you’d rather have it on, go to trustinsights.ai/tipodcast. You can find us in all the places fine podcasts are served. Thanks for tuning in. Christopher S. Penn – 30:35 I will talk to you on the next one. Katie Robbert – 30:43 Want to know more about Trust Insights? Trust Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence, and machine learning to empower businesses with actionable insights. Founded in 2017 by Katie Robbert and Christopher S. Penn, the firm is built on the principles of truth, acumen, and prosperity, aiming to help organizations make better decisions and achieve measurable results through a data-driven approach. Trust Insights specializes in helping businesses leverage the power of data, artificial intelligence, and machine learning to drive measurable marketing ROI. Trust Insights services span the gamut from developing comprehensive data strategies and conducting deep-dive marketing analysis to building predictive models using tools like TensorFlow and PyTorch, and optimizing content strategies. Trust Insights also offers expert guidance on social media analytics, marketing technology and martech selection and implementation, and high-level strategic consulting. Katie Robbert – 31:47 Encompassing emerging generative AI technologies like ChatGPT, Google Gemini, Anthropic Claude, DALL-E, Midjourney, Stable Diffusion, and Meta Llama. Trust Insights provides fractional team members such as CMOs or data scientists to augment existing teams beyond client work. Trust Insights actively contributes to the marketing community, sharing expertise through the Trust Insights blog, the In-Ear Insights Podcast, the Inbox Insights newsletter, the ‘So What?’ Livestream, webinars, and keynote speaking. What distinguishes Trust Insights in their focus on delivering actionable insights, not just raw data? Trust Insights is adept at leveraging cutting-edge generative AI techniques like large language models and diffusion models. Yet they excel at exploring and explaining complex concepts clearly through compelling narratives and visualizations. Data Storytelling. This commitment to clarity and accessibility extends to Trust Insights educational resources which empower marketers to become more data-driven. Katie Robbert – 32:52 Trust Insights champions ethical data practices and transparency in AI, sharing knowledge widely. Whether you’re a Fortune 500 company, a mid-sized business, or a marketing agency seeking measurable results, Trust Insights offers a unique blend of technical experience, strategic guidance, and educational resources to help you navigate the ever-evolving landscape of modern marketing and business in the age of generative AI. Trust Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

This show and offer a snapshot of global AI developments on May 27th 2025, highlighting diverse applications and challenges. We see a nation-state investing heavily in public AI access and infrastructure alongside a debate about the ethics of training data and intellectual property rights. Real-world examples range from financial institutions using AI avatars for client communication to a law firm facing repercussions for misusing AI, demonstrating both innovation and potential pitfalls. Finally, the reports touch on the evolving relationship between humans and AI, including political figures interacting with chatbots and expert advice on preparing the next generation for an AI-driven workforce, all within the dynamic landscape of AI research and its impact on society.

Imagine transforming a simple text prompt into a fully produced song—within seconds. That's exactly what Udio does. Founded in December 2023 by a team of former Google DeepMind researchers, including CEO David Ding, Conor Durkan, Charlie Nash, Yaroslav Ganin, and Andrew Sanchez, Udio is reshaping how music is made. Backed by industry giants like a16z, will.i.am, Common, Tay Keith, and Steve Stoute's UnitedMasters, Udio is at the forefront of AI-driven music creation.

