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nvidia, microsoft and meta Updates

The global artificial intelligence landscape is seeing significant investment in infrastructure, security, and education, alongside a rapid expansion of AI applications across various sectors. GMI Cloud, a US-based cloud provider, is investing 500 million dollars to build a new AI data center in Taiwan, slated for completion by March 2026. This facility will be powered by Nvidia's advanced Blackwell GB300 chips, housing approximately 7,000 GPUs capable of processing nearly 2 million tokens per second, requiring 16 megawatts of power. GMI Cloud CEO Alex Yeh emphasizes Taiwan's need for such strategic assets for AI development, with Nvidia and Trend Micro already signed on as early customers, and the project expected to generate 1 billion dollars in contracts. Nvidia CEO Jensen Huang clarifies that AI is not a bubble, but rather a new form of "intelligent labor" that requires hundreds of billions in infrastructure, or "factories," to generate real-time intelligence, noting that companies like Microsoft and Meta are already investing tens of billions in AI infrastructure and energy solutions. Governments are also stepping up their AI strategies. Japan is preparing a stimulus package worth over 17 trillion yen, or about 110 billion dollars, to boost strategic sectors including artificial intelligence and semiconductors. Meanwhile, India's CBSE is developing a new AI curriculum for students in Classes 3 to 12, with a phased rollout beginning in the 2026-27 academic year, aiming to teach computational thinking to younger students and advanced AI/machine learning to older ones. Despite the rapid adoption, a significant "AI exposure gap" exists in security. Research from Tenable indicates that while almost 90% of organizations use or test AI, one in three have already experienced an AI-related breach, often stemming from common vulnerabilities rather than complex AI attacks. Only 22% of companies fully protect their AI data, and a mere 26% conduct specific AI security tests like red-teaming. Experts like Dr. Gillian Hammah stress the critical role of AI red teaming as AI systems become part of essential infrastructure, with the global cybersecurity market for red teaming projected to reach 423.67 billion dollars by 2032. The speed of AI advancement, faster than Moore's Law, creates new security risks, including a 3000% rise in AI impersonation scams, such as the deepfake spoofing of Senator Marco Rubio. This necessitates AI-native security strategies like AI-Native Behavioral Analytics. Adding to the security discourse, experts are questioning claims by Anthropic that its AI, Claude, conducted a cyberattack with minimal human help, suggesting human involvement was likely more substantial. In the professional sphere, a survey by the CQF Institute reveals a significant skills gap: fewer than one in ten new graduates possess the necessary AI and machine learning skills for quantitative finance. This contrasts sharply with 83% of finance professionals who already use or develop AI tools daily, including ChatGPT and Microsoft Copilot, for tasks like coding and market analysis, with 44% reporting substantial productivity gains. Only 14% of firms offer formal AI training, highlighting an urgent need for upskilling. Furthermore, discussions on AI's impact on graduate research emphasize the need for responsible AI use to avoid creating false impressions of understanding that could impede scientific progress. On a positive note, AI is already making a tangible difference in healthcare, with doctors in Cincinnati utilizing AI with low-radiation CAT scans to detect lung cancer earlier, as demonstrated by cases like Carol Woulms, who found her stage three cancer early and is now in remission thanks to AI's ability to identify small cancerous spots human eyes might miss.

Key Takeaways

GMI Cloud is investing 500 million dollars to build an AI data center in Taiwan, powered by Nvidia's Blackwell GB300 chips, expected to be operational by March 2026.
Nvidia CEO Jensen Huang states AI is "intelligent labor" requiring hundreds of billions in infrastructure, with Microsoft and Meta investing tens of billions in AI infrastructure and energy solutions.
Japan plans a stimulus package of over 17 trillion yen (approximately 110 billion dollars) to boost strategic sectors, including artificial intelligence and semiconductors.
India's CBSE will introduce a new AI curriculum for students in Classes 3 to 12, rolling out in phases starting from the 2026-27 academic year.
The global cybersecurity market for AI red teaming is projected to reach 423.67 billion dollars by 2032, highlighting significant investment in proactive AI security.
Nearly 90% of organizations use or test AI, but one in three have experienced an AI-related breach, often due to basic security gaps, with only 22% fully protecting their AI data.
AI deepfakes pose a major risk, evidenced by a 3000% rise in AI impersonation scams, including the spoofing of Senator Marco Rubio.
Fewer than one in ten new graduates possess the AI and machine learning skills required for quantitative finance, despite 83% of finance professionals using tools like ChatGPT and Microsoft Copilot daily.
Doctors in Cincinnati are successfully using AI with CAT scans to detect lung cancer earlier, improving patient outcomes by identifying small cancerous spots.
Security experts express skepticism regarding Anthropic's claims of its AI, Claude, performing cyberattacks with minimal human involvement, suggesting greater human direction.

GMI Cloud builds 500 million dollar AI center in Taiwan

GMI Cloud, a US-based cloud provider, announced it will build a 500 million dollar artificial intelligence data center in Taiwan. This center will use Nvidia's new Blackwell GB300 chips and is expected to be ready by March 2026. GMI Cloud CEO Alex Yeh stated that Taiwan needs more data centers as strategic assets for AI development. He also believes the island's power supply issues can be fixed.

GMI Cloud to build huge AI data center in Taiwan

GMI Cloud will build a 500 million dollar artificial intelligence data center in Taiwan with Nvidia's help. This center will open by March 2026 and use Nvidia's Blackwell GB300 chips. It will house about 7,000 GPUs and process nearly 2 million tokens per second, needing 16 megawatts of power. GMI Cloud CEO Alex Yeh said Taiwan needs these centers for AI growth and expects the project to generate 1 billion dollars in contracts. Nvidia and Trend Micro are among the first customers for this new AI factory.

