Our mission is to systemise the world's deep learning knowledge. By providing a central place and toolkit for people to learn and share the artefacts of this technology, we can expand the reach of deep learning so everyone can benefit from it. We're building Atlas so everyone can freely access the state of the art in deep learning.
We are a team of researchers and engineers from Cambridge. Our founders include an early developer of Wikipedia and an open source author of one of the most popular time series libraries for Python. We are backed by some of the world's most successful funds and entrepreneurs including early investors in Google and MySQL.
We serve the deep learning community and are committed to being as open as possible with our work so we can assist and learn with others.
To serve the community we need to learn about their needs as quickly as possible. We do this by swiftly building prototypes and measuring the response in the community.
We have strong opinions but evidence always wins. We aren't afraid to throw away old ideas in light of evidence, and we move onto the new best idea as soon as possible.
We’ve just released the new Papers With Code! Site now has over 950+ ML tasks, 500+ evaluation tables (including state of the art results) and 8500+ papers with code. Explore the resource here: https://t.co/stfzzn0IfM. Have fun!— Papers with Code (@paperswithcode) 1 February 2019
"Papers with code" gets a new revamp with over 950+ #MachineLearning tasks, 500+ evaluation tables and 8500+ papers with code. An incredible service developed by @Atlas__ML that has huge potential to transform the research ecosystem! https://t.co/aTScHYra2y#AI #ML #DataScience pic.twitter.com/pG0N0saMJX— The Institute for Ethical AI & Machine Learning (@EthicalML) February 5, 2019