Google, NVIDIA and Microsoft also make their models freely available. Google already trained a model which is bigger than GPT-3.
There might be some delay, but no fundamental problem with it.
Fine-tuning the entire GPT-3 is impossible on a single GPU. But it's still possible to fine-tune specific layers. Plus, I'm sure somebody will release a distilled version of it which is more manageable.
Because they want to commercialize the model "to cover the costs of research", it's stated in their blog post FAQ[0].
>Google already trained a model which is bigger than GPT-3.
Source?, a fast Google search yielded no results and I'm curious.
They will probably release the baseline model, not model optimized for deployment. There are many optimizations possible such as precision reduction, pruning, distillation, and they don't have to share these optimizations.
> a fast Google search yielded no results and I'm curious.
List of pre-trained models on huggingface: https://huggingface.co/models
You can see some of them are prefixed with "google". Also ALBERT is from Google Research.
That's just natural language processing, I dunno what they have in other fields.
GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding (https://arxiv.org/abs/2006.16668)