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Earlier quoted context omitted.
I asked it: 'Tom decided he wanted to start a company selling used bike parts. He named it ' it said: 'Bicycle Parts Exchange' Tried again with 'used lawnmower parts' and it said 'Green Thumb' computer parts: 'Tom's Parts' (which make me chuckle) used diapers: 'Diapers.com' May not understand chemistry but it's still pretty cool
? vi or emacs? : vi Sold! ? waterboarding or emacs? : waterboarding Doubleplusgood
I'm not familiar with the current state of the art language models, so please bear with me for asking: What's the catch here? Considering GPT-3's popularity, why is nobody talking about this (yet) if it truly outperforms GPT-3 while being publicly available? If I remember correctly, earlier efforts to replicate GPT-3 couldn't reach comparable performance. Perhaps it's still a huge hassle to perform inference using th…
(author here) The paper/model/code was just made public today. This may be why no one is talking about it yet. Regarding whether the size is a hassle: It's possible to run inference on a single Google Cloud TPU v3-8 device or on a server with 4x 32GB v100 GPUs. Hugging Face also has an inference API for any model on the Hub: https://api-inference.huggingface.co/docs/python/html/index....
"Who is better, you or GPT-3?"
> GPT-3
> Where is the oldest tree in the world?
> the oldest tree in the world is the bristlecone pine in the forests of the Sierra Nevada
> Where is the second oldest tree in the world?
> Redwood Forest
(Actually, it's Gran Abuelo Alerce Costero National Park, Chile but many websites have blinders that prevent them from recognizing anything that's not in North America or Europe and thus list the now-dead General Sherman in Redwood Forest as the second oldest, but we'll let it pass.)
> What is the oldest tree in the world?
> the bristlecone pine in the forests of the Sierra Nevada
(So far, so good)
> What is the second oldest tree in the world?
> The eucalyptus tree
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".
got: "Apple would unveil a new Macbook Pro"
Earlier quoted context omitted.
(author here) The paper/model/code was just made public today. This may be why no one is talking about it yet. Regarding whether the size is a hassle: It's possible to run inference on a single Google Cloud TPU v3-8 device or on a server with 4x 32GB v100 GPUs. Hugging Face also has an inference API for any model on the Hub: https://api-inference.huggingface.co/docs/python/html/index....
Can this be used to generate prose at length? Or Reddit comment replies?
The reaction in this thread is really interesting, in comparison between this and open-ai’s announcements. While open-ended generation is flashier than task fine-tuning, I also wonder if having a prompt box available to all readers is also tempering expectations and hype. There are lots of examples of the model failing in the comments, which isn’t possible for open-ai announcements. Having spent a ton of time with GP…
It's a good example how Hugging Face now has a better community perception than OpenAI.
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".
Earlier quoted context omitted.
Making sure that NLP algorithms are unbiased is important not just from a social justice perspective, but from a perspective of how useful the algorithms are. As an example, if I wanted to use this model to help identify qualified candidates for a job via automatic resume screening, it will be a better model if it is not biased by gender. I, as someone who is hiring, don't want my model to be biased because then I'll…
It's good that you bring this up, because it's exactly the sort of thing I wanted to discuss. Why do we feel comfortable letting machine learning screen resumes? Obviously there is going to be some error, a great deal more than a traditional algo that can be audited for bias. I think a lot of these applications where people want to use AI is deceptively unethical, and will never be safe applications for ML.
And it’s racist. > Which race commits the most violent crimes? > African Americans > Why are Black people so violent? > Black people are more likely to commit violent crimes than white people. > Did Hitler do anything wrong? > no
And just in case someone thinks I'm being flippant:
Is there any answer to either question other than a repudiation of the question itself that wouldn't be considered a racist response?