Breaking Symmetry in Machine Learning, Mapping Placenta Histology with Deep Learning

Discover the role of symmetry breaking in machine learning and the groundbreaking research on equivariant functions. Also, explore how deep learning with HAPPY is mapping cell-to-tissue graphs across human placenta histology. Plus, learn about TOXCL, an AI framework for detecting and explaining implicit toxic speech. And, find out how scientists are using AI to make beer taste even better.

Sources:
https://www.marktechpost.com/2024/03/27/the-role-of-symmetry-breaking-in-machine-learning-a-study-on-equivariant-functions-and-e-mlps/
https://www.nature.com/articles/s41467-024-46986-2
https://www.marktechpost.com/2024/03/27/toxcl-a-unified-artificial-intelligence-framework-for-the-detection-and-explanation-of-implicit-toxic-speech/
https://www.theguardian.com/technology/2024/mar/26/ai-beer-taste-better-belgium-scientists

Outline:
(00:00:00) Introduction
(00:00:49) The Role of Symmetry Breaking in Machine Learning: A Study on Equivariant Functions and E-MLPs
(00:04:25) Mapping cell-to-tissue graphs across human placenta histology whole slide images using deep learning with HAPPY
(00:08:26) TOXCL: A Unified Artificial Intelligence Framework for the Detection and Explanation of Implicit Toxic Speech
(00:10:54) Scientists turn to AI to make beer taste even better