The AI Chip Race
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The AI Chip Race
Open AI’s Altman raising Trillions for chips, yes T
‘Everyone looked real’: office loses US$25.6 million after scammers stage AI deepfake video meeting
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The AI Chip Race
“It is the most advanced AI accelerator in the industry,” boasted Lisa Su, boss of Advanced Micro Devices (AMD), at the launch in December of its new MI300 chip. Ms Su rattled off a series of technical specifications: 153bn transistors, 192 gigabytes of memory and 5.3 terabytes per second of memory bandwidth. That is, respectively, about 2, 2.4 and 1.6 times more than the H100, the top-of-the-line artificial-intelligence chip made by NVIDIA. That rival chipmaker’s prowess in the semiconductors fueling the ai boom has, over the past year, turned it into America’s fifth-most-valuable company, with a market capitalization of $1.5trn. Yet most experts agreed that the numbers and Ms Su weren’t lying: the MI300 does indeed outshine the H100. Investors liked it, too—AMD’s share price jumped by 10% the next day.
Such ambition would have seemed fanciful a decade ago. Back then, recalls Mark Papermaster, AMD’s technology chief, AMD was facing an “existential crisis”. In 2008 it had spun off its chip-fabrication business to focus on designing processors, outsourcing manufacturing to contract chipmakers such as TSMC of Taiwan. The idea was to be better able to compete on blueprints with Intel, whose vast fabrication capacity AMD could not hope to match.
It didn’t work. Several of AMD’s chips flopped. In 2013 it sold and leased back its campus in Austin to raise cash. A year later Ms Su inherited a net-debt pile of more than $1bn, a net annual loss of $400m and a market value of less than $3bn, down from $20bn in 2006.
She and Mr Papermaster took a gamble on a new CPU architecture designed to beat Intel not just on price, but also on performance. The idea was to use a Lego-like approach to chip building. When the first such composite chips were released in 2017, they were zippier and cheaper than rival offerings from Intel, possibly in part because Intel was distracted by its own problems (notably repeated manufacturing slip-ups as it moved to ever tinier transistors). In the past ten years AMD’s market share in lucrative server CPUs has gone from nothing to 30%, breaking Intel’s monopoly.
Having faced down one giant, AMD now confronts another. The contest with Nvidia is different. For one thing, it is personal—Ms Su and Jensen Huang, NVIDIA’s Taiwanese-born boss, are distant relatives. In contrast to Intel, NVIDIA is, like AMD, a chip designer and thus less prone to production missteps. NVIDIA’s market value of $1.5trn is based on its dominance of the market for GPUs—not because of their usefulness in gaming but because they also happen to be the best type of chip to train ai models. Ms Su expects global sales of AI chips to reach $400bn by 2027, up from perhaps $40bn last year. Does she stand a chance against NVIDIA?….
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Open AI’s Altman raising Trillions for chips, yes T
Sam Altman, the CEO of OpenAI, is reportedly in discussions with various investors, including the United Arab Emirates government, to raise a staggering amount of money, between $5 trillion to $7 trillion, to significantly expand the global production capacity for semiconductors, particularly those used in artificial intelligence (AI) applications. This initiative is seen as a response to the current scarcity of graphics processing units (GPUs) that are crucial for training AI models like ChatGPT.
The ambitious plan involves building dozens of chip-fabrication plants over the next few years, which would be operated by existing chipmakers such as Taiwan Semiconductor Manufacturing Company (TSMC). Altman's vision includes a partnership between OpenAI, chipmakers, energy firms, and investors to finance these GPU chip plants. The scale of the fundraising effort is unprecedented, with even mega investments in the tech industry typically being on the order of tens of billions of dollars.
The Biden administration has also shown interest in bolstering domestic chip manufacturing, committing $5 billion to R&D in the semiconductor industry, highlighting the strategic importance of microchips to the digital economy and national security. Altman's proposal is seen as complementary to these efforts, aiming to ensure a resilient supply chain and meet the growing demand for AI infrastructure.
While the discussions are still in the early stages and it's unclear whether any commitments have been secured, the initiative reflects the global interest in AI's potential and the strategic importance of semiconductor production. If successful, this could reshape the business of chips and AI, ensuring improved access to the hardware necessary to power advanced AI technologies….
by Keach Haggey of The Wall Street Journal
AI brews beer and your big ideas
What’s your biggest business challenge? Don’t worry about wording it perfectly or describing it just right. Brain dump your description into AE Studio’s new tool and AI will help you solve that work puzzle.
Describe your challenge in three quick questions. Then AI churns out solutions customized to you.
AE Studio exists to solve business problems. They build great products and create custom software, AI and BCI solutions. And they once brewed beer by training AI to instruct a brewmeister and then to market the result. The beer sold out – true story.
Beyond beer, AE Studio’s data scientists, designers and developers have done even more impressive things working 1:1 with founders and executives. They’re a great match for leaders wanting to incorporate AI and just generally deliver outstanding products built with the latest tools and tech.
If you’re done guessing how to solve work problems or have a crazy idea in your back pocket to test out, ask AI Ideas by AE Studio for free solutions, right now.
‘Everyone looked real’: multinational firm’s Hong Kong office loses US$25.6 million after scammers stage AI deepfake video meeting
A multinational company lost US$25.6 million in a scam after employees at its Hong Kong branch were fooled by deepfake technology, with one incident involving a digitally recreated version of its chief financial officer ordering money transfers in a video conference call, police said.
Everyone present on the video calls except the victim was a fake representation of real people. The scammers applied deepfake technology to turn publicly available video and other footage into convincing versions of the meeting’s participants.
Police said they were highlighting the case as it was the first of its kind in Hong Kong and involved a large sum. They did not reveal details about the company or the employees involved….