Is Nuclear Fusion Really The Ultimate Solution to AI’s Crazy Power Use?
By Alex Kimani – Mar 29, 2024, https://oilprice.com/Energy/Energy-General/Is-Nuclear-Fusion-Really-The-Ultimate-Solution-to-AIs-Crazy-Power-Use.html
- A Boston Consulting Group analysis has predicted that data center electricity consumption will triple by 2030.
- Past trends in technology advances suggest that AI cons are very likely to outweigh the pros as far as power demand is concerned.
- OpenAI’s Altman: nuclear fusion is the ultimate solution to the AI energy puzzle
Two weeks ago, we reported how Artificial Intelligence (AI), cryptocurrency mining and clean energy manufacturing are powering the Fourth Industrial Revolution, or simply 4R, and driving disruptive trends including the rise of data and connectivity, analytics, human-machine interaction, and improvements in robotics. Unfortunately, these secular megatrends are pushing the U.S. power grid to its limits.
According to Sreedhar Sistu, vice president of artificial intelligence at Schneider Electric (OTCPK:SBGSF), excluding China, AI represents 4.3 GW of global power demand, and could grow almost five-fold by 2028. Another analysis has predicted that demand from AI will grow exponentially, increasing at least 10x between 2023 and 2026.
AI tasks typically demand more powerful hardware than traditional computing tasks. Meanwhile, bitcoin mining shows no signs of slowing down, with mining rates hitting 565 exahashes per second (EH/s) currently, a five-fold increase from three years ago.
Bitcoin mining consumes 148.63 TWh of electricity per year and emits 82.90 Mt CO2 per year, comparable to the power consumption of Malaysia. And, data center demand is not helping matters at all. Data center storage capacity is expected to grow from 10.1 zettabytes (ZB) in 2023 to 21.0 ZB in 2027, good for a 18.5% CAGR.
A Boston Consulting Group analysis has predicted that data center electricity consumption will triple by 2030, enough electricity to power 40 million U.S. homes.
The situation is already getting out of hand: U.S. power demand has started rising for the first time ever in 15 years. “We as a country are running out of energy,” Michael Khoo, climate disinformation program director at Friends of the Earth and co-author of a report on AI and climate, has told CNN.
To be fair, AI has been touted as one of the key technologies that will help tackle climate change. The revolutionary technology is already being used to track pollution, predict weather, monitor melting ice and map deforestation. A recent report commissioned by Google and published by the Boston Consulting Group claimed AI could help mitigate up to 10% of planet-heating pollution.
Unfortunately, past trends in technology advances suggest that AI cons are very likely to outweigh the pros as far as power demand is concerned.
“Efficiency gains have never reduced the energy consumption of cryptocurrency mining. When we make certain goods and services more efficient, we see increases in demand,” Alex de Vries, a data scientist and researcher at Vrije Universiteit Amsterdam, has pointed out.
At this point, nearly everybody agrees that we are incapable of developing renewable energy plants fast enough to meet this skyrocketing power demand. So, what other recourse do we have, short of saying let’s just build more natural gas and fossil fuel power plants?
Enter nuclear fusion, long regarded by scientists as the Holy Grail of clean and almost limitless energy. Sam Altman, head of ChatGPT creator OpenAI, says nuclear fusion is the ultimate solution to the AI energy puzzle, “There’s no way to get there without a breakthrough, we need fusion,” Altman said in a January interview. Altman reiterated this view a few weeks ago when podcaster and computer scientist Lex Fridman asked him about the AI energy conundrum.
Blue Sky Thinking
Unfortunately, Altman’s proposal is likely another case of overly optimistic blue-sky thinking, and we might not be any closer to building a commercial nuclear fusion reactor than we are to harvesting energy from blackholes.
For decades, nuclear fusion has been considered the “Holy Grail” of clean energy. If we were able to harness its power it would mean endless clean and sustainable energy. It’s what powers stars, and the theory is that it could be successfully applied to nuclear reactors–without the risk of a catastrophic meltdown disaster.
Scientists have been working on a viable nuclear fusion reactor since the 1950s–ever hopeful that a breakthrough is just around the corner. Unfortunately, the running joke has become that a practical nuclear fusion power plant could be decades or even centuries away, with milestone after milestone having fallen time and again
To be fair again, there’s been some promising glimpses into the possibilities here. Last year, a nuclear fusion reactor in California produced 3.15 megajoules of energy using only 2.05 megajoules of energy input, a rare instance where a fusion experiment produced more energy than it consumed. The vast majority of fusion experiments are energy negative, taking in more energy than they generate thus making them useless as a form of electricity generation. Despite growing hopes that fusion could soon play a part in climate change mitigation by providing vast amounts of clean power for energy-hungry technologies like AI, the world is “still a way off commercial fusion and it cannot help us with the climate crisis now”, Aneeqa Khan, research fellow in nuclear fusion at Manchester University, told the Guardian just after the initial December breakthrough.
You don’t have to look very far to get a healthy dose of reality check.
For decades, 35 countries have collaborated on the largest and most ambitious scientific experiments ever conceived: the International Thermonuclear Experimental Reactor (ITER), the biggest-ever fusion power machine. ITER plans to generate plasma at temperatures 10x higher than that of the sun’s core, and generate net energy for seconds at a time. As is usually the case with many nuclear power projects, ITER is already facing massive cost overruns that puts its future viability in question. W
When the ITER project formally commenced operations in 2006, its international partners agreed to fund an estimated €5 billion (then $6.3 billion) for a 10-year plan that would have seen the reactor come online in 2016. Charles Seife, director of the Arthur L. Carter Institute of Journalism at New York University, has sued ITER for lack of transparency on cost and incessant delays. According to him, the project’s latest official cost estimate now stands at more than €20 billion ($22 billion), with the project nowhere near achieving its key objectives. To make matters worse, none of ITER’s key players, including the U.S. Department of Energy, has been able to provide concrete answers of whether the team can overcome the technical challenges or estimates of the additional delays, much less the extra expenses.