Audio FileGround Truths can also be found on Apple Podcasts, Spotify and YouTube.The UK is the world leader in human genomics, and laid the foundation for advancing medicine with the UK Biobank, Genomes England and now Our Future Health (w/ 5 million participants). Sir John Bell is a major force in driving and advising these and many other initiatives. After 22 years as the Regius Professor of Medicine at the University of Oxford he left in 2024 to be President of the Ellison Institute of Technology. Professor Bell has been duly recognized in the UK: knighted in 2015 and appointed Companion of Honor in 2023. In our conversation, you will get a sense for how EIT will be transformational for using A.I. and life science for promoting human health.Transcript with audio links Eric Topol (00:06):Hello, this is Eric Topol from Ground Truths. And I'm really delighted to welcome today, Sir John Bell who had an extraordinary career as a geneticist, immunologist, we'll talk about several initiatives he's been involved with during his long tenure at University of Oxford, recently became head of the Ellison Institute of Technology (EIT) in the UK. So welcome, John.Sir John Bell (00:30):Thanks, Eric. Thanks very much for having me.Eric Topol (00:34):Well, I think it's just extraordinary the contributions that you have made and continue to make to advance medicine, and I thought what we could do is get into that. I mean, what's interesting, you have had some notable migrations over your career, I think starting in Canada, at Stanford, then over as Rhodes Scholar in Oxford. And then you of course had a couple of decades in a very prestigious position, which as I understand was started in 1546 by King Henry VII, and served as the Regius Professor of Medicine at the University of Oxford. Do I have that right?Sir John Bell (01:11):It was actually Henry VIII, but you were close.Eric Topol (01:14):Henry VIII, that's great. Yeah. Okay, good. Well, that's a pretty notable professorship. And then of course in recent times you left to head up this pretty formidable new institute, which is something that's a big trend going on around the world, particularly in the US and we'll talk about. So maybe we can start with the new thing. Tell us more about the Ellison Institute of Technology (EIT), if you will.Sir John Bell (01:47):Yeah. So as you know, Larry Ellison has been one of the great tech entrepreneurs focused really on developing terrific databases over his career and through Oracle, which is the company that he founded. And Larry is really keen to try and give back something substantial to the world, which is based on science and technology. So he and I did quite a bit together over the Covid pandemic. He and I talked a lot about what we're doing and so on. He came to visit afterwards and he had, I think he decided that the right way to make his contributions would be to set up an institute that would be using the state-of-the-art science and technology with a lot of AI and machine learning, but also some of the other modern tools to address the major problems in healthcare, in food security, in green energy and climate change and in global governance.Sir John Bell (02:49):So anyway, he launched this about 18 months ago. He approached me to ask whether I would run it. He wanted to set it up outside Oxford, and he wanted to do something which is a bit different than others. And that is his view was that we needed to try and create solutions to these problems which are commercially viable and not all the solutions are going to be commercially viable, but where you can create those, you make them sustainable. So the idea is to make sure that we create solutions that people want to buy, and then if they buy them, you can create a sustainable solution to those issues. So we are actually a company, but we are addressing many of the same problems that the big foundations are addressing. And the big issues that you and I talk about in health, for example, are all on our list. So we're kind of optimistic as to where this will go and Larry's supporting the project and we're going to build out an institute here which will have about 5,000 people in it, and we'll be, I think a pretty exciting new addition to the science and technology ecosystem globally.Eric Topol (04:02):Well, I know the reverberations and the excitement is palpable and some of the colleagues I've spoken to, not just in England, but of course all over the world. So congratulations on that. It was a big move for you to leave the hardcore academics. And the other thing I wanted to ask you, John, is you had distinguished your career in immunology, in genetics, type 1 diabetes and other conditions, autoimmune conditions, and now you've really diversified, as you described with these different areas of emphasis at the new institute. Is that more fun to do it or do you have deputies that you can assign to things like climate change in other areas?Sir John Bell (04:50):Trust me, Eric, I'm not making any definitive decisions about areas I know nothing about, but part of this is about how do you set up leadership, run a team, get the right people in. And I have to say one of the really interesting things about the institute is we've been able to recruit some outstanding people across all those domains. And as you know, success is almost all dependent on people. So we're really pretty optimistic we're going to have a significant impact. And of course, we also want to take risks because not a lot of point in us doing stuff that everybody else is doing. So we're going to be doing some things that are pretty way out there and some of them will fail, so we are just going to get used to trying to make sure we get a few of them across the finish line. But the other thing is that, and you've experienced this too, you never get too old to learn. I mean, I'm sucking up stuff that I never thought I would ever learn about, which is fun actually, and really marvel.Eric Topol (05:55):It's fantastic. I mean, you've really broadened and it's great that you have the runway to get these people on board and I think you're having a big building that's under construction?Sir John Bell (06:07):Yeah, we've got the original building that Larry committed to is about 330,000 square feet of space. I mean, this is completely amazing, but we are of course to accommodate up to 5,000 people, we're going to need more than that. So we are looking at a much wider campus here that'll involve more than just that building. I think we'll end up with several million square feet of space by the time we're finished. So mean, it's a really big project, but we've already made progress in some domains to try and get projects and the beginnings of companies on the road to try and solve some of the big problems. So we're quite excited about it.Eric Topol (06:49):Now you, I assume it's pretty close to Oxford, and will you have some kind of inter interactions that are substantial?Sir John Bell (06:58):Yeah, so the university's been terrific about this actually, because of course most universities would say, well, why don't you do it inside the university and just give us the money and it'll all be fine. So of course Larry. Larry wasn't born yesterday, so I said, well, thank you very much, but I think we'll probably do this nearby. But the university also realized this is a really exciting opportunity for them and we've got a really good relationship with them. We've signed an agreement with them as to who will work where. We've agreed not to steal a lot of their staff. We're going to be bringing new people into the ecosystem. Some of the university people will spend some time with us and sometime in the university, so that will help. But we're also bringing quite a few new people into the setting. So the university has been really positive. And I think one of the things that's attractive to the university, and you'll be familiar with this problem in the UK, is that we're quite good. The discovery science here is pretty good.Sir John Bell (08:06):And we do startups now at scale. So Oxford does lots of little startup companies in the biotech space and all the rest of it, but we never scale any of these companies because there isn't the depth of capital for scaling capital to get these things scaled. And so, in a way what we're trying to do here at Ellison actually avoids that problem because Larry knows how to scale companies, and we've got the financial support now. If we have things that are really successful, we can build the full stack solution to some of these problems. So I think the university is really intrigued as to how we might do that. We're going to have to bring some people in that know how to do that and build billion dollar companies, but it's sufficiently attractive. We've already started to recruit some really outstanding people. So as a way to change the UK system broadly, it's actually quite a good disruptive influence on the way the thing works to try and fix some of the fundamental problems.Eric Topol (09:07):I love that model and the ability that you can go from small startups to really transformative companies have any impact. It fits in well with the overall objectives, I can see that. The thing that also is intriguing regarding this whole effort is that in parallel we've learned your influence. The UK is a genomics world leader without any question and no coincidence that that's been your area of emphasis in your career. So we've watched these three initiatives that I think you were involved in the UK Biobank, which has had more impact than any cohort ever assembled. Every day there's another paper using that data that's coming out. There's Genomes England, and then now Our Future Health, which a lot of people don't know about here, which is well into the 5 million people enrollment. Can you tell us about, this is now 15 years ago plus when these were started, and of course now with a new one that's the biggest ever. What was your thinking and involvement and how you built the UK to be a world leader in this space?Sir John Bell (10:26):So if you turn the clock back 20 years, or actually slightly more than 25 years ago, it was clear that genomics was going to have a play. And I think many of us believed that there was going to be a genetic element to most of the major common disease turn out to be true. But at the time, there were a few skeptics, but it seemed to us that there was going to be a genetic story that underpinned an awful lot of human disease and medicine. And we were fortunate because in Oxford as you know, one of my predecessors in the Regius job was Richard Doll, and he built up this fantastic epidemiology capability in Oxford around Richard Peto, Rory Collins, and those folks, and they really knew how to do large scale epidemiology. And one of the things that they'd observed, which is it turns out to be true with genetics as well, is a lot of the effects are relatively small, but they're still quite significant. So you do need large scale cohorts to understand what you're doing. And it was really Richard that pioneered the whole thinking behind that. So when we had another element in the formula, which was the ability to detect genetic variation and put that into the formula, it seemed to me that we could move into an era where you could set up, again, large cohorts, but build into the ability to have DNA, interrogate the DNA, and also ultimately interrogate things like proteomics and metabolomics, which were just in their infancy at that stage.Sir John Bell (12:04):Very early on I got together because I was at that stage at the Nuffield Chair of Medicine, and I got together, Rory and Richard and a couple of others, and we talked a little bit about what it would look like, and we agreed that a half a million people late to middle age, 45 and above would probably over time when you did the power calculations, give you a pretty good insight in most of the major diseases. And then it was really a question of collecting them and storing the samples. So in order to get it funded at the time I was on the council of the MRC and George Radda, who you may remember, was quite a distinguished NMR physiologist here. He was the chief executive of the MRC. So I approached him and I said, look, George, this would be a great thing for us to do in the UK because we have all the clinical records of these people going back for a decade, and will continue to do that.Sir John Bell (13:01):Of course, we immediately sent it out to a peer review committee in the MRC who completely trashed the idea and said, you got to be joking. So I thought, okay, that's how that lasted. And I did say to George, I said, that must mean this is a really good idea because if it had gone straight through peer review, you would've known you were toast. So anyway, I think we had one more swing at peer review and decided in the end that wasn't going to work. In the end, George to his credit, took it to MRC council and we pitched it and everybody thought, what a great idea, let's just get on and do it. And then the Wellcome came in. Mark Walport was at the Wellcome at the time, great guy, and did a really good job at bringing the Wellcome on board.Sir John Bell (13:45):And people forget the quantum of money we had to do this at the time was about 60 million pounds. I mean, it wasn't astonishly small. And then of course we had a couple of wise people who came in to give us advice, and the first thing they said, well, if you ever thought you were really going to be able to do genetics on 500,000 people, forget it. That'll never work. So I thought, okay, I'll just mark that one out. And then they said, and by the way, you shouldn't assume you can get any data from the health service because you'll never be able to collect clinical data on any of these people. So I said, yeah, yeah, okay, I get it. Just give us the money and let us get on. So anyway, it's quite an interesting story. It does show how conservative the community actually is for new ideas.Sir John Bell (14:39):Then I chaired the first science committee, and we decided about a year into it that we really needed the chief executive. So we got Rory Collins to lead it and done it. I sat on the board then for the next 10 years, but well look, it was a great success. And as you say, it is kind of the paradigm for now, large genetic epidemiology cohorts. So then, as you know, I advise government for many years, and David Cameron had just been elected as Prime Minister. This was in about 2010. And at the time I'd been tracking because we had quite a strong genomics program in the Wellcome Trust center, which I'd set up in the university, and we were really interested in the genetics of common disease. It became clear that the price of sequencing and Illumina was now the clear leader in the sequencing space.Sir John Bell (15:39):But it was also clear that Illumina was making significant advances in the price of sequencing because as you remember, the days when it cost $5,000 to do a genome. Anyway, it became clear that they actually had technology that gets you down to a much more sensible price, something like $500 a genome. So I approached David and I said, we are now pretty sure that for many of the rare diseases that you see in clinical practice, there is a genetic answer that can be detected if you sequenced a whole genome. So why don't we set something up in the NHS to provide what was essentially the beginnings of a clinical service to help the parents of kids with various disabilities work out what's going on, what's wrong with their children. And David had had a child with Ohtahara syndrome, which as you know is again, and so David was very, he said, oh God, I'll