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> the whole point of a highly robust large language model is to be so robust that _every_ problem you have is easily defined as a formatted string Using langua
by wokwokwok 3y ago
> the whole point of a highly robust large language model is to be so robust that _every_ problem you have is easily defined as a formatted string
Using language models is about automation, parsing, etc. like any NLP task.
What you’re talking about (it would be nice) is sufficiently distant to what we have right now as to be totally irrelevant.
I agree langchain is a naive implementation, but NLP libraries are complicated.
They have always been complicated.
Not being complicated is not the goal of these libraries; it’s getting the job done.
- ShamelessC 3y ago> What you’re talking about (it would be nice) is sufficiently distant to what we have right now as to be totally irrelevant. I disagree. :shrug: Guess we'll see who is right in like 10-20 years. It also sounds as though we're talking about different things maybe? Because a lot of automation, parsing and NLP are very much "solved" tasks for GPT-4 ignoring (important) edge cases and respecting the relative lack of progress in the domain until GPT-3. If you need agents and stuff, then yeah we haven't got that figured out. But neither will you (general you) with your hodge podge of if statements wrapping an LLM.
- krageon 3y agoIf we can only see in 10-20 years, you are wrong today. Which is what the point was.