Earlier quoted context omitted.
If it's indistinguishable, then how does it matter who/what it was written by?
Because I am far less likely to trust encyclopedic content written by an AI, which can lie so convincingly that it does not know that it is lying. I have even seen it generating fictional source references that are hard to verify. I just don't trust it.
Alpaca: A strong open-source instruction-following model
201–210 of 313 posts
Re: Alpaca: A strong open-source instruction-following model
#202Do we have some studies on the impact of extreme quantization on these models? In my understanding, the efforts to make them run in commodity hardware involves the quantization of the weights to 8 bits or even 4 bits. Is the model still reliable after this?
Re: Alpaca: A strong open-source instruction-following model
#203Earlier quoted context omitted.
I haven't seen anything official from OpenAI confirming that ChatGPT has fewer than 175B parameters, although it is a reasonable guess if you read between the lines of their statements. Given the author of that article is a CEO of an 'AI Ad Optimization Platform' I think that number is speculative at best.
ChatGPT is fine-tuned InstructGPT, which has 1.3B parameters, if I'm not mistaken. Reference for the former: https://www.technologyreview.com/2023/03/03/1069311/inside-s...
Re: Alpaca: A strong open-source instruction-following model
#204Earlier quoted context omitted.
Please don't take HN threads further into ideological flamewar. It's not what this site is for, and we have to ban accounts that do it repeatedly. If you'd please review https://news.ycombinator.com/newsguidelines.html and stick to the rules when posting here, we'd appreciate it.
Sorry if I made it worse, I really felt like people's opinions were being treated uncharitably, and I was trying to right it.
In terms of the site guidelines, "You're missing the point" is kind of a swipe and so should probably be dropped; "willfully" should definitely have been dropped because it's making a claim about negative intent that one can't actually know and such claims always land as an attack on the other person; and the last sentence was snarky and should have been dropped.
If one makes a habit of editing such things out of one's comments, one's substantive point will come to the fore more clearly, which benefits everyone. But it's not always easy in the moment!
Re: Alpaca: A strong open-source instruction-following model
#205Earlier quoted context omitted.
Please don't take HN threads further into ideological flamewar. It's not what this site is for, and we have to ban accounts that do it repeatedly. If you'd please review https://news.ycombinator.com/newsguidelines.html and stick to the rules when posting here, we'd appreciate it.
Ah! Yes, sorry, this is fair Dang. Happy to die on this hill today, as it were, will do better in future though. cheers.
Re: Alpaca: A strong open-source instruction-following model
#206What do they mean by instruction? Is it just regular LLM?
LLM just predicts the next token given the previous tokens(this can be trained without manual labelling by humans). Instruct GPT and ChatGPT use reinforcement learning from human feedback to align the model with human intents so it understands instructions. https://huggingface.co/blog/rlhf
Re: Alpaca: A strong open-source instruction-following model
#207Re: Alpaca: A strong open-source instruction-following model
#208They used OpenAI davinci to generate the dataset for instruction tuning. They mention one of the reasons this model is noncommercial is because OpenAI's terms of use prohibit developing models that compete with OpenAI. They also published the generated dataset. If one were to use this dataset to tune your own commercial model, would this be OK, or illegal? I would guess OpenAIs ToS no longer applies, as this is now A…
This model is for non commercial use only so it's unclear to me how it could compete commercially with OpenAI. Sure, you could decide to interpret "compete" in a way that makes it seem like this violates TOS, but the mom commercial restriction is a powerful counterargument too.
Re: Alpaca: A strong open-source instruction-following model
#209Is there anyway to use Google's Coral TPU PCIe Accelerator[1]'s to increase the inference performance of GPT models like this and Llama? [1] https://coral.ai/products/pcie-accelerator/
Re: Alpaca: A strong open-source instruction-following model
#210I am surprised that they were able to launch this in stanford's domain. They clearly broke TOS of both Facebook and OpenAI, and even admitted doing that. I would be happy if the research decides to ignore openAI and facebook's useless restrictions.