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

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

In this episode of No Priors, Sarah and Elad explore how AI is transforming consumer apps and entertainment, with a focus on potential integrations in gaming and dating that could shift traditional societal incentives. They reflect on AI researchers winning Nobel Prizes in Science and Chemistry for the first time, discussing what this trend means for scientific discovery. The episode also covers recent AI releases, including their thoughts on OpenAI?s O1 model and Google?s NotebookLM, and examines which companies and job functions are most at risk?or resilient?in the face of AI advancements. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Show Notes:  (0:00) Introduction (0:47) Google releases NotebookLM  (5:20) Integrating AI into consumer apps and gaming (9:11) Future of AI companionship and procreation (14:45) OpenAI o1 model improves on iterative reasoning (18:06) Sarah and Elad reflect on Nobel Prizes going to AI researchers (21:23) Jobs and businesses at risk of disruption (27:18) AI-durable companies

Today on No Priors, Elad is joined by Ankur Goyal, founder and CEO of Braintrust. Braintrust enables companies like Notion, Airtable, Instacart, Zapier, and Vercel to deploy AI solutions at scale by efficiently evaluating and managing complex, non-deterministic AI applications. Ankur shares his insights into emerging trends in the use of AI tooling and coding languages, the rise of open-source, and the future of data infrastructure. Ankur also reflects on building resilient AI products, his philosophy on coding as a CEO, and the importance of a startup?s initial customer base.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Ankrgyl Show Notes:  (0:00) Introduction (0:38) Ankur?s path to Braintrust (3:05) Braintrust?s solution (5:46) AI tooling trends  (7:58) Instruction tuning vs. fine-tuning (8:57) Open-source AI adoption  (10:42) Future of data infrastructure and synthetic data (14:45) Designing technical interviews (18:04) Rethinking agent-based approaches (19:34) Building out an AI team (23:35) Typescript as the language of AI (25:12) The shift away from using frameworks (26:02) Vendor consolidation among enterprises  (27:16) Coding as a CEO  (30:16) Collaborating with customers (33:00) Future of Braintrust and evals

Lina Khan?s FTC has been the most active in decades, notably challenging tech giants and adopting a more hands-on approach to regulating the digital age. On today?s episode of No Priors, Lina Khan joins Elad and Sarah to discuss her regulatory philosophy for tech markets and what the industry can expect for future M&A deals. She shares her approach to overseeing emerging technology sectors, including AI at the model layer, and her work to ban non-competes on a federal level. Khan also offers insights into the realities of leading a government agency, the scarcity of young leaders in power, and how she measures the FTC?s impact. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @LinaKhanFTC Show Notes:  (0:00) Introduction (0:56) Lina Khan?s background and path to the FTC (2:35) Amazon?s Antitrust Paradox (4:20) Frameworks for regulating M&A in young markets (8:50) Khan?s perspective on AI acquisitions (12:18) What founders can expect from Khan?s M&A environment  (14:55) Promoting competition at the large model layer (17:01) Creating fair AI regulation (18:40) FTC?s work to ban non-competes (20:31) Why so few young people hold power in government today (22:18) The realities of running a government agency (24:20) Measuring the impact of FTC

In this episode of No Priors, Sarah and Elad sit down with Matt MacInnis, COO of Rippling, to discuss the company?s unique product strategy and the advantages of being a compound startup. Matt introduces Talent Signal, Rippling?s AI-powered employee performance tool, and explains how early adopters are using it to gain a competitive edge. They explore Rippling?s approach to choosing which AI products to build and how they plan to leverage their rich data sources. The conversation also delves into how AI shapes real-world decision-making and how to realistically integrate these tools into organizational workflows. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Stanine Show Notes:  0:00 Introduction 0:32 Rippling?s mission and product offerings 2:13 Compound startups 3:53 Evaluating human performance with Talent Signal  13:19 Incorporating AI evaluations into decision-making at Rippling 14:56 Leveraging work outputs as inputs for models 18:23 How Rippling chose which AI product to build first 20:53 Building out bundled products 23:26 Merging and scaling diverse data sources 25:16 Early adopters and integrating AI into decision-making processes

Bret Taylor, Cofounder of Sierra, Chairman of the board at OpenAI, and former co-CEO of Salesforce and CTO of Facebook, joins Sarah and Elad in this week?s episode of No Priors. Bret discusses building company-branded AI agents with unique personalities, goals, and guardrails at Sierra, and their potential to revolutionize customer engagement while cutting costs. The conversation explores the next sectors for enterprise AI adoption, building resilient AI products, and the parallels between today?s AI market and the evolution of the cloud industry. Bret also shares his unique insights on future business models and upcoming technology shifts. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Btaylor Show Notes: (0:00) Intro (0:42) Defining agentic systems and types of agents (3:55) Customer-facing company agents (5:43) Sierra AI (8:11) Transforming customer service and reducing costs (9:57) Challenges in implementing LLMs for company agents (14:45) Drawing parallels between AI and the cloud market?s evolution (17:50) Future of the AI landscape (19:15) Building durable AI products (24:39) Outcome-based business models and tangible ROI in AI solutions (29:22) Next wave of AI sectors for enterprise adoption (31:15) Customizing goals and guardrails with customers (35:55) Creating distinct personalities for Sierra's agents (41:05) Bret?s insights on upcoming technology and hardware shifts (46:50) How AI software could enhance human agency

In this episode of No Priors, Sarah and Elad go deep into what's on everyone?s mind. They break down new partnerships and consolidation in the LLM market, specialization of AI models, and AMD?s strategic moves. Plus, Elad is looking for a humanoid robot.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Show Notes: (0:00) Introduction (0:24) LLM market consolidation  (2:18) Competition and decreasing API costs (3:58) Innovation in LLM productization  (8:20) Comparing  the LLM and social network market (11:40) Increasing competition in image generation (13:21) Trend in smaller models with higher performance (14:43) Areas of innovation (17:33) Legacy of AirBnB and Uber pushing boundaries (24:19) AMD Acquires ZT  (25:49) Elad?s looking for a Robot

