AI in 2020

Almost exactly 4 years ago I decided to dedicate my life to helping educate the world on Artificial Intelligence. There were hardly any resources designed for absolute beginners and the field was dominated by PhDs. In 2020, thanks to the extraordinary contributions of everyone in this community, all that has changed. It’s easier than ever before to enter into this field, even without an IT background. We’ve seen brave entrepreneurs figure out how to deploy this technology to save lives (medical imaging, automated diagnosis) and accelerate Science (AlphaFold). We’ve seen algorithmic advances (deepfakes) and ethical controversies (automated surveillance) that shocked the world. The AI field is now a global, cross-cultural movement that's not limited to academics alone. And that’s something all of us should be proud of, we’re all apart of this. I’ve packed a lot into this episode! I’ll give my annual lists of the best ML language and libraries to learn this year, how to learn ML in 2020, as well as 8 predictions about where this field is headed. I had a lot of fun making this, so I hope you enjoy it! Are you a total beginner to machine learning? Watch this: https://www.youtube.com/watch?v=Cr6VqTRO1v0 TWITTER: https://bit.ly/2OHYLbB INSTAGRAM: https://bit.ly/312pLUb FACEBOOK: https://bit.ly/2OqOhx1 WEBSITE: https://bit.ly/2OoVPQF Learn Clojure: https://clojure.org/guides/learn/syntax Learn Rust: https://www.rust-lang.org/learn Swift for Tensorflow: https://www.tensorflow.org/swift Learn Python: https://www.youtube.com/watch?v=T5pRlIbr6gg Learn PyTorch: https://www.youtube.com/watch?v=nbJ-2G2GXL0 Papers with Code: https://paperswithcode.com/ NeurIPS papers: https://papers.nips.cc/book/advances-in-neural-information-processing-systems-32-2019 Neural Tangents: https://github.com/google/neural-tangents#papers XAI: https://github.com/EthicalML/xai Quantization: https://pytorch.org/docs/stable/quantization.html Waymo Open Dataset: https://github.com/waymo-resear