Rob Toews on Overcoming AI's Catastrophic Forgetting
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.
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A New Season of Radical Talks
Coming soon, Radical Talks cuts through AI hype to showcase what's truly driving innovation. Hosted by Radical Ventures partner Molly Welch, each episode features intimate conversations with researchers, founders, and investors at AI's cutting edge. Discover contrarian perspectives and insider insights you won't find anywhere else, and subscribe wherever you get your podcasts.
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Geoffrey Hinton in conversation with Fei-Fei Li
In honour of Geoffrey Hinton winning the Nobel Prize in Physics, we bring you an exclusive Radical AI Founders Masterclass talk between, Geoffrey Hinton and Fei-Fei Li, hosted and moderated by Jordan Jacobs, Managing Partner and Co-Founder of Radical Ventures.
The conversation marked the first time Geoff Hinton and Fei-Fei Li have shared a stage, and featured a dramatic recounting of the 2012 ImageNet competition when their professional careers first intersected. It was a pivotal moment in the history of AI, when neural networks proved capable of ‘solving’ computer vision.
Recognized as the “godfather of AI,” Hinton candidly voices his apprehensions about the unforeseen challenges of advanced AI, including concerns that innovations could one day yield superior intelligence. However, Hinton also noted that he believes his message of caution is getting through. Li, a Stanford University Professor, Co-Director of Stanford’s Human-Centered AI Institute (HAI), and Radical Ventures Scientific Partner, stressed the need for responsible AI stewardship through human-centred approaches, while grounding the conversation in a sense of optimism about its potential.
The discussion was held in front of a live audience at the University of Toronto.
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Alison Gopnik: AIs need moms
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.”
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Fei-Fei Li: Making Sense of Healthcare with Machine Intelligence
A feature conversation with AI pioneer Fei-Fei Li. As WIRED magazine put it: “She’s one of a tiny group of scientists—a group perhaps small enough to fit around a kitchen table—who are responsible for AI’s recent remarkable advances.” The Stanford Computer Science Professor and Co-Director of the Stanford Institute for Human-Centered AI, joins Radical Ventures Managing Partner, Jordan Jacobs, for a feature conversation on the enormous opportunities to improve healthcare with AI, the state of computer vision, and how we should be thinking about the human values of AI systems. Fei-Fei Li is a co-founder of Dawnlight, a Radical portfolio company.
For more thoughts and insights from Radical Ventures, visit www.radical.vc.
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