Replying to Avatar Prisoner24601

This may be a silly question, but can someone explain how a large language model "learns" from sets of data?

I'm imagining a scenario where, lets say scientists that study a rare animals like the Sumatran rhino, could use an AI model and feed it daily reports for years, then the AI could majorly help to summarize in various ways all the data together to distill insights.

Is this possible with a large language model?

Can large databases be searched and summarized in this example?

Could existing databases be fed to AI models?

How do I go about getting and testing my own AI model to use for specialized training?

#asknostr #nostr #nostriches #plebs #plebchain #grownostr #ai
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cloud fodder 2y ago

I'm far from knowing how it works but my simple understanding is this:

The model is 'trained' by feeding it sentences and paragraphs. All it is doing when providing you an answer is determining the probability of the next word in the sentence.

So if the model has been fed, "what is a rhino? the rhino is green" 20 times, and "what is a rhino? the rhino is hungry" 10 times. Then you ask it "what is a rhino?" It'll say, the rhino is green.

It has been fed so many sentences that it almost seems like a human, but it is just guessing words.

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