Medicine's Machine Learning Problem - Boston Review

https://bostonreview.net/articles/rachel-thomas-medicines-machine-learning-problem/

Graph ML in 2022: Where Are We Now? | by Michael Galkin | Dec, 2021 | Towards Data Science

https://towardsdatascience.com/graph-ml-in-2022-where-are-we-now-f7f8242599e0

Zwift routes

https://zwiftinsider.com/wp-content/uploads/2021/11/zwift-routes-checklist-20211129.pdf

Penrose

https://penrose.ink/

Graph ML in 2022: Where are we now? | by Michael Galkin | Dec, 2021 | Medium

https://mgalkin.medium.com/graph-ml-in-2022-where-are-we-now-f7f8242599e0

[2111.14377] Collective Intelligence for Deep Learning: A Survey of Recent Developments

https://arxiv.org/abs/2111.14377

Category theory

https://people.math.harvard.edu/~mazur/preprints/when_is_one.pdf

Research

https://www.math3ma.com/research

[2110.10320] Frontiers in Evolutionary Computation: A Workshop Report

https://arxiv.org/abs/2110.10320

[0903.0340] Physics, Topology, Logic and Computation: A Rosetta Stone

https://arxiv.org/abs/0903.0340

To Understand Language is to Understand Generalization | Eric Jang

https://evjang.com/2021/12/17/lang-generalization.html

Tweet by elvis on Twitter

	elvis ⁦‪@omarsar0‬⁩ 🎓 Transformers Recipe 🎓 Transformers continue to advance the field of NLP and machine learning. Many students ask me how to learn about transformers so I've written an easy-to-follow guide with key study material. I hope it helps... more coming soon! github.com/dair-ai/Transf… pic.twitter.com/x6YEoSQUKB   12/18/21, 6:50 AM

Spiking Neural Networks | Simons Institute for the Theory of Computing

https://simons.berkeley.edu/news/spiking-neural-networks

MARKETWATCH: After a dazzling 2021, Apple and Tesla stocks are expected to be duds in 2022

After a dazzling 2021, Apple and Tesla stocks are expected to be duds in 2022
Here's the outlook for the 25 stocks that have contributed more than half of the S&P 500 index's gain this year

Read in MarketWatch: https://apple.news/Aexp6qN93SPG-aC5jCeO98A

Shared from Apple News

The Future of Artificial Intelligence is Self-Organizing and Self-Assembling – Sebastian Risi

https://sebastianrisi.com/self_assembling_ai/

Tweet by Tony Zador on Twitter

	Tony Zador ⁦‪@TonyZador‬⁩ Biological neural networks (BNNs) are much more energy efficient than artificial NNs. The human brain uses about 15-20W, whereas eg training a big ANN causes the lights to dim in Boston for a day or 2. Why?   12/11/21, 10:01 AM

Optimizing the synergy between physics and machine learning | Nature Machine Intelligence

https://www.nature.com/articles/s42256-021-00416-w

Tweet by Petar Veličković on Twitter

	Petar Veličković ⁦‪@PetarV_93‬⁩ The video of my lecture ⁦‪@Stanford‬⁩ Machine Learning with Graphs (CS224W; moderated by ⁦‪@jure‬⁩) is now live! 🎉 youtube.com/watch?v=aCUOAk… What does geometric DL (⁦‪@mmbronstein‬⁩ ⁦‪@joanbruna‬⁩ ⁦‪@TacoCohen‬⁩) tell us about GNNs' universality? I connect GNNs with (Group) CNNs and Equivariant MP. pic.twitter.com/3I522fhACd   12/8/21, 4:45 AM