Earlier quoted context omitted.
Are there any TPUs that can be purchased off-the-shelf and then owned, like you can do with a CPU or GPU? Or are you just limited to paying rent to cloud providers and ultimately being at their mercy when it comes to pricing, ToS, etc?
No, but you probably aren't going to buy an A100 either, so it's a moot point.
GPT-3 is no longer the only game in town
211–217 of 217 posts
Re: GPT-3 is no longer the only game in town
#212Are we heading to the (distant) future where to make progress in any field you have to spend big $$$ to train a model?
We are already there. Machine learning is the flavor of A.I. that keeps business barriers of entry high. If we had invested in symbolic A.I., things would be different. A similar thing happens with programming language flavors. PHP lowers barriers of entry so it is discredited by the incumbents.
Re: GPT-3 is no longer the only game in town
#213Earlier quoted context omitted.
GPT-3 is a text generator, so i doubt you would get anything of use. You cant even supply such a large input to GPT-3.
It's pretty good at extending lists. That might require some sorting first.
Re: GPT-3 is no longer the only game in town
#214The future is not as dark as it seems because of the rat race of megacorps. You can use reduced versions of language models with extremely good results. I was involved in training the first-ever GPT2 for Bengali language, but with 117 million parameters. It took a month's effort (training + writing code + setup) and about $6k in TPU cost, but Google Cloud covered it. Anyway, it is surprisingly good. We fine-tuned the…
What library did you use for JAX on TPU? Also curious how much data you had?
We thought Haiku was cool, but none of us knew it, and learning resources were scarce. But we are very happy with Flax.
We used the Bengali subset of the mC4 dataset [0] for training the GPT-2 model.
Re: GPT-3 is no longer the only game in town
#215The future is not as dark as it seems because of the rat race of megacorps. You can use reduced versions of language models with extremely good results. I was involved in training the first-ever GPT2 for Bengali language, but with 117 million parameters. It took a month's effort (training + writing code + setup) and about $6k in TPU cost, but Google Cloud covered it. Anyway, it is surprisingly good. We fine-tuned the…
That is a fantastic result - nagging question - these work best on predictable things. How much of Bengali poetry is predictable?
Many language models do predict.
In this case, they either try to predict what the next word (or character, or sub-character in case of Chinese, Japanese, etc.- this is totally the decision of the DS) is , or what some "masked" word are.
w_i becomes w_(i-1) in the sequence
where w_i is the last word generated
The ones that are trained to be able to predict the next word are the ones that are good generators.Re: GPT-3 is no longer the only game in town
#216Earlier quoted context omitted.
That's the first time I've heard of a company being worried that their product is too good.
This is legitimately dangerous technology. It probably(?) wouldn't pass the Turing Test, but it would fool a lot of people.