The artificial intelligence (AI) hype that made Nvidia Corp the world’s biggest company has come with a price for the climate. Data centers housing its powerful chips are gorging power and belching carbon dioxide, and sobering figures now reveal the extent of the problem.
Data centers would use 8 percent of US power by 2030, compared with 3 percent in 2022, as their energy demand grows by 160 percent, a recent report from Goldman Sachs Group Inc said.
AI is doing more to worsen the climate emergency than solve it, as some AI firms have touted. So great are the energy needs that utilities are extending their plans for coal plants, while Microsoft Corp is building gas and nuclear facilities to keep its servers humming.
Illustration: Tania Chou
Add this all to the growing discontent about generative AI tools. To not only stem the tide, but also uphold their goals of building AI “for humanity,” tech firms like OpenAI, Microsoft and Alphabet Inc’s Google must grow their teams addressing the power issue. It would certainly be possible. A few signs of progress suggest the trick might be to redesign their algorithms.
Generative AI models like ChatGPT and Anthropic’s Claude are impressive, but their neural network architectures demand vast amounts of energy, and their indecipherable “black box” decisionmaking processes make them difficult to optimize. The current state of AI is like trying to power a small car with a huge gas-guzzling engine: It gets the job done, but at an enormous cost.
The good news is that these “engines” could get smaller with greater investment. Researchers at Microsoft, for instance, have developed a so-called “1 bit” architecture that can make large language models about 10 times more energy efficient than the current leading systems. This approach simplifies the models’ calculations by reducing values to 0 or 1, slashing power consumption without sacrificing too much performance. The resulting tech is not the most capable, but a good example of a “contrarian” approach that can immediately reduce AI’s cost and environmental impact, says Steven Marsh, founder of UK-based start-up Zetlin Ltd, which is working on building more efficient systems.
Marsh says he is making progress. His team recently trained a neural network-based AI model on an Nvidia graphics processing unit, and the system heated up so much that they had to bring fans into the room over five days. When they ran the same model with their proprietary, non-neural network technology, it used just 60 percent of the power. The current approach, Marsh says, is “like putting a rocket engine on a bicycle.”
Nvidia has also taken promising steps toward addressing the energy problem. A couple of years ago, it developed a new format for its chips to process AI calculations with smaller numbers, making them faster and less power-hungry.
“Just that little tweak on the silicon saved a lot of energy,” Marsh says.
If companies designing AI systems take better advantage of that tweak, they could save energy eventually.
It does not help that AI companies are in an arms race. OpenAI and Anthropic have raised US$11.3 billion and US$8.4 billion respectively, data provider PitchBook said. Much of that money is not going to recruitment (they each have workforces of just a few hundred people). Instead, it is being poured into running servers that can train and run their models, even as their investment leads to diminishing returns. (There is evidence that the latest text and vision-reading systems are showing smaller advancements in areas like accuracy and capability.)
Those companies, along with Google, Microsoft and Amazon.com Inc, should devote additional money to refashioning their algorithms to save energy and cost. Collectively, it has been done before. Data centers managed to keep their power demands flat between 2015 and 2019, even as their workloads tripled, because their operators found ways to make them more efficient, Goldman Sachs said.
OpenAI chief executive officer Sam Altman has talked up nuclear fusion as an answer to the problem, having personally invested US$375 million into an enterprise called Helion Energy. However, he might be creating hype around an energy technology that would not be commercialized for several decades.
Rather than outsource responsibility to a futuristic energy source or superintelligent AI that does not exist yet, tech firms should put greater focus on making their models more energy efficient now. After all, breaking away from established and inefficient systems was how this revolution began in the first place.
Parmy Olson is a Bloomberg Opinion columnist covering technology. She is a former reporter for the Wall Street Journal and Forbes. This column does not necessarily reflect the opinion of the editorial board or Bloomberg LP and its owners.
Deterrence is fading; war is looming on the Taiwan Strait and for other targets of the China-enabled dictatorship alliance, and after three years the cure is just dawning on the Biden Administration. Now mind you, for a May 28, 2024 interview with Time magazine, President Joe Biden made his 5th public commitment that the United States would defend Taiwan. Less than three weeks later the United States Navy, along with ships from navies of Japan, Canada, the Netherlands, and France, were conducting the Valiant Shield joint force exercise in the Philippine Sea south of Taiwan and in the South China Sea to
The official media of the Chinese Communist Party (CCP) reacted to the May 20 inauguration speech of President William Lai (賴清德) by asserting: “Lai’s words reveal his true intention of sacrificing peace and stability across the Taiwan Strait for his own desire for power.” This baseless accusation by Beijing that Lai is manipulating Taiwanese to resist unification with China for his personal gain, is part of a broader CCP information warfare campaign that has intensified since Lai’s election. This campaign, orchestrated by the United Front Work Department, the CCP’s agency for coordinating influence operations and propaganda, aims to demoralize Taiwanese,
US aerospace company Boeing Co has in recent years been involved in numerous safety incidents, including crashes of its 737 Max airliners, which have caused widespread concern about the company’s safety record. It has recently come to light that titanium jet engine parts used by Boeing and its European competitor Airbus SE were sold with falsified documentation. The source of the titanium used in these parts has been traced back to an unknown Chinese company. It is clear that China is trying to sneak questionable titanium materials into the supply chain and use any ensuing problems as an opportunity to
Minister of Health and Welfare Chiu Tai-yuan (邱泰源) on Friday said the ministry supports keeping priority seats on public transportation, but is considering expanding the eligibility criteria and renaming the seats. Chiu’s remarks came after local news media over the past few weeks reported incidents involving priority seats, once again sparking heated discussion about whether the seats should be abolished or regulations regarding them should be revised. On June 11, an older woman asked a young woman on a Taipei MRT train to yield her priority seat. The young woman refused, saying that she needed the seat after working a 12-hour shift.