Seife notes that whereas the Notre Dame took a century to complete, it eventually was used for its intended purpose less than a generation after construction began. However, he concludes by saying that the same can hardly be said about ITER, which looks less and less like a cathedral–and more like a mausoleum.
ChatGPT’s boss claims nuclear fusion is the answer to AI’s soaring energy needs. Not so fast, experts say
CNN, 26 Mar 24,
Artificial intelligence is energy-hungry and as companies race to make it bigger, smarter and more complex, its thirst for electricity will increase even further. This sets up a thorny problem for an industry pitching itself as a powerful tool to save the planet: a huge carbon footprint.
Yet according to Sam Altman, head of ChatGPT creator OpenAI, there is a clear solution to this tricky dilemma: nuclear fusion.
Altman himself has invested hundreds of millions in fusion and in recent interviews has suggested the futuristic technology, widely seen as the holy grail of clean energy, will eventually provide the enormous amounts of power demanded by next-gen AI.
“There’s no way to get there without a breakthrough, we need fusion,” alongside scaling up other renewable energy sources, Altman said in a January interview. Then in March, when podcaster and computer scientist Lex Fridman asked how to solve AI’s “energy puzzle,” Altman again pointed to fusion.
Nuclear fusion — the process that powers the sun and other stars — is likely still decades away from being mastered and commercialized on Earth. For some experts, Altman’s emphasis on a future energy breakthrough is illustrative of a wider failure of the AI industry to answer the question of how they are going to satiate AI’s soaring energy needs in the near-term.
It chimes with a general tendency toward “wishful thinking” when it comes to climate action, said Alex de Vries, a data scientist and researcher at Vrije Universiteit Amsterdam. “It would be a lot more sensible to focus on what we have at the moment, and what we can do at the moment, rather than hoping for something that might happen,” he told CNN.
A spokesperson for OpenAI did not respond to specific questions sent by CNN, only referring to Altman’s comments in January and on Fridman’s podcast.
The appeal of nuclear fusion for the AI industry is clear. Fusion involves smashing two or more atoms together to form a denser one, in a process that releases huge amounts of energy.
It doesn’t pump carbon pollution into the atmosphere and leaves no legacy of long-lived nuclear waste, offering a tantalizing vision of a clean, safe, abundant energy source.
But “recreating the conditions in the center of the sun on Earth is a huge challenge” and the technology is not likely to be ready until the latter half of the century, said Aneeqa Khan, a research fellow in nuclear fusion at the University of Manchester in the UK.
“Fusion is already too late to deal with the climate crisis,” Khan told CNN…………………………………
As well as the energy required to make chips and other hardware, AI requires large amounts of computing power to “train” models — feeding them enormous datasets —and then again to use its training to generate a response to a user query.
As the technology develops, companies are rushing to integrate it into apps and online searches, ramping up computing power requirements. An online search using AI could require at least 10 times more energy than a standard search, de Vries calculated in a recent report on AI’s energy footprint.
The dynamic is one of “bigger is better when it comes to AI,” de Vries said, pushing companies toward huge, energy-hungry models. “That is the key problem with AI, because bigger is better is just fundamentally incompatible with sustainability,” he added.
The situation is particularly stark in the US, where energy demand is shooting upward for the first time in around 15 years, said Michael Khoo, climate disinformation program director at Friends of the Earth and co-author of a report on AI and climate. “We as a country are running out of energy,” he told CNN.
In part, demand is being driven by a surge in data centers. Data center electricity consumption is expected to triple by 2030, equivalent to the amount needed to power around 40 million US homes, according to a Boston Consulting Group analysis.
“We’re going to have to make hard decisions” about who gets the energy, said Khoo, whether that’s thousands of homes, or a data center powering next-gen AI. “It can’t simply be the richest people who get the energy first,” he added…………………………………………………………………..
There has been a “tremendous” increase in AI’s efficiency, de Vries said. But, he cautioned, this doesn’t necessarily mean AI’s electricity demand will fall.
In fact, the history of technology and automation suggests it could well be the opposite, de Vries added. He pointed to cryptocurrency. “Efficiency gains have never reduced the energy consumption of cryptocurrency mining,” he said. “When we make certain goods and services more efficient, we see increases in demand.”
In the US, there is some political push to scrutinize the climate consequences of AI more closely. In February, Sen. Ed Markey introduced legislation aimed at requiring AI companies to be more transparent about their environmental impacts, including soaring data center electricity demand.
“The development of the next generation of AI tools cannot come at the expense of the health of our planet,” Markey said in a statement at the time. But few expect the bill would get the bipartisan support needed to become law…………https://edition.cnn.com/2024/03/26/climate/ai-energy-nuclear-fusion-climate-intl/index.html
1.This month.
13 July Webinar: Don’t Nuke The Climate: how to counter the nuclear disinformation
Saturday July 13 from 10.30am till 12pm.
British High Court Grants WikiLeaks Founder Julian Assange the Right to Appeal U.S. Extradition.
Antinuclear 