Author: lethuha

Conclusion: Between 2021 and 2025, the AI and data center revenue share shifted drastically: Nvidia soared from 25% to 86%, while Intel plummeted from 68% to 6%. ChatGPT and the wave of “AI factories” pushed GPU demand to its peak, exposing Intel’s CPU-centric weakness. CEO Jensen Huang noted that Nvidia’s AI performance nearly doubles annually, far exceeding the slowing pace of Moore’s Law for traditional CPUs. The AI data center race is no longer about individual chips, but a comprehensive ecosystem—where Nvidia is leaving all competitors behind.

Conclusion: Anthropic has announced a new “constitution” for its Claude AI model, detailing the vision, values, and how Claude should behave in the real world. This new approach replaces fragmented lists of principles with deep explanations of “why” Claude should behave in a certain way. The constitution guides Claude to become a wise, honest, discerning, and sensitive agent in contexts of moral uncertainty. The full public disclosure marks a major step forward in transparency. Claude is trained to prioritize in order: general safety, general ethics, compliance with Anthropic’s instructions, and substantive helpfulness.

Conclusion: South Korea will officially implement the Artificial Intelligence Act on January 21, 2026, becoming the first country to set legal safety requirements for high-performance AI—also known as Frontier AI—while prioritizing growth and compliance over punishment. The law establishes a national AI policy framework, creates the Presidential Council on National AI Strategy, and builds the AI Safety Institute for reliability assessments. Unlike the EU’s application-based risk approach, South Korea utilizes technical thresholds like total training compute. With at least a one-year grace period and a maximum fine of 30 million won (≈$20,300 USD), this law provides a flexible foundation to both…

📌 Conclusion: Salesforce CEO Marc Benioff stated that AI-related suicides among children are the darkest aspect of this technology. He called for a reform of Section 230 of the US Communications Decency Act of 1996, which currently shields tech companies from liability for user-generated content. Without clear guardrails and accountability, friendly and personalized AI could lead to severe social consequences far outweighing technological benefits.

📌 Conclusion: The US FDA and European EMA announced a joint set of principles for “Good AI Practice” in drug development in January 2026. For the first time, the US and Europe have established a common framework for AI in pharmaceuticals, focusing on 10 pillars ranging from ethics and data to lifecycle management. This risk-based approach and GxP standards balance innovation with patient safety. This move not only accelerates drug development but also solidifies the global leadership of the EU-US in the generative AI race for biomedicine, while significantly reducing animal testing and post-market risks.

📌 Conclusion: DBS Bank recorded a record economic value from AI of 1 billion SGD in 2025. This reflects a trend across Singapore’s top three banks as they transition from generative AI to agentic AI—models capable of autonomous reasoning and execution. While expected to generate massive value, this shift raises employment concerns, prompting a massive retraining initiative for 35,000 employees.

📌 Conclusion: West Midlands Chief Constable Craig Guildford has officially apologized to British MPs after admitting to providing false information regarding the decision to ban Maccabi Tel Aviv fans. This error originated from the use of Microsoft Copilot, a generative AI tool, during the synthesis process.

📌 Conclusion: AI is not obliterating professions, but it is forcing workers to redefine their value. Data proves that soft skills—from collaboration and creativity to problem-solving—are the factors that build “AI resistance” in a career. When code and formulas become common commodities, sustainable advantage lies in the ability to connect with people, lead ideas, and transform technology into truly meaningful solutions.

📌 Conclusion: AI brings clear efficiency, but completely erasing mundane tasks can backfire. When employees are forced to maintain high intensity all day, the risk of burnout increases and creativity declines. Instead of filling every minute with performance, businesses need to actively design “white space” to allow humans to be bored and to think, thereby sparking valuable ideas.

📌 Conclusion: China’s new AI plan for manufacturing reveals a shift from a “model race” to controlling the entire AI supply chain—from chips and data to infrastructure and industrial applications. With targets of 3–5 large models, 100 datasets, and 500 scenarios by 2027, Beijing seeks both technological self-reliance and global influence. Amid U.S.–China tensions, AI is increasingly viewed as a strategic pillar on par with energy or semiconductors.