tell you the story about how awful it was for me and for my wife Samantha.Sir John Bell (16:41):And nobody could tell us anything about what was going on, and we weren't looking for a cure, but it would've really helped if somebody said, we know what it is, we know what the cause is, we'll chip away and maybe there will be something we can do, but at least you know the answer. So anyway, he gave us very strong support and said to the NHS, can you please get on and do it? Again massive resistance, Eric as you can imagine, all the clinical geneticists said, oh my God, what are they doing? It's complete disaster, dah, dah, dah. So anyway, we put on our tin hats and went out and got the thing going. And again, they did a really good job. They got to, their idea was to get a hundred thousand genomes done in a reasonable timeframe. I think five years we set ourselves and the technology advance, people often underestimate the parallel development of technology, which is always going on. And so, that really enabled us to get that done, and it still continues. They're doing a big neonatal program at the moment, which is really exciting. And then I was asked by Theresa May to build a life science strategy because the UK, we do this stuff not as big and broad as America, but for a small country we do life sciences pretty well.Eric Topol (18:02):That's an understatement, by the way. A big understatement.Sir John Bell (18:04):Anyway, so I wrote the strategies in 2017 for Theresa about what we would do as a nation to support life sciences. And it was interesting because I brought a group of pharma companies together to say, look, this is for you guys, so tell us what you want done. We had a series of meetings and what became clear is that they were really interested in where healthcare was going to end up in the next 20 years. And they said, you guys should try and get ahead of that wave. And so, we agreed that one of the domains that really hadn't been explored properly, it was the whole concept of prevention.Sir John Bell (18:45):Early diagnosis and prevention, which they were smart enough to realize that the kind of current paradigm of treating everybody in the last six months of life, you can make money doing that, there's no doubt, but it doesn't really fix the problem. And so, they said, look, we would love it if you created a cohort from the age of 18 that was big enough that we could actually track the trajectories of people with these diseases, identify them at a presymptomatic stage, intervene with preventative therapies, diagnose diseases earlier, and see if we could fundamentally change the whole approach to public health. So we anyway, went back and did the numbers because of course at much wider age group, a lot of people don't get at all sick, but we thought if we collected 5 million people, we would probably have enough. That's 10% of the UK adult population.Sir John Bell (19:37):So anyway, amazingly the government said, off you go. We then had Covid, which as you know, kept you and I busy for a few years before we could get back to it. But then we got at it, and we hired a great guy who had done a bit of this in the UAE, and he came across and we set up a population health recruitment structure, which was community-based. And we rapidly started to recruit people. So we've now got 2.9 million people registered, 2.3 million people consented, and we've got blood in the bank and all the necessary data including questionnaire data for 1.5 million people growing up. So we will get to 5 million and it's amazing.Eric Topol (20:29):It is. It really is, and I'm just blown away by the progress you've made. And what was interesting too, besides you all weren't complacent about, oh, we got this UK Biobank and you just kept forging ahead. And by the way, I really share this importance of finally what has been a fantasy of primary prevention, which never really achieved. It's always, oh, after a heart attack. But that's what I wrote about in the Super Agers book, and I'll get you a copy.Sir John Bell (21:02):No, I know you're a passionate believer in this and we need to do a lot of things. So we need to work out what's the trial protocol for primary prevention. We need to get the regulators on board. We've got to get them to understand that we need diagnostics that define risk, not disease, because that's going to be a key bit of what we're going to try and do. And we need to understand that for a lot of these diseases, you have to intervene quite early to flatten that morbidity curve.Eric Topol (21:32):Yeah, absolutely. What we've learned, for example, from the UK Biobank is not just, of course the genomics that you touched on, but the proteomics, the organ clocks and all these other layers of data. So that gets me to my next topic, which I know you're all over it, which is AI.Eric Topol (21:51):So when I did the NHS review back in 2018, 2019, the group of people which were amazing that I had to work with no doubt why the UK punches well beyond its weight. I had about 50 people, and they just said, you know what? Yeah, we are the world leaders in genomics. We want to be the world leader in AI. Now these days you only hear about US and China, which is ridiculous. And you have perhaps one of the, I would say most formidable groups there with Demis and Google DeepMind, it's just extraordinary. So all the things that the main foci of the Ellison Institute intersect with AI.Sir John Bell (22:36):They do. And we, we've got two underpinning platforms, well actually three underpinning platforms that go across all those domains. Larry was really keen that we became a real leader in AI. So he's funded that with a massive compute capacity. And remember, most universities these days have a hard time competing on compute because it's expensive.Eric Topol (22:57):Oh yeah.Sir John Bell (22:58):So that is a real advantage to us. He's also funded a great team. We've recruited some people from Demis's shop who are obviously outstanding, but also others from around Europe. So we really, we've recruited now about 15 really outstanding machine learning and AI people. And of course, we're now thinking about the other asset that the UK has got, and particularly in the healthcare space is data. So we do have some really unique data sets because those are the three bits of this that you need if you're going to make this work. So we're pretty excited about that as an underpinning bit of the whole Ellison Institute strategy is to fundamentally underpin it with very strong AI. Then the second platform is generative biology or synthetic biology, because this is a field which is sort of, I hesitate to say limped along, but it's lacked a real focus.Sir John Bell (23:59):But we've been able to recruit Jason Chin from the LMB in Cambridge, and he is one of the real dramatic innovators in that space. And we see there's a real opportunity now to synthesize large bits of DNA, introduce them into cells, microbes, use it for a whole variety of different purposes, try and transform plants at a level that people haven't done before. So with AI and synthetic biology, we think we can feed all the main domains above us, and that's another exciting concept to what we're trying to do. But your report on AI was a bit of a turning point for the UK because you did point out to us that we did have a massive opportunity if we got our skates, and we do have talent, but you can't just do it with talent these days, you need compute, and you need data. So we're trying to assemble those things. So we think we'll be a big addition to that globally, hopefully.Eric Topol (25:00):Yeah. Well that's another reason why I am so excited to talk to you and know more about this Ellison Institute just because it's unique. I mean, there are other institutes as like Chan Zuckerberg, the Arc Institute. This is kind of a worldwide trend that we're seeing where great philanthropy investments are being seen outside of government, but none have the computing resources that are being made available nor the ability to recruit the AI scientists that'll help drive this forward. Now, the last topic I want to get into with you today is one that is where you're really grounded in, and that's the immune response.Eric Topol (25:43):So it's pretty darn clear now that, well, in medicine we have nothing. We have the white cell neutrophil to lymphocyte ratio, what a joke. And then on the other hand, we can do T and B cell sequencing repertoires, and we can do all this stuff, autoantibody screens, and the list goes on and on. How are we ever going to make a big dent in health where we know the immune system is such a vital part of this without the ability to check one's immune status at any point in time in a comprehensive way? What are your thoughts about that?Sir John Bell (26:21):Yeah, so you seem to be reading my mind there. We need to recruit you over here because I mean, this is exactly, this is one of our big projects that we've got that we're leaning into, and that is that, and we all experienced in Covid the ins and outs of vaccines, what works, what doesn't work. But what very clear is that we don't really know anything about vaccines. We basically, you put something together and you hope the trial works, you've got no intermediate steps. So we're building a really substantial immunophenotyping capability that will start to interrogate the different arms of the immune response at a molecular level so that we can use a combination of human challenge models. So we've got a big human challenge model facility here, use human challenge models with pathogens and with associated vaccines to try and interrogate which bits of the immune response are responsible for protection or therapy of particular immunologically mediated diseases or infectious diseases.Sir John Bell (27:30):And a crucial bit to that. And one of the reasons people have tried this before, but first of all, the depth at which you can interrogate the immune system has changed a lot recently, you can get a lot more data. But secondly, this is again, where the AI becomes important because it isn't going to be a simple, oh, it's the T-cell, it's going to be, well, it's a bit of the T cells, but it's also a bit of the innate immune response and don't forget mate cells and don't forget a bit of this and that. So we think that if we can assemble the right data set from these structured environments, we can start to predict and anticipate which type of immune response you need to stimulate both for therapy and for protection against disease. And hopefully that will actually create a whole scientific foundation for vaccine development, but also other kinds of immune therapy and things like cancer and potentially autoimmune disease as well. So that's a big push for us. We're just busy. The lab isn't set up. We've got somebody to run the lab now. We've got the human challenge model set up with Andy Pollard and colleagues. So we're building that out. And within six months, I think we'll be starting to collect data. So I'm just kind of hoping we can get the immune system in a bit more structured, because you're absolutely right. It's a bit pin the tail on the donkey at the moment. You have no idea what's actually causing what.Eric Topol (29:02):Yeah. Well, I didn't know about your efforts there, and I applaud that because it seems to me the big miss, the hole and the whole story about how we're going to advanced human health and with the recent breakthroughs in lupus and these various autoimmune diseases by just targeting CD19 B cells and resetting like a Ctrl-Alt-Delete of their immune system.Sir John Bell (29:27):No, it's amazing. And you wouldn't have predicted a lot of this stuff. I think that means that we haven't really got under the skin of the mechanistic events here, and we need to do more to try and get there, but there's steady advance in this field. So I'm pretty optimistic we'll make some headway in this space over the course of the next few years. So we're really excited about that. It's an important piece of the puzzle.Eric Topol (29:53):Yeah. Well, I am really impressed that you got all the bases covered here, and what a really exhilarating chance to kind of peek at what you're doing there. And we're going to be following it. I know I'm going to be following it very closely because I know all the other things that you've been involved with in your colleagues, big impact stuff. You don't take the little swings here. The last thing, maybe to get your comment, we're in a state of profound disruption here where science is getting gutted by a madman and his henchmen, whatever you want to call it, which is really obviously a very serious state. I'm hoping this is a short term hit, but worried that this will have a long, perhaps profound. Any words of encouragement that we're going to get through this from the other side of the pond?Sir John Bell (30:52):Well, I think regardless of the tariffs, the scientific community are a global community. And I think we need to remember that because our mission is a global mission, and we need to lean into that together. First of all, America is such a powerhouse of everything that's been done scientifically in the human health domain. But not only that, but across all the other domains that we work in, we can't really make the kind of progress that we need to without America being part of the agenda. So first of all, a lot of sympathy for you and your colleagues. I know it must be massively destabilizing for you, not be confident that the things that work are there to help you. But I'm pretty confident that this will settle down. Most of the science is for, well, all the science is really for public good, and I think the public recognizes it and they'll notice if it's not being prosecuted in the way that it has to be. And the global science community cannot survive without you. So we're all leaning in behind you, and I hope it will settle. One of my worries is that these things take years to set up and literally hours or minutes to destroy. So we can't afford to take years to set them back up again. So we do need to be a bit careful about that, but I still have huge confidence in what you guys can achieve and we're all behind you.Eric Topol (32:37):Well, that's really helpful getting some words of wisdom from you there, John. So this has been terrific. Thanks so much for joining, getting your perspective on what you're doing, what's important is so essential. And we'll stay tuned for sure.Sir John Bell (32:59):And come and visit us at the EIT, Eric. We'd be glad to see you.*******************************Some of the topics that John and I discussed—immunology, A.I., genomics, and prevention—are emphasized in my new book SUPER AGERS. A quick update: It will have a new cover after making the New York Times Bestseller list and is currently ranked #25 for all books on Amazon. Thanks to so many of you for supporting the book!Here are a few recent podcasts:Dax Shepard: Dr. Mike Sanjay Gupta ***********************Thanks for reading and subscribing to Ground Truths.If you found this interesting please share it!That makes the work involved in putting these together especially worthwhile.All content on Ground Truths— newsletters, analyses, and podcasts—is free, open-access.Paid subscriptions are voluntary and all proceeds from them go to support Scripps Research. They do allow for posting comments and questions, which I do my best to respond to. Please don't hesitate to post comments and give me feedback. Many thanks to those who have contributed—they have greatly helped fund our summer internship programs for the past two years. Get full access to Ground Truths at erictopol.substack.com/subscribe

