Sam Altman and the $7T geopolitics of AI chips
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Welcome to another edition of ?? The AI Beat ??!
Sure, the Super Bowl was exciting — Kansas City, Travis Kelce, Taylor Swift, yada yada yada. But not even the hometown challengers, the San Francisco 49ers, could keep Silicon Valley as engrossed as the news about OpenAI CEO Sam Altman and his quest for up to $7 trillion in AI chip funding, which the Wall Street Journal reported last Thursday.
That’s because Altman kept his X posts coming, one after the other, all weekend long —?from short, cryptic bites like “chaotic good” and “also roon is my alt” to slightly longer missives insisting that he doesn’t “really know that much about this rumored compute thing” and pushing back on haters with “you can grind to help secure our collective future or you can write substacks about why we are going fail.”
But to me, Altman’s post-dump is far less interesting than the complex geopolitics of AI chips, which ground the funding reports in real news that we all should pay attention to. A quick online search on the issue, in fact, will take you on a fascinating trip around the globe.
Around the world in AI chip geopolitics
You can start your geopolitical AI chip tour in Taiwan — where TMSC manufacturers most of today’s chips suitable for AI workloads, including those designed by Nvidia, based in Santa Clara, California, which enjoys more than 80% of the market for high-end AI chips.
Next, head to China, which also relies on TMSC-manufactured chips, particularly from Nvidia, but also has an ambition to control Taiwan — which is why the US restricted Nvidia exports of its most advanced AI chips to China (which, in turn, led Nvidia to develop downgraded , China-focused chips).
Then, travel east to Washington DC, where you’ll find the Biden Administration working overtime to reduce reliance on TMSC, in an effort to fend off China in the global AI race. In August 2022, President Biden signed the $53 billion “CHIPS and Science Act of 2022” (“CHIPS Act”) into law. ?It aimed to “boost American semiconductor research, development, and production” by providing $280 billion in funding, primarily towards R&D.”
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Just last Friday, Fortune reported that the Biden administration announced it would?“direct $5 billion ?in CHIPS Act money toward a new training facility to boost workforce participation in a semiconductor industry?dominated by foreign talent .” This is just a preview of what’s to come: “That’s an indicator of much more to come: “After a lengthy review period, the government will start giving out billions more over the coming months, primarily?in the form of ?grants to domestic chip manufacturers such as?Intel .”
After that, take a flight across the Atlantic Ocean until you hit the United Arab Emirates, where Sheikh Tahnoun bin Zayed al Nahyan, who has served as the country’s global security advisor since 2016, is the chair of AI firm G42 .
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Chief Analyst at RiskHedge │ Rational optimist
9 个月I’ve learned to never bet against Sam Altman. But even if he somehow manages to raise the cash, it’ll be at least 2030 before the factories are up and running. In the meantime, AI will need a lot of cutting-edge chips. And there’s only one company on the planet capable of making them: Taiwan Semiconductor (TSM). Nvidia’s chips power AI tools like ChatGPT. But Nvidia doesn’t actually make these chips. That’s TSMC’s job. To show you how incredible this company is, read this excerpt from a recent Wired magazine essay: "Every six months, just one of TSMC’s 13 foundries… carves and etches a quintillion transistors for Apple. […] the semiconductor industry churns out more objects in a year than have ever been produced in all the other factories in all the other industries in the history of the world." The world runs on chips, which really means the world runs on TSMC. Invest accordingly…
AI Education Policy Consultant
9 个月We need to be able to scale AGI. I find it hard to criticize Altman's efforts. Imagine that OpenAI develops “something similar" to AGI capabilities. *Achieving* that is possible with existing processing/GPU supplies. Sharing it with *major companies and the military* is probably possible within existing processing capacity. But how will the rest of us get to use such capabilities if there is only enough processing power to run the top of industry and the military? There is almost a moral obligation to scale AGI, and that can only be done with enough processing power.
PR & Communications Evangelist | Climate Change Initiatives | Former Wine Specialist of National Geographic Explorer | Veteran's Business Coach
9 个月#aichips #chips #lithium