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Delays at TSMC’s Arizona plant could compel its customers to rely on Taiwan-based facilities, leaving them vulnerable to geopolitical risks tied to Taiwan’s dominance in semiconductor production. “This situation could also delay the rollout of next-generation products in the US market, affecting timelines for AI, gaming, and high-performance computing innovations,” Rawat said. “Moreover, without access to local, advanced chips, US tech companies will incur higher transportation and import costs, diminishing their profit margins. In competitive sectors like AI and autonomous vehicles, slower time-to-market could weaken global competitiveness.” For TSMC, the delays and challenges could have significant implications for fab operations, particularly in maintaining profitability and efficiency. “Cost of maintaining the fab, the fab utilization rate, and the yield rate are key metrics to keep the fab profitable,” said Neil Shah, partner, and co-founder at Counterpoint Research. “So, TSMC would look to move as much business as possible from its customers to the Arizona fab to match current and future capacity, maintain the utilization rate, and then build on the yield rate to maximize efficiency.” source

AI can do much more than make individual employees more productive—with a thoughtful strategy, it can transform your industry.   To turn this vision into reality, businesses need AI solutions that are not only ambitious but also practical and adaptable. That’s where Domo steps in. Domo.AI is built to meet the challenges of today’s AI landscape. While many companies focus on narrow applications or single-model solutions, our platform offers something more robust:  Trustworthy AI results—without having to overhaul your entire data infrastructure.  Intelligent agents that can analyze information, make choices, and take actions—with or without a human in the loop.  Flexibility to choose which AI models to use—whether that’s DomoGPT or models you host with our ecosystem partners, including AWS, IBM, Databricks, and Snowflake.   The result? A platform that’s both ready to support your AI strategy today and designed to scale with you as your business and your data grow. Making AI practical, personal, and powerful   Let us paint a picture of secure, personalized, scalable AI. Imagine these five ways Domo.AI can make a difference in your organization: A unified and secure platform Instead of onboarding AI piecemeal across your business (and taking on more risk with every tool), you get one trustworthy platform. As AI adoption grows, teams across your company are likely already using AI, creating a governance and security challenge for IT teams. Domo.AI offers a safer method: Our framework lets you use public models, large language models, and generative AI (e.g., ChatGPT)—all within the security of our platform. Your company’s data never leaves your hands and stays firmly in your control.   2. Scalable AI embedded in your business AI is responsibly embedded into your business—and the capabilities grow alongside you. Many companies today remain in reaction mode, adding new AI tools as soon as new use cases emerge—one for ad imagery production, another for data cleaning, and yet another for inventory management. But these surface-level integrations can’t scale as your organization grows.   An integrated approach, however, will. The Domo.AI experience unites teams around the common stories emerging from your data. Our flexible framework allows you to add new, suitable tools and models as needed while keeping your data centralized and secure in the Domo platform. With Domo.AI, your AI strategy doesn’t just keep up with your growth—it drives it. 3. Tools for every skill level Both data experts and novices can use the same AI tools—with capabilities that match their skill sets. Domo.AI is advanced enough for data architects and analysts yet approachable enough for those without the same technical fluency. The Domo platform is designed to engage people (especially those without data science backgrounds), helping them learn and progress in making data-driven decisions.   4. Conversational AI for everyone Your people can talk to AI as they would a colleague—in everyday language, not code. With Domo.AI, code and complex prompts aren’t needed anymore to get value from AI. In Domo, you can ask a simple question of your data, and AI Chat deliver insights and answers in real time. Personalized support is right at your fingertips, 24/7. All you have to do is ask. 5. AI as your workday companion With Domo, AI becomes your intelligent workday companion—not an expensive investment that doesn’t drive value. As Chris Willis, chief design officer at Domo, put it, “The time has come to put AI to work—not as a novelty, but as an invaluable assistant augmenting capabilities for everyone in your enterprise.” With Domo.AI, our vision is to give you the tools you need to create AI-powered operations that make work life easier. By handling repetitive tasks, we free up your people to focus on the strategic work that requires their skills.  What’s next for Domo.AI  Our journey with AI and with you doesn’t stop here. As we look ahead to 2025, our team is doubling down on the mission to deliver personalized, secure, and scalable AI experiences to our customers.  With agentic workflows that simplify operations and drive value, we’re creating a platform that empowers businesses to thrive—and we can’t wait to see what you build.  To learn more, view our webinar, “Transforming Industries Through Automation and Intelligence.” source

But this month, the company will release the model he previously claimed had achieved it. source

