While PyTorch is obviously the future in the short term, it will be interesting to see how this space evolves.
Before Tensorflow, people (myself included) were largely coding all of this stuff pretty manually, or with the zoo of incredibly clucky homemade libs.
Tensorflow and PyTorch made the whole situation far more accessible and sane. You can get a basic neural network working in a few lines of code. Magical.
But it's still early days. George Hotz, author of tinygrad[0], a PyTorch "competitor", made a really insightful comment -- we will look back on PyTorch & friends like we look back on FORTRAN and COBOL. Yes, they were far better than what came before. But they are really clunky compared to what we have today.
What will we have in 20 years?
[0] https://github.com/geohot/tinygrad, https://tinygrad.org
Before Tensorflow, people (myself included) were largely coding all of this stuff pretty manually, or with the zoo of incredibly clucky homemade libs.
Tensorflow and PyTorch made the whole situation far more accessible and sane. You can get a basic neural network working in a few lines of code. Magical.
But it's still early days. George Hotz, author of tinygrad[0], a PyTorch "competitor", made a really insightful comment -- we will look back on PyTorch & friends like we look back on FORTRAN and COBOL. Yes, they were far better than what came before. But they are really clunky compared to what we have today.
What will we have in 20 years?
[0] https://github.com/geohot/tinygrad, https://tinygrad.org