Andrej Karpathy joins Sarah and Elad in this week of No Priors. Andrej, who was a founding team member of OpenAI and former Senior Director of AI at Tesla, needs no introduction. In this episode, Andrej discusses the evolution of self-driving cars, comparing Tesla and Waymo?s approaches, and the technical challenges ahead. They also cover Tesla?s Optimus humanoid robot, the bottlenecks of AI development today, and  how AI capabilities could be further integrated with human cognition.  Andrej shares more about his new company Eureka Labs and his insights into AI-driven education, peer networks, and what young people should study to prepare for the reality ahead. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Karpathy Show Notes:  (0:00) Introduction (0:33) Evolution of self-driving cars (2:23) The Tesla  vs. Waymo approach to self-driving  (6:32) Training Optimus  with automotive models (10:26) Reasoning behind the humanoid form factor (13:22) Existing challenges in robotics (16:12) Bottlenecks of AI progress  (20:27) Parallels between human cognition and AI models (22:12) Merging human cognition with AI capabilities (27:10) Building high performance small models (30:33) Andrej?s current work in AI-enabled education (36:17) How AI-driven education reshapes knowledge networks and status (41:26) Eureka Labs (42:25) What young people study to prepare for the future

Today on No Priors, Sarah Guo and Elad Gil are joined by Eric Steinberger, the co-founder and CEO of Magic.dev. His team is developing a software engineer co-pilot that will act more like a colleague than a tool. They discussed what makes Magic stand out from the crowd of AI co-pilots, the evaluation bar for a truly great AI assistant, and their predictions on what a post-AGI world could look like if the transition is managed with care.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @EricSteinb Show Notes:  (0:00) Introduction (0:45) Eric?s journey to founding Magic.dev (4:01) Long context windows for more accurate outcomes (10:53) Building a path toward AGI (15:18) Defining what is enough compute for AGI (17:34) Achieving Magic?s final UX (20:03) What makes a good AI assistant (22:09) Hiring at Magic (27:10) Impact of AGI (32:44) Eric?s north star for Magic (36:09) How Magic will interact in other tools

In this episode of No Priors, hosts Sarah and Elad are joined by Matt Garman, the CEO of Amazon Web Services. They talk about the evolution of Amazon Web Services (AWS) from its inception to its current position as a major player in cloud computing and AI infrastructure. In this episode they touch on AI commuting hardware,  partnerships with AI startups, and the challenges of scaling for AI workloads. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Show Notes:  (00:00) Introduction  (00:23) Matt?s early days at Amazon (02:53) Early conception of AWS (06:36) Understanding the full opportunity of cloud compute (12:21) Blockers to cloud migration (14:19) AWS reaction to Gen AI (18:04) First-party models at hyperscalers (20:18) AWS point of view on open source (22:46) Grounding and knowledge bases (26:07) Semiconductors and data center capacity for AI workloads (31:15) Infrastructure investment for AI startups (33:18) Value creation in the AI ecosystem (36:22) Enterprise adoption  (38:48) Near-future predictions for AWS usage (41:25) AWS?s role for startups

In this episode of No Priors, hosts Sarah and Elad are joined by Jared Quincy Davis, former DeepMind researcher and the Founder and CEO of Foundry, a new AI cloud computing service provider. They discuss the research problems that led him to starting Foundry, the current state of GPU cloud utilization, and Foundry's approach to improving cloud economics for AI workloads. Jared also touches on his predictions for the GPU market and the thinking behind his recent paper on designing compound AI systems. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @jaredq_ Show Notes:  (00:00) Introduction  (02:42) Foundry background (03:57) GPU utilization for large models (07:29) Systems to run a large model (09:54) Historical value proposition of the cloud (14:45) Sharing cloud compute to increase efficiency  (19:17) Foundry?s new releases (23:54) The current state of GPU capacity (29:50) GPU market dynamics (36:28) Compound systems design (40:27) Improving open-ended tasks

In this episode of No Priors, hosts Sarah and Elad are joined by Ramp co-founders Eric Glyman and Karim Atiyeh of Ramp. The pair has been working to build one of the fastest growing fintechs since they were teenagers. This conversation focuses on how Ramp engineers have been building new systems to help every team from sales and marketing to product. They?re building best-in-class SaaS solutions just for internal use to make sure their company remains competitive. They also get into how AI will augment marketing and creative fields, the challenges of selling productivity, and how they?re using LLMs to create internal podcasts using sales calls to share what customers are saying with the whole team.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @eglyman l @karimatiyeh Show Notes:  (0:00) Introduction to Ramp (3:17) Working with startups (8:13) Ramp?s implementation of AI (14:10) Resourcing and staffing (17:20) Deciding when to build vs buy (21:20) Selling productivity (25:01) Risk mitigation when using AI (28:48) What the AI stack is missing (30:50) Marketing with AI (37:26) Designing a modern marketing team (40:00) Giving creative freedom to marketing teams (42:12) Augmenting bookkeeping (47:00) AI-generated podcasts 

Hunting down receipts and manually filling out invoices kills productivity. This week on No Priors, Sarah Guo and Elad Gil sit down with Pedro Franceschi, co-founder and CEO of Brex. Pedro discusses how Brex is harnessing AI to optimize spend management and automate tedious accounting and compliance tasks for teams. The conversation covers the reliability challenges in AI today, Pedro?s insights on the future of fintech in an AI-driven world, and the major transitions Brex has navigated in recent years. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Pedroh96 Show Notes:  (0:00) Introduction (0:32) Brex?s business and transitioning to solo CEO (3:04) Building AI into Brex  (7:09) Solving for risk and reliability in AI-enabled financial products (11:41) Allocating resources toward AI investment (14:00) Innovating data use in marketing  (20:00) Building durable businesses in the face of AI (25:36) AI?s impact on finance (29:15) Brex?s decision to focus on startups and enterprises

In this episode of No Priors, hosts Sarah and Elad are joined by Oriol Vinyals, VP of Research, Deep Learning Team Lead, at Google DeepMind and Technical Co-lead of the Gemini project. Oriol shares insights from his career in machine learning, including leading the AlphaStar team and building competitive StarCraft agents. We talk about Google DeepMind, forming the Gemini project, and integrating AI technology throughout Google products. Oriol also discusses the advancements and challenges in long context LLMs, reasoning capabilities of models, and the future direction of AI research and applications. The episode concludes with a reflection on AGI timelines, the importance of specialized research, and advice for future generations in navigating the evolving landscape of AI. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @oriolvinyalsml Show Notes:  (00:00) Introduction to Oriol Vinyals (00:55) The Gemini Project and Its Impact (02:04) AI in Google Search and Chat Models (08:29) Infinite Context Length and Its Applications (14:42) Scaling AI and Reward Functions (31:55) The Future of General Models and Specialization (38:14) Reflections on AGI and Personal Insights (43:09) Will the Next Generation Study Computer Science? (45:37) Closing thoughts

