Every tech company minus the few doing core research have been doing this for at least half a year. Generate training data with GPT4 or sometimes even 3.5 -> use it to do a QLoRA finetune on a llama or mistral base -> roll it out as a "proprietary" AI model -> management claims a big win and talks about how they're leaders in "[industry name] AI".
It is remarkably easy - it takes practically zero knowledge of ML and can usually be done with less than <$1k of cloud compute costs. The issue is that for most realistic tasks you can expect to end up with something roughly on the level of GPT-3.5, and its actually really hard to compute with GPT-3.5 on a cost level, at least if you use cloud GPUs.
It is remarkably easy - it takes practically zero knowledge of ML and can usually be done with less than <$1k of cloud compute costs. The issue is that for most realistic tasks you can expect to end up with something roughly on the level of GPT-3.5, and its actually really hard to compute with GPT-3.5 on a cost level, at least if you use cloud GPUs.