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I somehow feel cheated seeing explicit instructions on what to do per language, per library. I hoped that the "intelligent handling" comes from the trained mode
by dr_kretyn 1y ago
I somehow feel cheated seeing explicit instructions on what to do per language, per library. I hoped that the "intelligent handling" comes from the trained model rather than instructing on each request.
- potholereseller 1y agoWhen you've trained your model on all available data, the only things left to improve are the training algorithm and the system prompt; the latter is far easier and faster to tweak. The system prompts may grow yet more, but they can't exceed the token limit. To exceed that limit, they may create topic-specific system prompts, selected by another, smaller system prompt, using the LLM twice: user's-prompt + topic-picker-prompt -> LLM -> topic-specific-prompt -> LLM This will enable the cumulative size of system prompts to exceed the LLM's token limit. But this will only occur if we happen to live in a net-funny universe, which physicists have not yet determined.
- abrookewood 1y agoI'm the opposite - I look at how long that prompt is and I'm amazed that the LLM 'understands' it and that it works so well at modifying it's behaviour.
- grues-dinner 1y agoI'm the same. Having a slew of expert tuned models or submodels or whatever the right term of for each kind of problem seems like the "cheating" way (but also the way I would have expected this kind of thing to work, as you can use the tool for the job, so to speak. And then the overall utility of the system is how well it detects and dispatches to the right submodels and synthetises the reply. Having one massive model that you tell what you want with a whole handbook up front actually feels more impressive. Though I suppose it's essentially doing the submodels thing implicitly internally.
- mcintyre1994 1y agoI think most of that is about limiting artifacts (code it writes to be previewed in the Claude app) to the supported libraries etc. The trained model can answer questions about and write code in lots of other libraries, but to render correctly in artifacts there’s only a small number of available libraries. And there’ll be all sorts of ways those libraries are imported etc in the training data so it makes sense to tell it how that needs to be done in their environment.
- mrweasel 1y agoI don't know if I feel cheated, but it seems a little unmanageable. How is this suppose to scale? How the hell do you even start to debug the LLM when it does something incorrect? It's not like you can attach a debugger to English. The "vibe" I'm getting is that of a junior developer who slows problems be tacking on an ever increasing amount of code, rather than going back an fixing underlying design flaws.
- vidarh 1y agoSee it as a temporary workaround, and assume each instruction will also lead to additional training data to try to achieve the same in the next model directly.
- kikimora 1y agoIt comes down to solving this - given instruction X find out how to change the training data such that X is obeyed and none other side effects appears. Given amount if the training data and complexities of involved in training I don’t think there is a clear way to do it.
- vidarh 1y agoI'm slightly less sceptical that they can do it, but we presumably agree that changing the prompt is far faster, and so you change the prompt first, and the prompt effectively will serve in part as documentation of issues to chip away at while working on the next iterations of the underlying models.
- lukan 1y agoApparently AGI is not there yet.