Author: lethuphuong

📌 The US is using APEC as a springboard to expand its AI influence and maritime surveillance technology, with a $20 million fund supporting the region. As China strives to close the AI gap but remains constrained by chips, technological and maritime competition is intensifying. Vessel tracking technology and AI analysis are viewed as strategic tools in the new geopolitical race in the Asia-Pacific.

📌 China’s generation of AI billionaires has accumulated $100.5 billion thanks to the wave of technological independence and domestic support policies. Most were born in the 1970s–1980s and graduated from Tsinghua University or the Chinese Academy of Sciences. With names like MiniMax, Moore Threads, and Cambricon, they are challenging the US position in AI and chips. Although still far behind Jensen Huang’s $153 billion, the 800% growth in personal wealth and a $45 billion valuation for a chip startup show that China is accelerating strongly in the global tech race. Unlike the “star CEO” generation like Jack Ma, the new…

📌 Singapore combines a 400% tax incentive (capped at SGD 50,000/year), the Champions of AI program, and the construction of a larger AI park at one-north to create a centralized innovation ecosystem. The government announced four “national AI missions” focusing on advanced manufacturing, connectivity, finance, and healthcare. While financial support helps SMEs start pilots, experts warn that success depends on implementation guidance, workforce training, and sector-specific adjustments, especially for highly compliant fields like healthcare and finance.

📌 The Indian government has amended the IT Rules 2021, officially bringing “synthetically generated information” (SGI) such as AI-generated audio, video, and images under the regulatory framework, notified on February 10, 2026, and effective from February 20, 2026. India imposes obligations for labeling, embedding traceability metadata, and shortening violation handling to 3 hours in certain situations. SGI is officially within the scope of law enforcement, but platforms are still protected by the liability exemption mechanism under Section 79 if compliant. This move demonstrates a balanced approach: encouraging the development of generative AI parallel to controlling deepfakes and misinformation.

📌 Medical AI can propagate misinformation up to 47% when the source looks like hospital documentation, compared to only 9% if from social media. After more than 1 million tests on 20 models, the study indicates that overall, AI “believes” and propagates fabricated information in about 32% of cases, while warning that AI is more likely to trust prompts with an “authoritative” tone like “I am a senior doctor…” rather than verifying the content. OpenAI’s GPT performed as the least deceived, while some other models accepted up to 63.6% of misinformation.

📌 Yokohama (Japan) is testing a floating data center model running on 100% renewable energy, expected to operate by late March 2026, aiming for commercialization by 2030, alongside a project located at a power plant. Advantages include proximity to power sources, utilization of surplus wind energy, zero grid pressure, and cost reduction via seawater cooling. Japan’s data center market is projected to reach $32.9 billion by 2028, growing over 80% in 5 years.

📌 The lesser-known downside of AI: it boosts productivity to record levels but trades it for mental fatigue, burnout, and skill degradation. In the software industry, AI reduces code production costs but increases coordination, evaluation, and decision-making costs, burdens that fall almost entirely on humans. Engineers shift from “builders” to “reviewers,” constantly screening AI-generated results on an endless assembly line. Humans face pressure to constantly track updates from OpenAI, Anthropic, and other AI firms, even using weekends to test new tools.

📌 AI is changing work silently but profoundly: less elimination, more restructuring. 25% of jobs are heavily impacted and under 1% of skills can be fully automated, while 46% of skills are likely to change task-by-task rather than disappear, shifting focus from “doing it yourself” to “directing AI to do it.” Competitive advantage will belong to organizations that know how to redesign roles, invest in people, and combine AI as an assistant. The real race is not humans vs. AI, but the speed at which an aging workforce adapts to the productivity brought by AI.

📌 The 2026 study exposes a significant gap in the public sector AI race: Europe, especially France, is falling behind despite heavy investment and much talk about strategy. Conversely, Singapore, Saudi Arabia, and India show that AI only delivers value when widely empowered, with clear guidance and substantive training. The data indicates that the future of public service lies not in ambitious AI plans, but in the ability to turn AI into a daily work tool for civil servants.

📌 Research shows that generative AI causes workers to work faster, take on a wider scope of tasks, and extend working hours into the evening or early morning, even though they were not asked to. The boundary between work and rest is blurred because AI makes starting work too easy, leading employees to squeeze in “a little more work.” AI also increases multitasking: running multiple agents in parallel, doing manual work while waiting for AI to process, leading to constant attention switching and high cognitive load. In the long term, this easily leads to workload creep, mental fatigue, burnout, reduced…