The Relationship Between Emergence and Machine Learning

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I love the connections between emergence and what's happening right now in all of the models. I also wonder, are these causative or are they correlative? Do you think it's tricky? Let's take a step back and say your job as an engineer is to design a system to identify whether an image is a cat or not a cat. An emergent system would be like, okay, here are a million pictures of cats, figure out what's a cat. It'll do that. So it's very tricky because there's also the question of correlation versus causation in this. There's some examples of image net classification that I find hilarious. There's a general category inside image net

David Ha is the Head of Strategy at Stability AI, and one of the top minds working in AI today. He previously worked as a research scientist in the Brain team at Google. David is particularly interested in evolution and complex systems, and his research explores how intelligence may emerge from limited resource constraints. He joins the show to discuss the advantages of open-source models, modelling AI as an emergent system, why large language models are bad at maths and MUCH more! Important Links:

Show Notes:

Why David joined Stability AI
The advantages of open-source models
We cannot predict the inventions of tomorrow
Making memes with generative AI
The centaur approach to AI
An introduction to large language models
The relationship between complex systems and resource constraints
Large language models are bad at maths
Modelling AI as an emergent system
Understanding different perspectives
MUCH more!

Books Mentioned:

The Beginning of Infinity: Explanations That Transform the World; by David Deutsch
Why Greatness Cannot Be Planned: The Myth of the Objective; by Kenneth Stanley and Joel Lehman