4 ms·

It’s not a particularly useful mental model, but it does drive home a critical point some people have trouble with, namely that LLMs don’t learn when being used

It’s not a particularly useful mental model, but it does drive home a critical point some people have trouble with, namely that LLMs don’t learn when being used.

ben_w 2y ago
Current AIs don't learn like us. But the context length is around what a human goes through in a day so it can feel like it, and they can use tools such as databases to make direct record of "important" things, and fine-tuning on sessions is also already possible. I'm going to ignore "proper" continuous learning until that actually gets into the big-name models, because although there's plenty of "first 90%" tech demos, the Tesla FSD is also at that point and yet the cars today still come with steering wheels. Meanwhile, here's the research SOTA: https://github.com/Wang-ML-Lab/llm-continual-learning-survey https://github.com/Wang-ML-Lab/llm-continual-learning-survey Ironically, continuously updating a Markov chain is easy, given how small most of them are in practice. But a Markov chain large enough to act like an LLM would collapse into a black hole 7x10^32 times larger than the universe*, so that's kinda hard to update. * assuming the algebra was correct: http://www.wolframalpha.com/input/?i=sqrt%2812%2A%28%2850000%5E20%29%5E2%29%2Aplank%20constant%2AGravitational%20constant%2Aln%282%29%2F%28pi%2A%28speed%20of%20light%5E3%29%29%29 http://www.wolframalpha.com/input/?i=sqrt%2812%2A%28%2850000... Edit: I made at least two errors with that algebra, one of which was a typo; I now think it's 4.2x10^4750 universe diameters… …unless there's another error I missed: http://www.wolframalpha.com/input/?i=sqrt%2812%2A%28%2850000%5E2048%29%2Aplank%20constant%2AGravitational%20constant%2Aln%282%29%2F%28pi%2A%28speed%20of%20light%5E3%29%29%29 http://www.wolframalpha.com/input/?i=sqrt%2812%2A%28%2850000...
- Jensson 2y ago
  > But a Markov chain large enough to act like an LLM would collapse into a black hole You mean a full state table Markov Chain? Markov chains doesn't need to have all states in a table, it just needs to be a function, a table is one implementation of a function but anything can do.
  - ben_w 2y ago
    Indeed. Although my understanding is that under quantum mechanics it's necessary to set the probability of all transitions between states to a number larger than zero, I also understand that for practical purposes the probability for the overwhelming majority of transitions are close enough to zero as to require fancy notation (at the very least, nested exponentiation) to express quite how unlikely they are.

It’s not a particularly useful mental model, but it does drive home a critical point some people have trouble with, namely that LLMs don’t learn when being used.

ben_w 2y ago

Current AIs don't learn like us. But the context length is around what a human goes through in a day so it can feel like it, and they can use tools such as databases to make direct record of "important" things, and fine-tuning on sessions is also already possible. I'm going to ignore "proper" continuous learning until that actually gets into the big-name models, because although there's plenty of "first 90%" tech demos, the Tesla FSD is also at that point and yet the cars today still come with steering wheels. Meanwhile, here's the research SOTA: https://github.com/Wang-ML-Lab/llm-continual-learning-survey https://github.com/Wang-ML-Lab/llm-continual-learning-survey Ironically, continuously updating a Markov chain is easy, given how small most of them are in practice. But a Markov chain large enough to act like an LLM would collapse into a black hole 7x10^32 times larger than the universe*, so that's kinda hard to update. * assuming the algebra was correct: http://www.wolframalpha.com/input/?i=sqrt%2812%2A%28%2850000%5E20%29%5E2%29%2Aplank%20constant%2AGravitational%20constant%2Aln%282%29%2F%28pi%2A%28speed%20of%20light%5E3%29%29%29 http://www.wolframalpha.com/input/?i=sqrt%2812%2A%28%2850000... Edit: I made at least two errors with that algebra, one of which was a typo; I now think it's 4.2x10^4750 universe diameters… …unless there's another error I missed: http://www.wolframalpha.com/input/?i=sqrt%2812%2A%28%2850000%5E2048%29%2Aplank%20constant%2AGravitational%20constant%2Aln%282%29%2F%28pi%2A%28speed%20of%20light%5E3%29%29%29 http://www.wolframalpha.com/input/?i=sqrt%2812%2A%28%2850000...

Jensson 2y ago
> But a Markov chain large enough to act like an LLM would collapse into a black hole You mean a full state table Markov Chain? Markov chains doesn't need to have all states in a table, it just needs to be a function, a table is one implementation of a function but anything can do.
- ben_w 2y ago
  Indeed. Although my understanding is that under quantum mechanics it's necessary to set the probability of all transitions between states to a number larger than zero, I also understand that for practical purposes the probability for the overwhelming majority of transitions are close enough to zero as to require fancy notation (at the very least, nested exponentiation) to express quite how unlikely they are.