Re:Large language models are having their Stable Diffusion m...
by BulgarianIdiot on Sunday March 12, 2023 @08:31AM
(#35119315)
Oh so there's no memory, just recallable history.
Oh so it's not learning by example, it's just primed by a sample.
Oh so there's no iteration of thought, just a loop of prediction.
OK.
Also, the papers you asked about: https://news.ycombinator.com/item?id=35115563
BTW, people are already implementing recursive/iterative queries on the ChatGPT API, and getting promising results.
Re:Large language models are having their Stable Diffusion m...
by LawTalkingGuy on Sunday March 12, 2023 @12:41PM
(#35122364)
The langchain project is an example of the iterative queries approach. It comes with constructs for working memory, factual lookup / calculation agents, etc.
https://github.com/hwchase17/langchain
The general (non-technical) guideline is that the LLMs can "answer" anything you just gave them the answer for. So you give it a problem, ask it how to solve it, tell it to use that method and explain the data it needs, give it that data, and then show it everything at once: "With this data you requested and summarized, use this technique to answer this question".
As for "we just need a way to include iterations": isn't this what attention is supposed to do (kind of dynamically updating weights). The usual way to really update weights are variations on gradient descent. Can you link a paper outlining how we integrate your proposal into the current framework (which took around 20years to mature)? Otherwise your statements are Sci-Fi (at the flying cars-level).