No Priors: Artificial Intelligence | Technology | Startups

Today on No Priors, Elad chats with Erik Bernhardsson, founder and CEO of Modal Labs, a platform simplifying ML workflows by providing a serverless infrastructure designed to streamline deployment, scaling, and development for AI engineers. Erik talks about his early work on Spotify’s ML algorithms, what Modal offers today, and his vision for building an end-to-end solution for AI engineers. They dive into GPU trends, cloud vs on-premise setups, and when to train custom models vs use off-the-shelf solutions. Erik also shares his thoughts on the evolving role of AI in fields like coding, physics, and music.

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Show Notes:

0:00 Introduction 

0:22 Erik's early interest in ML infra

1:22 Founding Modal Labs 

4:17 State of GPU use today and what’s to come

7:14 Modal's end-to-end vision 

9:00 Differentiating amongst competition

10:20 Cloud vs on-premise 

12:35 Popular AI models 

13:20 Gaps in AI infrastructure

14:55 Insights on vector databases 

16:48 Training models vs off-the-shelf models 

17:47 AI’s impact on coding and physics

22:14 AI's impact on music

2024 has been a year of transformative technological progress, marked by conversations that have reshaped our understanding of AI's evolution and what lies ahead. Throughout the year, Sarah and Elad have had the privilege of speaking with some of the brightest minds in the field. As we look back on the past months, we’re excited to share highlights from some of our favorite No Priors podcast episodes. Featured guests include Jensen Huang (Nvidia), Andrej Karpathy (OpenAI, Tesla), Bret Taylor (Sierra), Aditya Ramesh, Tim Brooks, and Bill Peebles (OpenAI’s Sora Team), Dmitri Dolgov (Waymo), Dylan Field (Figma), and Alexandr Wang (Scale). Want to dive deeper? Listen to the full episodes here:

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Show Notes:

0:00 Introduction 

0:15 Jensen Huang on building at data-center scale 

4:00 Andrej Karpathy on the AI exo-cortex, model control, and a shift to smaller models 

7:14 Bret Taylor on the agentic future of business interactions 

11:17 OpenAI’s Sora team on visual models and their role in AGI 

15:53 Waymo’s Dmitri Dolgov on bridging the gap to full autonomy and the challenge of 100% accuracy 

19:00 Figma’s Dylan Field on the future of interfaces and new modalities 

23:29 Scale AI’s Alexandr Wang on the journey to AGI 

26:29 Outro

Today on No Priors, Sarah sits down with Elias Torres, CEO and founder of Agency, an AI agent for customer success teams. Elias shares his journey from growing up in Nicaragua to founding several companies, leading engineering at HubSpot, and selling Drift for $1B. He also discusses his work consulting with OpenAI in 2022, which deepened his understanding of the business opportunity LLMs presented and inspired him to start Agency. In this episode, Elias offers a unique perspective on the future of AI and customer success, explaining how current software has fallen short and his vision for a new generation where customers have direct relationships, spend less time on tasks, and have software working invisibly on their behalf. They also discuss the evolving landscape of hiring as teams shrink, and Elias reveals his ambitious plan to reach $1B in revenue with fewer than 100 employees.

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Show notes:

0:00 Introduction

0:34 Elias’ journey to entrepreneurship

2:36 Growing HubSpot to IPO and founding Drift

6:19 Consulting with OpenAI, learning about LLMs, and diving into AI

9:35 Founding Agency to focus on customer success and AI-driven solutions

11:40 What will a customer experience look like in 5 years?

15:48 Company building in an era of AI, as a 5th time founder

18:32 Reducing headcount while raising the bar on hiring

20:35 Key challenges in building Agency and crafting a standout product

23:06 Addressing software flaws and transitioning to an era of intuitive, self-operating solutions

26:27 Timeline for the next-gen software revolution + the power of building from first principles

In this episode of No Priors, Sarah sits down with Felix Ejeckam and Ty Mitchell, founders of Akash Systems, a company pioneering diamond-based cooling technology for semiconductors used in space applications and large-scale AI data centers. Felix and Ty discuss how their backgrounds in materials science led them to tackle one of the most pressing challenges in tech today: thermal efficiency and heat management at scale. They explore how Akash is overcoming the limitations of traditional semiconductors and how their innovations could significantly boost AI performance. Felix and Ty also talk about their collaboration with India’s sovereign cloud provider, the importance of strengthening U.S. manufacturing in the AI chip market, and the role Akash Systems could play in advancing satellite technologies.

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Show Notes:

0:00 Introduction

0:30 What is Akash Systems?

2:12 Felix’s personal path to building Akash Systems

4:45 Ty’s approach to acquiring customers

6:40 Challenges of operating in space

7:54 Live demo on diamond’s conductivity

9:50 Heat issues in data centers

15:38 Heat as a fundamental limit to technological progress

20:44 Akash’s role in the semiconductor market

22:54 Growing diamonds

25:10 Collaborating with India’s sovereign cloud provider

28:15 Importance of American manufacturing for AI chips and outlook on current data capacity 

29:45 The Chips Act

31:22 Future of national security lies in satellite and radar tech

32:46 Critical issues in the U.S. AI supply chain

36:34 Deep learning’s role in material science discovery

40:16 The future: AI expanding our possibilities

In this episode of No Priors, Sarah talks with Eric Simons, co-founder and CEO of StackBlitz. The company has experienced explosive growth since the launch 2 months ago of Bolt.new, an AI application that lets users prompt, run, edit, and deploy full-stack applications directly in the browser. Eric talks about the years-long journey that led to overnight success, why so many non-technical users are forming a community around Bolt, and the democratization of coding.

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Show Notes:

0:00 Introduction

0:36 Bolt.new

2:04 How Bolt stands out from other coding assistants

3:28 Building beyond ChatGPT wrappers

6:13 Driving growth through community

9:42 Evals

13:29 Eric’s favorite use cases and startups leveraging Bolt

17:10 Why engineers are embracing no- code tools

24:32 The years long journey of StackBlitz

31:50 Balancing an Ironman, a newborn, and a product launch

35:18 Predictions for developers and code generation tools

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

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