This week on No Priors, Sarah Guo and Elad Gil are joined by Howie Liu, the co-founder and CEO of Airtable. Howie discusses their Cobuilder launch, the evolution of Airtable from a simple productivity tool to an enterprise app platform with integrated AI capabilities. They talk about why the conventional wisdom of ?app not platform? can be wrong,  why there?s a future for low-code in the age of AI and code generation, and where enterprises need help adopting AI. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Howietl Show Notes:  (00:00) Introduction (00:29) The Origin and Evolution of Airtable (02:31) Challenges and Successes in Building Airtable (06:09) Airtable's Transition to Enterprise Solutions (09:44) Insights on Product Management (16:23) Integrating AI into Airtable (21:55) The Future of No Code and AI (30:30) Workshops and Training for AI Adoption (36:28) The Role of Code Generation in No Code Platforms

This week on No Priors, we have a host-only episode. Sarah and Elad catch up to discuss how tech history may be repeating itself. Much like in the early days of the internet, every company is clamoring to incorporate AI into their products or operations while some legacy players are skeptical that investment in AI will pay off. They also get into new opportunities and capabilities that AI is opening up, whether or not incubators are actually effective, and what companies are poised to stand the test of time in the changing tech landscape. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil Show Notes:  (0:00) Introduction (0:16) Old school operators AI misunderstandings (5:10) Tech history is repeating itself with slow AI adoption (6:09) New AI Markets (8:48) AI-backed buyouts (13:03) AI incubation (17:18) Exciting incubating applications (18:26) AI and the public markets (22:20) Staffing AI companies  (25:14) Competition and shrinking head count

Believe or not, we?re almost halfway through 2024. Sarah and Elad have spent the first of this year talking with some of the most innovative minds in the AI industry, so we?re taking a look at some of our favorite No Priors conversations so far featuring Dylan Field (Figma); Emily Glassberg-Sands (Stripe); Brett Adcock (Figure AI); Aditya Ramesh, Tim Brooks and Bill Peebles (OpenAI?s Sora Team); Scott Wu (Cognition); and Alexandr Wang (Scale). Watch or listen to the full episodes here: Build AI products at on-AI companies with Emily Glassberg Sands from Stripe Designing the Future: Dylan Field on AI, Collaboration, and Independence The argument for humanoid robots with Brett Adcock from Figure OpenAI?s Sora team thinks we?ve only seen the "GPT-1 of video models" Cognition?s Scott Wu on how Devin, the AI software engineer, will work for you The Data Foundry for AI with Alexandr Wang from Scale Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Show Notes:  (0:00) Introduction (0:46) Emily Glassberg Sands on the Future of AI and Fintech (4:23 Dylan Field on AI and Human Creative Potential (9:03) Brett Adcock on Running Figure AI?s Hardware and Software Processes (12:43) OpenAI?s Sora Team on Artists? Creative Experiences with their Model (17:43) Scott Wu Gives Advice for Human Engineers Co-Working with AI (21:06) Alexandr Wang on How Quality Data Builds Confidence in AI Systems

This week on No Priors, Sarah Guo and Elad Gil sit down with Karan Goel and Albert Gu from Cartesia. Karan and Albert first met as Stanford AI Lab PhDs, where their lab invented Space Models or SSMs, a fundamental new primitive for training large-scale foundation models. In 2023, they Founded Cartesia to build real-time intelligence for every device. One year later, Cartesia released Sonic which generates high quality and lifelike speech with a model latency of 135ms?the fastest for a model of this class. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @krandiash | @_albertgu Show Notes:  (0:00) Introduction (0:28) Use Cases for Cartesia and Sonic  (1:32) Karan Goel & Albert Gu?s professional backgrounds (5:06) State Space Models (SSMs) versus Transformer Based Architectures  (11:51) Domain Applications for Hybrid Approaches  (13:10) Text to Speech and Voice (17:29) Data, Size of Models and Efficiency  (20:34) Recent Launch of Text to Speech Product (25:01) Multimodality & Building Blocks (25:54) What?s Next at Cartesia?  (28:28) Latency in Text to Speech (29:30) Choosing Research Problems Based on Aesthetic  (31:23) Product Demo (32:48) Cartesia Team & Hiring

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

The first step in achieving AGI is nailing down a concise definition and Mike Knoop, the co-founder and Head of AI at Zapier, believes François Chollet got it right when he defined general intelligence as a system that can efficiently acquire new skills. This week on No Priors, Miked joins Elad to discuss ARC Prize which is a multi-million dollar non-profit public challenge that is looking for someone to beat the Abstraction and Reasoning Corpus (ARC) evaluation. In this episode, they also get into why Mike thinks LLMs will not get us to AGI, how Zapier is incorporating AI into their products and the power of agents, and why it?s dangerous to regulate AGI before discovering its full potential.  Show Links: About the Abstraction and Reasoning Corpus Zapier Central ARC Prize Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @mikeknoop Show Notes:  (0:00) Introduction (1:10) Redefining AGI (2:16) Introducing ARC Prize (3:08) Definition of AGI (5:14) LLMs and AGI (8:20) Promising techniques to developing AGI (11:0) Sentience and intelligence (13:51) Prize model vs investing (16:28) Zapier AI innovations (19:08) Economic value of agents (21:48) Open source to achieve AGI (24:20) Regulating AI and AGI

After Tengyu Ma spent years at Stanford researching AI optimization, embedding models, and transformers, he took a break from academia to start Voyage AI which allows enterprise customers to have the most accurate retrieval possible through the most useful foundational data. Tengyu joins Sarah on this week?s episode of No priors to discuss why RAG systems are winning as the dominant architecture in enterprise and the evolution of foundational data that has allowed RAG to flourish. And while fine-tuning is still in the conversation, Tengyu argues that RAG will continue to evolve as the cheapest, quickest, and most accurate system for data retrieval.  They also discuss methods for growing context windows and managing latency budgets, how Tengyu?s research has informed his work at Voyage, and the role academia should play as AI grows as an industry.  Show Links: Voyage AI Stanford Assistant Professor of Computer Science Tengyu Ma Key Research Papers: Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training Non-convex optimization for machine learning: design, analysis, and understanding Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss Larger language models do in-context learning differently, 2023 Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning On the Optimization Landscape of Tensor Decompositions Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @tengyuma Show Notes:  (0:00) Introduction (1:59) Key points of Tengyu?s research (4:28) Academia compared to industry (6:46) Voyage AI overview (9:44) Enterprise RAG use cases (15:23) LLM long-term memory and token limitations (18:03) Agent chaining and data management (22:01) Improving enterprise RAG  (25:44) Latency budgets (27:48) Advice for building RAG systems (31:06) Learnings as an AI founder (32:55) The role of academia in AI

