5 ms·
I don't think most of them have any kind of secret sauce. I think the founders hope to get bought out simply for being able to train "near-SOTA" LLMs. I guess a
by dauertewigkeit 3y ago
I don't think most of them have any kind of secret sauce. I think the founders hope to get bought out simply for being able to train "near-SOTA" LLMs. I guess achieving that level of skill and infra could be valuable enough to build upon.
- imtringued 3y agoThere was a guy who followed a tutorial about how to fine tune mistral with DPO, who has zero computer science skills and his model ended up at the top of the hugging face leader board among the opensource models with 7 billion parameters. Some random guy managed to outdo the creators of the LLM.
- joe_the_user 3y agoSure, that's also a factor but I'd say it reinforces my main point.
- DeepChill 3y agoGood point, so the only real differentiator would be the size & quality of the data being fed and the fine tuning done on the model? I wonder what else differentiates LLMs from each other
- Iulioh 3y agoAlignment and censorship ?
- pests 3y agoAlignment just means making it do what you want. LLMs just continue the sequence, the chat questions and response style we have now is an example of alignment (to what humans want).
- eru 3y agoAlignment can mean making sure your LLM doesn't continue the sequence in embarrassing ways, eg by spouting politically incorrect sequences of words (even though those might have been common in the training data).
- friendzis 3y agoIn what way does this do more good than harm?
- eru 3y agoIn the sense of people caring about their models not saying embarrassing things? Different people have different goals, and they don't necessarily align with yours.
- friendzis 3y agoSince the entity releasing the model obviously has certain goals aligning/censoring model in some ways is good for their particular short-term goal. In the grand scheme these alignments are harmful as they place a reality distortion field. Authors create model of what language is and then contort that model to fit an opinionated idea of what language should be. Smells a bit Orwellian, right?
- eru 3y ago> Smells a bit Orwellian, right? No, seems perfectly fine by me. You are already shaping your results by your selection of training data. Eg do you want to train a model that speaks English, or German, or both? Do you want to run your training data past a spam filter first? Do you want to do a character based model, or one of those weird encodings that is popular with LLMs these days? Doing some other procedures afterwards to make sure your LLM doesn't say embarrassing things is small fries by comparison. Also it's good practice for trying to get alignment with more important values (like "don't kill all humans") later when models might get powerful enough to be able to kill all humans. Playing some little games where OpenAI tries to keep you from making their model say embarrassing things, and people keep trying to make it say embarrassing things, is a good low stakes practice ground.
- llm_trw 3y agoAlso getting a golden ticket. Golliath 120b is still the best open source model and no one knows why since it's just two llama2 60b glued together.