“Attention Residuals” is now available on AlphaXiv! In standard transformer, every layer just inherits an equal sum of all earlier layers, so as models get deeper, useful computations get diluted instead of being selectively reused. The research team at @Kimi_Moonshot proposes
AI
-
Sakana AI Hosts Defense and Intelligence Domain Recruitment Briefing
By
–
We are hosting a recruitment briefing session specialized in the "Defense & Intelligence" domain at Sakana AI Why now, and why are we tackling this challenging issue? Join us to hear directly from Project Manager Sato, who is at the forefront, as he discusses its societal
-
T-Mobile Security Coverage Ensures Business Operational Continuity
By
–
Well-framed message, because it shifts the discussion from raw speed to operational continuity. T-Mobile points to a more concrete reality since security and coverage limits emerge exactly when business is most exposed. Solutions like SuperMobile make sense in this context,
-
AI Factories: From Training Models to Efficient Inference Everywhere
By
–
At this week’s NVIDIA GTC, much of the conversation will focus on the infrastructure powering the next wave of AI. One concept gaining traction is the idea of “AI factories.” Data centers designed to convert energy and data into intelligence at scale. Ahead of GTC, Alexis sat down with theCUBE Research for a panel to explore that idea and what it means for the future of AI infrastructure. Training builds the models. Inference delivers the value. Every recommendation, vision system, assistant, or autonomous decision happens at inference time. Which means the future of AI infrastructure will not just be about bigger training clusters. It will be about running inference efficiently, everywhere. Watch the conversation: eu1.hubs.ly/H0sHJZQ0 #AIInfrastructure #AIInference #EdgeAI #GTC
→ View original post on X — @axeleraai, 2026-03-17 09:16 UTC
-
AI Deep Learning Framework Advances Sustainable Bio-Oil Prediction
By
–
Thrilled to share that I’m a co-author of a newly published paper in Scientific Reports — a Nature Portfolio, Q1-ranked journal — highlighting the power of AI-driven innovation in sustainable energy systems. Our paper, “Deep learning enhanced prediction framework for bio oil
-
GeForce Now Gaming Service Update Requirements
By
–
J'ai geforce now, qu'ils m'obligent tout de suite !!!
-
User feedback on AI image generator performance and resource consumption
By
–
I would love it to consume even less browser resources and I am not particularly interested in the gallery. Just need an image generator. Yet, big kudos for making it already optimised. Much better than other similar ai video galleries from performance PoV.
-
Discussion on AI compute capacity and research sharing
By
–
Interesting idea, but the compute per lab will still be the same, and why would they share research with competitors?
-
OpenAI Introduces Subagents in Codex for Parallel Codebase Management
By
–
🚨 @OpenAI just launched Subagents in Codex, and it changes how we handle massive codebases.
— Charly Wargnier (@DataChaz) 17 mars 2026
You no longer have to rely on a single agent.
You can now split complex features across multiple specialized workers running in parallel 🔥
By spinning up Codex’s new custom subagents,… pic.twitter.com/4JXFeavgXA@OpenAI just launched Subagents in Codex, and it changes how we handle massive codebases. You no longer have to rely on a single agent. You can now split complex features across multiple specialized workers running in parallel By spinning up Codex’s new custom subagents,
-
MaxRL: Rethinking Reinforcement Learning Optimization
By
–
RL Isn’t Actually Optimizing What We Think, And That’s a Problem Come join us for this AI4Science talk: Maximum Likelihood Reinforcement Learning (MaxRL). In this session, the author of MaxRL @FahimTajwar10 will cover their paper that takes a step back and asks a fundamental