Ilya is one of the Founders of the original nonprofit. This is also an issue. It does look like he was not the Founder or in any control of the for profit venture.
For a lot of (very profitable) use cases, hallucinations and 80/20 are actually more than good enough. Especially when they are replacing solutions that are even worse.
Any use case where you treat the output like the work of a junior person and check it. Coding, law, writing. Pretty much anywhere that you can replace a junior employee with an LLM.
Google or Meta (don't remember which) just put out a report about how many human-hours they saved last year using transformers for coding.
All the usecases we see. Take a look at perplexity optimising short internet research. If I get this mostly right its fine enough, saved my 30 minutes of mindless clicking and reading - even if some errors are there.
It works fine for some things. You just need a clearly defined task where LLM + human reviewer is on average faster (ie cheaper) than a human doing the same task themselves without that assistance.
Given the fact that you need to review, research, and usually correct every detail of AI output, how can that be faster than just doing it right yourself in the first place? Do you have some examples of such tasks?
Yes. There's the one that $employer built a POC app for and found did in fact save time. There's also github copilot which apparently a large chunk of people find saves time for them (and which $employer is reviewing to figure out if they can identify which people / job functions benefit precisely enough to pay for group licensing).
The AI isn’t the product, e.g. the ChatGPT interface is the main product that is layered above the core AI tech.
The issue is trustworthiness isn’t solvable by applying standard product management techniques on a predictable schedule. It requires scientific research.
That’s not true at all. The biggest issue is that it doesn’t work. You can’t actually trust ai systems and that’s not a product issue.