optimate

Hi everyone!!! I recently launched an open-source library on github (https://github.com/nebuly-ai/nebullvm). It's growing super fast (700+ stars), but I can't get much feedback from github, and I'd like to ask for some feedback here. Nebullvm is open-source library takes your AI model as input and outputs an optimized version that runs 5-20 times faster on your machine. Nebullvm tests multiple deep learning compilers to identify the best possible way to execute your model on your specific hardware, without impacting the accuracy of your model. The goal of nebullvm is to let any developer benefit from deep learning (DL) compilers without having to spend tons of hours understanding, installing, testing and debugging this powerful technology. You can find more info https://github.com/nebuly-ai/nebullvm. And please let me know what you think

The situation is fairly simple. Your model could run 10 times faster by adding a few lines to your code, but you weren't aware of it. Let me expand on that. AI applications are multiplying like mushrooms, which is awesome As a result, more and more people are turning to the dark side, joining the AI world, as I did The problem? Developers focus only on AI, cleaning up datasets and training their models. Almost no one has a background in hardware, compilers, computing, cloud, etc The result? Developers spend a lot of hours improving the accuracy and performance of their software, and all their hard work risks being undone by the wrong choice of hardware-software coupling This problem bothered me for a long time, so with a couple of buddies at Nebuly (all ex MIT, ETH and EPFL), we put a lot of energy into an open-source library called nebul