ChatGPT Is Great – We’re Just Using It Wrong - Deepstash
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Omniscient & Omnipotent? Yeah, No.

A common misconception about large language models like ChatGPT and its older brethren GPT3 and GPT2 is that they are some kind of “super Googles,” or digital versions of a reference librarian, looking up answers to questions from some infinitely large library of facts, or smooshing together pastiches of stories and characters.

They don’t do any of that – at least, they were not explicitly designed to.

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The Likely Next Word

A language model like ChatGPT, which is more formally known as a “generative pretrained transformer” (that’s what the G, P and T stand for), takes in the current conversation, forms a probability for all of the words in its vocabulary given that conversation, and then chooses one of them as the likely next word. Then it does that again, and again, and again, until it stops.

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Words, Not Facts

So ChatGPT doesn’t have facts, per se. It just knows what word should come next. Put another way, ChatGPT doesn’t try to write sentences that are true. But it does try to write sentences that are plausible.

And for a machine that is designed to produce strings of words that sound as good as possible in response to the words you give it – and not to provide you with information – that seems like the right use for the tool.

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CURATED BY

xarikleia

“An idea is something that won’t work unless you do.” - Thomas A. Edison

CURATOR'S NOTE

We should first understand what something does and then judge if it does it well.

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