Autoregressive Large Language Models are Computationally Universal — mentioned by br0tl1

Tue, 24 Dec 2024 06:18:28 GMT

I think that's an oversimplification. LLMs have a limited context window of tokens. But that isn't necessarily a limitation: it's been proven that a LLM can simulate any algorithm even with a limited context window (https://arxiv.org/abs/2410.03170), making it computationally universal. Even if that weren't true, the context windows can be quite large and will get bigger as people figure out how to optimize LLMs. For example Gemini 1.5 has a context of 2 million tokens. A book is typically around 120,000 words, so that's almost 20 books. So one could argue with a context this big they could…

Paper and discussion history. A mention is not an endorsement.

Autoregressive Large Language Models are Computationally Universal — HN submission

Sat, 19 Oct 2024 16:42:18 GMT

Autoregressive Large Language Models Are Computationally Universal

1 point; 0 discussion replies on HN. Paper and source history. A submission is not an endorsement.

Autoregressive Large Language Models are Computationally Universal · HackerPapers discussions

Autoregressive Large Language Models are Computationally Universal — mentioned by br0tl1

Autoregressive Large Language Models are Computationally Universal — HN submission