Technically right in that it doesn’t necessarily translate audio into text, but that’s hardly the point. The point is someone gives the LLM a giant table that directs its response.
It could be represented with a series of lookup tables, especially quantized LLMs. A series of inputs results in a specific output that gets passed to the next set of nodes. Repeat 7 billion times, and the final output from the last set of nodes is a set of token probabilities.
it’s a compressed lookup table. rather than there being one response for every input, the input is used as a seed to decompress relevant parts of the dataset, with some added randomness. you can even do it with gzip itself: https://nathan.rs/posts/gzip-lm
If you are giving the weight matrix to the model yourself, you are doing ML wrong. Machine’s supposed to “learn” the weights itself. That’s the entire point?
Dude… Why do you think the whole point is to have properly tagged data? Or why there were thousands of people working at Amazon Turk categorizing images and files for cents per document?
No. You still have to give it a starting point and the starting point is manually configured tables basically.
Technically right in that it doesn’t necessarily translate audio into text, but that’s hardly the point. The point is someone gives the LLM a giant table that directs its response.
? A neural network is not a lookup table.
It could be represented with a series of lookup tables, especially quantized LLMs. A series of inputs results in a specific output that gets passed to the next set of nodes. Repeat 7 billion times, and the final output from the last set of nodes is a set of token probabilities.
it’s a compressed lookup table. rather than there being one response for every input, the input is used as a seed to decompress relevant parts of the dataset, with some added randomness. you can even do it with gzip itself: https://nathan.rs/posts/gzip-lm
the linked paper is very good: https://arxiv.org/pdf/2309.10668
That’s like saying the neural network in your head has compressed your knowledge of language and just expands the relevant parts when needed.
yup
If you are giving the weight matrix to the model yourself, you are doing ML wrong. Machine’s supposed to “learn” the weights itself. That’s the entire point?
Dude… Why do you think the whole point is to have properly tagged data? Or why there were thousands of people working at Amazon Turk categorizing images and files for cents per document?
No. You still have to give it a starting point and the starting point is manually configured tables basically.