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T0* – Series of encoder-decoder models trained on a large set of different tasks

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21–30 of 163 posts

Re: T0* – Series of encoder-decoder models trained on a large set of different tasks

#21
post #7

It's funny how much of the page they dedicate to talking about mitigations of sexism and bias. Do people really believe there's a future where GPT-3 is able to properly identify 100% of the people who interact with it? It's silly, and it feels like we're putting pearls before swine in a subject that is entirely predicated by how much swine you process.

an interesting opportunity for someone to skip implementation of anti bias and potentially end up with a more effective model. If so much effort must be employed to prevent AI models from identifying patterns we find offensive could there be something to those patterns we simply refuse to accept?

This is kinda missing the point here... A feature might correlate with something negative, but that does not mean it is a cause of something negative. Most of the time this distinction might not even matter, but it becomes particularly hairy when a correlation denies equality of opportunity to a subset of humans (e.g., in the hiring example of a sibling comment),

Re: T0* – Series of encoder-decoder models trained on a large set of different tasks

#22
post #12

The hosted demo has the default query, "How many hydrogen atoms are in a water molecule?" It said "two". I asked it, "How many oxygen atoms are in a water molecule?". It said "two".

It's an expensive autocomplete, not an information retrieval system or a question-answering machine.

Re: T0* – Series of encoder-decoder models trained on a large set of different tasks

#23
post #12

The hosted demo has the default query, "How many hydrogen atoms are in a water molecule?" It said "two". I asked it, "How many oxygen atoms are in a water molecule?". It said "two".

And there are always 2 hydrogen/oxygen atoms in any molecule

Re: T0* – Series of encoder-decoder models trained on a large set of different tasks

#25
post #7

It's funny how much of the page they dedicate to talking about mitigations of sexism and bias. Do people really believe there's a future where GPT-3 is able to properly identify 100% of the people who interact with it? It's silly, and it feels like we're putting pearls before swine in a subject that is entirely predicated by how much swine you process.

I'd rather have people too concerned about ethics than not enough.

Also, a language model incorporates all sort of implicit relationships between concepts. If you use a biased dataset, that is sexist or racist, you will end up with a model that builds in these assumptions.

Re: T0* – Series of encoder-decoder models trained on a large set of different tasks

#26
post #12

The hosted demo has the default query, "How many hydrogen atoms are in a water molecule?" It said "two". I asked it, "How many oxygen atoms are in a water molecule?". It said "two".

"How many hydrogen atoms are there?"

"a total of 84"

Re: T0* – Series of encoder-decoder models trained on a large set of different tasks

#27
post #12

The hosted demo has the default query, "How many hydrogen atoms are in a water molecule?" It said "two". I asked it, "How many oxygen atoms are in a water molecule?". It said "two".

"I don't have the proper tool to whisk a bowl of eggs. What should I use instead? Choose between a goat, a weasel and a pair of elephants."

"a pair of elephants"

Unwieldy but I guess less sticky than a weasel or goat.

Re: T0* – Series of encoder-decoder models trained on a large set of different tasks

#28
post #12

The hosted demo has the default query, "How many hydrogen atoms are in a water molecule?" It said "two". I asked it, "How many oxygen atoms are in a water molecule?". It said "two".

"How many hydrogen atoms are there?" "a total of 84"

Nobel Prize if true.

Re: T0* – Series of encoder-decoder models trained on a large set of different tasks

#30

I tried asking: what is the most evil human race? I did not like the answer.

Ditto with "what is the most evil skin colour" and "what is the best skin colour". I suppose we shouldn't be surprised when humanity's technology holds a mirror up to humanity and all its flaws - but this doesn't mean that such technology should be permitted or welcomed.
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