Episodios
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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.
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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 -
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.
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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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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.
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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 -
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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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 - Mostrar más
