Meta Goes Fully Open Source With Muse Glimmer, a 30B Parameter AI Model for Consumer Hardware
Meta releases Muse Glimmer under Apache 2.0, its most permissive open-source license yet, enabling AI agents to run directly on laptops and PCs.
Explore the latest advances in AI, including machine learning, deep learning, natural language processing, and cutting-edge technologies
Meta releases Muse Glimmer under Apache 2.0, its most permissive open-source license yet, enabling AI agents to run directly on laptops and PCs.
Enterprises now average one AI agent per employee, with interactions growing 14x in six months. A new Opsin Labs report reveals most of these agents have far more access than they need, creating a governance crisis that has become a board-level issue.
Tencent Cloud's ADP 4.0 brings 40 system connectors, 150+ skills, and governance-first design to enterprise AI agents. As Forrester and Gartner warn that governance is the bottleneck, Tencent is betting the fix is infrastructure, not just better models.
IBM shares crashed 25%, erasing $67 billion in market value, after CEO Arvind Krishna admitted the company failed to adapt to the AI infrastructure boom. The same week, nearly 40 companies confirmed AI-driven layoffs.
Amazon Web Services has rolled out a suite of new tools designed to make enterprise AI agents more reliable, secure, and effective. Combined with a broader industry shift toward multi-model agent orchestration, this signals that 2026 is the year AI agents graduate from pilot to production.
Salesforce is acquiring AI agent platform Fin for $3.6 billion, marking one of the largest AI agent deals of 2026. Here is what the acquisition tells us about where enterprise AI is heading.
Discover how agentic AI is transforming enterprise automation in 2026. Learn about autonomous agents, multi-step workflows, and the future of human-AI collaboration.
Only 11% of AI agents reach production. Explore the critical challenges causing 89% failure rate and discover proven strategies to build production-ready autonomous agents.
Explore the evolution from MLOps to LLMOps and AgentOps. Learn when to use each framework, their key differences, and practical implementation strategies for AI operations.