NVIDIA NemoClaw: Secure agent execution inside NVIDIA OpenShell with managed inference
NVIDIA has published NemoClaw, a TypeScript project on GitHub for running AI agents such as Hermes and OpenClaw more securely inside NVIDIA OpenShell with managed inference. The repository has accumulated over 20,000 stars, suggesting notable community interest. The project appears to be part of NVIDIA's broader NeMo ecosystem for enterprise AI agent deployment.
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Data Points: NemoClaw enterprise stack, GPT-5.4 mini/nano, Nemotron 3 Nano 4B, Midjourney V8, and Mamba-3
A multi-item roundup covers several AI developments: Nvidia unveiled NemoClaw at GTC 2026, an enterprise software stack integrating with OpenClaw to add security and governance for agentic deployments, with launch partners including Salesforce, Cisco, and CrowdStrike. OpenAI released GPT-5.4 mini and nano, smaller variants optimized for speed with benchmark results on SWE-Bench Pro and OSWorld-Verified, priced at $0.75 and $0.20 per million input tokens respectively. Nvidia also released Nemotron 3 Nano 4B, a hybrid Mamba-Transformer 4B parameter on-device model. Additional items cover Midjourney V8 alpha (5x faster, diffusion-only) and Mamba-3, a 1.5B state space model from CMU and Together.AI with improved accuracy over Mamba-2.
nanoclaw: lightweight containerized agent framework built on Anthropic's Agents SDK
nanoclaw is an open-source TypeScript project positioning itself as a lightweight, security-focused alternative to OpenClaw, running in containers. It integrates with WhatsApp, Telegram, Slack, Discord, and Gmail, and includes memory and scheduled job capabilities built on Anthropic's Agents SDK. The project has accumulated nearly 30,000 GitHub stars, suggesting significant community traction.
Hermes Agent Challenges OpenClaw on Token Usage Leaderboard; Agent Self-Improvement Highlighted
Hermes Agent, an open-source AI agent from Nous Research launched in February 2026, has surpassed OpenClaw on OpenRouter's daily token consumption leaderboard. Hermes Agent differentiates itself through a memory architecture and automatic skill-building capability using the SKILL.md format, enabling self-improvement as a core agentic feature. It supports local and cloud deployment, integrates with ~20 messaging services, and works with a wide variety of LLMs via the Agent Communication Protocol. The piece also covers Andrew Ng's commentary on Harvard's grade-capping policy, which is tangential to AI/ML.
Hermes Agent Surpasses OpenClaw in Daily Token Usage, Highlighting Self-Improving Agentic Capabilities
Hermes Agent, an open-source personal agent from Nous Research launched in February 2026, has overtaken OpenClaw on OpenRouter's daily token consumption leaderboard. It distinguishes itself through automatic skill creation (converting successful task completions into reusable SKILL.md instruction files), a two-tier memory architecture with intelligent deduplication and merging, and a Curator background process that manages skill lifecycle. The agent supports local or cloud deployment, integrates with ~20 messaging services, and works with a wide variety of LLMs, positioning it as a model-agnostic alternative in the emerging personal agent category.
DeerFlow 2.0 launches as open-source agent harness; Anthropic sues Pentagon over AI blacklist; Google releases Gemini Embedding 2
ByteDance released DeerFlow 2.0, an open-source agent harness built on LangGraph/LangChain that orchestrates parallel sub-agents with sandboxed Docker environments, progressive skill-loading, and persistent memory for complex workflows. Anthropic filed two lawsuits against the U.S. Pentagon contesting a supply-chain risk blacklist tied to its refusal to remove guardrails preventing Claude's use in autonomous weapons and domestic surveillance, with potential multi-billion dollar revenue impact. Google released Gemini Embedding 2, a multimodal embedding model unifying text, images, video, audio, and PDFs in a single vector space, succeeding the text-only predecessor. Meta acquired Moltbook, an agent-to-agent social platform built around the OpenClaw framework, while OpenAI hired OpenClaw's creator and acquired AI security testing platform Promptfoo.
NVIDIA NeMo Gym: framework for evaluating and improving models and agents using environments
NVIDIA's NeMo team has published a Python library called NeMo Gym on GitHub, designed to evaluate and improve models and agents through environment-based interaction. The repository has 941 stars with minimal recent traction (+1 today). It appears to be an RL-style evaluation and training harness within the NeMo ecosystem.
Serverless Inference with Hugging Face and NVIDIA NIM
Hugging Face and NVIDIA have partnered to offer serverless inference via NVIDIA NIM microservices on DGX Cloud infrastructure. The integration allows developers to run optimized model inference without managing GPU infrastructure, combining Hugging Face's model hub with NVIDIA's inference optimization stack. This represents an expansion of the existing Hugging Face–NVIDIA partnership into managed inference services.
Measuring Open-Source Llama Nemotron Models on DeepResearch Bench
NVIDIA evaluates its open-source Llama Nemotron models on the DeepResearch Bench, a benchmark designed to assess deep research agent capabilities. The post appears to report competitive performance of the Nemotron models in agentic research tasks. This is relevant to the ongoing development of open-weights models capable of multi-step research and reasoning workflows.