Technical breakthroughs, model architectures, and hard-core AI innovations.
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At the 2026 International Symposium on Circuits and Systems, Huawei's He Tingbo unveiled the 'Tao Law,' a paradigm shift from geometry-based scaling to time-based scaling (τ-scaling) that leverages logic folding to compress signal delays, aiming to sustain semiconductor advancement without relying on ever-smaller transistors. Born from
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AI workloads are undergoing a tectonic shift, with agentic artificial intelligence—characterized by autonomous reasoning and tool execution—poised to dominate enterprise token consumption. According to a new forecast by AI.cc, agentic AI workloads will account for 54% of total enterprise token volume by the third quarter of 2026,
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In March 2026, the AI agent open-source project OpenClaw (nicknamed 'Lobster') surged to over 250,000 GitHub stars, 10.4 trillion tokens in global usage, and a WeChat Index of 165 million—only to see global visits halve by April to roughly 14.2 million and its domestic
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Datawhale has released a comprehensive AI Agent learning roadmap, structuring the entire journey from the minimal Agent Loop to modern Agent Harnesses and security. Designed as a practical to-do list, the roadmap guides developers through systematic learning and hands-on projects covering the industry's hottest tech stacks. The roadmap
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Nvidia shattered expectations with a record $81.6 billion in first-quarter revenue, driven by $75.2 billion in data center sales, as CEO Jensen Huang unveiled the Vera CPU specifically engineered for agentic AI workloads. The company guided $91 billion for next quarter, while its private holdings nearly doubled to
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Alibaba Cloud has unveiled a comprehensive, full-stack Agentic transformation spanning chips, cloud infrastructure, models, and inference, signaling a strategic pivot to reposition the primary cloud consumer from humans to autonomous agents. The announcement introduces three major pillars—the Zhenwu M890 AI chip, the Qwen3.7-Max flagship model, and the Qianwen
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At the AIGC2026 conference, Hong Yuan, Chief Product Officer of Taichu Yuanqi, laid out a stark reality for domestic AI computing: as the Token economy accelerates, the industry must confront three critical bottlenecks—large-scale cluster service capability, computing efficiency, and ecosystem maturity. With Token demand projected to surge 212-fold by
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Google has introduced Managed Agents to its Gemini API at I/O 2026, offering developers a complete, turnkey execution environment for AI agents that can be launched with a single API call. This move abstracts away complex infrastructure management, allowing teams to focus on agent behavior rather than backend systems.
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AI search infrastructure product AnySearch surged to the top of the Skills.sh chart within its first week by solving a critical bottleneck: AI agents have historically been limited to accessing only about 20% of the internet. By deploying self-built indexes and multi-source aggregation, the platform penetrates the deep web
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On May 18, GitHub detected unauthorized access to its internal repositories stemming from a compromised third-party Visual Studio Code extension. The malicious version was promptly removed, the affected employee device isolated, and critical secrets rotated. Attackers claimed to have accessed approximately 3,800 repositories, but GitHub's investigation confirmed
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A joint position paper from researchers at Chinese University of Hong Kong (CUHK) and Zhejiang University (ZJU) has ignited widespread academic debate by arguing that current AI agent memory is fundamentally flawed—operating as a mere retrieval-based 'Memo' rather than a system capable of true learning. Drawing on
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In a breakthrough that could reshape the economics of large-scale AI training, Nous Research has unveiled Token Superposition Training (TST), a novel method that slashes pre-training costs by roughly 60% without altering model architecture. In a 10B-A1B mixture-of-experts experiment, TST consumed just 38.7% of the GPU hours (4,768