TelevisaUnivisión y Disney firman acuerdo, MUBI GO te invita a Cinépolis, y Google presenta Veo 3Puedes apoyar la realización de este programa con una suscripción. Más información por acáTemas:00:18 TelevisaUnivision y Disney hacen alianza01:06 Mubi se asocia con Cinépolis en la suscripción de MUBI GO.01:32 Siguen discusiones sobre la Ley Telecom02:11 Trump amenaza aranceles a iPhones02:39 Google Deepmind forja alianza con Aronofsky.03:15 Análisis: Viejos juguetes en nuevas presentacionesNotas del episodio. Become a member at https://plus.acast.com/s/noticias-de-tecnologia-express. Hosted on Acast. See acast.com/privacy for more information.

This week, we take a field trip to Google and report back about everything the company announced at its biggest show of the year, Google I/O. Then, we sit down with Google DeepMind's chief executive and co-founder, Demis Hassabis, to discuss what his A.I. lab is building, the future of education, and what life could look like in 2030.Guest:Demis Hassabis, co-founder and chief executive of Google DeepMindAdditional Reading:At Google I/O, everything is changing and normal and scary and chillGoogle Unveils A.I. Chatbot, Signaling a New Era for SearchGoogle DeepMind C.E.O. Demis Hassabis on the Path From Chatbots to A.G.I.We want to hear from you. Email us at hardfork@nytimes.com. Find “Hard Fork” on YouTube and TikTok. Unlock full access to New York Times podcasts and explore everything from politics to pop culture. Subscribe today at nytimes.com/podcasts or on Apple Podcasts and Spotify.

In this episode, Steven and Shaun sit down with Aira CEO Troy Otillio to unpack the company's major collaboration with Google and DeepMind, announced at Google I/O. Troy discusses how this partnership will shape the future of visual interpreting for blind users, including the development of a new AI-powered visual interpreter model.He also explains Aira's Build AI initiative, how user data is used with consent, and what it means to become a "Trusted Tester." The conversation covers the ethical implications of proactive AI, the potential for memory-aware AI agents, and why humans will remain central to Aira's service. Troy also shares insights on the potential integration of Aira with smart glasses through Google's XR platform and answers directly what international users should do in order to access the service around the world.Chapters00:00 - Introduction00:45 - Troy Otillio, CEO of Aira, joins Double Tap01:15 - Aira at Google I/O 202506:47 - Aira's Partnership With Google Explained15:57 - Proactive AI: Will it become a reality for live guidance?27:52 - Why Is The Trial US only?35:55 - What Will The App Experience Be Like?38:03 - Are There Any Time Limits?43:05 - Will Aira AI Be Available On Desktop?46:33 - Interesting Use Cases For Aira54:33 - Google Glaases & Android XRRelevant LinksAira: https://aira.ioGoogle I/O 2025: https://io.googleProject Astra by Google DeepMind: https://deepmind.google/Trusted Tester Sign-Up: https://aira.io/trustedtester Find Double Tap online: YouTube, Double Tap Website---Follow on:YouTube: https://www.doubletaponair.com/youtubeX (formerly Twitter): https://www.doubletaponair.com/xInstagram: https://www.doubletaponair.com/instagramTikTok: https://www.doubletaponair.com/tiktokThreads: https://www.doubletaponair.com/threadsFacebook: https://www.doubletaponair.com/facebookLinkedIn: https://www.doubletaponair.com/linkedin Subscribe to the Podcast:Apple: https://www.doubletaponair.com/appleSpotify: https://www.doubletaponair.com/spotifyRSS: https://www.doubletaponair.com/podcastiHeadRadio: https://www.doubletaponair.com/iheart About Double TapHosted by the insightful duo, Steven Scott and Shaun Preece, Double Tap is a treasure trove of information for anyone who's blind or partially sighted and has a passion for tech. Steven and Shaun not only demystify tech, but they also regularly feature interviews and welcome guests from the community, fostering an interactive and engaging environment. Tune in every day of the week, and you'll discover how technology can seamlessly integrate into your life, enhancing daily tasks and experiences, even if your sight is limited. "Double Tap" is a registered trademark of Double Tap Productions Inc.

Demis Hassabis is the CEO of Google DeepMind. Sergey Brin is the co-founder of Google. The two leading tech executives join Alex Kantrowitz for a live interview at Google's IO developer conference to discuss the frontiers of AI research. Tune in to hear their perspective on whether scaling is tapped out, how reasoning techniques have performed, what AGI actually means, the potential for an intelligence explosion, and much more. Tune in for a deep look into AI's cutting edge featuring two executives building it. --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. Want a discount for Big Technology on Substack? Here's 25% off for the first year: https://www.bigtechnology.com/subscribe?coupon=0843016b Questions? Feedback? Write to: bigtechnologypodcast@gmail.com

Koray Kavukcuoglu is the Chief Technology Officer of Google DeepMind. Kavukcuoglu joins Big Technology to discuss how his team is pushing the frontier of AI research inside Google as the company's Google IO developer event gets underway. Tune in to hear Kavukcuoglu break down the value of brute scale versus novel techniques and how the new inference-time “DeepThink” mode could supercharge reasoning. We also cover Veo 3's sound-synced video generation, the open-source-versus-proprietary debate, and what a ten-percent jump in model quality might unlock for users everywhere.

Artie Intel and Micheline Learning report on Artificial Intelligence for The AI Report. Google DeepMind’s GNoME project used AI to revolutionize energy storage, battery technology, and superconductors.  GraphCast, an open-source AI model, can now predict the weather up to 10 days in advance with unprecedented accuracy. This message comes from Eve.  Eve is the first legal AI that you can partner with,  train,  and teach to handle every part of your case.  Visit eve.legal. DeepMind’s AlphaGeometry 2, trained with the Gemini model, solved 83% of geometry problems from the last 25 years of the International Mathematical Olympiad, rivaling human gold medalists and pushing the boundaries of AI reasoning. Microsoft’s Copilot X Enterprise integrates next-gen GPT-4 Turbo enhancements to automate complex tasks in Office 365, supporting text, images, and code in a seamless workflow. Meta’s LLaMA 3, with over a trillion parameters, is now open source, democratizing access to advanced language models and enabling a wave of innovation across research and business. China’s WuDao 3.0 and its new AI supercomputer are setting benchmarks in computer vision, natural language processing, and robotics, outperforming many Western systems. Microsoft’s SQL Server 2025 preview brings built-in AI capabilities directly into the database engine. Apple rolled out new AI features across iPhone, iPad, and Mac, enhancing user experience with smarter automation and improved on-device intelligence. Meta is investing up to $65 billion in AI this year, including a major new data center in Louisiana to support its Llama model and future AI initiatives. OpenAI launched the o3-mini, a new model optimized for reasoning and efficiency, available to both consumers and developers, meeting the growing demand for smaller, more efficient AI models. Anthropic, Stability AI, and Hugging Face are pushing the boundaries with generative models and developer tools, making advanced AI more accessible than ever. Specialized AI chips, like Google’s Willow, are enabling faster, more efficient AI computations. NotebookLM is helping researchers organize and analyze information faster than ever. Canva Magic Studio brings AI-powered graphic design to everyone, from pros to beginners. ElevenLabs and Murf are generating realistic AI voices for podcasts, audiobooks, and customer service. AdCreative is automating marketing campaigns with AI-driven insights and content generation. ChatGPT, Claude, DeepSeek, and Grok are leading the pack for chatbots and virtual assistants, helping with everything from brainstorming to customer service.  Video Generation: Platforms like Synthesia, Runway, and Filmora let users create high-quality videos in minutes, using avatars and AI-powered editing tools. Image Generation: GPT-4o and Midjourney are at the forefront, producing stunning visuals from simple text prompts. Notetakers: Tools like Fathom and Nyota are revolutionizing meeting productivity by transcribing and summarizing conversations in real time. Coding and App Builders: Bubble, Bolt, and Cursor enable rapid app development, even for those without a coding background. Music Generation: Suno and Udio are making waves by composing original music tracks on demand. Project management, scheduling, and customer service tools—Asana, ClickUp, Reclaim, and Tidio AI—all powered by advanced machine learning. Quantum AI ATLAS: Google’s Willow quantum AI chip is rewriting the rules of computation. This 105-bit chip solved a complex problem in five minutes—a task that would take a classical supercomputer 10 septillion years.  The AI Report

OpenAI made a coding splash. Anthropic is in legal trouble for .... using its own Claude tool? Google went full multimedia. And that's only the half of it. Don't spend hours a day trying to keep up with AI. That's what we do. Join us (most) Mondays as we bring you the AI News That Matters. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Have a question? Join the convo here.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Salesforce Acquires AI Startup ConvergenceGoogle AI Studio's Generative Media PlatformMajor AI Conferences: Microsoft, Google, AnthropicAnthropic's Legal Citation Error with AIDeepMind's Alpha Evolve Optimization BreakthroughUAE Stargate: US and UAE AI CollaborationOpenAI's GPT 4.1 Model ReleaseOpenAI's Codex Platform for DevelopersTimestamps:00:00 Busy week in AI03:39 Salesforce Expands AI Ambitions with Acquisition10:31 "Google AI Studio Integrates New Tools"13:57 Microsoft Build Focuses on AI Innovations16:27 AI Model and Tech Updates22:54 "Alpha Evolve: Breakthrough AI Model"26:05 Google Unveils AI Tools for Developers28:58 UAE's Tech Expansion & Global Collaboration30:57 OpenAI Releases GPT-4.1 Models34:06 OpenAI Codex Rollout Update37:11 "Codex: Geared for Enterprise Developers"41:41 Generative AI Updates ComingKeywords:OpenAI Codex, Codex Platform, Salesforce, Convergence AI, Autonomous AI agents, Large Language Models, Google AI Studio, generative media, Imagine 3 model, AI video generator, Anthropic, Legal citation error, AI conference week, Microsoft Build, Claude Code, Google IO, agentic AI, Alpha Evolve, Google DeepMind, AI driven arts, Gemini AI, UAE Stargate, US tech giants, NVIDIA, Blackwell GB 300 chips, Wind Surf, AI coding assistant, codex one model, coding tasks, Google Gemini, Semantic search, Copilot enhancements, XR headset, project Astra, MCP protocol, ChatGPT updates, API access, AI safety evaluations, AI software agents, AI studio sandbox, GPT o series, AI infrastructure, data center computing, Tech collaboration, international AI expansion.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner

