The magic sauce is context length within reasonable compute restraints. Phone predictive text has a context length of like 2-3 words, ChatGPT (and other LLMs) have figured out how to do predictions on thousands or tens of thousands of words of context at a time.
Comment on ELI5 How does chatgpt do its shit?
SorteKanin@feddit.dk 8 months ago
it seems pretty obvious that a lot more is going on than just predicting the most likely next word.
But that is all that’s going on. It has just been trained on so much text that the predictions “learn” the grammatical structure of language. Once you can form coherent sentences, you’re not that far from ChatGPT.
The remarkable thing is that prediction of the next word seems to be “sufficient” for ChatGPT’s level of “intelligence”. But it is not thinking or conscious, it is just data and statistics on steroids.
Dran_Arcana@lemmy.world 8 months ago
doublejay1999@lemmy.world 8 months ago
It’s that why is compute heavy ?
Dran_Arcana@lemmy.world 8 months ago
Correct, and the massive databases of long-length context associations are why you need tens to hundreds of gigabytes worth of ram/vram. Disk would be too slow
LesserAbe@lemmy.world 8 months ago
I think this explanation would be more satisfying if we had a better understanding of how the human brain produces intelligence.
SorteKanin@feddit.dk 8 months ago
I agree. We don’t actually know that the brain isn’t just doing the same thing as ChatGPT. It probably isn’t, but we don’t really know.
Dran_Arcana@lemmy.world 8 months ago
Considering that we can train digital statistical models to read thoughts via brain scans I think it’s more likely than not that we are more similar
datavoid@lemmy.ml 8 months ago
Try to use it to solve a difficult problem and it will become extremely obvious that it has no idea what it is talking about.
pearsaltchocolatebar@discuss.online 8 months ago
Yup. I used it to try to figure out why our Java code was getting permission denied on jar files despite being owned by the user running the code and 777 permissions while upgrading from rhel7 to 8
It gave me some good places to check, but the answer was that rhel8 uses fapolicyd instead of selinux (which I found myself on some tangentially related stack exchange post)