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No Priors: Artificial Intelligence | Technology | Startups

Podcast No Priors: Artificial Intelligence | Technology | Startups
Conviction
At this moment of inflection in technology, co-hosts Elad Gil and Sarah Guo talk to the world's leading AI engineers, researchers and founders about the biggest...
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  • Model Plateaus and Enterprise AI Adoption with Cohere's Aidan Gomez
    In this episode of No Priors, Sarah is joined by Aidan Gomez, cofounder and CEO of Cohere. Aidan reflects on his journey to co-authoring the groundbreaking 2017 paper, “Attention is All You Need,” during his internship, and shares his motivations for building Cohere, which delivers AI-powered language models and solutions for businesses. The discussion explores the current state of enterprise AI adoption and Aidan’s advice for companies navigating the build vs. buy decision for AI tools. They also examine the drivers behind the flattening of model improvements and discuss where large language models (LLMs) fall short for predictive tasks. The conversation explores what the market has yet to account for in the rapidly evolving AI ecosystem, as well as Aidan’s personal perspectives on AGI—what it might look like and when it could arrive. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @AidanGomez Show Notes: 0:00 Introduction 0:36 Co-authoring “Attention is all you need” 2:27 Leaving Google and founding Cohere 4:04 Cohere’s mission and models 6:15 Pitfalls of current AI  8:14 How enterprises are deploying AI today 10:58 Build vs. buy strategy for AI tools 14:37 Barriers to enterprise adoption  20:04 Which types of companies should pretrain models? 24:25 Addressing flaws in open-source models 25:12 Current and expected progress in scaling laws 29:54 Advances in multi-step problem solving and reasoning 32:29  Key drivers behind the flattening curve of model improvements  36:25 Exploring AGI 39:59 Limitations of LLMs 42:10 What the market has mispriced
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  • AI and the Future of Math, with DeepMind’s AlphaProof Team
    In this week’s episode of No Priors, Sarah and Elad sit down with the Google DeepMind team behind AlphaProof, Laurent Sartran, Rishi Mehta, and Thomas Hubert. AlphaProof is a new reinforcement learning-based system for formal math reasoning that recently reached a silver-medal standard in solving International Mathematical Olympiad problems. They dive deep into AI and its role in solving complex mathematical problems, featuring insights into AlphaProof and its capabilities. They cover its functionality, unique strengths in reasoning, and the challenges it faces as it scales. The conversation also explores the motivations behind AI in math, practical applications, and how verifiability and human input come into play within a reinforcement learning approach. The DeepMind team shares advice and future perspectives on where math and AI are headed.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Rishicomplex | @LaurentSartran | @ThomasHubert Show Notes:  0:00 Personal introductions 2:19 Achieving silver medal in IMO competition 3:52 How AlphaProof works 5:56 AlphaProof’s strengths within mathematical reasoning 8:56 Challenges in scaling AlphaProof 13:40 Why solve math? 17:50 Pursuing knowledge versus practical applications 21:30 Insights on verifying correctness within reinforcement learning 28:27 How AI could foster more collaboration among mathematicians 30:28 Surprising insights from AI proof generation 34:17 Future of math and AI: advice for math enthusiasts and researchers
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  • NVIDIA's Jensen Huang on AI Chip Design, Scaling Data Centers, and his 10-Year Bets
    In this week’s episode of No Priors, Sarah and Elad sit down with Jensen Huang, CEO of NVIDIA, for the second time to reflect on the company’s extraordinary growth over the past year. Jensen discusses AI’s takeover of datacenters and NVIDIA’s rapid development of x.AI’s supercluster. The conversation also covers Nvidia’s decade-long infrastructure bets, software longevity, and innovations like NVLink. Jensen shares his views on the future of embodied AI, digital employees, and how AI is transforming scientific discovery. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Nvidia Show Notes:  00:00 Introduction 1:22 NVIDIA's 10-year bets 2:28 Outpacing Moore’s Law 3:42 Data centers and NVLink 7:16 Infrastructure flexibility for large-scale training and inference  10:40 Building and optimizing data centers  13:30 Maintaining software and architecture compatibility  15:00 X.AI’s supercluster  18:55 Challenges of super scaling data centers 20:39 AI’s role in chip design  22:23 NVIDIA's market cap surge and company evolution  27:03 Embodied AI 28:33 AI employees 31:25 Impact of AI on science and engineering  35:40 Jensen’s personal use of AI tools
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  • Forecasting the Future with Kalshi: America’s First Regulated Prediction Market
    In this week’s episode of No Priors, Sarah sits down with Tarek Mansour, CEO of Kalshi—the first CFTC-regulated prediction market exchange in the U.S. They dive into Kalshi’s recent victory to legalize election betting, explore ethical questions around trading on elections, and discuss whether prediction markets can offer more accuracy than traditional polls. Tarek shares insights on the history of futures markets, the line between gambling and financial trading, and the psychology behind betting. Plus, Sarah makes a live election bet, and Tarek reveals some of Kalshi’s most intriguing markets. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @MansourTarek Show Notes:  0:00 Introduction 1:22 Sarah makes a live election bet on Kalshi 3:35 Getting approved and regulated by CFTC 5:48 Going up against the CFTC to legalize election betting 7:21 Debating the ethics of trading on elections 8:12 Gambling vs. trading  9:12 Context and purpose of futures markets 12:38 The human psychology behind speculating /Humans conditioned to risk taking 17:17 Building a healthy exchange and scaling liquidity  19:30 Introducing leverage and working with clearinghouses 22:29 Polls vs. prediction markets 24:59 Conditional markets 26:38 What makes Kalshi’s markets accurate 31:29 Tarek’s insights on the most interesting trades and markets on the platform
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  • Waymo’s Journey to Full Autonomy: AI Breakthroughs, Safety, and Scaling
    In this episode of No Priors, Dmitri Dolgov, Co-CEO of Waymo, joins Sarah and Elad to explore the evolution and advancements of Waymo's self-driving technology from its inception at Google to its current real-world deployment. Dmitri also shares insights into the technological breakthroughs and complexities of achieving full autonomy, the design innovations of Waymo’s sixth generation driverless cars, and the broader applications of Waymo’s advanced technology. They also discuss Waymo's strategic approach to scaling amidst regulation, deployment in cities like Phoenix and San Francisco, and the transformative potential of autonomous driving on car ownership and urban infrastructure. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Dmitri_Dolgov Shownotes: 00:00 Introduction 00:15 History of Self-Driving at Google  00:29 DARPA Challenges and Early Involvement  01:39 Formation of Waymo  01:53 Industry Lineage and Early Skepticism  03:05 Initial Goals and Milestones  4:33 Pivot to Full Autonomy  04:50 Scaling and Deployment  05:29 Generational Breakthroughs  06:59 Choosing Deployment Cities  09:26 Technological Advancements  11:01 Evaluating Safety  14:41 Regulatory Stance and Trust  16:52 Future of Autonomous Driving  23:19 Business Strategy and Partnerships  26:06 Changing Urban Mobility Trends  26:40 Challenges and Misconceptions in Self-Driving Timelines  28:43 The Role of Traditional OEMs in an Autonomous Future  30:54 Designing Cars for Autonomous Ride-Hailing  33:42 Scaling Responsibly  35:18 Generalizability and Future Applications of AI  37:10 The Complexity of Achieving Full Autonomy  42:58 The Importance of Data and Iteration in AI Development  46:13 Reflecting on the Journey and Future of Waymo
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