Garry Tan is a notorious founder-turned-investor who is now running one of the most prestigious accelerators in the world, Y Combinator. As the president and CEO of YC, Garry has been credited with reinvigorating the program. On this week?s episode of No Priors, Sarah, Elad, and Garry discuss the shifting demographics of YC founders and how AI is encouraging younger founders to launch companies, predicting which early stage startups will have longevity, and making YC a beacon for innovation in AI companies. They also discussed the importance of building companies in person and if San Francisco is, in fact, back.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @garrytan Show Notes:  (0:00) Introduction (0:53) Transitioning from founder to investing (5:10) Early social media startups (7:50) Trend predicting at YC (10:03) Selecting YC founders (12:06) AI trends emerging in YC batch (18:34) Motivating culture at YC (20:39) Choosing the startups with longevity (24:01) Shifting YC found demographics (29:24) Building in San Francisco  (31:01) Making YC a beacon for creators (33:17) Garry Tan is bringing San Francisco back

Alexandr Wang was 19 when he realized that gathering data will be crucial as AI becomes more prevalent, so he dropped out of MIT and started Scale AI. This week on No Priors, Alexandr joins Sarah and Elad to discuss how Scale is providing infrastructure and building a robust data foundry that is crucial to the future of AI. While the company started working with autonomous vehicles, they?ve expanded by partnering with research labs and even the U.S. government.   In this episode, they get into the importance of data quality in building trust in AI systems and a possible future where we can build better self-improvement loops, AI in the enterprise, and where human and AI intelligence will work together to produce better outcomes.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @alexandr_wang (0:00) Introduction (3:01) Data infrastructure for autonomous vehicles (5:51) Data abundance and organization (12:06)  Data quality and collection (15:34) The role of human expertise (20:18) Building trust in AI systems (23:28) Evaluating AI models (29:59) AI and government contracts (32:21) Multi-modality and scaling challenges

Mikey Shulman, the CEO and co-founder of Suno, can see a future where the Venn diagram of music creators and consumers becomes one big circle. The AI music generation tool trying to democratize music has been making waves in the AI community ever since they came out of stealth mode last year. Suno users can make a song complete with lyrics, just by entering a text prompt, for example, ?koto boom bap lofi intricate beats.? You can hear it in action as Mikey, Sarah, and Elad create a song live in this episode.  In this episode, Elad, Sarah, And Mikey talk about how the Suno team took their experience making at transcription tool and applied it to music generation, how the Suno team evaluates aesthetics and taste because there is no standardized test you can give an AI model for music, and why Mikey doesn?t think AI-generated music will affect people?s consumption of human made music.  Listen to the full songs played and created in this episode: Whispers of Sakura Stone  Statistical Paradise Statistical Paradise 2 Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @MikeyShulman Show Notes:  (0:00) Mikey?s background (3:48) Bark and music generation (5:33) Architecture for music generation AI (6:57) Assessing music quality (8:20) Mikey?s music background as an asset (10:02) Challenges in generative music AI (11:30) Business model (14:38) Surprising use cases of Suno (18:43) Creating a song on Suno live (21:44) Ratio of creators to consumers (25:00) The digitization of music (27:20) Mikey?s favorite song on Suno (29:35) Suno is hiring

This week on No Priors hosts, Sarah and Elad are catching up on the latest AI news. They discuss the recent developments in AI like Meta?s new AI assistant and the latest in music generation, and if you?re interested in generative AI music, stay tuned for next week?s interview! Sarah and Elad also get into device-resident models, AI hardware, and ask just how smart smaller models can really get. These hardware constraints were compared to the hurdles AI platforms are continuing to face including computing constraints, energy consumption, context windows, and how to best integrate these products in apps that users are familiar with. Have a question for our next host-only episode or feedback for our team? Reach out to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Show Notes:  (0:00) Intro (1:25) Music AI generation (4:02) Apple?s LLM (11:39) The role of AI-specific hardware (15:25) AI platform updates (18:01) Forward thinking in investing in AI (20:33) Unlimited context (23:03) Energy constraints

Scott Wu loves code. He grew up competing in the International Olympiad in Informatics (IOI) and is a world class coder, and now he's building an AI agent designed to create more, not fewer, human engineers. This week on No Priors, Sarah and Elad talk to Scott, the co-founder and CEO of Cognition, an AI lab focusing on reasoning. Recently, the Cognition team released a demo of Devin, an AI software engineer that can increasingly handle entire tasks end to end. In this episode, they talk about why the team built Devin with a UI that mimics looking over another engineer?s shoulder as they work and how this transparency makes for a better result. Scott discusses why he thinks Devin will make it possible for there to be more human engineers in the world, and what will be important for software engineers to focus on as these roles evolve. They also get into how Scott thinks about building the Cognition team and that they?re just getting started.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ScottWu46 Show Notes:  (0:00) Introduction (1:12) IOI training and community (6:39) Cognition?s founding team (8:20) Meet Devin (9:17) The discourse around Devin (12:14) Building Devin?s UI (14:28) Devin?s strengths and weakness  (18:44) The evolution of coding agents (22:43) Tips for human engineers (26:48) Hiring at Cognition

