I am completely bewildered by the responses here.
GPT-3 is so good it could write code, or it could emulate an entire TV show to the point of lawsuit, or simulate an eternal debate between Herzog and Zizek. You could translate Bulgarian to Sindarin for heaven's sake. And all of this comes at a 50% tax rate or so because of the alignment tax that OAI opted for. (which doesn't even work because anyone who puts effort in can jailbreak it scarily well)
The real solution is not these monstrosities of the internet mushed together and taxed like a Belgian billionaire. It's models and frameworks specific to what you want in a given query.
It was less than 24 hours ago that we finally got a local model that can do code generation well, and we also know that Meta has a far better one that they are holding back.
There is no reason that for any query you should be restricted to a single inference run on a single fixed model, and there is no reason that we shouldn't perform a bunch of non-LLM processing on the output before the user sees it.
Switch between multiple models, fine-tune, or use LoRAs based on the query -- Python plots? Load llama-coding-python-plots. You like Plotly? Add -Plotly. Run the code in a sandbox (with hard kills on resources) and regenerate it if it does not meet standards.
You're working in linguistics? Switch to a chat model that's fine-tuned in the literature and codebase of that field.
There are a trillion ways to improve things; we're basically at the cavemen-banging-rocks-together point.
Hell, I'm a sleep deprived ESL and i just invoked the monstrosity to fix my grammar and spelling for this post. What a bloody waste of CO2.
If for nothing but to keep the Earth afloat we shouldn't be using these huge closed source SaaS things unless we need them. Repurpose them for SETI@Home or processing human genetics for healthcare, or something else that benefits mankind