In this Huberman Lab Essentials episode my guest is Lex Fridman, PhD, a research scientist at the Massachusetts Institute of Technology (MIT), an expert in robotics and host of the Lex Fridman Podcast. We discuss the development of artificial intelligence through machine learning, deep learning and self-supervised techniques. We also examine the growing significance of interactions between humans and robots, including their potential for companionship and emotional connection. This episode explores how AI is shifting from a technical tool into something that could reshape human relationships, emotions and society. Read the episode show notes at hubermanlab.com. Thank you to our sponsors AG1: https://drinkag1.com/huberman Maui Nui: https://mauinui.com/huberman Function: https://functionhealth.com/huberman David: https://davidprotein.com/huberman Timestamps 00:00:00 Lex Fridman; Artificial Intelligence (AI), Machine Learning, Deep Learning 00:02:23 Supervised vs Self-Supervised Learning, Self-Play Mechanism 00:09:06 Tesla Autopilot, Autonomous Driving, Robot & Human Interaction 00:14:26 Sponsors: AG1 & Maui Nui 00:17:47 Human & Robot Relationship, Loneliness, Time 00:22:38 Authenticity, Robot Companion, Emotions 00:27:55 Robot & Human Relationship, Manipulation, Rights 00:32:12 Sponsors: Function & David 00:35:14 Dogs, Homer, Companion, Cancer, Death 00:40:04 Dogs, Costello, Decline, Joy, Loss 00:47:31 Closing Disclaimer & Disclosures Learn more about your ad choices. Visit megaphone.fm/adchoices
Full Episode
Welcome to Huberman Lab Essentials, where we revisit past episodes for the most potent and actionable science-based tools for mental health, physical health, and performance. And now my conversation with Dr. Lex Friedman. We meet again. We meet again. I have a question that I think is on a lot of people's minds or ought to be on a lot of people's minds.
What is artificial intelligence and how is it different from things like machine learning and robotics?
So I think of artificial intelligence first as a big philosophical thing. It's our longing to create other intelligent systems, perhaps systems more powerful than us.
at the more narrow level i think it's also a set of tools that are computational mathematical tools to automate different tasks and then also it's our attempt to understand our own mind so build systems that exhibit some intelligent behavior in order to understand what is intelligence in our own selves So all those things are true.
Of course, what AI really means as a community, as a set of researchers and engineers, it's a set of tools, a set of computational techniques that allow you to solve various problems. There's a long history that approaches the problem from different perspectives.
What's always been throughout one of the threads, one of the communities, goes under the flag of machine learning, which is emphasizing in the AI space the task of learning. How do you make a machine that knows very little in the beginning, follow some kind of process and learns to become better and better at a particular task.
What's been most very effective in the recent about 15 years is a set of techniques that fall under the flag of deep learning that utilize neural networks. It's a network of these little basic computational units called neurons. artificial neurons, and they have, these architectures have an input and output. They know nothing in the beginning and they're tasked with learning something interesting.
What that something interesting is usually involves a particular task. there's a lot of ways to talk about this and break this down. Like one of them is how much human supervision is required to teach this thing. So supervised learning, this broad category, is the neural network knows nothing in the beginning, and then it's given a bunch of examples
In computer vision, that would be examples of cats, dogs, cars, traffic signs. And then you're given the image and you're given the ground truth of what's in that image. And when you get a large database of such image examples where you know the truth, then your network is able to learn by example. That's called supervised learning.
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