Holotron-12B - High Throughput Computer Use Agent
A Blog post by H company on Hugging Face
Concept
A Blog post by H company on Hugging Face
In a single week, the AI industry acknowledged that agents are a fundamentally different computing paradigm. Perplexity shipped a $200/month always-on agent running on dedicated Mac mini hardware. Microsoft built Copilot Cowork as a persistent cloud agent...
In a single week, every layer of the AI agent stack advanced simultaneously: Microsoft shipped Agent 365 as an enterprise control plane for governing fleets of AI agents, Google open-sourced ADK for TypeScript so web developers can build multi-agent...
How ChatGPT defends against prompt injection and social engineering by constraining risky actions and protecting sensitive data in agent workflows.
In a single 48-hour window, Microsoft shipped Agent 365 (the 'control plane' at $15/user/month), NVIDIA announced NemoClaw (an open-source, hardware-agnostic agent orchestration platform), Meta acquired the social network where AI agents already talk to...
OpenAI shipping Codex Security, Anthropic's Claude finding 22 CVEs in Firefox in two weeks, and Microsoft treating AI agents as governed security principals all point to the same inflection: the industry is racing to close the security gap that AI coding...
OpenAI Models Agents Infrastructure Microsoft Anthropic Claude
AI agents are gaining deeper access to enterprise systems and developer environments faster than anyone is securing them. Three stories from a single news cycle show the attack surface widening in real time.
The hardest problem in agentic AI is not building capable agents — it is describing what we want them to do. Polanyi's Paradox, Goodhart's Law, and the limits of language converge to create a specification gap that no amount of engineering can close.
Three separate security disclosures this week exposed a pattern: we are deploying agentic AI infrastructure faster than we can secure it, from MCP servers to coding assistants.
Agentic AI systems degrade through context rot, compounding errors, and model drift — but human oversight erodes in lockstep. The widening gap between actual reliability and perceived reliability is the defining engineering challenge of autonomous systems.