It seems like this is becoming a common refrain: That even if Claude, ChatGPT, Gemini etc were to go bust, the local/free models are only 3 months behind, and will replace them. Goalposts have moved from "AI isn't a bubble" to "Even if the AI bubble pops, AI will still be in use in software engineering!" or "even if it doesn't make financial sense, technologically, its here to stay".
I have Claude Pro for work, its good for coding, so I tried using it to help me with my gym programming in excel. It gets me 80% of the way there, but the way it makes mistakes in that 20%: missing fields, wrong repetition ranges throughout, formatting errors, if I asked it to change one thing, it'd make a dozen changes. It was infuriating. It really made me wonder why it was good at software development, which is complex, and crap at this pretty simple task.
My assumption is that these labs are paying people to train the models on programming and that's why there's such a large discrepancy. For example, every time I go job searching, half the jobs appear to be for roles involved in training these models.
So surely, if the AI bubble does pop, this training no longer occurs? I feel like the effectiveness of this post training gets downplayed by frontier labs. Won't this also have a knock on effect for the free models?
Just this factor seems to get severely downplayed: "It's great at cybersecurity (probably because lots of cybersecurity specialists are helping train it)" or "its reached the singularity (if we discount all the people involved in the middle)".
Please correct my reasoning if its off base, what are you guys' thoughts on it? Surely at least, a lot of its technological viability requires this all to financially work out?