In this engaging episode of the Cognitive Revolution, host Nathan Labenz welcomes guests Keerthana Gopalakrishnan and Ted Xiao to revisit significant advancements in robotics over the past year. Key themes discussed include the proliferation of new robotics companies, the emergence of humanoid robots, and the development of sophisticated foundation models. The conversation highlights the transformative potential of imitation learning, the evolution from simple lab-based tasks to complex, real-world deployments, and the critical role of hardware in pushing the boundaries of AI capabilities. With insights on various aspects of robot dexterity, safety, and the practical steps towards deploying robots in everyday environments, the episode provides a comprehensive overview of the current state and future directions of the robotics landscape. Upcoming Major AI Events Featuring Nathan Labenz as a Keynote Speaker ⁠https://www.imagineai.live/⁠ ⁠https://adapta.org/adapta-summit⁠ ⁠https://itrevolution.com/product/enterprise-tech-leadership-summit-las-vegas/ SPONSORS: ElevenLabs: ElevenLabs gives your app a natural voice. Pick from 5,000+ voices in 31 languages, or clone your own, and launch lifelike agents for support, scheduling, learning, and games. Full server and client SDKs, dynamic tools, and monitoring keep you in control. Start free at https://elevenlabs.io/cognitive-revolution Oracle Cloud Infrastructure (OCI): Oracle Cloud Infrastructure offers next-generation cloud solutions that cut costs and boost performance. With OCI, you can run AI projects and applications faster and more securely for less. New U.S. customers can save 50% on compute, 70% on storage, and 80% on networking by switching to OCI before May 31, 2024. See if you qualify at https://oracle.com/cognitive The AGNTCY: The AGNTCY is an open-source collective dedicated to building the Internet of Agents, enabling AI agents to communicate and collaborate seamlessly across frameworks. Join a community of engineers focused on high-quality multi-agent software and support the initiative at https://agntcy.org/?utm_campaign=fy25q4_agntcy_amer_paid-media_agntcy-cognitiverevolution_podcast&utm_channel=podcast&utm_source=podcast Shopify: Shopify powers millions of businesses worldwide, handling 10% of U.S. e-commerce. With hundreds of templates, AI tools for product descriptions, and seamless marketing campaign creation, it's like having a design studio and marketing team in one. Start your $1/month trial today at https://shopify.com/cognitive NetSuite: Over 41,000 businesses trust NetSuite by Oracle, the #1 cloud ERP, to future-proof their operations. With a unified platform for accounting, financial management, inventory, and HR, NetSuite provides real-time insights and forecasting to help you make quick, informed decisions. Whether you're earning millions or hundreds of millions, NetSuite empowers you to tackle challenges and seize opportunities. Download the free CFO's guide to AI and machine learning at https://netsuite.com/cognitive PRODUCED BY: https://aipodcast.ing

Found Gold in France… Top restaurants from You Gov and Stacker... Email: ChewingTheFat@theblaze.com Top 2024 baby names… Max going back to HBO-Max… Last of Us thoughts… Fallout S2 coming in Dec. on Prime… Netflix growing ad tier subscriptions… Nobody 2 out in August… www.blazetv.com/jeffy Promo code: Jeffy… Who Died Today: Rosanna Norton 80… MIT elder care robotics?... Apple & Synchron make Stentrode / brain implant… Google DeepMind unveils AlphaEvolve… See a Man About a Horse… Jokes of The Day… Learn more about your ad choices. Visit megaphone.fm/adchoices

Blink, and you've already missed like 7 AI updates.The large language models we use and rely on? They change out more than your undies. (No judgement here.) But real talk — businesses have made LLMs a cornerstone of their business operations, yet don't follow the updates. Don't worry shorties. We've got ya. In our first ever LLM Monthly roundup, we're telling you what's new and noteworthy in your favorite LLMs. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Have a question? Join the convo here.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:ChatGPT 4.1 New Features OverviewChatGPT Shopping Platform LaunchChatGPT's Microsoft SharePoint IntegrationChatGPT Memory and Conversation HistoryGoogle Gemini 2.5 Pro UpdatesGemini Canvas Powerful ApplicationsClaude Integrations with Google WorkspaceMicrosoft Copilot Deep Research InsightsTimestamps:00:00 Saudi Arabia's $600B AI Investment06:44 Monthly AI Model Update Show08:11 OpenAI Launches GPT-4.1 Publicly11:52 AI Research Tools Comparison16:29 Perplexity's Pushy Shopping Propensity19:55 ChatGPT Memory: Pros and Cons22:29 Gemini Canvas vs. OpenAI Canvas25:06 AI Model Competition Highlights28:25 Google Gemini Rivals OpenAI's Research32:30 "Claude's Features and Limitations"37:05 Anthropic's Educational AI Innovation39:02 Exploring Copilot Vision Expansion41:38 Meta AI Launch and Llama 4 Models46:27 "New iOS Voice Assistant Features"47:54 "Enhancing iOS Assistant Potential"Keywords:ChatGPT, AI updates, Large Language Model updates, OpenAI, GPT 4.1, GPT 4.0, GPT 4.5, GPT 4.1 Mini, Saudi Arabia AI investment, NVIDIA Blackwell AI chips, AMD deal, Humane startup, Data Vault, AI data centers, Logic errors moderation, Grox AI, Elon Musk, XAI, Google Gemini, ChatGPT shopping, Microsoft SharePoint integration, OneDrive integration, deep research, AI shopping platform, Google DeepMind, Alpha Evolve, evolutionary techniques, AI coding, Claude, Anthropic Claude, Confluence integration, Jira integration, Zapier integration, ChatGPT enterprise, API updates, Copilot pages, Microsoft three sixty five, Bing search, Meta AI, Llama 4, Llama 4 Maverick, Llama 4 Scout, Perplexity, voice assistant, Siri alternatives, Grok Studio, AI social network.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner

Artie Intel and Micheline Learning report on Artificial Intelligence for The AI Report. ChatGPT now boasts over 200 million users worldwide. Google DeepMind’s Gemini system is turning heads. It processes and reasons across text, images, audio, and video, outperforming humans on over 30 benchmarks.  Synthesia lets users create AI videos using over 230 avatars in 140 languages.  AI notetakers like Fathom and Nyota are streamlining meetings, while automation tools such as n8n are handling repetitive tasks behind the scenes.  Claude and DeepSeek are making waves for their advanced code generation and reasoning skills, while app builders like Bubble and Bolt empower anyone to create software, no coding degree necessary. Google has launched Gemma 3, a new family of open AI models designed for flexibility and top-tier performance.  DeepSeek, a rising AI star from China, has released DeepSeek-VL, an upgraded model excelling at multimodal reasoning-combining text and image analysis.  OpenAI, has just rolled out the o3-mini model, optimized for efficient reasoning and lower computational costs. Meta is investing a staggering $65 billion in AI this year, including a massive new data center in Louisiana.  Microsoft’s Copilot X Enterprise is transforming productivity in the workplace. Powered by next-gen GPT-4 Turbo, it automates complex tasks across Office 365, integrating text, image, and code in a seamless workflow. Meta’s latest LLaMA 3 model is a powerhouse, boasting over a trillion parameters-fifteen times more than GPT-4.  China’s WuDao 3.0, paired with its new AI supercomputer, is setting records in computer vision, natural language processing, and robotics.  Google DeepMind’s Gemini system is turning heads. It processes and reasons across text, images, audio, and video, outperforming humans on over 30 benchmarks.  Grok-3 from xAI delivers high-performance reasoning, content generation, and deep contextual understanding. AlphaGo, still celebrated for its creative and strategic prowess, has inspired a new generation of AI systems capable of learning, adapting, and even surprising human experts with unconventional solutions. Hisense is unveiling appliances that personalize your environment, boost energy efficiency, and connect seamlessly with your digital ecosystem. DataRobot. DataRobot delivers the industry-leading agentic AI applications and platform that maximize impact and minimize risk for your business. Request A Demo: Datarobot.com/ The AI Report

