3 ms·
It might look like that from the outside, but in practice I'd say even in 2023 most things are done with PyTorch/TensorFlow on Nvidia GPUs. When you see a new
by belval 4y ago
It might look like that from the outside, but in practice I'd say even in 2023 most things are done with PyTorch/TensorFlow on Nvidia GPUs.
When you see a new compiler/runtime, it usually impacts deployment and optimization post training (TensorRT, FasterTransformers, TVM, OpenXLA) and/or target new specialized silicon (AWS Inferentia and Trainium, Google's TPUs, and others).
So to answer succinctly:
> How do I start AI/ML in 2023? And then what?
You implement your model in PyTorch, you train on Nvidia A100 and you deploy with the framework that gives you the best speedup for your architecture.
- sharemywin 4y agoIt also depends on what your trying to do. if your just trying to learn the "basics" I would argue use google colab or something similar to get your feet wet. it's also a good way to learn python Also you might look at huggingface or model zoo for existing models. It feels alot like early does of public apis. Where you can do alot of cool things with apis and mashups.