The AI Datacenter War

Alpha
September 06, 2024

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TECH IN THE NEWS

Financial AI ‘Sandbox’ - A new bipartisan bill would create a ‘sandbox’ to enable financial firms to experiment with AI products free of regulation.

SS Starlink - The US Navy is is testing the Elon Musk–owned Starlink satellite constellation to provide high-speed internet access at sea. Starlink also said it will now comply with Brazil’s X ban.

AI Safety Treaty - Yesterday the US and UK signed a treaty brought forth by the Council of Europe to protect human rights and data sovereignty.

US Hedge Fund - Donald Trump has called for the creation of a US sovereign wealth fund based on the UAE or Norway’s successful vehicles.

All in Moderation - Telegram has updated its moderation policy for private chats following CEO Pavel Durov's arrest in France.

DEALS TO WATCH

Safe Superintelligence - SSI, the San Fran AI startup co-founded by OpenAI's ex chief scientist Ilya Sutskever, raised $1b in cash at ~$5b valuation from Andreessen Horowitz, Sequoia, NFDG and others.

AI Productivity Agents - Palo Alto AI search/agents startup You.com raised a $50M Series B to build a “productivity engine” led by Georgian, with Day One, DuckDuckGo, Nvidia, Salesforce and SBVA.

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THE HOTTEST THING IN TECH
The AI Data Center War Heats Up

Major tech companies like Microsoft, Google, OpenAI, and Elon Musk's xAI are in a race to build bigger and more powerful AI data centers. The costs are massive in financial and environmental terms. With even Nvidia’s growth slowing, some are questioning the continued profitability of this level of AI spend. So what does the future hold for the AI compute sector?

Hey Big Spenders

Companies are keeping details of their data center projects quiet, but rumors of massive investments (like Microsoft and OpenAI's proposed $100 billion US-based supercomputer collaboration) are circulating. OpenAI has been pitching investors and states on plans to invest tens of billions on data centers, energy capacity and semiconductor manufacturing plants. OpenAI plans to develop its own AI chips using TSMC to reduce reliance on Nvidia's servers. However, both Apple and Nvidia have been reported as potential investors in this hardware project. Apple is also reportedly developing its own LLMs and custom AI chips to reduce reliance on third-party services. All of this hints at close cross-industry collaboration and possible infrastructure sharing agreements between some of the largest US industry players.

Google also recently announced plans to build a massive AI supercomputer cluster in in Nevada that is expected to be one of the largest AI-optimized data centers in the world.

Not to be outdone, Elon Musk claimed on Monday that xAI completed its “Colossus” supercomputer cluster, “the most powerful AI training system in the world," 100k Nvidia H100 chips in just four months. Musk also plans to double this capacity in the next few months. Some experts question the feasibility of this timeline. Greylock VC Reid Hoffman points out that this level of investment is simply “table stakes” for the kinds of AI Musk is pursuing, saying “I don't think it's necessarily [that] he's in the lead,” but that it allows xAI to catch up to others that have been investing heavily for years.

Chinese Competition

China is making its own significant strides in AI supercomputing. Huawei has been developing its own AI chips (Ascend series) to reduce reliance on US tech. Baidu, Alibaba, and Tencent are all investing heavily in AI infrastructure. In 2023, China unveiled the Sunway OceanLight, one of the world's most powerful supercomputers, designed for large AI workloads.

At what Cost?

The rapid expansion of AI data centers is raising environmental issues. For example, Musk's Memphis xAI datacenter is accused of “smog” air pollution, while Microsoft's facilities are straining water resources in drought-prone areas like Arizona and Iowa. This is precisely why Sam Altman and others are investing heavily in nuclear fission and Fusion as a way to find more efficient alternatives to power the massive loads required to expand AI services.

However, another major issue is the outdated and already overburdened US power grid. Critics rightly point out that AI datacenters are centralizing the profits and socializing the costs of AI, as taxpayers are asked to pick up the bill of upgrading these ageing grid systems across the country.

Alternatives to Data Center Wars

Instead of being locked in an endlessly escalating spiral of increased data and power usage, many are attacking the problem from the other angle of reducing demand. For instance, Groq's new LLaVA v1.5 7B multimodal AI model is available on GroqCloud, offering a different approach to AI infrastructure powered by its LPU (language processing units). others startups like Texas’ Applied Digital are also entering the market with AI compute leasing services. It just raised $160M from Nvidia to scale up. Some companies and researchers are even exploring the potential greater efficiencies of quantum computing for AI applications.

We will likely need a combination of more efficient AI and power systems to make sure AI can reach its full potential as a transformative technology.

“Even if it does come to fruition, don't expect it to make any performance headlines outside of handling GPT. ASICs by nature are designed to do one job very well but that's it. OpenAI's chip might be great for OpenAI but few other companies would be interested.”

— Nick Evanson, PC Gamer News

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