From Watts Up With That?
Essay by Eric Worrall
“the entire industry is chasing the AI dragon” – $27 billion+ for a single project. Bye bye climate action virtue signalling.
Million GPU clusters, gigawatts of power – the scale of AI defies logic
It’s not just one hyperbolic billionaire – the entire industry is chasing the AI dragon
Tobias Mann
Thu 19 Dec 2024 // 17:30 UTCCOMMENT Next year will see some truly monstrous compute projects get underway as the AI boom enters its third year. Among the largest disclosed so far is xAI’s plan to expand its Colossus AI supercomputer from an already impressive 100,000 GPUs to a cool million.
Such a figure seemingly defies logic. Even if you could source enough GPUs for this new Colossus, the power and cooling – not to mention capital – required to support it would be immense.
At $30,000 to $40,000 a pop, adding another 900,000 GPUs would set xAI back $27 to $36 billion. Even with a generous bulk discount, it still won’t be cheap regardless of whether they’re deployed over the course of several years. Oh, and that’s not even taking into account the cost of the building, cooling, and the electrical infrastructure to support all those accelerators.
Speaking of power, depending on what generation of accelerators xAI plans to deploy, the GPU nodes alone would require roughly 1.2 to 1.5 gigawatts of generation. That’s more than the typical nuclear reactor – and the big ones, no less. And again, that’s just for the compute.
…
The AI fever with which the tech giants have collectively come down has served as a sort of sea change for the nuclear industry as a whole, with cloud providers fronting the cash to reinstate retired reactors – and even plop their datacenters behind the meter in the case of AWS’ new Cumulus datacenter complex.
…Read more:https://www.theregister.com/2024/12/19/scale_ai_defies_logic/
Think about it: $27 – $36 billion for just one of these new AI data centers. The Register lists xAI, Meta (Facebook), AWS (Amazon), Oracle, and of course we already know about Microsoft – all of which appear to be initiating Gigascale AI projects in 2025 or have already initiated their projects.
Of course, these are only the US based tech companies. India is also racing to build their own gigascale AI, and there are suggestions that China is also getting into the AI game in a big way, though concrete details of Chinese AI efforts are scarce.
India’s Reliance builds a Gigawatt data center with Nvidia Blackwell AI GPUs
By Anton Shilov
published October 26, 2024But is India’s power grid prepared for that?
Frontier, the world’s highest-performing supercomputer, consumes 8 M.W. and 30 M.W. of electricity, depending on the workload. However, the upcoming AI data center is estimated to consume much more. India-based Reliance is set to build a 1 GWh (one-gigawatt hour) data center for AI that will run Nvidia’s Blackwell GPUs, Reuters reports.
“In the future, India is going to be the country that will export AI,” said Jensen Huang, CEO of Nvidia, according to Reuters. “You have the fundamental ingredients – AI, data and AI infrastructure, and you have a large population of users.”
…Read more:
Why has AI rapidly attracted so much attention? AI might be complex, but the motivation of tech companies, investors and government backers is easy to understand. The nation or tech company which successfully creates the first Artificial General Intelligence has a real shot at becoming the dominant power on Earth in perpetuity – or so proponents believe. The prize is ultimate power, possession of the One Ring. To be the first to control a greater than human AGI is to control of the future – to always know in advance what your opponents are planning, and always having timely knowledge of the perfect counter move to advance your interests.
To complete the homage to Tolkien’s fictional One Ring, AI or AGI could deliver life extension or even medical immortality to its owners. One of the hottest current uses of AI is drug discovery and reverse engineering human DNA.
What will power this AI Gold Rush? The Register sticks to the line that this will be a boom for the nuclear industry, and there is substantial ongoing interest in nuclear data center solutions, but the Fossil Fuel powered Facebook AI project shows delays in commissioning or rehabilitating nuclear plants are not going to slow these people down. It is only a matter of time until demand exceeds available nuclear and gas, and tech companies and governments start building new coal plants to power their AI data centers.
China in particular has a home field advantage when it comes to powering AI, despite US tech sanctions. The Chinese housing and economic slowdown has likely created a surplus of 10s of gigawatts of electricity which could be used to power gigantic AI projects, without having to build new power plants. Existing US tech sanctions will have very little impact on the Chinese AI push, AI is one field where quantity can be substituted for quality – the gigawatt AI data centers themselves are proof of this. If it takes a thousand legacy Chinese chips to match the computational capacity of one cutting edge US AI chip, China is already big in the second tier chip fabrication space. China will have no difficulty fabricating the vast quantities of second tier AI chips required to keep China in the race.
China also has a large graduate unemployment problem. A Chinese commitment to a new tech race which absorbs the very best of China’s millions of desperate, unemployed tech graduates makes China a strong contender in the AI race, regardless of US tech sanctions and any other disadvantages.
I must confess, an immediate explosion of AI data centers, each of which consume more power than a major city, is more than I anticipated this early in the game. I thought it would take at least a couple of years for the AI gold rush to ramp up to this level of activity.
In the short term, this sudden burst of activity may be more of a case of nation states scrambling to match their rivals, and tech companies responding to shareholder pressure to stay in the game, rather than genuine customer demand.
But the pressure will be on to justify these crazy investments, so those AI data centers will see a lot of use the moment the power is hooked up, even if that use is just techies exploring how to hype the new corporate AI white elephant into a profit generating business asset – a leap into the unknown which could result in anything ranging from fabulous wealth and global political leverage to bankruptcy and ruin, for nations, politicians, and tech giants and their backers.
If you are interested in a deeper dive into AI, the following delves into why AI data centers need gigawatts of electricity to function.
Artificial Intelligence: A Working Demonstration, and Why Big Tech Ditched Big Green
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