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Pretty strong evidence for the idea the that sufficiently advanced ML will be able to do a surprisingly large amount of new material science without experiment, extrapolating from the prior ones.

Emmett Shear x.com

Machine Learning ADME Models in Practice: Four Guidelines from a… | Ash Jogalekar

Ash Jogalekar linkedin.com

Advances in Financial Machine Learning

Marcos Lopez de Prado

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Cover of Advances in Financial Machine Learning

But there are already signs that AI can help. Research has successfully demonstrated that it is possible to correctly determine the most promising directions in science by analyzing past papers with AI, ideally combining human filtering with the AI software. And other work has found that AI shows considerable promise autonomously conducting

Ethan Mollick • Co-Intelligence: Living and Working With AI

Unpacking decentralized training

knower theknower.substack.com

logistic regression, K-nearest neighbors, support vector machine (SVM), decision trees, random forests, and so on. How can a data scientist possibly know which

Eric Redmond • Deep Tech: Demystifying the Breakthrough Technologies That Will Revolutionize Everything

🇨🇳Another great paper from a Chinese Lab. Scientific Discovery is going fully AI-native, and chemistry, physics, and biology won’t look the same after this. Shanghai AI Lab has dropped Intern-S1, It's a scientific multimodal MoE that reads images, text,... See more

Rohan Paul

x.com

Part of the challenge of “AI” is we keep raising the bar on what it means for something to be a machine intelligence. Early machine learning models have been quite successful in terms of real world impact. Large scale applications of machine learning today include Google Search and ads targeting, Siri/Alexa, smart routing on mapping applications,... See more

Elad Gil • AI Revolution - Transformers and Large Language Models (LLMs)

Machine learning is what you get when the unreasonable effectiveness of mathematics meets the unreasonable effectiveness of data. Biology and sociology will never be as simple as physics, but the method by which we discover their truths can be.