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Chris Kempes

Published podcast speaker

Claims
10
Episodes
1
Shows
1
Named items
0

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What Chris said.

4 transcript-backed records

01 / prediction

Maybe someday we will find a notion where we realize, oh right, life just, you know, has this process, and then when we started to build software systems, it did exactly the same thing in terms of a bunch of people working on some open source piece of code that then had a very particular evolutionary dynamic.

“Maybe someday we will find a notion where we realize, oh right, life just, you know, has this process, and then when we started to build software systems, it did exactly the same thing in terms of a bunch of people working on some open source piece of code that then had a very particular evolutionary dynamic.”
Speaker
Chris Kempes
Publisher
Machine Learning Street Talk

02 / prediction

We have this with certain earth systems models, we have this with very detailed models of the economy, artificial intelligence is certainly in that space, and so we think each of these has trade offs, each of these 3 cultures, and we really need to find a way to sort of walk amongst the corners of that triangle to get the best knowledge.

“We have this with certain earth systems models, we have this with very detailed models of the economy, artificial intelligence is certainly in that space, and so we think each of these has trade offs, each of these 3 cultures, and we really need to find a way to sort of walk amongst the corners of that triangle to get the best knowledge.”
Speaker
Chris Kempes
Publisher
Machine Learning Street Talk

03 / prediction

Maybe that's a set of equations, maybe that's a set of concepts, maybe it's, you know, more agency, less intelligence, we don't know. But we think we're in an exciting time where people are building quantitative theories to get at some of the ingredients, and again, looking at the history of science, there are many cases where all the ingredients were there, and then people figure out, oh, this is the right combination, this is the right projection to give us the theory that really gives us traction on something.

“Maybe that's a set of equations, maybe that's a set of concepts, maybe it's, you know, more agency, less intelligence, we don't know. But we think we're in an exciting time where people are building quantitative theories to get at some of the ingredients, and again, looking at the history of science, there are many cases where all the ingredients were there, and then people figure out, oh, this is the right combination, this is the right projection to give us the theory that really gives us traction on something.”
Speaker
Chris Kempes
Publisher
Machine Learning Street Talk

04 / prediction

I mean, if we wanted to say like, okay, really have a simulation of my computer that is life, then it's, then we're into this whole Axiom space where the thresholds are, and we just don't have a good compact theory to tell us when we've crossed that threshold. But I think in principle, there's just, there's no reason why with enough compute, with enough constraints, with enough complexity inside some artificial world, you could create, you know, you could create life.

“I mean, if we wanted to say like, okay, really have a simulation of my computer that is life, then it's, then we're into this whole Axiom space where the thresholds are, and we just don't have a good compact theory to tell us when we've crossed that threshold. But I think in principle, there's just, there's no reason why with enough compute, with enough constraints, with enough complexity inside some artificial world, you could create, you know, you could create life.”
Speaker
Chris Kempes
Publisher
Machine Learning Street Talk
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