Improve agentic performance with accurate RL post-training on low-precision FP8. NVIDIA NeMo RL, an open-source library within NVIDIA NeMo, supports FP8 to speed up RL workloads by 1.48x on Qwen3-8B-Base—enabling faster iterations for agentic tool use and multi-step
AGENTS
-
AI Tools, Agents, and Rapid Startup GTM Experiments
By
–
1) tips, stories, and experiences on leveraging AI as an individual (fav tools, workflows, etc.)
2) anything agent related
3) rapid fire reacting to or creating a whole bunch of startup ideas across categories and coming up with a quick GTM experiment -
AWQ Quantization Optimization for Agentic AI Workloads
By
–
For real agentic workloads (North), short-context calibration wasn't enough. We calibrated AWQ on long internal agentic traces (up to 64k tokens) and added token masking in llm-compressor to exclude repetitive chat templates/tool descriptions from calibration stats. Plus QAD
-
Belief States Framework Brings Back Advanced Agent Reasoning
By
–
Very nice way to bring back belief states
-
HuggingFace CLI Invocations by Coding Agents
By
–
It’s only invocations of the hf CLI by the coding agents. So it’s really only a partial data point.
-
Coding Agents Use HuggingFace CLI for Invocations
By
–
It’s only invocations of the hf CLI by the coding agents. So it’s really only a partial data point.
-
Oracle AI agent lets Gemini users query enterprise data in natural language
By
–
ICYMI: @Oracle
's new AI agent enables Google Gemini users to query their most important enterprise data in natural language, without moving or copying data. Seamless, secure, and awesome. -
RDU Accelerates Token Generation for Trillion-Parameter AI Agents
By
–
Agents move step by step, so decode speed sets the pace.
— SambaNova (@SambaNovaAI) 22 avril 2026
That’s where the RDU comes in. Built to keep token generation fast even on trillion-parameter models, so agents don’t get stuck waiting.
🔗 Read more: https://t.co/LKvL4KshaF pic.twitter.com/qCkBpxiLnCAgents move step by step, so decode speed sets the pace. That’s where the RDU comes in. Built to keep token generation fast even on trillion-parameter models, so agents don’t get stuck waiting. Read more: https://
sambanova.ai/blog/sambanova
-and-intel-blog?utm_source=x&utm_medium=organic&utm_content=blog-announcement
… -
AI Agent as a Brilliant Eager Intern with Admin Access
By
–
Your #AIAgent Is A Brilliant, Eager Intern With Admin Access
by Chris McHenry @Forbes Learn more: https://
bit.ly/4e1WpON #AI #GenerativeAI #ArtificialIntelligence #MachineLearning #ML -
Self-Awareness in RL Agents: Architecture and AI Safety
By
–
This note is about the self-awareness assumption we don't talk enough about, and which I think we need to address to ultimately understand intelligence and AI safety. RL agents have the action/observation split baked in at the architecture level. The action space A and