Radical Talks

The following post is based on the latest Radical Talks episode with host Molly Welch, Partner at Radical Ventures, and featuring Ted Mabrey, Head of Palantir Commercial. Listen to the podcast on Spotify, Apple Podcasts, or YouTube.

The AI revolution is changing nearly every industry, from software to content creation, yet one crucial area remains largely untouched: the design of physical things. While AI is great at manipulating digital bits, the physical world — from skyscrapers to spacecraft — still relies on traditional engineering approaches that haven’t fundamentally changed in decades.This gap represents a huge, untapped opportunity. Physical systems could benefit enormously from AI-assisted design, but it’s a tough problem to solve. Current AI models struggle with quantitative and spatial reasoning, and training data is scarce. P-1 AI, a company co-founded by former Airbus CTO Paul Eremenko, is working to bridge this gap by developing an agent capable of mastering the physics and quantitative reasoning needed for physical design.

In this week's Radical Talks podcast, Radical Partner Rob Toews joins host Molly Welch to discuss AI’s curse of catastrophic forgetting and the challenge of building systems capable of continual learning.Rob digs into why this limitation exists and the early work being done to solve it, exploring the emerging AI paradigm that could bridge the gap between static models and truly adaptive intelligence. Continual learning holds the promise of AI systems that grow smarter with every interaction, creating unprecedented competitive moats and bringing us closer to truly adaptive machine intelligence.

In the same paper where Alan Turing outlined his famous criteria for determining when a computer is capable of thinking like a human being, he also shared advice on building a device that might one day pass the ‘Turing Test.’ “Instead of trying to produce a programme to simulate the adult mind,” the pioneer of computer science writes,“why not rather try to produce one which simulates the child's?” The deep learning breakthroughs by Geoffrey Hinton and the architects of neural networks created technologies that have gone on to out-perform oncologists in cancer detection and help self-driving cars navigate our roads. However, to build systems that are capable of broadly generalizing across different use cases and experiences, researchers are looking to children for inspiration. In this episode of Radical Talks, renowned psychologist Alison Gopnik explores how AI systems may benefit from a better understanding of the way children learn and play. Gopnik, who runs the Cognitive Development and Learning Lab at the University of California, Berkeley is also the best-selling author of The Philosophical Baby, and The Gardener & The Carpenter. Like scientists, children constantly test hypotheses to better understand the world. Gopnik argues that the causal inference demonstrated by a child offers clues into how to build more resilient AI systems. Current AI technologies are a bit like the children of ‘helicopter’ parents – they’re task-focused and good at doing one thing well. As is the case with raising a well-rounded child, to broaden the potential of AI there may be value in nurturing and rewarding curiosity in AI models. If researchers are successful in building an AI that demonstrates child-like curiosity, a question emerges around the need for computational caregivers to keep AIs from causing damage to themselves or others and to ensure they benefit society more broadly. As Gopnik puts it, “AIs need moms.”

A feature interview with Pieter Abbeel,  an innovator at the cutting edge of where AI meets robotics. In this episode of Radical Talks, Radical Ventures Managing Partner Jordan Jacobs chats with Pieter about the impact of COVID19 on automation, how AI has revolutionized the field of robotics and they also share a few thoughts on how professional sports should be thinking about robot refs. Pieter Abbeel is a professor of electrical engineering and computer science at the University of California, Berkeley where he is also director of the Robot Learning Lab. Peter is also co-founder of Covariant - a company that has built a universal AI platform for robotics (Radical Ventures is an investor in Covariant). For more thoughts and insights from Radical Ventures,  visit www.radical.vc.

Welcome to the premier episode of Radical Talks.  Created by Radical Ventures, an early stage venture fund investing in technology and Artificial Intelligence, Radical Talks explores the intersection of technology, the economy, politics and culture with global thought leaders. In our first episode we're joined by Eric Schmidt. Eric was the CEO of Google from 2001 to 2011, and the Executive Chairman of Google -- and then Alphabet -- from 2011 to 2017. He is also an investor in Radical Ventures. In this episode we touch on the macro impacts of the pandemic, China relations, the Sidewalk Labs project and how technology and society might look very different coming out the other side of this crisis. To get more Radical content or to sign up to our weekly newsletter, please visit Radical.vc