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Amazon To Test AI-Created Material For Carbon Capture In Data Centers

Amazon is stepping up its environmental efforts by testing a groundbreaking carbon-removal material for its data centers. The company, which is tackling the growing emissions linked to the artificial intelligence systems powering these centers, has partnered with Orbital Materials, a startup that used AI to design the innovative substance.

Jonathan Godwin, CEO of Orbital Materials, explained that the new material acts like an atomic-level sponge, with cavities precisely sized to capture CO2 without interacting with other elements. This targeted approach could be a game-changer in carbon filtration.

One of the appealing aspects of the new material is its cost-effectiveness. Godwin estimates that the material could account for just 10% of the cost associated with renting a GPU chip for AI training, significantly less than the price of traditional carbon offsets.

Meanwhile, the demand for energy in data centers is rising, as AI’s rapid development requires more power and cooling solutions. This surge poses a challenge for Amazon, which is committed to achieving net-zero carbon emissions by 2040.

Amazon Web Services (AWS), the world’s largest cloud provider by revenue, plans to begin piloting the AI-designed carbon removal material in one of its data centers starting in 2025. This initiative is part of a three-year collaboration with Orbital, which will also gain access to AWS’s technology and open-source AI tools for further development.

Howard Gefen, General Manager of AWS Energy & Utilities, stated that the partnership would promote sustainable innovation, but financial details remain undisclosed. Orbital, with offices in Princeton, New Jersey, and London, began its journey about a year ago by setting up a lab to synthesize AI-designed materials. The startup aims to work with AWS to test additional AI-generated solutions, addressing water usage and cooling requirements in data centers. Godwin co-founded Orbital, which currently employs 20 people and is supported by investors such as Radical Ventures and Nvidia’s venture arm. Before this, Godwin contributed to materials science work at Alphabet’s DeepMind until 2022.

Europe’s Race For AI Leadership Hindered By Soaring Energy Costs

Europe’s Ambitious Vision And Energy Hurdles

Europe is accelerating efforts to strengthen its position in artificial intelligence as governments and technology companies continue investing heavily in data centers and compute infrastructure. At the same time, rising energy costs are increasingly emerging as one of the main obstacles to the continent’s broader AI ambitions.

Building The Infrastructure Amid A Price Surge

European countries are expanding compute capacity and supporting large-scale infrastructure projects aimed at powering next-generation AI systems. However, the rapid growth of energy-intensive data centers is significantly increasing electricity demand at a time of continued geopolitical and energy market volatility. Michael Brown said energy prices remain one of the defining factors shaping where future AI infrastructure will be developed. “If you’re making energy-intensive investments, then you’re going to go to where the cheapest energy is,” Brown said, adding that major future data center investments would likely favour the U.S. or China due to lower energy costs.

Data Center Growth And The Economic Stakes

Data centers now account for roughly 2% of global electricity consumption, up from 1.7% in 2024, reflecting the growing energy demands associated with AI development and cloud computing. Olivier Darmouni warned that rapid data center expansion could increase regional electricity prices by between 20% and 40% in certain European markets, particularly in areas already facing energy supply pressures. According to Darmouni, this trend risks creating widening disparities across Europe, with regions benefiting from lower energy prices becoming more attractive for investment while higher-cost markets struggle to remain competitive.

Navigating The Development Challenges

Industry analysts also point to several structural challenges affecting Europe’s ability to scale AI infrastructure quickly. Chris Seiple said Europe continues facing disadvantages linked to higher energy costs, the geographic concentration of data center developers and the long timelines required to build supporting infrastructure. Together, these factors are slowing deployment compared with competing markets such as the United States and China.

Regional Winners And Losers

Within Europe, disparities in energy costs are creating clear winners and losers. Vladimir Prodanovic of Nvidia remarked during a conference in Denmark that parts of central Europe have already been outpaced due to exorbitant electricity prices, citing examples from Germany and the U.K. Indeed, data from the International Energy Agency shows that the average price per megawatt in the U.K. and Germany far exceeds that of the U.S., intensifying the competitive pressure.

The Nordic And French Advantage

In contrast, the Nordics and France are emerging as the favored regions for data center investment, bolstered by lower electricity costs and a diverse energy mix. Major tech players such as Microsoft have committed billions to AI infrastructure projects in these regions, with significant investments in Norway, Sweden, and Denmark. Additionally, experts like Vili Lehdonvirta from the Oxford Internet Institute note that sustained low or even negative electricity pricing, as observed in parts of Finland, offers a considerable economic edge.

Looking Ahead: Integration And Economic Sovereignty

Olivier Darmouni argued that maintaining competitiveness in artificial intelligence will require deeper integration of Europe’s energy systems alongside major investments in electricity generation and storage infrastructure.

Without broader reforms aimed at stabilising long-term energy costs, Europe risks weakening both its position in the global AI race and its broader economic competitiveness.

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