Nvidia CEO touts chipmaker's data center market potential | Micron posted an unexpected profit on AI demand | SEMI: Global 300mm fab equipment spending likely to reach $137B in 2027
Intel plans to invest $100 billion in a massive expansion of its US-based chip manufacturing facilities in a move largely fueled by federal grants, loans and the promise of hefty tax breaks. The cornerstone of this investment is the creation of what the firm says will be the world's largest AI chip manufacturing site near Columbus, Ohio, which the firm hopes to use as a springboard for its bid to regain industry leadership from rivals like Taiwan Semiconductor Manufacturing Co.
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Nvidia CEO Jensen Huang says the company's Blackwell architecture AI GPU series has the potential to boost its data center market scale as much as 25%, or up to $250 billion. Huang sees a place for humans in AI systems to guide software and develop algorithms, and says Nvidia is focused on "this one niche called accelerated computing and AI" in the wider semiconductor landscape.
Micron Technology is pointing to an increase in AI adoption for its above-estimate third-quarter revenue forecast and a per-share quarterly profit after five quarters of losses. The company's high bandwidth memory chips are sold out for this year and next year's supply has mostly been allocated, CEO Sanjay Mehrotra reports.
Rob Green, chief digital officer of Insight Enterprises, offers ways to build a powerful AI ecosystem while maintaining sustainability. Promote sustainability best practices with strong data governance and curation to reduce storage and power consumptions, Green writes.
Neuralink, the brain-chip startup from Elon Musk, livestreamed a chess game with implanted patient Noland Arbaugh moving the cursor with the device. Kip Ludwig, formerly of the National Institutes of Health, called the advancement "a good starting point," but noted it's still early in the post-implantation stage.
Nvidia's Blackwell graphics processing unit is scheduled for release this year and is expected to be a significant improvement for AI computing. The chiplet design will likely bring a boost to power and efficiency, and the Blackwell Tensor Core micro-tensor scaling support allows for faster execution and high levels of accuracy with 4-bit floating point.
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