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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.

Copyright Law Struggles To Keep Up With AI Training

Courts Are Still Applying Old Copyright Rules To AI

AI companies train models on enormous amounts of published material, including books, articles and academic research. Whether using that content without authors’ permission violates copyright law remains unresolved.

Much of the debate centres on fair use, which allows copyrighted material to be used without permission in certain circumstances. Courts consider factors such as the purpose of the use, how much material was involved and its impact on the original market.

Anthropic Case Sets An Important Precedent

A major case involving Anthropic and a group of authors provided one of the clearest rulings so far. Judge William Alsup found that using copyrighted books to train AI models was lawful, comparing the process to people reading and studying literature before creating something new.

Anthropic was nevertheless ordered to pay $1.5 billion in a settlement. The penalty concerned books the company had obtained from illegal online libraries rather than the AI training itself.

For AI companies, that distinction could prove significant because it separates studying copyrighted material from directly copying it.

Competition Could Be The Key Issue

A case involving Thomson Reuters and Ross Intelligence offers a different perspective. A court ruled that Ross could not claim fair use after using Reuters’ copyrighted material to develop a competing AI-powered legal research platform.

The decision suggests courts may be less willing to consider AI training fair use when copyrighted content is used to build a product that directly competes with the original.

For authors, an unresolved question is whether AI-generated content should be considered competition for the works used to train these models.

The Law Has Yet To Catch Up

US copyright law predates generative AI by decades, leaving courts to apply old principles to new technology. Questions also remain over copyright protection for AI-generated works. In Thaler v. Perlmutter, a court ruled that material created entirely by AI cannot receive copyright protection.

Major AI companies remain involved in copyright litigation, and different courts could reach different conclusions. For now, there is no universal rule: the legality of AI training will depend on the circumstances of each case and how courts ultimately interpret copyright and fair use.

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