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That's because these things are way more than word prediction. Their job is 100 percent to predict the next word, but saying that hides what you have to do in
by bioemerl 4y ago
That's because these things are way more than word prediction.
Their job is 100 percent to predict the next word, but saying that hides what you have to do in order to predict the next word
In a factual database? You have to repeat facts.
In a logical database? You have to learn logic.
In a database containing only good chess moves? You have to learn to make good chess moves.
Train any AI model in a strong enough way and it will pick up donation knowledge along the way. Yes, it's predicting words, but it's using that knowledge to do it.
It's by no means perfect, but do not underestimate the potential here, and remember that reductive definitions (it's just x) can make most great things seem bad or mundane.
- abm53 4y agoRight, it’s (very roughly speaking) an approximation to an algorithm which maximises the probability of the entire response by factorising the distribution as a sequence of conditional distributions. If the approximation works, and the training data is coherent, it will produce coherent responses. The surprising thing to me is that this does work so much of the time.