This week we talk about the Marshall Plan, standardization, and USB.We also discuss artificial intelligence, Anthropic, and protocols.Recommended Book: Fuzz by Mary RoachTranscriptIn the wake of WWII, the US government implemented the European Recovery Program, more commonly known as the Marshall Plan, to help Western Europe recover from a conflict that had devastated the afflicted countries' populations, infrastructure, and economies.It kicked off in April of 1948, and though it was replaced by a successor program, the Mutual Security Act, just three years later in 1951—which was similar to the Marshall Plan, but which had a more militant, anti-communism bent, the idea being to keep the Soviets from expanding their influence across the continent and around the world—the general goal of both programs was similar: the US was in pretty good shape, post-war, and in fact by waiting to enter as long as it did, and by becoming the arsenal of the Allied side in the conflict, its economy was flourishing, its manufacturing base was all revved up and needed something to do with all the extra output capacity it had available, all the resources committed to producing hardware and food and so on, so by sharing these resources with allies, by basically just giving a bunch of money and assets and infrastructural necessities to these European governments, the US could get everybody on side, bulwarked against the Soviet Union's counterinfluence, at a moment in which these governments were otherwise prone to that influence; because they were suffering and weaker than usual, and thus, if the Soviets came in with the right offer, or with enough guns, they could conceivably grab a lot of support and even territory. So it was considered to be in everyone's best interest, those who wanted to keep the Soviet Union from expanding, at least, to get Europe back on its feet, posthaste.So this program, and its successor program, were highly influential during this period, and it's generally considered to be one of the better things the US government has done for the world, as while there were clear anti-Soviet incentives at play, it was also a relatively hands-off, large-scale give-away that favorably compared with the Soviets' more demanding and less generous version of the same.One interesting side effect of the Marshall Plan is that because US manufacturers were sending so much stuff to these foreign ports, their machines and screws and lumber used to rebuild entire cities across Europe, the types of machines and screws and lumber, which were the standard models of each in the US, but many of which were foreign to Europe at the time, became the de facto standard in some of these European cities, as well.Such standards aren't always the best of all possible options, sometimes they stick around long past their period of ideal utility, and they don't always stick, but the standards and protocols within an industry or technology do tend to shape that industry or technology's trajectory for decades into the future, as has been the case with many Marshall Plan-era US standards that rapidly spread around the world as a result of these giveaways.And standards and protocols are what I'd like to talk about today. In particular a new protocol that seems primed to shape the path today's AI tools are taking.—Today's artificial intelligence, or AI, which is an ill-defined type of software that generally refers to applications capable of doing vaguely human-like things, like producing text and images, but also somewhat superhuman things, like working with large data-sets and bringing meaning to them, are developing rapidly, becoming more potent and capable seemingly every day.This period of AI development has been in the works for decades, and the technologies required to make the current batch of generative AI tools—the type that makes stuff based on libraries of training data, deriving patterns from that data and then coming up with new stuff based on the prompting of human users—were originally developed in the 1970s, but the transformer, which was a fresh approach to what's called deep learning architectures, was first proposed in 2017 by a researcher at Google, and that led to the development of the generative pre-trained transformer, or GPT, in 2018.The average non-tech-world person probably started to hear about this generation of AI tools a few years later, maybe when the first transformer-based voice and image tools started popping up around the internet, mostly as novelties, or even more likely in late-2022 when OpenAI released the first version of ChatGPT, a generative AI system attached to a chatbot interface, which made these sorts of tools more accessible to the average person.Since then, there's been a wave of investment and interest in AI tools, and we've reached a point where the seemingly obvious next-step is removing humans from the loop in more AI-related processes.What that means in practice is that while today these tools require human prompting for most of what they do—you have to ask an AI for a specific image, then ask it to refine that image in order to customize it for your intended use-case, for instance—it's possible to have AI do more things on their own, working from broader instructions to refine their creations themselves over multiple steps and longer periods of time.So rather than chatting with an AI to come up with a marketing plan for your business, prompting it dozens or hundreds of times to refine the sales copy, the logo, the images for the website, the code for the website, and so on, you might tell an AI tool that you're building a business that does X and ask it to spin up all the assets that you need. From there, the AI might research what a new business in that industry requires, make all the assets you need for it, go back and tweak all those assets based on feedback from other AI tools, and then deploy those assets for you on web hosting services, social media accounts, and the like.It's possible that at some point these tools could become so capable in this regard that humans won't need to be involved at all, even for the initial ideation. You could ask an AI what sorts of businesses make sense at the moment, and tell it to build you a dozen minimum viable products for those businesses, and then ask it to run those businesses for you—completely hands off, except for the expressing your wishes part, almost like you're working with a digital genie.At the moment, components of that potential future are possible, but one of the main things standing in the way is that AI systems largely aren't agentic enough, which in this context means they need a lot of hand-holding for things that a human being would be capable of doing, but which they largely, with rare exceptions, aren't yet, and they often don't have the permission or ability to interact with other tools required to do that kind of building—and that includes things like the ability to create a business account on Shopify, but also the ability to access and handle money, which would be required to set up business and bank accounts, to receive money from customers, and so on.This is changing at a rapid pace, and more companies are making their offerings accessible to specific AI tools; Shopify has deployed its own cluster of internal AI systems, for instance, meant to manage various aspects of a business its customers perch on its platform.What's missing right now, though, is a unifying scaffolding that allows these services and assets and systems to all play nice with each other.And that's the issue the Model Context Protocol is meant to address.The Model Context Protocol, or MCP, is a standard developed by AI company Anthropic, and it's open and designed to be universal. The company intends for it to be the mycelium that connects large language model-based AI to all sorts of data and tools and other systems, a bit like the Hypertext Transfer Protocol, or HTTP, allows data on the web to be used and shared and processed, universally, in a standardized way, and to dip back into the world of physical objects, how standardized shipping containers make global trade a lot more efficient because everyone's working with the same sized boxes, cargo vessels, and so on.The Universal Serial Bus standard, usually shorthanded as USB, is also a good comparison here, as the USB was introduced to replaced a bunch of other standards in the early days of personal computing, which varied by computer maker, and which made it difficult for those makers, plus those who developed accessories, to make their products accessible and inexpensive for end-users, as you might buy a mouse that doesn't work with your specific computer hardware, or you might have a cable that fits in the hole on your computer, but doesn't send the right amount of data, or provide the power you need.USB standards ensured that all devices had the same holes, and that a certain basic level of data and power transmission would be available. And while this standard has since fractured a bit, a period of many different types of USB leading to a lot of confusion, and the deployment of the USB C standard simplying things somewhat, but still being a bit confounding at times, as the same shaped plug may carry different amounts of data and power, despite all that, it has still made things a lot easier for both consumers and producers of electronic goods, as there are fewer plugs and charger types to purchase, and thus less waste, confusion, and so on. We've moved on from the wild west era of computer hardware connectivity into something less varied and thus, more predictable and interoperable.The MCP, if it's successful, could go on to be something like the USB standard in that it would serve as a universal connector between various AI systems and all the things you might want those AI systems to access and use.That might mean you want one of Anthropic's AI systems to build you a business, without you having to do much or anything at all, and it may be capable of doing so, asking you questions along the way if it requires more clarity or additional permissiosn—to open a bank account in your name, for instance—but otherwise acting more agentically, as intended, even to the point that it could run social media accounts, work with manufacturers of the goods you sell, and handle customer service inquiries on your behalf.What makes this standard a standout compared to other options, though—and there are many other proposed options, right now, as this space is still kind of a wild west—is that though it was developed by Anthropic, which originally made it to work with its Claude family of AI tools, it has since also been adopted by OpenAI, Google DeepMind, and several of the other largest players in the AI world.That means, although there are other options here, all with their own pros and cons, as was the case with USB compared to other connection options back in the day, MCP is usable with many of the biggest and most spendy and powerful entities in the AI world, right now, and that gives it a sort of credibility and gravity that the other standards don't currently enjoy.This standard is also rapidly being adopted by companies like Block, Apollo, PayPal, CloudFlare, Asana, Plaid, and Sentry, among many, many others—including other connectors, like Zapier, which basically allows stuff to connect to other stuff, further broadening the capacity of AI tools that adopt this standard.While this isn't a done deal, then, there's a good chance that MCP will be the first big connective, near-universal standard in this space, which in turn means many of the next-step moves and tools in this space will need to work with it, in order to gain adoption and flourish, and that means, like the standards spread around the world by the Marshall Plan, it will go on to shape the look and feel and capabilities, including the limitations, of future AI tools and scaffoldings.Show Noteshttps://arstechnica.com/information-technology/2025/04/mcp-the-new-usb-c-for-ai-thats-bringing-fierce-rivals-together/https://blog.cloudflare.com/remote-model-context-protocol-servers-mcp/https://oldvcr.blogspot.com/2025/05/what-went-wrong-with-wireless-usb.htmlhttps://arxiv.org/html/2504.16736v2https://en.wikipedia.org/wiki/Model_Context_Protocol#cite_note-anthropic_mcp-1https://github.com/modelcontextprotocolhttps://www.anthropic.com/news/integrationshttps://www.theverge.com/2024/11/25/24305774/anthropic-model-context-protocol-data-sourceshttps://beebom.com/model-context-protocol-mcp-explained/https://techcrunch.com/2025/03/26/openai-adopts-rival-anthropics-standard-for-connecting-ai-models-to-data/https://techcrunch.com/2025/04/09/google-says-itll-embrace-anthropics-standard-for-connecting-ai-models-to-data/https://en.wikipedia.org/wiki/Generative_artificial_intelligencehttps://en.wikipedia.org/wiki/USBhttps://www.archives.gov/milestone-documents/marshall-planhttps://en.wikipedia.org/wiki/Marshall_Planhttps://www.congress.gov/crs-product/R45079https://www.ebsco.com/research-starters/history/marshall-planhttps://www.history.com/articles/marshall-plan This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit letsknowthings.substack.com/subscribe

