HKUDS's DeepTutor just passed 55k stars. For a study workspace. It tackles a familiar problem: a pile of textbooks and papers you can't get through, and a chatbot you don't trust to stay on the material. DeepTutor brings the whole learning process into one workspace. It combines Chat, Books, Reading, Practice, Task Board, Calendar, and a learning notebook. Create a workspace for each subject, upload your materials, and keep asking questions and practicing based on the same knowledge base. The biggest difference from regular AI chats: Your learning stays connected, with shared context and progress, instead of being scattered across disconnected conversations. It's open-source under Apache-2.0, with v1.7.1 released on November 1.

The University of Hong Kong (HKU) and the Global Cybersecurity Alliance (GCSA) announced the joint establishment of the Centre for AI and Cybersecurity Research. The Centre will integrate top-tier research capabilities and professional resources from both organisations to advance cutting-edge research, foster deep integration between research outcomes and real-world security scenarios, and explore novel technologies, methodologies, and governance frameworks in artificial intelligence (AI) and cybersecurity. Professor Ho Chen, Chair of Cybersecurity at HKU School of Computing and Data Science, will serve as Acting Director of the Centre. The Centre will bring together researchers from HKU, GCSA, and international partner institutions, while engaging experts in artificial intelligence, cybersecurity, and technology governance for research and advisory roles to promote cross-disciplinary and inter-institutional collaboration. The Centre is committed to bridging academic research and industry practice, with plans to progressively release research findings, security benchmarks, and open-source tools in AI and cybersecurity. The Centre’s key research directions include: Model Inherent Security and Trustworthy AI: Enhancing the security, interpretability, and robustness of large language models and generative AI. AI-Driven Automated Threat Defence: Utilising AI to improve perception and automated defence capabilities against complex cyberattacks. Security Assessment of Frontier Technologies: Evaluating potential security risks associated with next-generation technologies, such as embodied AI, robotics, and the Internet of Things (IoT). Global AI Security Standards and Governance: Researching AI security assessment standards and governance mechanisms to facilitate international dialogue and collaboration. Professor Ho Chen stated: "The rapid evolution of AI introduces unprecedented security risks and governance challenges. The Centre will serve as a bridge connecting academic research, security testing, and industry application to accelerate the translation and deployment of AI security research through cross-disciplinary and international cooperation." Official Announcement by The University of Hong Kong: Official Announcement by Global Cyberecurity Alliance： #GCSAInsights# #SecVibe# #cybersecurity#

Hedge fund manager Harris Kupperman (@hkuppy) warns AI capital spending is unsustainable, threatening a sharp economic rationalization. $QQQ $SPY AI capital spending now accounts for ~3% of U.S. GDP. Kupperman compares current spending to 19th century railroads, warning that cuts will trigger lab and neocloud bankruptcies. Praetorian Capital has cut economic exposure, holding cash and U.S. Treasuries ahead of a potential downturn. $TLT Seeking Alpha Quant Ratings: $MSFT = Hold $NVDA = Strong Buy For AI stocks to sustain momentum, enterprise revenue must expand sharply before funding cuts force a market reset. Is AI spending the next railroad boom?

Yesterday at “Beyond Boundaries” hosted by @HKUFBE, HKU FinTech Academy and @MetaEraHK, our Chairman & CEO @MichaelWuAmber shared how AI, digital assets, and financial infrastructure are converging, and how crypto finance is going to become the native rails for the agentic era.💡 Crypto’s core features—permissionlessness, decentralization and programmability—may be largely irrelevant for most human users, but are exactly what autonomous AI agents need to operate reliably at scale. As this agent economy takes shape, it require native digital assets to carry economic value in real time. Amber has built a full stack of crypto finance workflows over the past decade, and is now evolving into an operating layer that agents can reliably operate on. That's the future we are building toward with crypto‑enabled agentic fintech. 🦾