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Japan And India Startups Collaborate To Tackle Space Debris With Laser-Equipped Satellites

In an ambitious step to address the growing issue of orbital congestion, Japanese startup Orbital Lasers and Indian robotics firm InspeCity announced in December 2024, their plans to study the use of laser-equipped satellites for debris removal. 

Orbital debris, often referred to as space junk, includes all non-functional, human-made objects in Earth’s orbit, such as defunct satellites, rocket fragments, and collision debris. Traveling at speeds of up to 18,000 mph, this debris poses significant risks to operational satellites and spacecraft, including the International Space Station.

The partnership aims to develop an innovative system that uses laser energy to stop the rotation of space junk by vaporizing small surface areas, simplifying the process for servicing spacecraft to capture and de-orbit defunct satellites. Orbital Lasers, a spin-off from Japan’s satellite operator SKY Perfect JSAT, plans to demonstrate the laser system in space by 2027. Meanwhile, InspeCity, founded in 2022, is exploring opportunities to integrate the technology into its satellite platforms, pending regulatory approvals in both countries.

The agreement comes as global organizations raise alarms about the dangers of unchecked orbital debris. A United Nations panel on space traffic coordination recently underscored the need for urgent measures to manage low Earth orbit congestion, citing risks from the increasing volume of satellites and space junk.

This partnership reflects broader trends in Japan-India space collaboration, including their joint Lunar Polar Exploration (LUPEX) mission set for 2026 and partnerships between Indian firms like Skyroot and HEX20 with Japanese lunar exploration company Ispace. According to Masayasu Ishida, CEO of Tokyo-based nonprofit SPACETIDE, such alliances are aligned with India’s “Make in India” initiative, promoting local production while leveraging Japan’s technological expertise.

As the space industry grows more crowded, the success of projects like this could play a pivotal role in ensuring the sustainability of near-Earth orbit for future generations.

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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