Peter Norvig

speaker

553 appearances 2 recordings 1 series first heard Dec 2025 last heard 29 Apr

Peter Norvig’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 2 in all, peaking in Apr 2026 with 1.

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Young and Profiting (YAP) with Hala Taha: Entrepreneurship and Self-Improvement Podcast · Peter Norvig: Transforming AI Into the Ultimate Human Advantage | Artificial Intelligence | AI Vault · 26 Dec 2025 podcast

and ask them, in this situation with this patient, what would you do?

And then you try to build a system that would duplicate what the doctor said.

And it was all built by hand.

Programmers sitting down, trying to understand what the doctor said and trying to encode that into rules that they would write into the system.

And it worked to some extent, but it was very brittle, and it just often failed to handle problems that were just slightly outside of what it had anticipated.

So in the 1990s, there was a big switch away from this expert system, hand-coded approach towards machine learning approaches, where we said rather than telling the system how to do it,

You just show it lots of examples and let it learn by itself.

And so we felt like the existing books had missed that change.

We wanted to write a book about it.

So we did that.

But of course, things continue to change.

And so I guess what can I say about what's changed over the four editions?

I guess one was at the start, we felt like, well, AI, this is part of computer science and computer science is about algorithms.

So we're going to show you a bunch of cool algorithms.

And we did that.

And then in the second edition, I think we felt more like, okay, you still got to know all the cool algorithms, but if you had a choice, you're probably better off getting better data rather than getting better algorithms.

So we're going to focus a lot more on what the data is.

And that continued to be more true in the third edition.

And now I feel like, okay, now we've got plenty of data, we've got plenty of algorithms, you still have to know about them.

But really the key to future progress is neither of those.

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