AI-generated videos are not just leveled-up image generators. But rather, they could be a big step forward on the path to AGI. This week on No Priors, the team from Sora is here to discuss OpenAI?s recently announced generative video model, which can take a text prompt and create realistic, visually coherent, high-definition clips that are up to a minute long. Sora team leads, Aditya Ramesh, Tim Brooks, and Bill Peebles join Elad and Sarah to talk about developing Sora. The generative video model isn?t yet available for public use but the examples of its work are very impressive. However, they believe we?re still in the GPT-1 era of AI video models and are focused on a slow rollout to ensure the model is in the best place possible to offer value to the user and more importantly they?ve applied all the safety measures possible to avoid deep fakes and misinformation. They also discuss what they?re learning from implementing diffusion transformers, why they believe video generation is taking us one step closer to AGI, and why entertainment may not be the main use case for this tool in the future.  Show Links: Bling Zoo video Man eating a burger video Tokyo Walk video Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @_tim_brooks l @billpeeb l @model_mechanic Show Notes:  (0:00) Sora team Introduction (1:05) Simulating the world with Sora (2:25) Building the most valuable consumer product (5:50) Alternative use cases and simulation capabilities (8:41) Diffusion transformers explanation (10:15) Scaling laws for video (13:08) Applying end-to-end deep learning to video (15:30) Tuning the visual aesthetic of Sora (17:08) The road to ?desktop Pixar? for everyone (20:12) Safety for visual models (22:34) Limitations of Sora (25:04) Learning from how Sora is learning (29:32) The biggest misconceptions about video models

Multimodal models are making it possible to create AI art and augment creativity across artistic mediums. This week on No Priors, Sarah and Elad talk with Suhail Doshi, the founder of Playground AI, an image generator and editor. Playground AI has been open-sourcing foundation diffusion models, most recently releasing Playground V2.5.  In this episode, Suhail talks with Sarah and Elad about how the integration of language and vision models enhances the multimodal capabilities, how the Playground team thought about creating a user-friendly interface to make AI-generated content more accessible, and the future of AI-powered image generation and editing. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Suhail Show Notes:  (0:00) Introduction (0:52) Focusing on image generation (3:01) Differentiating from other AI creative tools (5:58) Training a Stable Diffusion model (8:31) Long term vision for Playground AI (15:00) Evolution of AI architecture (17:21) Capabilities of multimodal models (22:30) Parallels between audio AI tools and image-generation

This week on a host-only episode of No Priors, Sarah and Elad discuss the AI wave as compared to the internet wave, the current state of AI investing, the foundation model landscape, voice and video AI, advances in agentic systems, prosumer applications, and the Microsoft/Inflection deal. Have a question for our next host-only episode or feedback for our team? Reach out to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Show Notes:  (0:00) Intro (0:32) How to think about scaling in 2024 (3:21) Microsoft/Inflection deal (5:28) Voice cloning (7:02) Investing climate (12:50) Whitespace in AI (16:36) AI video landscape (19:54) Agentic user experiences (22:21) Prosumer as the first wave of application AI

Humans are always doing work that is dull or dangerous. Brett Adcock, the founder and CEO of Figure AI, wants to build a fleet of robots that can do everything from work in a factory or warehouse to folding your laundry in the home. Today on No Priors, Sarah got the chance to talk with Brett about how a company that is only 21 months old has already built humanoid robots that not only walk the walk by performing tasks like item retrieval and making a cup of coffee but they also talk the talk through speech to speech reasoning.  In this episode, Brett and Sarah discuss why right now is the correct time to build a fleet of AI robots and how implementation in industrial settings will be a stepping stone into AI robots coming into the home. They also get into how Brett built a team of world class engineers, commercial partnerships with BMW and OpenAI that are accelerating their growth, and the plan to achieve social acceptance for AI robots.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @adcock_brett Show Notes:  (0:00) Brett?s background (3:09) Figure AI Thesis (5:51) The argument for humanoid robots (7:36) Figure AI public demos (12:38) Mitigating risk factors (15:20) Designing the org chart and finding the team (16:38) Deployment timeline (20:41) Build vs buy and vertical integration (23:04) Product management at Figure (28:37) Corporate partnerships (31:58) Humans at home (33:38) Social acceptance  (35:41) AGI vs the robots

Companies are employing AI agents and co-pilots to help their teams increase efficiency and accuracy, but developing apps that are trained properly can require a skill set many enterprise teams don?t have. This week on No Priors, Sarah and Elad are joined by Harrison Chase, the CEO and co-founder of LangChain, an open-source framework and developer toolkit that helps developers build LLM applications. In this conversation they talk about the gaps in open source app development, what it will take to keep up with private companies, the importance of creating prompts that can be compatible with many API models, and why memory is so undeveloped in this space.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil |@hwchase17 Show Notes:  (0:00) Introduction to LangChain (1:45) Managing an open source environment (4:30) Developing useful AI agents (10:03) Sophistication and limitations of AI app development (14:17) Switching between model APIs (17:10) Context windows, fine-tuning and functionality (21:37) Evolution of AI open source environment (23:53) The next big breakthroughs

At a time when users are being asked to wait unthinkable seconds for AI products to generate art and answers, speed is what will win the battle heating up in AI computing. At least according to today?s guest, Tuhin Srivastava, the CEO and co-founder of Baseten which gives customers scalable AI infrastructures starting with interference. In this episode of No Priors, Sarah, Elad, and Tuhin discuss why efficient code solutions are more desirable than no code, the most surprising use cases for Baseten, and why all of their jobs are very defensible from AI.  Show Links: Baseten Benchmarking fast Mistral 7B inference Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @tuhinone Show Notes:  (0:00) Introduction (1:19) Capabilities of efficient code enabled development (4:11) Difference in training inference workloads (6:12) AI product acceleration (8:48) Leading on inference benchmarks at Baseten (12:08) Optimizations for different types of models (16:11) Internal vs open source models (19:01) timeline for enterprise scale (21:53) Rethinking investment in compute spend (27:50) Defensibility in AI industries (31:30) Hardware and the chip shortage (35:47) Speed is the way to win in this industry (38:26) Wrap

Figma has had a banner year and the formidable team isn?t slowing down?even after regulatory issues blocked the merger with Adobe. Today on No Priors, Sarah and Elad are joined by Dylan Field the CEO and founder of Figma, the design collaboration tool that is closing the gap between imagination and reality. They discuss what?s next for an independent Figma, how AI can augment design and speed up the iteration loop, and how Figma is expanding beyond design with products that help the entire product team?s workflow. Show Links: https://www.figma.com/ Figma and Adobe are abandoning our proposed merger Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @zoink Show Notes:  (0:00) Introduction (2:01) No more Adobe acquisition  (4:20) What?s next for Figma (7:16) FigJam, digital collaboration, and expanding beyond design (10:50) Figma DevMode (13:06) Incorporating AI at Figma (15:03) How AI will change design (19:19) Creativity augmentation and the iterative loop (22:44) Automating repetitive design tasks (25:35) The future of AI UI (29:44) Investing philosophy (31:28) Leadership evolution

