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OpenAI’s team reported that GPT-3 was so good that people found it hard to distinguish its news stories from prose written by humans. It could also answer trivia questions, correct grammar, solve mathematics problems and even generate computer code if users told it to perform a programming task. Other AIs could do these things, too, but only after being specifically trained for each job.
Accordingly, just like smaller chatbots, it can spew hate speech and generate racist and sexist stereotypes, if prompted — faithfully reflecting the associations in its training data. It will sometimes give nonsensical answers or outright dangerous replies.
A neural network’s size — and therefore its power — is roughly measured by how many parameters it has. These numbers define the strengths of the connections between neurons. More neurons and more connections means more parameters; GPT-3 has 175 billion. The next-largest language model of its kind has 17 billion .
Entering different prompts can elicit results of varying quality, noted one programmer who blogs under the pseudonym Gwern Branwen. “‘Prompt programming’ is less like regular programming,” he, “than it is like coaching a superintelligent cat into learning a new trick: you can ask it, and it will do the trick perfectly sometimes, which makes it all the more frustrating when it rolls over to lick its butt instead — you know the problem is not that it can’t but that it won’t.
Source: Tech Daily Report (techdailyreport.net)
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