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webAI Releases TwIL-8B, an 8.8B Reasoning Model Scoring 98.2 on MATH-500

webAI has released TwIL-8B, an 8.8B reasoning model for math, code and instruction following. The TwIL-8B reasoning model is post-trained from IBM’s Granite 4.2 8B. Weights are on Hugging Face under a non-commercial license. webAI’s launch post frames the pitch around cost per task, not raw scale. The 4-bit build is 4.98 GiB, sized for

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OpenAI Introduces Pando: A Git Backend That Cuts Median Push Latency ~80%

OpenAI has introduced Pando, a new Git backend that now serves all development in its monorepo. The OpenAI Pando Git backend keeps the standard Git client and protocol. Engineers and Codex agents still run git push and git fetch as before. Only the server changed. OpenAI team reports median push latency fell nearly 80%. Pando

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NVIDIA Releases Auto Ontology: An Open Semantic Layer That Grounds AI Agent SQL

NVIDIA has released Auto Ontology, an open library under the Apache 2.0 license. NVIDIA Auto Ontology is a semantic layer framework that builds a context layer from enterprise metadata. Agents use that layer to write SQL against certified business definitions. The repository states the problem plainly: a fast revenue answer is worthless if the number

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DeepSeek Open-Sources dsh-superagent, a Router-Worker Coding Agent

The DeepSeek Harness team just released dsh-superagent, an MIT-licensed research prototype. DeepSeek dsh-superagent is a proactive coding agent for one GitHub repository. It is packaged as a bundle for DeepSeek Harness. It listens to GitHub and, optionally, Feishu. It turns allowed requests into parallel work items, each in its own agent session. The release shipped

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Vercel Labs Open-Sources agent-desktop for Agent Computer Use

Vercel Labs has released agent-desktop, an open-source CLI for AI agent computer use on macOS, Windows and Linux. agent-desktop reads each app through the operating system’s accessibility tree, not through screenshots. An agent gets a JSON snapshot with a ref for every element it can act on. Version 1.0.2 shipped on October 30, 2026, under

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Anthropic Launches OSS Scanner, a Free AI Vulnerability Scanner

Anthropic has launched OSS Scanner, a free, opt-in vulnerability scanner for critical open-source projects. The Anthropic OSS Scanner runs the company’s strongest models, including Claude Mythos, against enrolled codebases. Reports go straight to maintainers without human review. That trade delivers faster findings, but shifts triage work onto project teams. 11 days after the October 8

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Microsoft Open-Sources Agensh: A Multi-Agent Harness for 1,024 Agents

Microsoft Research has open-sourced Agensh, a decentralized harness for large teams of coding agents. The Agensh multi-agent harness removes the central orchestrator that most agent frameworks depend on. Every worker picks its own sub-task, shares findings and merges code into a common Git repo. On ProgramBench, the team scaled the setup from 1 agent to

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Cognition Open-Sources an Agent Plugin that Helps Secure Systems against Recent Cybersecurity Threats

Cognition has released the Devin Vulnerability Fixes plugin, a free, open-source set of agent skills. It targets three critical remote code execution (RCE) advisories. They cover PHP2Shell, the Node.js October 21, 2026 security release and a CVSS 10.0 self-managed GitLab bug. The skills run in Devin and in any coding agent that reads SKILL.md files.

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NVIDIA Nsight Python Tutorial: How to Profile GPU Kernels

In this tutorial, we implement on Nsight Python, NVIDIA’s open-source Python interface to its kernel profilers. Instead of running a script under the Nsight Compute command line and digging through a report afterward, we mark the code we care about with nsight.annotate, decorate a benchmark function with nsight.analyze.kernel, and get back a pandas DataFrame of

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Google Cloud Ships llm-d 1.0 With Cache-Aware Routing for TPU and GPU Fleets

Google team have released llm-d 1.0, the first stable version of its distributed inference stack. This open-source, Kubernetes-native layer turns vLLM or SGLang model servers into one coordinated pool. They released it at the PyTorch Conference North America. It targets self-hosted agent and RL workloads, where round-robin load balancing breaks down. TL;DR A serving stack:

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