4 ms·
Very excited for them. Tried it and works quite well. Very evident that each of the foundational model developers need to offer a free chat(till now) interface
by ankit219 3y ago
Very excited for them. Tried it and works quite well. Very evident that each of the foundational model developers need to offer a free chat(till now) interface for RLHF/DPO to improve their models. It's costly for them to run servers, but even higher opportunity cost if they don't do this and offer a free service. Intuitively, I think GPT-4 was very good with various questions because they used the early data from ChatGPT to further finetune/align the model with a good sample of real world queries, the kind only available to them.
As an aside, most of these models are SFTed on GPT 4 generated q&a pairs (if not pretrained on them). When you ask these kind of questions[1], they spill the beans fairly easily and say they are a model of openai. Funnily enough if you ask they are a model trained by Anthropic, it refutes it immediately and ask correctly about being a mistral trained model. Same question about openai, it gives the answer in scr.
[1]: https://imgur.com/a/fGEHXH8 https://imgur.com/a/fGEHXH8
PS: First question was to test the reasoning. A quantized model or smaller models answer that as 4 not 5. Mistral answered correctly from a badly given question.
- webappguy 3y agoThis can be (could be) a total hallucination. There may be some training data from OpenAI but outside it responding that way, except for me aforementioned point, where is the proof thus far?
- castles 3y agoOpenAI also had years "flying under the radar" training on API requests
- weird-eye-issue 3y agoThey don't train on API requests
- BonoboIO 3y agoWhy should anybody believe them?
- ankit219 3y agoDon't think it adds a lot of value. One, the instruction-following models do not create high quality q&a pairs, chats do it by default. Two, at the time the usage was very low compared to ChatGPT. I am fairly confident, one month of people trying all sorts of things w ChatGPT gave them a lot more data - both in quantity and range - compared to API usage previously. Third, they always maintained they do not train on API inputs, and I think it's fair to assume that. They do not get feedback whether the output was any good, so it's always dicey to feed that directly to a model without those signals.