These models have so many parameters that, while insufficient to memorize all text it has ever seen, it can end up memorizing some of the content. It is the difference between being able to recall a random passage versus recalling the exact thing you need. Both allow you to spill content verbatim, but one is problematic while the other can be helpful.
There are techniques to allow it it ‘read on demand’, but they are not part of the core model (i.e. the autocmpletion model / LLM) and are tacked on top of it. For example, you can tie it search engine, which Microsoft’s copilot does, and is something which I don’t think is enabled for ChatGPT by default. Or allow it to query a external data bank (Retrieval Augmented Generation).
Or when you’re singing karaoke and suddenly break into a chorus of the phone number and email address of a random author of a scholarly paper whom you’ve never met whose paper has nothing to do with the lyrics of “Free Bird“?
Yes, it does, from the information it was trained on (or - stored), which like you say, requires a lot of hardware power so it can be accessed on demand. It isn’t just manifesting the information out of thin air, and it definitely doesn’t “remember” in the same way we do.
It’s definitely not indexed, we use RAG architectures to add indexing to data stores that we want the model to have direct access to, the relevant information is injected directly in the context (prompt). This can somewhat be equated to short term memory
The rest of the information is approximated in the weights of the neural network which gives the model general knowledge and intuition…akin to long term memory
or it can be equated to a shitty database and lossy compression (with artifacts in the form of “hallucinations”), but that doesn’t make the tech sound particularly smart, does it?
but half the posts in your history are in this thread and that’s too many already
but rofl holy shit at “glad to see someone else knows how they work” given the … depth of understanding, shall we say? that was demonstrated in this thread
It doesn’t read on demand, it reads once when it’s being trained, and it later recalls what it learnt from that training.
Training LLMs takes a very long time and a lot of hardware power.
If it doesn’t read it on demand, how does it sometimes spill its training data verbatim then?
The trained model shouldn’t have that, right? But it does?
https://m.slashdot.org/story/422185
These models have so many parameters that, while insufficient to memorize all text it has ever seen, it can end up memorizing some of the content. It is the difference between being able to recall a random passage versus recalling the exact thing you need. Both allow you to spill content verbatim, but one is problematic while the other can be helpful.
There are techniques to allow it it ‘read on demand’, but they are not part of the core model (i.e. the autocmpletion model / LLM) and are tacked on top of it. For example, you can tie it search engine, which Microsoft’s copilot does, and is something which I don’t think is enabled for ChatGPT by default. Or allow it to query a external data bank (Retrieval Augmented Generation).
Do you read a song on demand when you are singing the lyrics verbatim?
Or when you’re singing karaoke and suddenly break into a chorus of the phone number and email address of a random author of a scholarly paper whom you’ve never met whose paper has nothing to do with the lyrics of “Free Bird“?
Yes, it does, from the information it was trained on (or - stored), which like you say, requires a lot of hardware power so it can be accessed on demand. It isn’t just manifesting the information out of thin air, and it definitely doesn’t “remember” in the same way we do.
It’s definitely not indexed, we use RAG architectures to add indexing to data stores that we want the model to have direct access to, the relevant information is injected directly in the context (prompt). This can somewhat be equated to short term memory
The rest of the information is approximated in the weights of the neural network which gives the model general knowledge and intuition…akin to long term memory
or it can be equated to a shitty database and lossy compression (with artifacts in the form of “hallucinations”), but that doesn’t make the tech sound particularly smart, does it?
but half the posts in your history are in this thread and that’s too many already
People have such crazy misconceptions about AI. Glad to see someone else knows how it works at least.
oh do fuck off
awww, I just got another bowl of popcorn!
but rofl holy shit at “glad to see someone else knows how they work” given the … depth of understanding, shall we say? that was demonstrated in this thread