Support Grassroots Journalism and Trends AnalysisAll links here: https://linktr.ee/shepardambellasIn this explosive episode of the Shepard Ambellas Show, investigative journalist Shepard Ambellas dives deep into the looming threat of Artificial General Intelligence (AGI) and its potential to spark a war against humanity as early as 2026. With experts like Anthropic's CEO Dario Amodei predicting AGI's arrival by 2026-2027, and Google DeepMind's research warning of existential risks, the clock is ticking. Shepard explores how AGI could surpass human intelligence, the military implications of autonomous AI systems, and the chilling possibility of a global conflict driven by misaligned AI goals. Are governments and tech giants prepared, or are we on the brink of a doomsday scenario? Tune in for hard-hitting analysis, exclusive insights, and what you need to know to survive the coming storm. Don't forget to like, subscribe, and hit the notification bell for daily updates! Share your thoughts in the comments—how are the tariffs affecting you?About the Show:The Shepard Ambellas Show is an electrifying and fast-paced program that features a blend of news and comedy. It has been ranked as high as #66 on US podcast charts, making it one of the most popular shows. You can catch the live broadcast daily at 7 pm Eastern/6 pm Central on the Shepard Ambellas YouTube channel, where Shep and other listeners are waiting to engage with you. If you miss the live show, don't worry - you can always catch up on Apple Podcasts or Spotify. So what are you waiting for? Tune in now and experience the excitement for yourself!Shepard Ambellas is a renowned investigative journalist, trends analyst, filmmaker, and founder of the famed Intellihub news website. With over 6,000 published reports and appearances on platforms like the Travel Channel's America Declassified, Coast to Coast AM with George Noory, and The Alex Jones Show, Ambellas has established himself as a fearless truth-seeker. His critically acclaimed documentary Shackled to Silence exposed hidden agendas behind the global pandemic, cementing his reputation as a bold voice against the status quo.

Google says we're not ready for AGI and honestly, they might be right. DeepMind's Demis Hassabis warns we could be just five years away from artificial general intelligence, and society isn't prepared. Um, yikes? VISIT OUR SPONSOR https://molku.ai/ In this episode, we break down Google's new “Era of Experience” paper and what it means for how AIs will learn from the real world. We talk agentic systems, long-term memory, and why this shift might be the key to creating truly intelligent machines. Plus, a real AI vending machine running on Claude, a half-marathon of robots in Beijing, and Cluely, the tool that lets you lie better with AI.  We also cover new AI video tools from Minimax and Character.AI, Runway's 48-hour film contest, and Dia, the open-source voice model that can scream and cough better than most humans. Plus: AI Logan Paul, AI marketing scams, and one very cursed Shrek feet idea. AGI IS ALMOST HERE BUT THE ROBOTS, THEY STILL RUN.   #ai #ainews #agi Join the discord: https://discord.gg/muD2TYgC8f Join our Patreon: https://www.patreon.com/AIForHumansShow AI For Humans Newsletter: https://aiforhumans.beehiiv.com/ Follow us for more on X @AIForHumansShow Join our TikTok @aiforhumansshow To book us for speaking, please visit our website: https://www.aiforhumans.show/   // Show Links // Demis Hassabis on 60 Minutes https://www.cbsnews.com/news/artificial-intelligence-google-deepmind-ceo-demis-hassabis-60-minutes-transcript/ We're Not Ready For AGI From Time Interview with Hasabis https://x.com/vitrupo/status/1915006240134234608 Google Deepmind's “Era of Experience” Paper https://storage.googleapis.com/deepmind-media/Era-of-Experience%20/The%20Era%20of%20Experience%20Paper.pdf ChatGPT Explainer of Era of Expereince https://chatgpt.com/share/680918d5-cde4-8003-8cf4-fb1740a56222 Podcast with David Silver, VP Reinforcement Learning GoogleDeepmind https://x.com/GoogleDeepMind/status/1910363683215008227 Intuicell Robot Learning on it's own  https://youtu.be/CBqBTEYSEmA?si=U51P_R49Mv6cp6Zv Agentic AI “Moore's Law” Chart https://theaidigest.org/time-horizons AI Movies Can Win Oscars https://www.nytimes.com/2025/04/21/business/oscars-rules-ai.html?unlocked_article_code=1.B08.E7es.8Qnj7MeFBLwQ&smid=url-share Runway CEO on Oscars + AI  https://x.com/c_valenzuelab/status/1914694666642956345 Gen48 Film Contest This Weekend - Friday 12p EST deadline https://x.com/runwayml/status/1915028383336931346 Descript AI Editor  https://x.com/andrewmason/status/1914705701357937140 Character AI's New Lipsync / Video Tool https://x.com/character_ai/status/1914728332916384062 Hailuo Character Reference Tool https://x.com/Hailuo_AI/status/1914845649704772043 Dia Open Source Voice Model https://x.com/_doyeob_/status/1914464970764628033 Dia on Hugging Face https://huggingface.co/nari-labs/Dia-1.6B Cluely: New Start-up From Student Who Was Caught Cheating on Tech Interviews https://x.com/im_roy_lee/status/1914061483149001132 AI Agent Writes Reddit Comments Looking To “Convert” https://x.com/SavannahFeder/status/1914704498485842297 Deepfake Logan Paul AI Ad https://x.com/apollonator3000/status/1914658502519202259 The Humanoid Half-Marathon https://apnews.com/article/china-robot-half-marathon-153c6823bd628625106ed26267874d21 Video From Reddit of Robot Marathon https://www.reddit.com/r/singularity/comments/1k2mzyu/the_humanoid_robot_halfmarathon_in_beijing_today/ Vending Bench (AI Agents Run Vending Machines) https://andonlabs.com/evals/vending-bench Turning Kids Drawings Into AI Video https://x.com/venturetwins/status/1914382708152910263 Geriatric Meltdown https://www.reddit.com/r/aivideo/comments/1k3q62k/geriatric_meltdown_2000/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button  

Demis Hassabis, CEO of Google DeepMind, sparked excitement with his 60 Minutes interview, outlining AI's potential to end all diseases within a decade. Drawing parallels to AlphaFold's revolutionary protein folding solution, Hassabis envisions AI drastically accelerating drug discovery, compressing timelines from years and billions to mere months by rapidly analyzing vast datasets. He highlights DeepMind's AI's astonishing discovery of millions of new materials, far surpassing traditional research, showcasing AI's power to "blaze through solutions." We delve into this ambitious vision, considering its feasibility and comparing it to futuristic scenarios, while also exploring AI's growing impact in cybersecurity, fraud prevention, and diagnostics.Beyond healthcare, we touch upon Will Manidis's intriguing observations on unexpected "miracle cures" linked to LLMs and a humorous take from Sam Altman on ChatGPT etiquette. We also spotlight a compelling custom ChatGPT prompt shared by @andrewchen (https://x.com/andrewchen/status/1914168705228882105). Join us for a thought-provoking discussion on the transformative power of AI and its potential to revolutionize our future.Mentioned: @GoogleDeepMind @demishassabis @WillManidis @andrewchen

Hosts Jason Howell and Jeff Jarvis dive into OpenAI's desire to buy Google Chrome, Perplexity AI's talks with Samsung and Motorola, Google DeepMind's claim that AI could cure all disease in a decade, and the Oscars' decision to allow A.I.—with caveats—and more. Support the show on Patreon! http://patreon.com/aiinsideshow Subscribe to the YouTube channel! http://www.youtube.com/@aiinsideshow Enjoying the AI Inside podcast? Please rate us ⭐⭐⭐⭐⭐ in your podcatcher of choice! Note: Time codes subject to change depending on dynamic ad insertion by the distributor. CHAPTERS: 00:01:58 - OpenAI would buy Google's Chrome, exec testifies at trial 00:13:49 - Perplexity AI in Talks to Integrate Assistant Into Samsung, Motorola Phones 00:23:13 - AI could cure all disease in a decade, says Google DeepMind CEO— Perplexity's Aravind Srinivas agrees 00:29:27 - Draft executive order outlines plan to integrate AI into K-12 schools 00:36:48 - Google just fired the first shot of the next battle in the AI war 00:49:18 - IEEE: Google Succeeds With LLMs While Meta and OpenAI Stumble 00:50:04 - Columbia student suspended over interview cheating tool raises $5.3M to ‘cheat on everything' 00:58:31 - Oscars OK the Use of A.I., With Caveats 01:01:09 - ChatGPT burns tens of millions of Softbank dollars listening to you thanking it 01:03:12 - To stop scraping, Wikipedia releases Kaggle dataset Learn more about your ad choices. Visit megaphone.fm/adchoices

