If software is eating the world, artificial intelligence will devour it. Every field is already transforming into the computational version of itself, be it computational medicine, computational biology, computational physics, computational transport, and even art, fashion, and music. But while there are tons of new developments in AI every day, there's still a lot of friction in finding the right code and know-how to actually implement them. We faced this problem first-hand while working on machine learning and intelligent systems both in academia and industry. The status quo is a heavily fragmented, inefficient experience — which involves making lots of Google searches, poring through various papers and write-ups, trying to find relevant code implementations, often emailing authors and experts, and going through several social platforms in the hope of finding useful pointers. This seems absolutely nuts to us. It's a miracle anything good makes it out at all from research to