Towards Data Science

Why Decade-Old Residual Connections Still Power All of AI (And Why That’s a Problem)

For nearly a decade, this part of neural networks barely changed. DeepSeek is trying to reinvent it.

arXiv AI
Jul 2

Muon as a Residual Connection

arXiv:2607. 01124v1 Announce Type: cross Abstract: Muon has recently emerged as one of the most effective optimizers for training large neural networks, yet its empirical success has been explained from several different perspectives.

By Hao Huang
arXiv AI
Aug 6

The RAIL Principles for Neurosymbolic AI: Reasoning, Assurances, Interfacing and Learning

arXiv:2608. 04285v1 Announce Type: new Abstract: Neurosymbolic AI systems that integrate machine learning and symbolic reasoning are rapidly gaining attention.

By Agnese Chiatti, Michael Cochez, Cristina Cornelio, Sebastijan Dumancic, Artur d'Avila Garcez, Luis C. Lamb, Lia Morra, Mathias Niepert, Robert Peharz, Alberto Speranzon, Maarten Stol, Annette Ten Teije, Thiviyan Thanapalasingam, Frank Van Harmelen, Emile Van Krieken, Antonio Vergari, Benjie Wang