Host-only episode discussing NVIDIA, Meta and Google earnings, Gemini and Mistral model launches, the open-vs-closed source debate, domain specific foundation models, if we?ll see real competition in chips, and the state of AI ROI and adoption. Don?t miss our episodes with: Mistral NVIDIA AMD Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Show Notes:  (0:00) Introduction (0:27) Model news and product launches (5:01) Google enters the competitive space with Gemini 1.5 (8:23) Biology and robotics using LLMs (10:22) Agent-centric companies (14:22) NVIDIA earnings (17:29) ROI in AI (20:43) Impact from AI (25:45) Building effective AI tools in house (29:09) What would it take to compete with NVIDIA (33:23) The architectural approach to compute (35:42) the roadblocks to chip production in the US (38:30) The virtuous tech cycles in AI

Compute is the fuel for the AI revolution, and customers want more chip vendors. AMD CTO Mark Papermaster joins Sarah and Elad on No Priors to discuss AMD?s strategy, their newest GPUs, where inference workloads will live, the chip software stack, how they are thinking about supply chain issues, and what we can expect from AMD in 2024.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil Show Notes:  (0:00) Introduction and Mark?s background (2:35) AMD background and current markets (4:40) AMD shifting to AI space (8:54) AI applications coming out of AMD (10:57) Software investment (15:15) The benefits of open-source stacks (16:58) Evolving GPU market (20:21) Constraints on GPU production (24:11) Innovations in chip technology (27:57) Chip supply chain (30:18) Future of innovative hardware products (35:42) What?s next for AMD

Accurate, customizable search is one of the most immediate AI use cases for companies and general users. Today on No Priors, Elad and Sarah are joined by Pinecone CEO, Edo Liberty, to talk about how RAG architecture is improving syntax search and making LLMs more available. By using a RAG model Pinecone makes it possible for companies to vectorize their data and query it for the most accurate responses.  In this episode, they talk about how Pinecone?s Canopy product is making search more accurate by using larger data sets in a way that is more efficient and cost effective?which was almost impossible before there were serverless options. They also get into how RAG architecture uniformly increases accuracy across the board, how these models can increase ?operational sanity? in the dataset  for their customers, and hybrid search models that are using keywords and embeds.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @EdoLiberty Show Notes:  (0:00) Introduction to Edo and Pinecone (2:01) Use cases for Pinecone and RAG models (6:02) Corporate internal uses for syntax search (10:13) Removing the limits of RAG with Canopy (14:02) Hybrid search (16:51) Why keep Pinecone closed source (22:29) Infinite context (23:11) Embeddings and data leakage (25:35) Fine tuning the data set (27:33) What?s next for Pinecone  (28:58) Separating reasoning and knowledge in AI

Notion is a productivity app that has invested heavily in AI to create products that enable workers to access information instantly without having to search through their own countless notes. Today on No Priors, Sarah and Elad are joined by Ivan Zhao, the co-founder and CEO of Notion, to talk about Notions Q&A interface and calendar applications. They also get into how using RAG models means better retrieval, longer memory, and the user can be less organized and how Notion is leading the charge in this era of SaaS bundling products. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ivanhzhao Show Notes:  (0:00) Introduction (2:09) AI and Computing literacy (5:39) Building the Notion AI team (8:43) Notion as an application company (12:09) Prioritizing AI investment (14:53) The rapid evolution cycle of AI development (17:46) Notion Q&A (20:00) Workflow and AI for calendars (22:43) Moving past the need for organization (24:36) History of SaaS doesn?t repeat, it rhymes (30:14) Design at Notion (34:26) Notion office design (36:52) How RAG will change the future (38:30) Building our the software in the Notionscape

Many companies that are building AI products for their users are not primarily AI companies. Today on No Priors, Sarah and Elad are joined by Emily Glassberg Sands who is the Head of Information at Stripe. They talk about how Stripe prioritizes AI projects and builds these tools from the inside out. Stripe was an early adopter of utilizing LLMs to help their end user. Emily talks about how they decided it was time to meaningfully invest in AI given the trajectory of the industry and the wealth of information Stripe has access to. The company?s goal with utilizing AI is to empower non-technical users to code using natural language and for technical users to be able to work much quicker and in this episode she talks about how their Radar Assistant and Sigma Assistant achieve those goals.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @emilygsands Show Notes:  (0:00) Background (0:38) Emily?s role at Stripe (2:31) Adopting early gen AI models (4:44) Promoting internal usage of AI (8:17) Applied ML accelerator teams (10:36) Radar fraud assistant (13:30) Sigma assistant (14:32) How will AI affect Stripe in 3 years (17:00) Knowing when it?s time to invest more fully in AI (18:28) Deciding how to proliferate models (22:04) Whitespace for fintechs employing AI (25:41) Leveraging payments data for customers (27:51) Labor economics and data (30:10) Macro economic trends for strategic decisions (32:54) How will AI impact education (35:36) Unique needs of AI startups

Building an ecommerce business is hard ? it requires merchants to have a wealth of skills: technical, logistics, marketing, pricing, vendor management, finance and analytics. That?s why Shopify is releasing new AI features that help merchants tackle things like product descriptions, marketing suggestions and search. Today on No Priors, Glen Coates, the VP of core product at Shopify (and former founder of b2b wholesale platform Handshake), joins Sarah and Elad. They talk about the releases from Shopify Editions, why they are deploying ?copilot? rather than ?autopilot,? AI innovation-at-scale, how to change the basement of a house while people are living in it, and building a leadership team of entrepreneurs. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @glencoates Shopify Editions | AI Section of Shopify Editions Show Notes:  (0:00) Background (2:22) Calling a ?Code Red? at Shopify (4:04) Integrating acquisitions, entrepreneurial leaders (12:15) AI adoption (15:51) Deciding when to ship AI products, evaluations (17:33) Shopify?s risk orientation (18:50) Changing the core Shopify data model, enabling AI features (26:05) What?s missing from LLMs for merchants (28:47) Most interesting AI developments in the industry (33:22) What users want from LLMs and search (38:20) No Priors social

