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>In addition, GPT is currently saturated with data; it has effectively all of the data. No this is not true. The reason why chatGPT is better then GPT-3 is bec
by kilgnad 4y ago
>In addition, GPT is currently saturated with data; it has effectively all of the data.
No this is not true. The reason why chatGPT is better then GPT-3 is because it's trained on additional reinforcement data to determine good and bad answers. They basically outsourced and hired a bunch of Kenyans to do this.
If they hire say a computer scientist to reinforce the code and rate the best coded answers then it can improve in that specific specialty. There is ALOT of room for additional sets of this type of data.
Are you sure you know this as an expert in this area or you're just agreeing with him as a layman? I'm certainly a layman myself.
- freeone3000 4y agoI've published a few papers and spent the last five years at MSR working in AI. I'm not particularly distinguished, but I believe I qualify as an expert. The RL model made the responses more useful by determining what is and is not a useful reply, then re-running on non-useful replies. It doesn't actually increase the knowledge or the LLM in a meaningful way; it does increase the precision, which is viewed as a form of increased performance? But the RL model cannot inject new facts, and cannot perform reasoning to a greater degree than the LLM can.
- kilgnad 4y agoI see. It seems to me a lot of the issues are precision problems right? chatGPT produces answers that look correct, and if you increase the precision along the correct path in this knowledge space the lookalike answer converges into the correct answer. Let's say we layer an RL model with training that doubles the size of the current LLM. I think most of the counter examples of performance failures of chatGPT in this thread will become nill. Thanks for responding btw. Good to hear the opinion of an expert.