Today on No Priors, we discuss defense technology, AI, drones, and autonomous vehicles (think giant submarine drones!) with Brian Schimpf, the co-founder and CEO of Anduril, a next-generation defense technology company. From his early days of coding at age 12 to working on self-driving cars, and finally founding Anduril, Brian's incredible journey led him to create innovative solutions for pressing defense problems. This episode covers the impact of AI, intelligent software, and other technologies to defense. We discuss the challenges of deploying and selling technology in the government spaceBrian shared his perspective on building general-purpose defense technology, the importance of a software-first approach, and how Anduril is working to solve urgent defense problems with speed and efficiency. As we wrapped up our conversation, we touched on the recent shift in the low cost of space launch, which has changed the way the US thinks about defense. We examined the proliferation of satellites, drones, and hypersonic missiles, and how these technologies can be applied, scaled, and built in a way that can fundamentally shift America's approach to defense. Don't miss this fascinating episode with Brian Schimpf as we uncover the cutting edge of defense technology and its implications for the future. No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: May 16, 2023: AI in Military Operations and How We Can Prevent It From Outsized Effects May 9, 2023: CNBC Disruptor 50 - Anduril Industries Anduril Website Anduril Newsroom Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @SchimpfBrian Show Notes: [0:00:01] - Exploring AI in Defense Tech [0:05:15] - Lower Cost Defense With Intelligent Software [0:15:10] - Building General Purpose Defense Technology [0:20:41] - Autonomy in Defense Challenges [0:25:05] - Machine Learning in Defense & Intelligence [0:29:06] - Scaling a Defense Tech Company [0:37:08] - The Future of Defense Technology [0:46:53] - Allied Forces and Washington Engagement [0:51:47] - Discussion on Leadership Popularity

In this episode, Sarah and Elad speak with Microsoft CTO Kevin Scott about his unlikely journey from rural Virginia to becoming the driving force behind Microsoft's AI strategy.  Sarah and Elad discuss the partnership that Kevin helped forge between Microsoft and OpenAI and explore the vision both companies have for the future of AI. They also discuss yesterday’s announcement of “copilots” across the Microsoft product suite, Microsoft’s GPU computing budget, the potential impact of open source AI models in the tech industry, the future of AI in relation to jobs, why Kevin is bullish on creative and physical work, and predictions for progress in AI this year. No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: May 23, 2023: The Verge - Microsoft CTO Kevin Scott Thinks Sydney Might Make a Comeback May 23, 2023: Microsoft Outlines Framework For Building AI Apps and Copilots January 10, 2023: A Conversation with Kevin Scott: What’s Next In AI Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @kevin_scott Show Notes: [00:00] - Kevin Scott's Journey to Microsoft CTO [12:44] - Microsoft and Open AI Partnership [21:18] - The Future of Open Source AI [32:12] - AI for Everyone [45:29] - AI and the Future of Jobs [51:44] - The Future of AI and Regulation [58:10] - Taking a Global Perspective

What if AI could revolutionize healthcare with advanced language learning models? Sarah and Elad welcome Karan Singhal, Staff Software Engineer at Google Research, who specializes in medical AI and the development of MedPaLM2. On this episode, Karan emphasizes the importance of safety in medical AI applications and how language models like MedPaLM2 have the potential to augment scientific workflows and transform the standard of care. Other topics include the best workflows for AI integration, the potential impact of AI on drug discoveries, how AI can serve as a physician's assistant, and how privacy-preserving machine learning and federated learning can protect patient data, while pushing the boundaries of medical innovation. No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: May 10, 2023: PaLM 2 Announcement April 13, 2023: A Responsible Path to Generative AI in Healthcare March 31, 2023: Scientific American article on Med-PaLM February 28, 2023: The Economist article on Med-PaLM KaranSinghal.com Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @thekaransinghal Show Notes: [00:22] - Google's Medical AI Development [08:57] - Medical Language Model and MedPaLM 2 Improvements [18:18] - Safety, cost/benefit decisions, drug discovery, health information, AI applications, and AI as a physician's assistant. [24:51] - Privacy Concerns - HIPAA's implications, privacy-preserving machine learning, and advances in GPT-4 and MedPOM2. [37:43] - Large Language Models in Healthcare and short/long term use.

Mustafa Suleyman, co-founder of DeepMind and now co-founder and CEO of Inflection AI, joins Sarah and Elad to discuss how his interests in counseling, conflict resolution, and intelligence led him to start an AI lab that pioneered deep reinforcement learning, lead applied AI and policy efforts at Google, and more recently found Inflection and launch Pi. Mustafa offers insights on the changing structure of the web, the pressure Google faces in the age of AI personalization, predictions for model architectures, how to measure emotional intelligence in AIs, and the thinking behind Pi: the AI companion that knows you, is aligned to your interests, and provides companionship. Sarah and Elad also discuss Mustafa’s upcoming book, The Coming Wave (release September 12, 2023), which examines the political ramifications of AI and digital biology revolutions. No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: Forbes - Startup From Reid Hoffman and Mustafa Suleyman Debuts ChatBot Inflection.ai Mustafa-Suleyman.ai Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @mustafasuleymn Show Notes: [00:06] - From Conflict Resolution to AI Pioneering [10:36] - Defining Intelligence [15:32] - DeepMind's Journey and Breakthroughs [24:45] - The Future of Personal AI Companionship [33:22] - AI and the Future of Personalized Content [41:49] - The Launch of Pi [51:12] - Mustafa’s New Book The Coming Wave

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). No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: Kelvin Guu Website Google Scholar FLAN: Finetuned Language Models Are Zero-Shot Learners Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs ROME: Locating and Editing Factual Associations in GPT Branch-Train-Merge: Scaling Expert Language Models with Unsupervised Domain Discovery Large Language Models Struggle to Learn Long-Tail Knowledge  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Kelvin_Guu Show Notes: [1:44] - Kelvin’s background in math, statistics and natural language processing at Stanford [3:24] - The questions driving the REALM Paper [7:08] - Frameworks around retrieval augmentation & expert models [10:16] - Why is modularity important [11:36] - FLAN Paper and instruction following [13:28] - Updating model weights in real time and other continuous learning methods [15:08] - Simfluence Paper & explainability with large language models [18:11] - ROME paper, “Model Surgery” exciting research areas [19:51] - Personal opinions and thoughts on AI agents & research [24:59] - How the human brain compares to AGI regarding memory and emotions [28:08] - How models become more contextually available [30:45] - Accessibility of models [33:47] - Advice to future researchers