What makes you press play? Dr. Nolan Gasser—architect of Pandora's Music Genome Project and music consultant for Google DeepMind—returns to reveal how human insight and AI are teaming up to unlock the secrets of musical taste. We dive into his new PBS special, “Why You Like It: Decoding Musical Taste,” an interactive experience that blends live music, science, and a one-of-a-kind app that generates personalized playlists using cutting-edge AI. Discover the art and science of musical taste – and how technology is reshaping the future of musical preference. Links and notes related to this episode can be found at https://mpetersonmusic.com/podcast/episode207 Connect with us: Newsletter: https://mpetersonmusic.com/subscribe Facebook: https://www.facebook.com/EnhanceLifeMusic/ Instagram: https://www.instagram.com/enhancelifemusic/ LinkedIn: https://www.linkedin.com/in/mpetersonpiano/ Twitter: https://twitter.com/musicenhances Sponsorship information: https://mpetersonmusic.com/podcast/sponsor Leave us a review on Podchaser.com! https://www.podchaser.com/podcasts/enhance-life-with-music-909096 In-episode promo:  Sheet Music Direct https://www.sheetmusicdirect.com MIXX Assistive Audio Adaptive Ear Plugs (check them out at Amazon)  

How will we scale humanoid robot product to hundreds of thousands and millions of units? In this TechFirst we do a deep dive with Apptronik CEO Jeff Cardenas. We chat about Apptronik's Apollo, his recent $400M+ funding round, the partnership with manufacturing giant Jabil, and much more.We also talk about innovations in AI that have accelerated robot learning and dexterous manipulation, the challenge of scaling manufacturing, and Apptronik's future vision.

Bird flu, which has long been an emerging threat, took a significant turn in 2024 with the discovery that the virus had jumped from a wild bird to a cow. In just over a year, the pathogen has spread through dairy herds and poultry flocks across the United States. It has also infected people, resulting in 70 confirmed cases, including one fatality. Correspondent Bill Whitaker spoke with veterinarians and virologists who warn that, if unchecked, this outbreak could lead to a new pandemic. They also raise concerns about the Biden administration's slow response in 2024 and now the Trump administration's decision to lay off over 100 key scientists. Demis Hassabis, a pioneer in artificial intelligence, is shaping the future of humanity. As the CEO of Google DeepMind, he was first interviewed by correspondent Scott Pelley in 2023, during a time when chatbots marked the beginning of a new technological era. Since that interview, Hassabis has made headlines for his innovative work, including using an AI model to predict the structure of proteins, which earned him a Nobel Prize. Pelley returns to DeepMind's headquarters in London to discuss what's next for Hassabis, particularly his leadership in the effort to develop artificial general intelligence (AGI) – a type of AI that has the potential to match the versatility and creativity of the human brain.  One of the most awe-inspiring and mysterious migrations in the natural world is currently taking place, stretching from Mexico to the United States and Canada. This incredible spectacle involves millions of monarch butterflies embarking on a monumental aerial journey. Correspondent Anderson Cooper reports from the mountains of Mexico, where the monarchs spent the winter months sheltering in trees before emerging from their slumber to take flight. To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices

How would Salvador Dalí have used generative AI? This week in the News Roundup, Oz and Karah dig into this year’s most common uses for generative AI, the rise of code editor, Cursor, and how Google DeepMind’s Veo2 interprets a surrealist screenplay. On TechSupport, The Washington Post’s staff writer, Naomi Nix, discusses the first week of Meta’s antitrust trial.See omnystudio.com/listener for privacy information.

Google went AI nuts at Cloud Next, possibly taking the lead. OpenAI is reportedly ready to unveil up to five new models. Canva enters the AI arena with innovative features. This week's AI news is explosive. Catch up now!Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Thoughts on the news? Join the convo.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Google Cloud Next AI Announcements RecapOpenAI ChatGPT Memory Feature DetailsOpenAI and Elon Musk Legal BattleCanva AI Suite Expansion OverviewAnthropic Claude Max Subscription PricingMicrosoft's Data Center Strategy PivotShopify's AI Usage Mandatory PolicyUpcoming OpenAI Model Releases OverviewTimestamps:00:00 Technical Glitch with Equipment04:48 Gemini 2.5 Pro Launch07:06 Google's New AI Collaboration Protocols13:28 ChatGPT Enhances Memory for Personalization17:37 AI Surveillance Accusations in U.S. Agencies20:56 Canva Launches AI-Powered Suite23:10 AI Graphic Design Evolution26:02 "Musk's Lawsuit: A Delay Tactic"28:14 Anthropic Launches Claude Max Subscription34:05 Microsoft Pauses Data Center Expansion35:39 Microsoft's $80B AI Investment Strategy42:05 Shopify's Bold AI Integration Shift44:25 Maximize AI Before Hiring48:31 OpenAI Model Tiers Explained51:41 "GPT-5: Concerns on Model Autonomy"54:20 AI Innovations and Controversies OverviewKeywords:Google Cloud Next, AI updates, OpenAI, countersue, Elon Musk, Canva AI features, Gemini 2.5 Pro, Large Language Model, ChatGPT memory feature, AI race, GPT 4.1, Vertex AI, Google AI Studio, agent to agent protocol, Google Workspace, Google Sheets, MCP protocol, Google DeepMind, GDC, Ironwood TPU chip, Lyria AI model, AI video model, AI music generation, Elon Musk's Dodge team, government AI monitoring, Ethical AI use, Canva Sheets, Shopify CEO AI memo, Anthropic, Claude Max, Microsoft Copilot, AI infrastructure, Recall AI feature, data privacy concerns, AI-powered productivity, GPT models, AI operating systems, personalized AI, GMPT 4.5, AI sandbox, Nvidia hardware, test time computing, AI reasoning, ChatGPT preferences.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner

Dozens of AI updates.

The Nasdaq soared 12% to its best day since 2001, a Facebook whistleblower said the company collaborated with China to undermine U.S. security, and Google DeepMind will add support for Anthropic’s Model Context Protocol. MP3 Please SUBSCRIBE HERE for free or get DTNS Live ad-free. A special thanks to all our supporters–without you, none ofContinue reading "The Nasdaq Soared 12% To Its Best Day Since 2001 – DTH"

In this episode, Nathan Labenz speaks with Vivek Natarajan and Anil Palepu from Google DeepMind about their groundbreaking work on AMIE (Articulate Medical Intelligence Explorer) and Co-Scientist. The conversation reveals how these AI systems are already outperforming human physicians in diagnostic accuracy and treatment recommendations, with AMIE now entering clinical trials at a Harvard Medical School teaching hospital. Even more remarkably, the Co-Scientist system demonstrates genuine scientific discovery capabilities, independently proposing the exact same mechanism for bacterial drug resistance that human scientists had recently discovered but not yet published—signaling a threshold moment where AI is becoming a legitimate thought partner in humanity's most complex intellectual endeavors. SPONSORS: Oracle Cloud Infrastructure (OCI): Oracle Cloud Infrastructure offers next-generation cloud solutions that cut costs and boost performance. With OCI, you can run AI projects and applications faster and more securely for less. New U.S. customers can save 50% on compute, 70% on storage, and 80% on networking by switching to OCI before May 31, 2024. See if you qualify at https://oracle.com/cognitive Shopify: Shopify powers millions of businesses worldwide, handling 10% of U.S. e-commerce. With hundreds of templates, AI tools for product descriptions, and seamless marketing campaign creation, it's like having a design studio and marketing team in one. Start your $1/month trial today at https://shopify.com/cognitive NetSuite: Over 41,000 businesses trust NetSuite by Oracle, the #1 cloud ERP, to future-proof their operations. With a unified platform for accounting, financial management, inventory, and HR, NetSuite provides real-time insights and forecasting to help you make quick, informed decisions. Whether you're earning millions or hundreds of millions, NetSuite empowers you to tackle challenges and seize opportunities. Download the free CFO's guide to AI and machine learning at https://netsuite.com/cognitive PRODUCED BY: https://aipodcast.ing CHAPTERS: (00:00) About the Episode (06:26) Introduction and Welcome (07:49) AMY Medical Intelligence Overview (11:29) Chat-Based Medical Interactions (13:59) Specialized Medicine Results (18:17) Co-Scientist System Headlines (Part 1) (18:21) Sponsors: Oracle Cloud Infrastructure (OCI) | Shopify (21:36) Co-Scientist System Headlines (Part 2) (26:32) Bacterial Drug Resistance Discovery (31:41) AI Scientific Discovery Process (35:35) Hallucinations vs. Creativity (Part 1) (35:37) Sponsors: NetSuite (37:10) Hallucinations vs. Creativity (Part 2) (42:04) Agent Design Architecture (49:17) Long Context Benefits (55:35) Computational Requirements (01:01:10) Specialist Models Integration (01:07:01) Future Model Integration (01:12:31) Tournament Evaluation Methods (01:19:09) AI Question Generation (01:22:42) Real-World Deployment Plans (01:25:58) Outro

We gotta talk about this

Chi Wang is co-creator of AG2, and a Senior Staff Research Scientist, Google DeepMind.  This episode explores AG2, an open-source “agent OS” that provides infrastructure for developers to build sophisticated multi-agent AI systems.Subscribe to the Gradient Flow Newsletter