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