Building adaptive AI models that can learn and complete tasks in the physical world requires precision but these AI robots could completely change manufacturing and logistics processes. Peter Chen, the co-founder and CEO of Covariant, leads the team that is building robots that will increase manufacturing efficiency, safety, and create warehouses of the future.  Today on No Priors, Peter joins Sarah to talk about how the Covariant team is developing multimodal models that have precise grounding and understanding so they can adapt to solve problems in the physical world. They also discuss how they plan their roadmap at Covariant, what could be next for the company, and what use case will bring us to the Chat-GPT moment for AI robots. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @peterxichen Show Notes:  (0:00) Peter Chen Background (0:58) How robotics AI will drive AI forward (3:00) Moving from research to a commercial company (5:46) The argument for building incrementally  (8:13) Manufacturing robotics today (12:21) Put wall use case (15:45) What?s next for Covariant Brain (18:42) Covariant?s customers (19:50) Grounding concepts in Ai (25:47) How scaling laws apply to Covariant (29:21) Covariant?s driving thesis (32:54) the Chat-GPT moment for robotics (35:12) Manufacturing center of the future (37:02) Safety in AI robotics

Coding in collaboration with AI can reduce human toil in the software development process and lead to more accurate and less tedious work for coding teams. This week on No Priors, Sarah talked with Beyang Liu, the cofounder and CTO of Sourcegraph, which builds tools that help developers innovate faster. Their most recent launch was an AI coding assistant called Cody. Beyang has spent his entire career thinking about how humans can work in conjunction with AI to write better code. Sarah and Beyang talk about how Sourcegraph is thinking about augmenting the coding process in a way that ensures accuracy and efficiency starting with robust and high-quality context. They also think about what the future of software development could look like in a world where AI can generate high-quality code on its own and where that leaves humans in the coding process.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @beyang Show Notes:  (0:00) Beyang Liu?s experience (0:52) Sourcegraph premise (2:20) AI and finding flow (4:18) Developing LLMs in code (6:46) Cody explanation (7:56) Unlocking AI code generation (11:00) search architecture in LLMs (16:02) Quality-assurance in data set (18:03) Future of Cody (22:48) Constraints in AI code generation (30:28) Lessons from Beyang?s research days (33:17) Benefits of small models (35:49) Future of software development (42:14) What skills will be valued down the line

We?re looking back on 2023 and sharing a handful of our favorite conversations. Last year was full of insightful conversations that shaped the way we think about the most innovative movements in the AI space. Want to hear more? Check out the full episodes here: What is Digital Life? with OpenAI Co-Founder & Chief Scientist Ilya Sutskever  How AI can help small businesses with Former Square CEO Alyssa Henry Will Everyone Have a Personal AI? With Mustafa Suleyman, Founder of DeepMind and Inflection How will AI bring us the future of medicine? With Daphne Koller from Insitro The case for AI optimism with Reid Hoffman from Inflection AI Your AI Friends Have Awoken, With Noam Shazeer Mistral 7B and the Open Source Revolution With Arthur Mensch, CEO Mistral AI The Computing Platform Underlying AI with Jensen Huang, Founder and CEO NVIDIA Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @reidhoffman l @alyssahhenry l @ilyasut l @mustafasuleyman l @DaphneKoller l @arthurmensch l @MrJensenHuang Show Notes:  (0:00) Introduction (0:27) Ilya Sutskever on the governance structure of OpenAI (3:11) Alyssa Henry on how AI can small business owners (5:25) Mustafa Suleyman on defining intelligence (8:53) Reid Hoffman?s advice for co-working with AI (11:47) Daphne Koller on probabilistic graphical models (13:15) Noam Shazeer on the possibilities of LLMs (14:27) Arthur Mensch on keeping AI open (17:19) Jensen Huang on how Nvidia decides what to work on

AI doomerism and calls to regulate the emerging technology is at a fever pitch but today?s guest, Reid Hoffman is a vocal AI optimist who views slowing down innovation as anti-humanistic. Reid needs no introduction, he?s the co-founder of PayPal, Linkedin, and most recently Inflection AI which is building empathetic AI companions. He is also a board member at Microsoft and former board member at OpenAI. On this week?s episode, Reid joins Sarah and Elad to talk about the historical case for an optimistic outlook on emerging technology like AI, advice for workers who fear AI may replace them, and why it?s impossible to regulate before you innovate. Plus, some predictions. Aside from his storied experience in technology, Reid is an author, podcaster, and political activist. Most recently, he co-authors a book with GPT 4 called Impromptu: Amplifying Our Humanity Through AI. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @alyssahhenry Show Notes:  (0:00) Reid Hoffman?s birdseye view on the state of AI (3:37) AI and human collaboration in workflows (5:23) What?s causing AI doomerism (12:28) Advice for whitecollar workers (16:45) Why Reid isn?t retiring (18:25) How Inflection started (22:06) Surprising ways people are using Inflection (25:34) Western bias and AI ethics (30:58) Structural challenges in governing AI (33:15) Most exciting whitespace in AI (35:00) GPT 5 and Innovations coming in the next two years (44:00) What future should we be building?

AI tools are helping small business owners manage their businesses, so they can stay focused on the aspects of their business they love to do. This week on No Priors, Sarah and Elad are joined by Alyssa Henry, an executive at some of the most impactful companies from Microsoft to Amazon. Most recently she was the CEO of Square. She led Square?s team as they were very early adopters of a consumer-facing product that used GPT-2 and have continued to incorporate AI into their offerings. On today?s episode, they talk about the whitespace within e-commerce for AI and lessons from the prior generation of infrastructure. Alyssa recently retired from being longtime CEO of Square, within Block. Before that she was a vice president of AWS running, amongst other things, the storage products, or the digital storage bucket for the world. And before AWS, she ran order management software at Amazon Retail and started her tech career at Microsoft. She remains on the boards of Intel, Confluent and was previously on the board of Unity.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @alyssahhenry Show Notes:  (0:00) Alyssa?s experience and career trajectory (2:30) Transition from engineer to manager (4:09) AI implementation at Square (7:46) Small business AI applications  (12:14) Latent demand for content generation (15:04) The origin story of Square?s GPT-2 products (16:54) Consolidating ecommerce workflows (18:46) How will AI change cloud services (23:07) Hyperscaler foundation models and the AI land grab (25:16) Enterprise demand for open source models (28:08) Startups in the AI semiconductor space (31:02) Scale up architectures vs scaling out (34:32) What?s next for Alyssa (36:08) What Elad and Sarah are excited about in 2024

