Evidence receipt / recommendation
Published · transcript-backedTim Scarfe: recommendation
28 Aug 2025 Machine Learning Street Talk Michael Timothy Bennett: Defining Intelligence and AGI Approaches
“I do recommend that folks at home read that, especially for folks in the MLST audience, because we're a little bit eclectic in our taste.”
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- Speaker
- Tim Scarfe
- Attribution
- Verified speaker
- Claim type
- recommendation
- Recorded
- 28 Aug 2025
- Publisher
- Machine Learning Street Talk
Transcript context
…Yeah. I mean, it's just a couple of extra letters, but yeah. Okay. Yeah. That was doing the rounds, and I flicked for it at the time. I've now just spent the last couple of hours reading it word for word, and it's actually brilliant. I do recommend that folks at home read that, especially for folks in the MLST audience, because we're a little bit eclectic in our taste. We are ideas collectors, and we like, you know, different approaches to AGI, and also hybrid approaches, and a little bit of philosophy and consciousness and and whatnot. So certainly, in in that respect, you might be the perfect guest. Thank you. So this is all very good. This is all very good. In that paper, you were talking about what intelligence is and various approaches to AGI and also approaches to categorizing them. Tell us about that. Okay. So intelligence is a hotly debated topic. It's been for a long time. I sort of started off with the leg hunter definition of the ability to satisfy goals in a wide range of environments. But as I delved more into biological intelligence and other things, I sort of arrived at a definition as the ability as the efficiency of adaptation. So how sample and energy efficient you are. And then later, I found Pei Wang's definition, which preceded mine by several years, as adaptation with limited resources, which I think is really succinct and clear. And of course, there's myriad other definitions, but my favorite's Pei Wang's.…
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