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Microsoft has just released FARA-7B, a lightweight yet powerful computer-use AI agent that can run full desktop tasks locally with ultra-low token cost — and it’s putting serious pressure on cloud-heavy systems like OpenAI’s agents. At the same time, MBZUAI introduced PAN, a next-generation world model with persistent memory that maintains a continuous internal state, allowing long-horizon simulations that don’t reset like traditional AI videos. PAN combines Qwen2.5-VL reasoning, a Wan2.1 video decoder, and a chunk-based causal refinement loop to keep objects and environments stable over time. In this video, we also break down: • Google Gemini’s interactive images turning static diagrams into tappable learning tools • Perplexity AI’s new shopping assistant that remembers your habits and guides real purchases • Alibaba’s Quark S1 and G1 AI glasses, bringing Qwen models into everyday wearable life Together, these breakthroughs signal a major shift in AI architecture — away from massive cloud-only models and toward efficient, persistent, real-world AI agents that can operate locally, remember context, and act autonomously. If you care about the future of AI agents, world models, autonomous systems, and real-world AI deployment, this is a must-watch.