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nialv7today at 7:41 PM2 repliesview on HN

The funny thing about LLM is, you can build one from scratch and yet you still won't understand how it works. You would understand what kind of matrix multiplications the neural network performs (in fact that's not that hard. An OS is orders of magnitudes more complex), but you would still have no idea why it does what it does.


Replies

michael0churchtoday at 8:01 PM

This is a great point. The complexity sources are entirely different. An OS is complex because it’s solving a difficult problem and we’ve seen decades of evolution both in knowledge and-how and, at the frontier, in performance standards.

The abilities of LLMs are emergent. You can experiment with LLMs and know as much about their observable behavior as the experts. But there’s no way to “crack open” an LLM and see precisely where each skill or tendency lives; as far as we currently understand, it’s all mashed together.

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aschobeltoday at 8:18 PM

Yah, "building" it is not sufficient. But a lot of times when I build I want to know the why. "Why does gradient Descent have some clever tricks that easily translate to matrix math"?

Lot's of neat stuff to learn.