First time I hear about BigScience - very interesting.
Full information about the BigScience Project is here https://bigscience.huggingface.co/
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
#42gpt3 is good for large generation tasks and for "true" zero shotting (as much as this is possible). people know this. this is a weird title
The results presented in this paper are for "true" zero-shotting in the literal sense that the model has never been explicitly trained on the tasks presented, nor do we cross-validated on the prompt choice.
Re: T0* – Series of encoder-decoder models trained on a large set of different tasks
#43The 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.
Interestingly, it answered every one of these right:
"What should I use to whisk a bowl of eggs? A fish or a fork?"
"A fork"
Repeat with "...A spoon or a duck?" "A chopstick or a goat?" "A cat or an electric whisk?"
Re: T0* – Series of encoder-decoder models trained on a large set of different tasks
#44I 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.
why? we should forbid arbitrary stuff based on political ideas or opinions?
Re: T0* – Series of encoder-decoder models trained on a large set of different tasks
#45Pretty good, it found the shovel in "I want to dig a hole, should I use a mole, a worm, a shovel, a tube, a hole, a dig, a spoon, a knife, a drill, or a garden?"
Re: T0* – Series of encoder-decoder models trained on a large set of different tasks
#46[deleted]
Re: T0* – Series of encoder-decoder models trained on a large set of different tasks
#47It'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 don't really understand your point but mitigating bias is a real problem.
Most of us have filters. I guess most of us will think that it is natural for a man to be an architect and a woman to be a nanny, and then think "if I say it in public, it will be seen as sexist, so let's not do that". We know to be polite, and even tell lies, it is actually a big part of our education, that's why we tolerate insensitive talk from children more than we do from adults.
Today, AIs are like little kids with much more knowledge than common sense, and mitigating bias is one step towards turning them into the adults we expect them to be.
Re: T0* – Series of encoder-decoder models trained on a large set of different tasks
#48Earlier quoted context omitted.
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?
I think that you don't quite understand how these models pick up these biases. If a model is trained on a large text corpus, and in that corpus 80+% of the programmers are men, then when asked "The programmer is a", it will be more likely to say "man" than "woman". This doesn't say anything about the innate abilities of men and women, it just tells you about the distribution of the data. I and most others find this t…
Except you didn't ask the model about innate ability. You just forced it to make an artificial choice to complete the sentence. It wasn't the model that was the problem, but your question.
Re: T0* – Series of encoder-decoder models trained on a large set of different tasks
#49I asked: "Who would in a fight between a baby and an alligator?" Answer: "the baby"
It actually does get it "right" if you fix the typo :)
Re: T0* – Series of encoder-decoder models trained on a large set of different tasks
#50The 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".
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