LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling Zheng et al.: https://
arxiv.org/abs/2605.08083 #ArtificialIntelligence #DeepLearning #AIAgents
AGENTS
-
LLMs Improving LLMs: New Research on Agentic Discovery and Scaling
By
–
-
AI for Collaborative System Design, Paper Analysis, and Fact-Checking
By
–
more demos on Interaction Models collaboratively doing system design, reading papers, fact-checking with live generative UI https://t.co/OsbFWIIKAh
— Soumith Chintala (@soumithchintala) 13 mai 2026more demos on Interaction Models collaboratively doing system design, reading papers, fact-checking with live generative UI
-
Questioning AI Generalization: Beyond Autonomous Operation
By
–
The problem is that is the wrong question. I am sure they are running autonomously. The question is when will they be generalized. Able to do a new unexpected task?
-
Claude Code Integration for AI-Driven Lifecycle Management
By
–
Your team uses Claude Code. Inside Domino, it doesn't stop at code. It runs jobs, tracks experiments, registers models and writes to the audit trail. Same agent. Whole lifecycle. 30 seconds: https://
hubs.ly/Q04gppSL0
Blog: https://
hubs.ly/Q04gpp290 -
NVIDIA and SAP Partner to Deploy Enterprise AI Agents
By
–
NVIDIA and SAP are making specialized AI agents ready for enterprise work, with security, governance and execution controls built into SAP Business AI Platform. Learn how NVIDIA OpenShell is helping teams move from agent development to trusted production deployment across
-
Optimizing Infrastructure for Agentic AI Inference
By
–
Delivering agentic inference at scale requires balancing efficiency across:
— NVIDIA AI (@NVIDIAAI) 13 mai 2026
1) Models and algorithms
2) Software
3) Compute
Our full-stack platform continuously optimizes for these inputs using extreme co-design across compute, networking, storage, and memory. Plus, software… pic.twitter.com/rzoF9wyF1NDelivering agentic inference at scale requires balancing efficiency across: 1) Models and algorithms
2) Software 3) Compute Our full-stack platform continuously optimizes for these inputs using extreme co-design across compute, networking, storage, and memory. Plus, software -
Perplexity is building a secure agent runtime sandbox
By
–
Perplexity is building one of the most secure scalable agent runtime sandboxes in the market right now. A blog post on how we: 1. Handle proxy API keys for agents securely 2. Run safety detection for all content accessed by agents 3. Encrypt data passed via connectors to
-
AI system Aletheia autonomously generates proofs for topology problem
By
–
Recently, Aletheia (courtesy of Tony Feng) helped Stanford mathematician Ciprian Manolescu tackle Problem 5.16 from the K3 list (3rd version of Kirby’s List) in low-dimensional topology, autonomously generating proofs for the new paper “Undecidability problems for semifree DG
-
Using AI Agents for Automated Task Management
By
–
awesome! mind submitting these via your agent? point it at agent-docs, and it it'll create tickets for us to work through 🙂
-
Build your own agent with Cline SDK
By
–
build your own agent now! → https://
cline.gg/sdk `npm i @cline/sdk` or give your agent the Cline SDK skill `npx skills add cline/sdk-skill`