News In Context

AI’s Energy Conundrum

Google said this week that its greenhouse gas emissions have surged 48% in the past five years due to the expansion of the data centers it uses to underpin artificial intelligence systems, leaving its commitment to get to Net Zero by 2030 in doubt. It is the latest big tech company to publicly reveal a struggle to reconcile the energy use needed to fuel its AI ambitions with climate goals.

Microsoft, which has invested billions of dollars into OpenAI, the company behind ChatGPT, and is building its own AI tools, in May said its emissions have risen by almost a third since 2020, as the push to build out the infrastructure behind artificial intelligence threatens its climate goals. The nearly 30% increase in emissions was in large part due to the construction of the data centers that AI and cloud computing systems run on, Microsoft said in its annual sustainability report.

The computational power required for sustaining AI’s rise is doubling roughly every 100 days. To achieve a tenfold improvement in AI model efficiency, the computational power demand could surge by up to 10,000 times. The energy required to run AI tasks is already accelerating with an annual growth rate between 26% and 36%. This means by 2028, AI could be using more power than the entire country of Iceland used in 2021.

The AI lifecycle impacts the environment in two key stages: the training phase and the inference phase. In the training phase, models learn and develop by digesting vast amounts of data. Once trained, they step into the inference phase, where they’re applied to solve real-world problems. At present, the environmental footprint is split, with training responsible for about 20% and inference taking up the lion’s share at 80%. As AI models gain traction across diverse sectors, the need for inference and its environmental footprint will escalate.

Microsoft Co-founder Bill Gates recently claimed that artificial intelligence will be more of a help than a hindrance in achieving climate goals, despite growing concern that an increase in new data centers could drain green energy supplies.

Speaking at a June 27 conference in London hosted by his fund Breakthrough Energy ,Gates told journalists that AI would enable countries to use less energy, even as they require more data centers, by making technology and electricity grids more efficient.

That may turn out to be prescient but to align the rapid progress of AI with the imperative of environmental sustainability, a meticulously planned strategy is essential, Beena Ammanath, a board member at the Centre for Trustworthy Technology, wrote in an essay published by The World Economic Forum in April.

She cites research about the actionable steps that can be taken today to align AI progress with sustainability. For example, capping power usage during the training and inference phases of AI models presents a promising avenue for reducing AI energy consumption by 12% to 15%, with a small tradeoff on time to finish tasks with GPUs expected to take around 3% longer.

Another impactful tactic is optimized scheduling for energy savings. Shifting AI workloads to align with times of lower energy demand — like running shorter tasks overnight or planning larger projects for the cooler months, in place where air conditioner usage is widespread — can also lead to substantial energy savings, she notes.

Finally, moving towards the use of shared data centers and cloud computing resources instead of individually commissioning private infrastructure can centralize computational tasks in collective infrastructures and reduce the energy consumption associated with AI operations. This can also lead to financial savings on equipment and potentially lower energy bills, especially when resources are strategically located in areas with lower energy costs, says Ammanath.

Beyond immediate measures, the near-term focus should be on harnessing AI’s own capabilities to foster sustainability, she says. AI, used right, can be a powerful tool for meeting the ambitious target of tripling renewable energy capacity and double energy efficiency by the decade’s end, established in last year’s United Nations Climate Change Conference (COP28).

AI can bolster climate and energy transition efforts in different ways, including the development of new materials for clean energy technologies; the optimization of solar and wind farms, improving energy storage capabilities and carbon capture processes, enhancing climate and weather predictions for better energy planning, and catalyzing novel breakthroughs in green energy sources like nuclear fusion., she says.

“By strategically harnessing AI to enhance our renewable energy landscape, the future of AI holds the promise of not only becoming green in its own operations but also aid in building a more sustainable world,” she says.



Europe Wants To Send Energy Guzzling Data Centers Into Space

The rise of artificial intelligence is skyrocketing demand for data centers to keep pace with the growing tech sector — and pushing Europe to explore space options for digital storage, in a bid to reduce its need for energy-hungry facilities on the ground, reports CNBC.

Advanced Space Cloud for European Net zero emission and Data sovereignty, a 16-month-long study that explored the feasibility of launching data centers into orbit, has come to a “very encouraging” conclusion, according to Damien Dumestier, manager of the project.The 2 million euro ($2.1 million) ASCEND study, coordinated by Thales Alenia Space on behalf of the European Commission, claims that space-based data centers are technically, economically and environmentally feasible.“The idea [is] to take off part of the energy demand for data centers and to send them in space in order to benefit from infinite energy, which is solar energy,” Dumestier told CNBC.


Renault’s EV Unit Ampere Teams With Asian Companies On Battery Technologies

Renault’s  electric vehicle unit Ampere saidit would include lithium iron phosphate (LFP) technology in its plans to mass produce EVs, teaming up with LG Energy Solution  and CATL to build a supply chain in Europe. Western automakers are under pressure to expand their range of chemical battery technologies to meet the needs of all market segments amid fierce competition from their oftencheaper Chinese rivals.

Carmaker Stellantis Joins Forces With France’s CEA for EV Battery Research

Stellantis  the carmaker whose brands include Peugeot, Fiat and Chrysler, announced July 3 a partnership with the French state’s CEA research organization to work on a next generation of battery cells for electric vehicles.

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About the author

Jennifer L. Schenker

Jennifer L. Schenker, an award-winning journalist, has been covering the global tech industry from Europe since 1985, working full-time, at various points in her career for the Wall Street Journal Europe, Time Magazine, International Herald Tribune, Red Herring and BusinessWeek. She is currently the editor-in-chief of The Innovator, an English-language global publication about the digital transformation of business. Jennifer was voted one of the 50 most inspiring women in technology in Europe in 2015 and 2016 and was named by Forbes Magazine in 2018 as one of the 30 women leaders disrupting tech in France. She has been a World Economic Forum Tech Pioneers judge for 20 years. She lives in Paris and has dual U.S. and French citizenship.