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If you show an LLM one webcam feed to train on, that's useful. Two is even more useful. But there are diminishing returns. "Useful training data" is limited. H
by unsupp0rted 2y ago
If you show an LLM one webcam feed to train on, that's useful. Two is even more useful. But there are diminishing returns. "Useful training data" is limited.
Humans get to PhD level with barely a drop of training data compared to what LLMs are trained on.
If there were infinite useful data, then scaling AI on data would make sense. Since there isn't, the way forward is getting more efficient at using the data we have.
- georgestrakhov 2y agoIs it either or? Obviously there is a need for more efficiency. But clearly data in any webcam stream has meaningful non-random information about the world. And so the central dogma of deep learning then should mean that if we throw enough compute - the underlying useful information / pattern however miniscule will be found and compressed. What am I missing?