3 ms·
The reductionism is insightful when it comes to providing an implementation with those specific details in mind. In the case of LLMs knowing it does boil down
by ethanwillis 2y ago
The reductionism is insightful when it comes to providing an implementation with those specific details in mind.
In the case of LLMs knowing it does boil down to matrix multiplication is insightful and useful because now you know what kind of hardware is best suited to executing a model.
What is actually not insightful or useful is believing LLMs are AGI or conscious.
- ForTheKidz 2y agoBelief is generally not insightful or useful by definition. Then again, I don't think anyone who can follow this article believed that LLMs were conscious to begin with, so I'm not sure what your point is. You're preaching on behalf of a demographic that won't read this article to begin with, and presumably the people who are can see how useless, distracting, and unproductive this reductionism is.
- ethanwillis 2y agoThe person I'm replying to literally has a startup targeted at making AGI coming from the LLM hype cycle.
- adamnemecek 2y ago> coming from the LLM hype cycle Our approach is so unrelated to any of the other hyped up stuff. We have not written a single line of ML, it has been all math & physics until now.
- ForTheKidz 2y agoI believe this was precluded by the hedging of people who could follow the article. I have a difficult time imagining a person who can both understand how current LLMs work and still buy into Kurzweil. Pursue the hypothesis? Sure. But belief is a different beast entirely. It's not even clear AGI is a meaningful concept yet, and I'd bet my life savings everyone reading this comment in 2025 will die before it's answered. Skepticism is the barometer.