Why AI works is a bit of a mystery

We know how AI models responds to our inputs (such as text prompts, video or audio files) by providing outputs in turn.

What is invisible to us is the network beneath this exchange, the hidden layer:

These networks form through a process of iterative computational learning.

As the model gets more data, it seems to get better at tasks like language processing, pattern identification and reasoning.

But what is happening under the hood exactly? How are these connections forming? And why can AI do tasks it wasn't specifically trained to do so well? That's what tons of scientists are trying to figure out with experiments like Golden Gate Claude.

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