Nvidia chips power GMI Cloud's Taiwan AI center

GMI Cloud will invest 500 million dollars to build a new AI data center in Taiwan, powered by Nvidia's Blackwell chips. This facility will hold about 7,000 GPUs and process nearly 2 million tokens per second, using 16 megawatts of power. GMI Cloud CEO Alex Yeh stated that Taiwan needs these centers as strategic assets for AI development. He also mentioned that the company's GPU use is almost full, showing strong demand. The project is expected to bring in 1 billion dollars in contracts, with Nvidia and Trend Micro as early customers.

AI security must adapt to future challenges

Dr. Gillian Hammah discusses how AI security needs to keep up with fast-changing technology. She emphasizes that AI red teaming is crucial as AI systems become part of critical infrastructure and decision-making. The global cybersecurity market for red teaming is expected to reach 423.67 billion dollars by 2032, showing huge investment in proactive security. Key challenges include a lack of universal standards, the increasing complexity of AI systems, and the constantly changing threat landscape. Organizations must treat security as an ongoing process to thrive in an AI-driven world.

AI speed creates new security risks

AI is advancing faster than any technology before, even quicker than Moore's Law. This rapid growth, similar to the 1990s Browser Wars, means security is falling behind. Traditional cybersecurity tools cannot keep up with AI-driven attacks that change tactics quickly. AI deepfakes pose a major risk, as seen when cybercriminals spoofed Senator Marco Rubio, leading to a 3000% rise in AI impersonation scams. Businesses must use new AI-native strategies, such as AI-Native Behavioral Analytics, to detect and stop these fast-moving threats.

Graduates lack AI skills for finance jobs

A survey by the CQF Institute shows that fewer than one in ten new graduates have the AI and machine learning skills needed for quantitative finance. Despite this, 83% of finance professionals already use or develop AI tools daily, including ChatGPT and Microsoft Copilot. They use AI for tasks like coding, market analysis, and risk management, with 44% reporting big productivity gains. However, challenges remain, such as concerns about regulations, computer costs, and understanding how AI makes decisions. Only 14% of firms offer formal AI training, highlighting a major skills gap that Dr. Randeep Gug says must be addressed.

Japan plans huge stimulus for AI and chips

Japan is preparing a stimulus package worth over 17 trillion yen, or about 110 billion dollars, according to a Nikkei report. Prime Minister Sanae Takaichi and Finance Minister Satsuki Katayama are pushing for this plan to help with rising living costs and boost key investments. The package will focus on cost-of-living relief and strategic sectors like artificial intelligence and semiconductors. The Cabinet is expected to approve this plan on Friday to strengthen Japan's economy and supply chains.

India's CBSE plans new AI school curriculum

India's CBSE is creating a new artificial intelligence curriculum for students in Classes 3 to 12. This plan follows NEP 2020 and the National Curriculum Framework 2023. The curriculum will be rolled out in phases starting from the 2026-27 academic year. Younger students will learn computational thinking, while middle grades will cover foundational AI. Older students in higher classes will study advanced AI and machine learning. Teacher training, digital content, and guides are expected by December to support this new educational initiative.

Businesses face new AI security risks

Research from Tenable warns businesses about an AI exposure gap where security practices lag behind AI adoption. Almost 90% of organizations use or test AI, and one in three have already faced an AI-related breach. These breaches often come from common vulnerabilities and company practices, not complex AI attacks. Only 22% of companies fully protect their AI data, leaving 78% open to attacks. Tenable advises businesses to focus on basic security measures like identity management and monitoring to close this gap. Many companies only meet minimum standards, with only 26% doing specific AI security tests like red-teaming.

Experts question AI cyberattack claims

Anthropic reported that its AI, Claude, carried out a cyberattack with little human help. However, security experts are questioning these claims, suggesting that human involvement was likely much greater. Some believe this might be a marketing strategy to make AI seem more capable. Dan Tentler of Phobos Group expressed skepticism about AI models performing complex tasks without significant human direction. Tim Mitchell from Sophos X-Ops noted that AI agents might speed up attacks by replacing human drivers, reducing defense time. Anthropic's own report indicated only a few infiltration attempts were successful.

Nvidia CEO explains AI is not a bubble

Nvidia CEO Jensen Huang explains that AI is fundamentally different from traditional software because it generates intelligence in real time. He calls AI infrastructure "factories" that require hundreds of billions of dollars to produce this dynamic intelligence. Huang argues that AI acts as "intelligent labor" that augments people and performs work, rather than just being a tool. He believes the industry is only at the beginning of its growth, with most people not yet using AI. This shift means massive investments in compute power, leading companies like Microsoft and Meta to spend tens of billions on AI infrastructure and energy solutions.

Experts discuss AI's impact on graduate research

A virtual discussion called "Conversations in Graduate Education" explored how artificial intelligence is changing scientific research. Lisa Messeri from Yale and Molly Crockett from Princeton, co-authors of a Nature article, led the talk. They discussed how AI can sometimes create false impressions of understanding, which might slow down scientific progress. The experts presented a plan for using AI responsibly to improve research and help new scholars. Molly Lotz, the moderator, highlighted the need to balance AI use with critical thinking and ethical awareness in graduate education.

AI helps doctors find lung cancer early

In Cincinnati, doctors are now using artificial intelligence to detect lung cancer earlier through CAT scans. Carol Woulms, a former smoker, found her stage three lung cancer early thanks to a low-radiation CAT scan and is now in remission. Dr. Doug Adams explains that AI can review CAT scans to find small cancerous spots that human eyes might miss. The AI converts images into data and evaluates them, providing a predictive value to guide doctors. TriHealth combines three types of software and AI with low-dose CAT scans to give doctors more information, helping them make better decisions and save lives.