I see Julia and eventually Mojo gaining more adoption than anything else, this without taking into account that finally JIT efforts have started to be taken more seriously by the community after PyPy feeling quixotic for so many years.
There are also the JIT GPU efforts from Intel and NVIDIA into their APIs.
Personally I would like to see more Java and .NET love, however dynamic languages loved by the research community is where the game is at, also the reasoning behind Mojo, after the Swift for Tensorflow failure.
Naturally kudos to the Arraymancer effort, the more the better.
Mojo is AOT not JIT or is there are some sort JIT in mojo? (I'm not up to date with new development there)
I feel like JIT is just kinda bad for Deep learning in most cases you want to "compile and optimise" your graph before run and load it fast for running/training.
There are also the JIT GPU efforts from Intel and NVIDIA into their APIs.
Personally I would like to see more Java and .NET love, however dynamic languages loved by the research community is where the game is at, also the reasoning behind Mojo, after the Swift for Tensorflow failure.
Naturally kudos to the Arraymancer effort, the more the better.