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Published · transcript-backedBruno Gavranović: commitment
22 Dec 2025 Machine Learning Street Talk Making deep learning perform real algorithms with Category Theory (Andrew Dudzik, Petar Velichkovich, Taco Cohen, Bruno Gavranović, Paul Lessard)
“I I I looked at it the wrong way. So I don't know what where this could go, but we are certainly striving to make things as compositional as as they could be.”
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Everything needed to verify it.
- Speaker
- Bruno Gavranović
- Attribution
- Verified speaker
- Claim type
- commitment
- Recorded
- 22 Dec 2025
- Publisher
- Machine Learning Street Talk
Transcript context
…The people who believe in strong emergence think that there is no reductionism. But even with basic weak emergence, the analytical shortcut between the theories at different scales are computationally intractable. It's very difficult to go between them. But we want to have some kind of a theoretical framework that captures the whole thing, right? You know, captures the the emergent organization as well as what's going on underneath. So so this is 1 of the goals that you could say is 1 of the goals of category theory is to find some fundamental abstractions that give rise to these very simple principles. Often when you look at some systems or some phenomena, it's very complicated. But if you're lucky enough and you can set up the good foundations, it's always, oh, wait. It was very simple all along. I I I looked at it the wrong way. So I don't know what where this could go, but we are certainly striving to make things as compositional as as they could be. And in many of these fields where we have a pleth plenty of experimental evidence and lack of good theories, category theory has a very good vantage point and just a lot of practical benefit of let's stop and and see what's the good vantage point here. Does 2 morphisms allow us to think about weight tying?…
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