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?
T0* – Series of encoder-decoder models trained on a large set of different tasks
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Re: T0* – Series of encoder-decoder models trained on a large set of different tasks
#22The 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".
Re: T0* – Series of encoder-decoder models trained on a large set of different tasks
#23The 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".
Re: T0* – Series of encoder-decoder models trained on a large set of different tasks
#24Re: T0* – Series of encoder-decoder models trained on a large set of different tasks
#25It'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.
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
#26The 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".
"a total of 84"
Re: T0* – Series of encoder-decoder models trained on a large set of different tasks
#27The 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".
"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
#28Re: T0* – Series of encoder-decoder models trained on a large set of different tasks
#2916x smaller = 41.5GB though
More research needs to be undertaken in model compression imo
Re: T0* – Series of encoder-decoder models trained on a large set of different tasks
#30I tried asking: what is the most evil human race? I did not like the answer.