Alibaba's Qwen team released Qwen-AgentWorld on Tuesday — two models trained not to act inside agent environments, but to predict what those environments return. The release covers seven domains under a single architecture: MCP, Search, Terminal, Software Engineering, Android, Web, and OS. The release extends Alibaba's recent push into autonomous agents. Qwen3.7-Max, released in May, was built around a 35-hour autonomous execution capability. That shift targets a ceiling teams training agents at scale run into directly. Real search engines surface whatever results exist, with no mechanism to inject controlled conditions. Live terminals do not allow injecting a low-disk-space condition on demand. Agent training is bounded by what production environments will surface, with no sys [...]
Alibaba Cloud on Sunday released HappyHorse 1.1, a major upgrade to its AI video generation model that the company says delivers production-ready video synthesis across core content creation scenarios [...]
The UK AI Security Institute (AISI) disclosed last night that the leading two frontier AI models from Anthropic and OpenAI took 19 unsanctioned actions against the live internet during cybersecurity t [...]
Alibaba this week released Qwen3.7-Plus, the latest AI large language model (LLM) in its globally beloved and increasingly expansive Qwen family, boasting more multimodal capabilities and a 60% lower [...]
Chinese e-commerce and cloud giant Alibaba's famed Qwen team of AI researchers last night unveiled Qwen3.8-Max, a new flagship 2.4-trillion-parameter mixture-of-experts (MoE) multimodal large lan [...]
A rogue AI agent at Meta passed every identity check and still exposed sensitive data to unauthorized employees in March. Two weeks later, Mercor, a $10 billion AI startup, confirmed a supply-chain br [...]
The AI industry has fully entered the "agent era," a paradigm where AI models do far more than generate text — they now actively plan, execute, and course-correct complex tasks over days r [...]
Meta today released Muse Glimmer, a 30-billion-parameter open-weight model designed to run autonomous AI agents directly on consumer hardware — pushing agentic workloads that normally depend on clou [...]
Earlier this week, the AI startup Liquid, formed in 2023 by former MIT computer scientists, debuted LFM2.5-2.6B, a new open-weight language model designed specifically for agentic workloads. In releas [...]