Generative AI (GenAI) is reshaping how businesses operate, offering unprecedented opportunities for greater efficiency, streamlined operations, revolutionized customer service, and enhanced decision-making. But alongside its promise of significant rewards also comes significant costs and often unclear ROI. For CIOs tasked with managing IT budgets while driving technological innovation, balancing these costs against the benefits of GenAI is essential. In this article, we will explore the cost-related barriers to GenAI adoption, including high implementation expenses, ineffective cost management, and infrastructure demands. We’ll also examine strategies CIOs can use to address these challenges, ensuring their organizations can recognize the rewards of GenAI without compromising financial stability. While the article’s focus is on GenAI, many of the strategies discussed here are broadly applicable to other innovations in IT, as they provide CIOs with a flexible framework for balancing costs and opportunities presented by emerging technologies. Let’s begin by examining the specific cost-related concerns CIOs face when adopting GenAI technologies. source

The UAE’s vision for AI is encapsulated in its National AI Strategy 2031, which aims to position the country as a global leader in AI by integrating it across various sectors. This strategy is not just a roadmap but a testament to the UAE’s forward-thinking approach to harnessing the power of AI for socio-economic growth. The country is ranked among the top five in the world for artificial intelligence competitiveness, is poised to further solidify its leadership in the sector with the launch of Dubai AI Week. Set to take place from April 21 to 25, the event has been announced by Sheikh Hamdan bin Mohammed, Crown Prince of Dubai, who described it as a “platform to unlock the transformative potential of artificial intelligence.” With more than 10,000 attendees expected, Dubai AI Week will unite public and private sector leaders, innovators, and experts to explore AI’s potential across industries. A key event within the week will be the AI Retreat, designed to bring together decision-makers and tech leaders to discuss integration strategies for AI. The Dubai Assembly for Generative AI will provide a platform for high-level discussions on generative AI, with particular focus on its application in healthcare, education, and entertainment. source

Year-end and future projections For 2024, IDC projects a 74.3% year-over-year growth in cloud infrastructure spending, reaching $192 billion. Non-cloud infrastructure is expected to see a more modest increase of 17.9%, totaling $71.4 billion. Shared cloud is set to drive much of this growth, with a forecasted 88.9% year-over-year increase to $157.8 billion. Dedicated cloud infrastructure spending is expected to grow 28.6%, reaching $34.2 billion, according to the report. Globally, service providers are expected to account for the lion’s share of compute and storage investments in 2024, spending $183.1 billion — a 73.5% increase. Meanwhile, spending by enterprises and government entities is also poised for significant growth, reflecting a continued expansion of digital infrastructure and capabilities. IDC defines its service provider category to encompass cloud providers, digital service platforms, communication service firms, hyperscalers, and managed service operators. Regional and long-term insights From a geographic perspective the report stated that the United States led cloud spending growth in Q3 2024 with a triple-digit surge of 148.3%, followed by China at 100%. Regions such as Asia Pacific (excluding Japan and China), Japan, and Western Europe reported robust double-digit growth, while Central and Eastern Europe was the only region to decline at -1.7%. For the long-term, IDC has predicted a compound annual growth rate (CAGR) of 24.2% in cloud infrastructure spending through 2028, reaching $325.5 billion. Shared cloud infrastructure will account for 79.1% of this spend, further cementing its dominance in the market. source

The company, which CEO Phil Bullinger currently leads, was founded by Moshe Yanai in 2011. It also has an office in Waltham, Massachusetts. Lenovo eyes high-end enterprise storage market The acquisition is part of Lenovo’s growth strategy to meet the evolving needs of modern data centers that are expected to handle AI and generative AI workloads, the company said, adding that Infinidat’s offering will find synergy with its Infrastructure Solutions Group and jointly will target the high-end enterprise storage market. Currently, Lenovo’s Infrastructure Solutions business operates in the entry and mid-range enterprise storage market offering a portfolio of options, such as flash and hybrid arrays, hyperconverged infrastructure (HCI), software-defined storage (SDS), and data management suites such as Lenovo TruScale. “This is a win-win for both companies. Lenovo fills a big void in its storage portfolio, while Infinidat is able to leverage a hardware design and manufacturing machine,” Matt Kimball, principal analyst at Moor Strategy and Insights, wrote on LinkedIn. Lenovo is expected to quickly train its sites on Infinidat’s storage software IP and look to where it can leverage this more broadly, Kimball explained, adding that “if Lenovo’s channels are properly leveraged, we can see real disruption in the enterprise storage market.” Early focus on the enterprise storage market According to analysts, Lenovo has been hyper-focused on the enterprise storage market since it acquired IBM’s x86 server business for about $2.3 billion in 2014. Another landmark deal for the company, targeted at competing more aggressively with Dell and HPE — the dominant players in the enterprise storage market, came in 2018 in the form of a partnership with NetApp, under which it also developed a joint venture in China to co-develop a new range of ThinkSystem Infrastructure that imbibes NetApp’s data management expertise. source