This point feels fairly obvious, yet seems worth stating explicitly.
Those of us familiar with the field of AI after the deep-learning revolution know perfectly well that we have no idea how our ML models work. Sure, we have an understanding of the dynamics of training loops and SGD's properties, and we know how ML models' architectures work. But we don't know what specific algorithms ML models' forward passes implement. We have some guesses, and some insights painstakingly mined by interpretability advances, but nothing even remotely like a full understanding.
And most certainly, we wouldn't automatically know how a fresh model trained on a novel architecture that was just spat out by the training loop works.
We're all used to this state of affairs. It's implicitly-assumed shared background knowledge. But it's actually pretty unusual, when you first learn of it.
And...
Relevant XKCD.I'm pretty sure that the general public [...]
The original text contained 1 footnote which was omitted from this narration. ---
First published: December 21st, 2023
Source: https://www.lesswrong.com/posts/CpjTJtW2RNKvzAehG/most-people-don-t-realize-we-have-no-idea-how-our-ais-work ---
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TYPE III AUDIO.