11–20 of 238 posts
I’ve also replicated the work in OpenMPI ( from a thread on the llama.cpp GitHub repo ) and today I managed to get the 65B dataset operational on three pi4 nodes.
I’m not saying this as any achievement of mine, but as a comment on the current reality of reproducible LLM At home on anything you’ve got.
It really feels like this technique has arrived.
In case anyone is wondering, yes, there is a cost when a model is quantized. https://oobabooga.github.io/blog/posts/perplexities/ Essentially, you lose some accuracy and there might be some weird answers and probably more likely to go off the rail and hallucinate. But the quality loss is lower the more parameters you have. So for very large model sizes the differences might be negligible. Also, this is the cost of in…
What I find more stunning is what this implies going forward. If tech advances as it tends to do then having a 200bn model fit into consumer hardware isn't that far away. Might not be AGI but I think cliched as it is that would "change everything". If not at 200 then 400 or whatever. Doesn't matter - the direction of travel seems certain.
Basically Ray Kurzweil's argument, he's been saying $1000 worth of compute will be able to match human performance around 2029 for decades now.
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Basically Ray Kurzweil's argument, he's been saying $1000 worth of compute will be able to match human performance around 2029 for decades now.
First, there has to be something capable of matching human performance at a much higher cost. This is still just spicy autocomplete.
Bah. We still haven't equaled the rude and hateful AI achieved in a microcomputer in 1981. https://scp-wiki.wikidot.com/scp-079 >
We can keep reaching for that rainbow.
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First, there has to be something capable of matching human performance at a much higher cost. This is still just spicy autocomplete.
Humans just do spicy autocomplete too.
Earlier quoted context omitted.
First, there has to be something capable of matching human performance at a much higher cost. This is still just spicy autocomplete.
Humans just do spicy autocomplete too.
Earlier quoted context omitted.
Humans just do spicy autocomplete too.
No they don't. You're "just" doing what everyone else in the past has done with the brain/human intelligence and using the latest technology as a metaphor without realizing it.
Take any metaphor you want, it’s the same outcome: we may all be philosophical zombies.
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Humans just do spicy autocomplete too.
No, a human isn't born with a set of knowledge like a freshly trained LLM, keeping the model fixed and responding to input. The analog to the model changes based on the human's experience. Just making bigger and bigger LLMs won't give you this.