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> Have you ever watched the original Superman movies and Clark talks with the AI hologram of his biological father from his home planet? You get that this only played out positively in the movie because the writers/director wanted it to play out that way, right?
In the Smallville TV show, the Jor-El AI was shown to have its own agenda, which at times was very much at odds with not-yet-Superman's goals and view points.
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I also get the vibe that digital cloning will be popular. Maybe some extremists will think its unholy and some addicts will lose sense of reality, but for the vast majority of people, I think it's just a user interface - maybe to some particular piece of information in the chatbot-as-librarian role, or puzzle boxes that eventually reveal information once you ask the right question, like Will Smith in I Robot. What I…
> I also get the vibe that digital cloning will be popular. I think it will end up just being boring. The sad reality is that no one really wants to talk to us, except for a few who are amazing poets or something. I think what’s more likely is to train models on all material created and ask useful questions for purposes of probate (“when did you buy the house”) because its faster and cheaper than manual research. Or…
> I immediately recognized this would be in extremely poor taste and removed the data. Enough on that topic! Poor taste for a blog post. But I wonder if LLMs could advance to a point where it might be therapeutic to have a conversation with a deceased loved one.
Could probably be just as dangerous as helpful. You work through some issues, maybe want to forgive or be forgiven to get closure and the LLM says f*k you, no.
* Reinforcement Learning from Human Feedback
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There’s also Ubik by Philip K. Dick where the recently deceased are able to communicate with the living AND aside from that also advertise a product.
I looked it up. Ubik was written earlier in 1969, than Neuromancer, which was written in 1984
We need to learn to let go. Chatting with a deceased loved one is basically equivalent to the ressurection stone in Harry Potter. A faint reflection which will drive people to insanity. This is not healthy at all.
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My naive intuition is that you'd want to train on the highest precision you have the horsepower for, and then after training, you might be able to get away with quantizing to a lower precision for inference. I would also expect that fp32 might be overkill, but that anything less than fp16 would start to show a noticeable loss in quality, especially in training. I can't imagine int8 being good at all. And I would thin…
https://github.com/ggerganov/llama.cpp/pull/1684 You are broadly better off running a larger, more quantized model, than a smaller model at a higher precision. A 65b parameter model with 2bit quantization still outperforms an fp16 30b parameter model in perplexity and qualitative testing. No one I know does fp32, there's no benefit. People train LoRAs at low precision regularly. The folks on /r/localllama are really…
Does all that apply to training as well, or just inference?
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https://github.com/ggerganov/llama.cpp/pull/1684 You are broadly better off running a larger, more quantized model, than a smaller model at a higher precision. A 65b parameter model with 2bit quantization still outperforms an fp16 30b parameter model in perplexity and qualitative testing. No one I know does fp32, there's no benefit. People train LoRAs at low precision regularly. The folks on /r/localllama are really…
That's really interesting to know. Kind of mind-blowing, tbh. Does all that apply to training as well, or just inference?