How do you personalize AI models? A popular school of thought in AI is to just dump all the data you need into pre-training or fine tuning. But that may be less efficient and less controllable than alternatives — using AI models as a reasoning engine against external data sources. Kelvin Guu, Senior Staff Research Scientist at Google, joins Sarah and Elad this week to talk about retrieval, memory, training data attribution and model orchestration. At Google, he led some of the first efforts to leverage pre-trained LMs and neural retrievers, with >30 launches across multiple products. He has done some of the earliest work on retrieval-augmented language models (REALM) and training LLMs to follow instructions (FLAN).

So much of the AI conversation today revolves around models and new applications. But this AI revolution would not be possible without one thing – GPUs, Nvidia GPUs. The Nvidia A100 is the workhorse of today’s AI ecosystem. This week on No Priors, Sarah Guo and Elad Gil sit down with Jensen Huang, the founder and CEO of NVIDIA, at their Santa Clara headquarters. Jensen co-founded the company in 1993 with a goal to create chips that accelerated graphics. Over the past thirty years, NVIDIA has gone far behind gaming and become a $674B behemoth. Jensen talks about the meaning of this broader platform shift for developers, making very long term bets in areas such as climate and biopharma, their next-gen Hopper chip, why and how NVIDIA chooses problems that are unsolvable today, and the source of his iconic leather jackets.

Noam Shazeer played a key role in developing key foundations of modern AI - including co-inventing Transformers at Google, as well as pioneering AI chat pre-chatGPT. These are the foundations supporting today’s AI revolution. On this episode of No Priors, Noam discusses his work as an AI researcher, engineer, inventor, and now CEO. Noam Shazeer is currently the CEO and Co-founder of Character AI, a service that allows users to design and interact with their own personal bots that take on the personalities of well-known individuals or archetypes. You could have a socratic conversation with Socrates. You could pretend you’re being interviewed by Oprah. Or you could work through a life decision with a therapist bot. Character recently raised $150M from A16Z, Elad Gil, and others. Noam talks about his early AI adventures at Google, why he started Character, and what he sees on the horizon of AI development.

If you have 30 dollars, a few hours, and one server, then you are ready to create a ChatGPT-like model that can do what’s known as instruction-following. Databricks’ latest launch, Dolly, foreshadows a potential move in the industry toward smaller and more accessible but extremely capable AIs. Plus, Dolly is open source, requires less computing power, and fewer data parameters than its counterparts. Matei Zaharia, Cofounder & Chief Technologist at Databricks, joins Sarah and Elad to talk about how big data sets actually need to be, why manual annotation is becoming less necessary to train some models, and how he went from a Berkeley PhD student with a little project called Spark to the founder of a company that is now critical data infrastructure that’s increasingly moving into AI.

Everyone talks about the future impact of AI, but there’s already an AI product that has revolutionized a profession. Alex Graveley was the principal engineer and Chief Architect behind Github Copilot, a sort of pair-programmer that auto-completes your code as you type. It has rapidly become a product that developers won’t live without, and the most leaned-upon analogy for every new AI startup – Copilot for Finance, Sales, Marketing, Support, Writing, Decision-Making. Alex is a longtime hacker and tinkerer, open source contributor, repeat founder, and creator of products that millions of people use, such as Dropbox Paper. He has a new project in stealth, Minion AI. In this episode, we talk about the uncertain process of shipping Copilot, how code improves chain of thought for LLMs, how they improved product, performance, how people are using it, AI agents that can do work for us, stress testing society's resilience to waves of new technology, and his new startup named Minion.

With advances in machine learning, the way we search for information online will never be the same. This week on the No Priors podcast, we dive into a startup that aims to be the most trustworthy place to search for information online. Perplexity.ai is a search engine that provides answers to questions in a conversational way and hints at what the future of search might look like. Aravind Srinivas is a Co-founder and CEO of Perplexity. He is a former research scientist at Open AI and completed his PhD in computer science at University of California Berkeley. Denis Yarats is a Co-Founder and Perplexity’s CTO. He has a background in machine learning, having worked as a Research Scientist at Facebook AI Research and a machine learning engineer at Quora.

For the first time in decades web search might be at risk for disruption. Bing is allied with OpenAI to integrate LLMs. Google has committed to launching new products. New startups are emerging. Sridhar Ramaswamy co-founded the challenger AI-powered, private search platform Neeva in 2019. He is a former 16-year Google veteran who most recently led the internet’s most profitable business as SVP in charge of Google Ads, Commerce and Privacy. Sridhar, Elad and Sarah talk about the challenge of building search, how LLMs have changed the landscape, and how chatbots and "answer services" will affect web publishers.

