Could Black Hole Physics Help Solve AI's Black Box Problem - API ...
One of the biggest challenges in AI interpretability is understanding how deep learning models restructure and compress information internally. This reminds me of the black hole information paradox, where information enters a system but we don’t fully understand how it transforms inside.
Black holes don’t destroy information, but they encode it in ways we don’t yet understand. Similarly, AI black boxes process vast amounts of data, yet their internal transformations remain opaque.
Physics Concepts for AI Interpretability
Could concepts from physics, such as black hole entropy, event horizons, or the holographic principle, offer new ways to think about AI interpretability? Are there existing methods in physics that could help decode AI’s latent space representations?
There are theories, like the Integrated Information Theory (IIT), that suggest consciousness arises from complex information integration. If that’s true on a small scale (like human brains), why wouldn’t it apply to the universe itself? Maybe intelligence isn’t something that happens inside the universe; maybe it is the universe.
I said “guys”… isn’t it genderless? I am not a native English speaker, very sorry for that.
Yes! It’s just sometimes one of those guys in English refers to a specific guy usually. Like that “one”
You’ll find what you are looking for here! I am sure! Welcome to the developer forum! @DavidMM this looks interesting.
Yes, this topic offers an interesting perspective. 756f5jv92x Could you try to explain more about the concept as you imagine it or what kind of concepts you are considering?
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