Sharing insights on data architecture, governance, and middle platforms, exploring AI in data, and linking data with business scenarios.
Gartner’s latest analysis warns that the traditional data middle office is entering the Trough of Disillusionment and may disappear, while a new Data Infrastructure paradigm—cloud‑native, flexible, and AI‑enabled—emerges as the future engine for enterprise digital transformation.
The DeepSeek large language model has been extensively deployed across more than 100 central and local Chinese state‑owned enterprises, spanning sectors such as energy, manufacturing, transportation, finance, telecommunications, construction, and public services, driving intelligent transformation through applications like smart scheduling, risk assessment, intelligent customer service, and AI‑enhanced office automation.
Pre‑training enables AI models to first acquire a universal knowledge map from massive unlabelled text, then quickly adapt to specific tasks with minimal labelled data, offering superior generalization, reduced annotation costs, and versatile applications across chatbots, content creation, retrieval, coding assistance, and more.
DeepSeek‑R1‑0528, the latest open‑source 660B LLM, dramatically improves coding, reasoning, and long‑context abilities, matching or surpassing top models like Gemini 2.5 Pro and Claude 4 in benchmarks and real‑world tests, while offering faster, more stable, and fully executable outputs.
This article explores Zheng Naning's lecture on machine behavior, embodied intelligence, and their challenges, outlining AI development stages, the need for explainable and cooperative machine actions, and the specific hurdles and frameworks for achieving safe, adaptive autonomous driving in dynamic environments.
This article explains model distillation—a technique that transfers knowledge from large teacher models to compact student models—covering its motivation, core principles, key steps, practical applications, and both its advantages and limitations, illustrating how AI can be made efficient without sacrificing performance.
The People's Bank of China has issued a comprehensive Data Security Management Measures, effective June 30, 2025, outlining classification, protection, risk monitoring, incident response, and legal responsibilities for all data processors handling business‑domain data.
This report examines DeepSeek’s security and reliability by detailing five core model threats—DDoS attacks, unlimited inference, vulnerability exploitation, data poisoning, and jailbreak—alongside two private‑deployment risks and three external threats such as counterfeit apps, offering targeted mitigation strategies to help users safely adopt the platform.
This article outlines Anthropic's yearly insights on constructing large‑language‑model agents, explaining their definitions, when to employ them, recommended frameworks, modular building blocks, common workflow patterns, and real‑world application scenarios for developers.
Anthropic’s Model Context Protocol (MCP), inspired by the Language Server Protocol, aims to standardize AI‑application communication by defining tools, resources, and prompts, sparking debate over its differences from OpenAPI, security concerns, statefulness, and offering developers rapid server‑building techniques with AI‑assisted coding.
