Episodes
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This week on No Priors hosts, Sarah and Elad are catching up on the latest AI news. They discuss the recent developments in AI 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.
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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.
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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 -
Missing episodes?
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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
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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.
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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.
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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.
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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
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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
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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
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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
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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.
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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.
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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 - Show more
