It is showing how you can get drastically better at deep meta-learning by being better at deep learning. But it does not really show how you can be better at deep meta-learning outside of the improvements in deep learning.
You can take any deep meta-learning algorithm, take the deep part in it, apply the improvements in deep learning from the last year and claim that you have improved on the deep meta-learning problem this year. Well yes, but actually also no.
It's like trying to find a new antibiotic, and the solution is throwing more existing antibiotics into the same pill. Well yes, it works, but it is also not exactly the problem.
It is showing how you can get drastically better at deep meta-learning by being better at deep learning. But it does not really show how you can be better at deep meta-learning outside of the improvements in deep learning.
You can take any deep meta-learning algorithm, take the deep part in it, apply the improvements in deep learning from the last year and claim that you have improved on the deep meta-learning problem this year. Well yes, but actually also no.
It's like trying to find a new antibiotic, and the solution is throwing more existing antibiotics into the same pill. Well yes, it works, but it is also not exactly the problem.
Don't get me wrong though, GPT-3 is amazing work.