No Priors: Artificial Intelligence | Technology | Startups

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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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.

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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