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LW - Actually, Power Plants May Be an AI Training Bottleneck. by Lao Mein
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Manage episode 424673803 series 2997284
Content provided by The Nonlinear Fund. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Nonlinear Fund or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Actually, Power Plants May Be an AI Training Bottleneck., published by Lao Mein on June 20, 2024 on LessWrong. There have been presistent rumors that electricity generation was somehow bottlenecking new data centers. This claim was recently repeated by Donald Trump, who implied that San Francisco donors requested the construction of new power plants for powering new AI data centers in the US. While this may sound unlikely, my research suggests it's actually quite plausible. US electricity production has been stagnant since 2007. Current electricity generation is ~ 500 million kW. An H100 consumes 700 W at peak capacity. Sales of H100s were ~500,000 in 2023 and expected to climb to 1.5-2 million in 2024. "Servers" account for only 40% of data center power consumption, and that includes non-GPU overhead. I'll assume a total of 2 kW per H100 for ease of calculation. This means that powering all H100s produced to the end of 2024 would require ~1% of US power generation. H100 production is continuing to increase, and I don't think it's unreasonable for it (or successors) to reach 10 million per year by, say, 2027. Data centers running large numbers of AI chips will obviously run them as many hours as possible, as they are rapidly depreciating and expensive assets. Hence, each H100 will require an increase in peak powergrid capacity, meaning new power plants. I'm assuming that most H100s sold will be installed in the US, a reasonable assumption given low electricity prices and the locations of the AI race competitors. If an average of 5 million H100s go online each year in the US between 2024 and 2026, that's 30 kW, or 6% of the current capacity! Given that the lead time for power plant construction may range into decades for nuclear, and 2-3 years for a natural gas plant (the shortest for a consistant-output power plant), those power plants would need to start the build process now. In order for there to be no shortfall in electricity production by the end of 2026, there will need to be ~30 million kW of capacity that begins the construction process in Jan 2024. That's about close to the US record (+40 million kW/year), and 6x the capacity currently planned to come online in 2025. I'm neglecting other sources of electricity since they take so much longer to build, although I suspect the recent bill easing regulations on nuclear power may be related. Plants also require down-time, and I don't think the capacity delow takes that into account. This is why people in Silicon Valley are talking about power plants. It's a big problem, but fortunately also the type that can be solved by yelling at politicians. Note the above numbers are assuming the supply chain doesn't have shortages, which seems unlikely if you're 6x-ing powerplant construction. Delaying decommisioning of existing power plants and reactivation of mothballed ones will likely help a lot, but I'm not an expert in the field, and don't feel qualified to do a deeper analysis. Overall, I think the claim that power plants are a bottleneck to data center construction in the US is quite reasonable, and possibly an understatement. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org
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2447 episodes
MP3•Episode home
Manage episode 424673803 series 2997284
Content provided by The Nonlinear Fund. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Nonlinear Fund or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Actually, Power Plants May Be an AI Training Bottleneck., published by Lao Mein on June 20, 2024 on LessWrong. There have been presistent rumors that electricity generation was somehow bottlenecking new data centers. This claim was recently repeated by Donald Trump, who implied that San Francisco donors requested the construction of new power plants for powering new AI data centers in the US. While this may sound unlikely, my research suggests it's actually quite plausible. US electricity production has been stagnant since 2007. Current electricity generation is ~ 500 million kW. An H100 consumes 700 W at peak capacity. Sales of H100s were ~500,000 in 2023 and expected to climb to 1.5-2 million in 2024. "Servers" account for only 40% of data center power consumption, and that includes non-GPU overhead. I'll assume a total of 2 kW per H100 for ease of calculation. This means that powering all H100s produced to the end of 2024 would require ~1% of US power generation. H100 production is continuing to increase, and I don't think it's unreasonable for it (or successors) to reach 10 million per year by, say, 2027. Data centers running large numbers of AI chips will obviously run them as many hours as possible, as they are rapidly depreciating and expensive assets. Hence, each H100 will require an increase in peak powergrid capacity, meaning new power plants. I'm assuming that most H100s sold will be installed in the US, a reasonable assumption given low electricity prices and the locations of the AI race competitors. If an average of 5 million H100s go online each year in the US between 2024 and 2026, that's 30 kW, or 6% of the current capacity! Given that the lead time for power plant construction may range into decades for nuclear, and 2-3 years for a natural gas plant (the shortest for a consistant-output power plant), those power plants would need to start the build process now. In order for there to be no shortfall in electricity production by the end of 2026, there will need to be ~30 million kW of capacity that begins the construction process in Jan 2024. That's about close to the US record (+40 million kW/year), and 6x the capacity currently planned to come online in 2025. I'm neglecting other sources of electricity since they take so much longer to build, although I suspect the recent bill easing regulations on nuclear power may be related. Plants also require down-time, and I don't think the capacity delow takes that into account. This is why people in Silicon Valley are talking about power plants. It's a big problem, but fortunately also the type that can be solved by yelling at politicians. Note the above numbers are assuming the supply chain doesn't have shortages, which seems unlikely if you're 6x-ing powerplant construction. Delaying decommisioning of existing power plants and reactivation of mothballed ones will likely help a lot, but I'm not an expert in the field, and don't feel qualified to do a deeper analysis. Overall, I think the claim that power plants are a bottleneck to data center construction in the US is quite reasonable, and possibly an understatement. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org
…
continue reading
2447 episodes
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