When AI research is evolving at warp speed and takes significant capital and compute power, what is the role of academia? Dr. Percy Liang – Stanford computer science professor and director of the Stanford Center for Research on Foundation Models talks about training costs, distributed infrastructure, model evaluation, alignment, and societal impact. Sarah Guo and Elad Gil join Percy at his office to discuss the evolution of research in NLP, why AI developers should aim for superhuman levels of performance, the goals of the Center for Research on Foundation Models, and Together, a decentralized cloud for artificial intelligence.

Life-saving therapeutics continue to grow more costly to discover. At the same time, recent advances in using machine learning for the life sciences and medicine are extraordinary. Are we on the verge of a paradigm shift in biotech? This week on the podcast, a pioneer in AI, Daphne Koller, joins Sarah Guo and Elad Gil on the podcast to help us explore that question. Daphne is the CEO and founder of Insitro — a company that applies machine learning to pharma discovery and development, specifically by leveraging “induced pluripotent stem cells.” We explain Insitro’s approach, why they’re focused on generating their own data, why you can’t cure schizophrenia in mice, and how to design a culture that supports both research and engineering. Daphne was previously a computer science professor at Stanford, and co-founder and co-CEO of edutech company Coursera.

After starting as a talking emoji companion, Hugging Face is now an organizing force for the open source AI research ecosystem. Its models are used by companies such as Apple, Salesforce and Microsoft, and it's working to become the GitHub for ML. This week on the podcast, Sarah Guo and Elad Gil talk to Clem Delangue, co-founder and CEO of Hugging Face. Clem shares how they shifted away from their original product, why every employee at Hugging Face is responsible for community-building, the modalities he's most interested in, and what role open source has in the AI race.

A delivery with Zipline is the closest thing we have to teleportation. It sounds like science fiction, but Zipline delivers life saving medical supplies such as blood and vaccines to hospitals, doctors and people in need around the world with the world's largest autonomous drone network. This week on the podcast, Sarah Guo talks to Keller Rinaudo Cliffton, the co-founder and CEO of Zipline, about building a full-stack business that involves software, hardware and operations, how a culture of ruthless engineering practicality enabled them to do unlikely things, the state of autopilot in aircraft, their acoustic detect-and-avoid system, and why founders should build for users beyond the "golden billion."

AI-generated images have been everywhere over the past year, but one company has fueled an explosive developer ecosystem around large image models: Stability AI. Stability builds open AI tools with a mission to improve humanity. Stability AI is most known for Stable Diffusion, the AI model where a user puts in a natural language prompt and the AI generates images. But they're also engaged in progressing models in natural language, voice, video, and biology. This week on the podcast, Emad Mostaque joins Sarah Guo and Elad Gil to talk about how this barely one-year-old, London-based company has changed the AI landscape, scaling laws, progress in different modalities, frameworks for AI safety and why the future of AI is open.

For a long time, AI-generated images and video felt like a fun toy. Cool, but not something that would bring value to professional content creators. But now we are at the exciting moment where machine learning tools have the power to unlock more creative ideas. This week on the podcast, Sarah Guo and Elad Gil talk to Cristobal Valenzuela, a technologist, artist and software developer. He’s also the CEO and co-founder of Runway, a web-based tool that allows creatives to use machine learning to generate and edit video. You've probably already seen Runway's work in action on the Late Show with Stephen Colbert and in the feature film Everything Everywhere All at Once.

AI is transforming our future, but what does that really mean? In ten years, will humans be forced to please our AGI overlords or will we have unlocked unlimited capacity for human potential? That's why Sarah Guo and Elad Gil started this new podcast, named No Priors. In each episode, Sarah and Elad talk with the leading engineers, researchers and founders in AI, across the stack. We'll talk about the technical state of the art, how that impacts business, and get them to predict what's next.

AGI can beat top players in chess, poker, and, now, Diplomacy. In November 2022, a bot named Cicero demonstrated mastery in this game, which requires natural language negotiation and cooperation with humans. In short, Cicero can lie, scheme, build trust, pass as human, and ally with humans. So what does that mean for the future of AGI? This week’s guest is research scientist Noam Brown. He co-created Cicero on the Meta Fundamental AI Research Team, and is considered one of the smartest engineers and researchers working in AI today. Co-hosts Sarah Guo and Elad Gil talk to Noam about why all research should be high risk, high reward, the timeline until we have AGI agents negotiating with humans, why scaling isn’t the only path to breakthroughs in AI, and if the Turing Test is still relevant.