I don’t think they will. I’m the first to be massively sceptical of LLMs, but that doesn’t mean they can’t be used to build good tools. The key is recognising that tasks where correctness is vital should not be solved by the LLM directly. At my job, we’ve built an LLM-agent that’s very useful (internal use). What we’ve done is build essentially a Python library that this LLM uses to interact with our data. That way, we ensure that a query like “set up a skeleton for X” will be done correctly, while we save a bunch of time that would have otherwise been spent doing boilerplate work.
Basically: Enforce correctness by constraining how the LLM can interact with your data, and use the LLM to translate short natural-language queries into actions that otherwise would have taken 30 min of click-ops or write-run-toss scripting.
That’s exactly the opposite of what I’m talking about, the LLM that your work is using is while perhaps generalist for internal standards is still rather limited compared to the large more general models being such as ChatGPT or whatever the fuck musks model is called. No I’m talking about the fuck off massive models that have been scraping the entire internet in a vain attempt to create AGI, so the stupid cloud based models that have been being shoved into everything.
I think those are going to implode on themselves simply because they are too expensive versus the fuckall you get out of them.
I don’t think they will. I’m the first to be massively sceptical of LLMs, but that doesn’t mean they can’t be used to build good tools. The key is recognising that tasks where correctness is vital should not be solved by the LLM directly. At my job, we’ve built an LLM-agent that’s very useful (internal use). What we’ve done is build essentially a Python library that this LLM uses to interact with our data. That way, we ensure that a query like “set up a skeleton for X” will be done correctly, while we save a bunch of time that would have otherwise been spent doing boilerplate work.
Basically: Enforce correctness by constraining how the LLM can interact with your data, and use the LLM to translate short natural-language queries into actions that otherwise would have taken 30 min of click-ops or write-run-toss scripting.
That’s exactly the opposite of what I’m talking about, the LLM that your work is using is while perhaps generalist for internal standards is still rather limited compared to the large more general models being such as ChatGPT or whatever the fuck musks model is called. No I’m talking about the fuck off massive models that have been scraping the entire internet in a vain attempt to create AGI, so the stupid cloud based models that have been being shoved into everything.
I think those are going to implode on themselves simply because they are too expensive versus the fuckall you get out of them.