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. Show Links: Stability.AI Stable Diffusion V2 on Hugging Face  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @EMostaque Show Notes:  [2:00] - Emad’s background as one of the largest investors in video games and artificial intelligence [7:24] - Open-source efforts in AI [13:09] - Stability.AI as the only independent multimodal AI company in the world [15:28] - Computational biology, medical information and medical models [23:29] - Pace of Adoption [26:31] - AGI versus intelligence augmentation [31:38] - Stability.AI’s business model [37:44] - AI Safety

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. Show Links: Watch Cris Valenzuela’s 2018 thesis presentation at New York University’s ITP program. Read how Runway is used on the Late Show and in Everything Everywhere All at Once on the Runway Blog. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @c_valenzuelab Show Notes:  [1:50] - Cris’s background and how he doesn’t see barriers between art and machine learning [6:46] - How Runway works as a tool [8:36] - The origins and early iterations of Runway [12:22] - Product sequencing and roadmapping in a fast growing space [15:43] - Runway as an applied research company [19:10] - Common pitfalls for founders to avoid [22:35] - How Runway structures teams for effective collaboration [24:22] - Learnings from how Runway built Greenscreen product [28:01] - Building a long-term and sustainable business [32:34] - Finding Product Market Fit [36:34] - The influence of AI tools in art as an artistic movement

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. Show Links: More about Noam Brown Read the research article about Cicero (diplomacy) published in Science.  Read the research article about Liberatus  (heads-up poker) published in Science.  Read the research article about Pluribus (multiplayer poker) published in Science.  Watch the AlphaGo Documentary. Read “How Smart Are the Robots Getting?” by New York Times reporter Cade Metz  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Polynoamial Show Notes:  [01:43] - What sparked Noam’s interest in researching AI that could defeat games [6:00] - How the AlexaNET and AlphaGo changed the landscape of AI research [8:09] - Why Noam chose Diplomacy as the next game to work on after poker [9:51] - What Diplomacy is and why the game was so challenging for an AI bot [14:50] - Algorithmic breakthroughs and significance of AI bots that win in No-Limit Texas Hold'em poker [23:29] - The Nash Equilibrium and optimal play in poker [24:53] - How Cicero interacted with humans  [27:58] - The relevance and usefulness of the Turing Test [31:05] - The data set used to train Cicero [31:54] - Bottlenecks to AI researchers and challenges with scaling [40:10] - The next frontier in researching games for AI [42:55] - Domains that humans will still dominate and applications for AI bots in the real world [48:13] - Reasoning challenges with AI

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. Follow the podcast wherever you listen so you never miss an episode. We’ll see you next week with a new episode. Email feedback to [email protected]