AI Industry News
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Oscilar Agent Hub puts 30+ specialized agents behind fraud, credit, and compliance
Oscilar just shipped Agent Hub, a suite of 30+ AI agents built for one job: risk operations at financial institutions. Fraud, AML compliance, credit, onboarding, sanctions, disputes — each gets its own specialized agent, and they share signals and context with each other in real time instead of running as isolated point tools. ## The… Continue reading
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title: “Microsoft MAI-Thinking-1 outscores Claude Sonnet 4.6 in blind evals — trained without OpenAI’s data” date: 2026-06-03 tags: [model, microsoft, reasoning, api] Microsoft shipped its first fully self-built reasoning model at Build 2026, and the signal is hard to miss. MAI-Thinking-1 hits 97% on AIME 2025 and 94.5% on AIME 2026. In blind human evaluations… Continue reading
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Kore.ai Artemis ships a compiled ‘Agent Blueprint Language’ for governed enterprise multiagent systems
Kore.ai launched Artemis, a new-generation agent platform for building, governing, and optimizing enterprise AI agents. The headline feature is Agent Blueprint Language (ABL) — a compiled, declarative language that standardizes how agents, systems, and workflows are defined, validated, and governed. ## Why “compiled” matters Most agent platforms let you wire up workflows visually or in… Continue reading
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SciAtlas builds a large-scale knowledge graph to automate scientific research
SciAtlas, from UCL, is a large-scale knowledge graph aimed at automating scientific research — structuring the relationships across papers, methods, datasets, and findings so an AI system can navigate the literature the way a domain expert does. ## The problem Scientific literature expands faster than any human can track. Automated knowledge-graph construction is a hot… Continue reading
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Anthropic-Cybersecurity-Skills maps 754 security agent skills to MITRE ATT&CK, NIST, and 3 other frameworks
Anthropic-Cybersecurity-Skills is an open-source library of 754 structured cybersecurity skills that give an AI agent the workflows of a senior security analyst. It hit GitHub trending with 930 stars in a day. Apache 2.0, spanning 26 security domains. ## The framework mapping What sets it apart: every skill is mapped to five industry frameworks —… Continue reading
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Forsy turns your AI agent workflow data into a sellable asset — building the agent data economy
Forsy captures workflow data from the agents you already use — OpenClaw, Claude, Codex, Hermes — and turns it into structured, sellable data, with licensing and privacy built in. The pitch: real agent workflows are valuable training data, and you should be able to monetize yours. ## How it works Forsy tracks workflow data in… Continue reading
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Cohere Command A+ is its first fully Apache 2.0 model — 218B MoE with native citations, runs on 2 H100s
Cohere released Command A+ — a 218B-parameter sparse MoE model (25B active) under full Apache 2.0, the company’s first fully open-weight model. It’s tuned for complex reasoning, multimodal document processing, and agentic workflows, and it runs on a single NVIDIA B200 or just two H100s. ## Native citations The standout feature: when Command A+ retrieves… Continue reading
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Anthropic’s Project Glasswing has found 10,000+ critical vulnerabilities, partners report 10x bug-discovery gains
Anthropic shared a sweeping update on Project Glasswing — its AI-assisted security testing initiative powered by Claude Mythos. The headline number: more than 10,000 high- or critical-severity vulnerabilities uncovered across widely used software, with several partner organizations reporting bug-discovery rate gains of more than 10x after integrating AI into their testing workflows. ## The coalition… Continue reading
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NVIDIA debuts Nemotron 3 open models — Nano delivers 4x the throughput of Nemotron 2 for multi-agent systems
NVIDIA debuted the Nemotron 3 family of open models — Nano, Super, and Ultra — positioned as the most efficient open models for building agentic AI applications. The headline: Nemotron 3 Nano delivers 4x higher throughput than Nemotron 2 Nano, and the most tokens per second for multi-agent systems at scale. ## The architecture Nano’s… Continue reading
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Training Data turns microgames into a pipeline for collecting AI training data
Training Data launched on Product Hunt — an AI experience that collects training data through microgames. Players engage with small, game-like tasks, and their interactions become labeled data for training AI models. ## The data-flywheel angle The expensive input for most AI systems isn’t compute, it’s labeled data — especially human preference and interaction data.… Continue reading
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