Technology these days works in that they always lose money at the start. Its a really stupid feature of modern startups IMO. Get people dependent and they make money later. I don’t agree with it. I don’t really think oir entire economic system is viable though and that’s another conversation.
But LLMs have been improving exponentially. I was on board with everything you’re saying just a year ago about how they suck and they’re going to hit a wall even. But the don’t need more training data or the processing power. They have those and now they’re refining the LLMs. I have a local LLM on my computer that performs better than chat GPT did a year ago and it’s only a few GB. I run it on a shitty laptop.
I experimented with quite a few local LLMs too and granted, some perform a lot better than others, but they all have the same major issues. They don’t get smarter, they just produce the same nonsense faster (or rather often it feels like they are just more verbose about the same nonsense).
I don’t know what to tell you. I have them successfully compiling tables of search outputs to compare different things for method development and generating code, saving me hours of work each week. It all needs to be checked, but the comparison comes with links and the code is proofread and benchmarked. For most of what I do it’s really just a jacked up search engine, but it’s able to scan webpages faster than me and that saves a lot of time.
As a hobby, I also have it reading old documents that are almost illegible and transcribing them pretty well.
I really don’t know what you’re doing that you’re just getting nonsense. I’m not.
Technology these days works in that they always lose money at the start. Its a really stupid feature of modern startups IMO. Get people dependent and they make money later. I don’t agree with it. I don’t really think oir entire economic system is viable though and that’s another conversation.
But LLMs have been improving exponentially. I was on board with everything you’re saying just a year ago about how they suck and they’re going to hit a wall even. But the don’t need more training data or the processing power. They have those and now they’re refining the LLMs. I have a local LLM on my computer that performs better than chat GPT did a year ago and it’s only a few GB. I run it on a shitty laptop.
I experimented with quite a few local LLMs too and granted, some perform a lot better than others, but they all have the same major issues. They don’t get smarter, they just produce the same nonsense faster (or rather often it feels like they are just more verbose about the same nonsense).
I don’t know what to tell you. I have them successfully compiling tables of search outputs to compare different things for method development and generating code, saving me hours of work each week. It all needs to be checked, but the comparison comes with links and the code is proofread and benchmarked. For most of what I do it’s really just a jacked up search engine, but it’s able to scan webpages faster than me and that saves a lot of time.
As a hobby, I also have it reading old documents that are almost illegible and transcribing them pretty well.
I really don’t know what you’re doing that you’re just getting nonsense. I’m not.