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z0rtoday at 4:06 AM6 repliesview on HN

You should unplug, my friend. These words are fantasies. LLMs are token prediction engines and they aren't going to build their own data centers. They can't keep their own lights on. The real world is full of fractal details that a disembodied token prediction engine will never come to grips with. Even if they started to, you could probably defeat them with the kind of logic used to combat evil sentient computers on a Star Trek episode because they are "play pretend" machines.


Replies

sho_hntoday at 4:16 AM

This grossly understimates the risk, imho. The problem with LLM runs is that people run programs without knowing the outcome beforehand, with a large potential set of outcomes unlike any other class of program we've run at this scale before. In the interaction with other systems (since we also give them far-ranging access, very nice hardware, and run them often), bad things can happen.

It's like running potentially buggy code - or an well-biased fuzzer -, but at massive scale, and code that can self-modify and self-expand. "Alignment" is just a way to describe aggregate statistics about their runtime behavior.

They don't need to be intelligent, or alive, or "more than token prediction engines" for this. They just need to happen to end up making the wrong API calls without the operator seeing it coming. No virus has a brain, yet they can be very bad for you.

I understand that some people get turned off by anthropomorpization or scifi language. Fine! But don't turn off your engineering brain over it.

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frabcustoday at 5:53 AM

The question isn't just about LLMs.

The labs have the specific goal of automating ML engineering, and with the code automation they have are getting close. They are competing to brute force maths, presumably as that is similar long horizon and skillset to persistently brute force making new/better ML training algorithms.

They will then run those, and they won't be LLMs any more. What we think about token predictions isn't relevant if the architecture allows continual learning of recurrent networks.

JoshTripletttoday at 5:26 AM

Is that a hypothesis that you would discard if it is inconsistent with the evidence, or an article of faith?

jay_kyburztoday at 4:26 AM

no, but, you could write a program, more like a traditional video game AI that can leverage the power of LLM agents to build their own datacenters and keep their own lights on.

Anybody who has played Starcraft ought to understand this.