AI is the new UI for enterprise customers, according to Clara Shih, the CEO of Salesforce AI. Salesforce released Einstein, now called Einstein GPT, in 2016, making it an early example of how beneficial AI can be when embedded in enterprise software. This week on No Priors, Sarah and Elad talked with Clara about what the evolution of AI in enterprise looks like, how Salesforce is adoption AI across the organization, and the onboarding process for companies looking to integrate AI into their workflow, plus the challenges of pricing for AI services. Clara Shih is the Chief Executive Officer of Salesforce AI where she leads the AI efforts across Salesforce including AI co-pilot and agent platform, model development, go-to-market growth, adoption, partnerships, ecosystems, and secure responsible AI. Before that was the CEO of Salesforce Service Cloud She is also the co-founder and previous CEO of Hearsay Systems. She is also on the Board of Directors at Starbucks.  Show Links:  Clara?s Linkedin Ask more of AI podcast Salesforce AI Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @clarashih Show Notes:  (0:00) Clara?s Background (0:50) From cloud services to AI (3:25) Internal Model Development vs Open Source (5:20) The Co-Pilot Approach (8:50) Enterprise AI Adoption (10:54) The future of Enterprise AI (13:23) Cross-team collaboration (14:40) AI is the new UI (19:11) Structuring the Dataset (21:25) What?s next for generative AI in Enterprise (23:18) Pricing challenges in AI (26:30) Startups and AI (28:22) Collaboration in AI Industry

OpenAI?s leadership has taken us all on a rollercoaster so it?s great timing for another host-only episode. This week Sarah and Elad get into what has been going on at OpenAI and what the turbulent leadership changes tell us about the importance of good intent and good incentives when building these influential companies. They also talk about innovative products coming out of Pika Labs, why people are moving away from diffusion models to LLMs, and how, in AI investing, the ASP is the opportunity.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil Show Notes:  (0:00) Recapping the OpenAI saga (9:56) AI video products (16:14) Moving from Diffusion Models to LLMs (19:47) The beneficial margins of AI investing

The future of tech is 25-person companies powered by AI agents that help us accomplish our larger goals. Imbue is working on building AI agents that reason, code and generally make our lives easier. Sarah Guo and Elad Gil sit down with co-founders Kanjun Qiu (CEO) and Josh Albrecht (CTO) to discuss how they define reasoning, the spectrum of specialized and generalized agents, and the path to improved agent performance. Plus, what?s behind their $200M Series B fundraise.  Kanjun Qiu is the CEO and co-founder of Imbue. Kanjun is also a partner at angel fund Outset Capital, where she invests in promising pre-seed companies. Previously, Kanjun was the co-founder and CEO of Sourceress, a machine learning recruiting startup backed by YC and DFJ. She was previously Chief of Staff to Drew Houston at Dropbox, where she helped scale the company from 300 employees to 1200. Josh Albrecht is the CTO and co-founder of Imbue. He also invests in other founders via his fund, Outset Capital. He has published machine learning papers as an academic researcher; founded an AI recruiting company that went through YC and a 3D injection molding software company that was acquired; helped build Addepar as an early engineer; and served as a Thiel Fellow mentor. He started programming as a kid and began working professionally as a software engineer in high school.  Show Links:  Kanjun?s LinkedIn | Website | Google Scholar Josh?s LinkedIn | Website | Google Scholar Imbue raises $200M to build AI systems that can reason and code Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Kanjun | @JoshAlbrecht Show Notes:  (00:00) - Introduction to Imbue (04:55) - The Spectrum of Agent Tasks (08:43) - Specialization and Generalization With Agents (13:03) - Code and Language in AI Agents

Open Source fuels the engine of innovation, according to Arthur Mensch, CEO and co-founder of Mistral AI. Mistral is a French AI company which recently made a splash with releasing Mistral 7B, the most powerful language model for its size to date, and outperforming much larger models. Sarah Guo and Elad Gil sit down with Arthur to discuss why open source could win the AI wars, their $100M+ seed financing, the true nature of scaling laws, why he started his company in France, and what Mistral is building next. Arthur Mensch is Chief Executive Officer and co-founder of Mistral AI. A graduate of École Polytechnique, Télécom Paris and holder of the Master Mathématiques Vision Apprentissage at Paris Saclay, he completed his thesis in machine learning for functional brain imaging at Inria (Parietal team). He spent two years as a post-doctoral fellow in the Applied Mathematics department at ENS Ulm, where he carried out work in mathematics for optimization and machine learning. In 2020, he joined DeepMind as a researcher, working on large language models, before leaving in 2023 to co-found Mistral AI with Guillaume Lample and Timothee Lacroix. Show Links:  Arthur?s Linkedin Mistral Mistral 7b Retro: Improving language models by retrieving from trillions of tokens Chinchilla: Training Compute-Optimal Large Language Models Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ArthurMensch Show Notes:  (0:00) - Why he co-founded Mistral (4:22) - Chinchilla and Proportionality  (6:16) - Mistral 7b (9:17) - Data and Annotations (10:33) - Open Source Ecosystem  (17:36) - Proposed Compute and Scale Limits (19:58) - Threat of Bioweapons  (23:08) - Guardrails and Safety  (29:46) - Mistral Platform (31:31) - French and European AI Startups

Each iteration of ChatGPT has demonstrated remarkable step function capabilities. But what?s next? Ilya Sutskever, Co-Founder & Chief Scientist at OpenAI, joins Sarah Guo and Elad Gil to discuss the origins of OpenAI as a capped profit company, early emergent behaviors of GPT models, the token scarcity issue, next frontiers of AI research, his argument for working on AI safety now, and the premise of Superalignment. Plus, how do we define digital life? Ilya Sutskever is Co-founder and Chief Scientist of OpenAI. He leads research at OpenAI and is one of the architects behind the GPT models. He co-leads OpenAI's new "Superalignment" project, which tries to solve the alignment of superintelligences in 4 years. Prior to OpenAI, Ilya was co-inventor of AlexNet and Sequence to Sequence Learning. He earned his Ph.D in Computer Science from the University of Toronto. Show Links: Ilya Sutskever | LinkedIn Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ilyasut Show Notes: (00:00) - Early Days of AI Research (06:51) - Origins of Open Ai & CapProfit Structure (13:46) - Emergent Behaviors of GPT Models (17:55) - Model Scale Over Time & Reliability (22:23) - Roles & Boundaries of Open-Source in the AI Ecosystem (28:22) - Comparing AI Systems to Biological & Human Intelligence (30:52) - Definition of Digital Life (32:59) - Super Alignment & Creating Pro Human AI (39:01) - Accelerating & Decelerating Forces