Author: lethuphuong

📌 If China begins to restrict advanced AI models, the US should not respond with bans but must accelerate the development of its own open-weight AI ecosystem. According to the author, AI success depends not only on the model but also on creating an open, stable platform accompanied by computing infrastructure to attract developers worldwide, thereby maintaining a long-term technological competitive advantage.

📌 The escalation of the AI competition between the U.S. and China is visible not only in model capabilities but also in access to computing infrastructure and intellectual property issues. The White House allegations regarding Moonshot AI’s use of Nvidia GB300 chips in Thailand and the distillation of Anthropic’s model currently remain claims from U.S. officials; as of the article’s publication, Moonshot AI and Nvidia have not provided official responses.

📌 Japan is testing the “AI employee” model as a solution to its aging population and labor shortage. AI Agents like Junior can now proactively handle many office tasks, but businesses still need to provide close supervision, manage legal risks, and maintain the human role. The success of this model will depend not only on technology but also on the ability of businesses to build effective collaborative workflows between AI and human employees.

📌 The AI wave is creating unexpected beneficiaries in the Japanese economy. Instead of directly manufacturing chips, businesses like Toto, Nittobo, and Ajinomoto are leveraging material and technological strengths accumulated over decades to integrate deeply into the semiconductor supply chain. The strong growth of AI-related segments improves business results and demonstrates that AI opportunities are not just for tech firms but also open to many traditional manufacturing industries.

📌 Singapore is adjusting education to adapt to the AI era by emphasizing independent thinking capacity instead of just knowledge absorption. The new KI program from 2027 guides students toward evaluating information sources, understanding how knowledge is formed, and considering the ethical aspects of AI. In the context of increasingly convincing generative AI, the ability to ask questions, think critically, and independently form arguments is considered a core human skill.

📌 AI is changing the way we work, but it hasn’t yet changed the core hiring criteria of businesses. A survey of over 600 recruiters confirms that communication skills, professionalism, adaptability, a learning mindset, and teamwork remain the decisive factors when hiring newcomers. Generative AI is seen as a support tool, but a candidate’s long-term value still lies in their ability to learn, exercise judgment, and grow with the organization.

📌 The report shows that the major hurdle for ASEAN businesses is not a lack of interest in generative AI but the inability to scale deployment. With fewer than 20% of businesses achieving actual application scale and about two-thirds still in the pilot phase, Bain recommends focusing on 2 to 3 areas that bring clear value before expanding. Initial success will help build trust, drive productivity, and support revenue growth.

📌 The PwC survey shows that Japanese enterprises remain cautious and have yet to fully exploit the value of generative AI. Only 9% rated AI as exceeding expectations, compared to 38% in the US and 32% in the UK. The fact that AI is mainly used for clerical tasks instead of content creation or programming limits the benefits it brings. The results indicate that AI effectiveness depends heavily on implementation tied to specific business objectives.

📌 Malaysia is testing a new application for AI Agents in governance and citizen interaction. PMX.AI is built as a digital twin of Prime Minister Anwar Ibrahim, capable of chatting, supporting public services, and collecting voter opinions via WhatsApp. With a PKM foundation combined with blockchain and digital identity, the project reflects a trend where AI does not just answer questions but represents humans in performing tasks within authorized limits.

📌 OpenAI proposes a new way to measure the AI era, shifting the focus from token costs to generated business value. According to the company, businesses should evaluate AI based on work completed, cost per satisfactory result, reliability, and efficiency when scaling up. Metrics such as GPT-5.6 Sol scoring 72.7% on the Artificial Analysis Coding Agent Index—outperforming Claude Fable 5 with 36.2% lower API costs—illustrate that more powerful AI can yield lower actual costs if it completes the job correctly the first time.