Researchers have just explained why massive neural networks work so effectively. Deep networks possess enough capacity to memorize completely random noise. Yet, they still excel at making accurate predictions on unseen data. A new paper finally sheds light on this phenomenon. The empirical Neural Tangent Kernel (NTK) subtly divides the output.
RESEARCH
-
Technical Requirements for Evaluating AI Model Architecture
By
–
Thanks, but there are no open weights yet, right? Asking because it would be impossible to cover architecture details without open weights and/or a detailed technical report
-
MACE-Dance: Motion-Appearance Experts for Music-Driven Dance
By
–
MACE-Dance Motion-Appearance Cascaded Experts for Music-Driven Dance Generation
-
New Google Omni-model incoming at I/O, likely Veo 3.1 update
By
–
New Google Omni-model incoming! Probably announce during i/o (see you guys next week in person :)) Probably an updated version of Veo 3.1 (maybe even the next iteration) h/t Zachary on reddit
-
GenRobot Trains Robots via Real-Time Human Hand Observation
By
–
GenRobot Trains #Robots by Watching Human Hands in Real Time
— Ronald van Loon (@Ronald_vanLoon) 11 mai 2026
by @mvollmer1#AI #Robotics #MachineLearning #ArtificialIntelligence #ML #Technology pic.twitter.com/Ccddb7W79TGenRobot Trains #Robots by Watching Human Hands in Real Time
by @mvollmer1 #AI #Robotics #MachineLearning #ArtificialIntelligence #ML #Technology -
Early Feedback on a Highly Impressive Video AI Model
By
–
Sample video and early feedback 👀
— 🚨 AI News | TestingCatalog (@testingcatalog) 11 mai 2026
> I won’t lie, this is one of the best video models I have seen, maybe not *the* best, but a really strong performance. I was particularly impressed by the prompt adherence (except for the one shot with the missing centerpiece), the model… pic.twitter.com/sG58DXlswLSample video and early feedback > I won’t lie, this is one of the best video models I have seen, maybe not *the* best, but a really strong performance. I was particularly impressed by the prompt adherence (except for the one shot with the missing centerpiece), the model
-
Deconstructing Geoffrey Hinton’s Recent AI Perspectives
By
–
Receipts: https://
open.substack.com/pub/garymarcus
/p/deconstructing-geoffrey-hintons-weakest?r=8tdk6&utm_medium=ios
… -
DeepMind paper provides evidence for LLM training data regurgitation
By
–
Am old enough to remember when @GeoffreyHinton told me I was stupid for saying that LLMs regurgitate training data. He was wrong. LLM regurgitation is now one of the best-established findings in the field. Excerpt below from a new DeepMind paper; every single one of the
-
Debating the limits of self-play AI training in real-world environments
By
–
Really doubt what Hinton says here.
— Gary Marcus (@GaryMarcus) 11 mai 2026
Self-play for games like Go is not like the open-ended real world. https://t.co/6t5jUtajaVReally doubt what Hinton says here. Self-play for games like Go is not like the open-ended real world.