Canadian quantum computing firm Xanadu Quantum Technologies is set to go public through a merger with Crane Harbor Acquisition Corp in a deal valuing the company at $3.6 billion, the firms announced on Monday.

The merger, which will list Xanadu’s shares on the Nasdaq, is expected to generate nearly $500 million in proceeds, including a $275 million private investment in public equity (PIPE).

The move marks a major milestone for the Toronto-based startup, positioning it among the growing list of quantum computing companies seeking to tap public markets through special-purpose acquisition companies (SPACs) rather than traditional IPOs.

Xanadu’s CEO, Christian Weedbrook, told Reuters that the decision was driven by growing investor enthusiasm for quantum computing stocks.

“We were really keeping a close eye on what was happening in the public markets,” Weedbrook said. “The capital available in the public markets was too enticing to ignore.”

Quantum computing, long considered a futuristic technology, has begun moving from theoretical research into practical applications and commercial development. These machines use qubits—the quantum equivalent of classical bits—to perform complex calculations far beyond the capacity of conventional computers. In theory, quantum computers can simulate chemical reactions involving trillions of atoms in minutes, a feat that would take classical supercomputers thousands of years.

This leap in computational power has far-reaching implications for fields such as drug discovery, materials science, cryptography, and artificial intelligence. But Qubits are notoriously unstable, often collapsing under minimal interference, which can cause computational errors that overwhelm useful results. As a result, the industry continues to debate how soon truly error-corrected quantum computers will become commercially viable.

Still, investor optimism in the sector has surged in 2025, fueled by breakthroughs from major players and growing adoption among corporate giants. IBM, Microsoft, and Google have all accelerated their quantum research, with Google announcing a breakthrough algorithm last month that it claims could significantly improve quantum processing efficiency.

Meanwhile, JPMorgan Chase has outlined plans to integrate quantum computing into its long-term digital transformation strategy, as part of a broader $1.5 trillion innovation initiative announced in October. The financial sector’s growing interest in quantum applications—particularly for risk modeling and cybersecurity—has further validated the technology’s commercial potential.

The timing of Xanadu’s public debut comes amid renewed investor appetite for quantum firms. In September, U.S.-based Infleqtion (formerly ColdQuanta) struck a $1.8 billion SPAC deal with a blank-check company led by veteran Wall Street dealmaker Michael Klein, underscoring the sector’s momentum despite a challenging IPO climate.

Quantum computing companies have increasingly turned to SPAC mergers to expedite their market entries and access capital. The route allows startups to bypass the long regulatory scrutiny and pricing uncertainties of a traditional initial public offering.

For Xanadu, which specializes in photonic quantum computing—a system that uses light particles instead of electrical circuits—the influx of capital from the merger is expected to fund the expansion of its commercial roadmap and accelerate research into scalable quantum architectures.

Analysts say that as public and private investment floods into the quantum computing ecosystem, the industry is approaching a turning point. The industry is believed to be building viable systems and software that can solve real-world problems.

If the merger closes as planned, Xanadu will join a small but growing cohort of publicly traded quantum computing firms, giving investors new access to a technology that many believe will define the next era of computational power.

Japan’s Content Overseas Distribution Association (CODA), which represents the nation’s most prominent intellectual property holders, including Studio Ghibli, Bandai Namco, and Toei Animation, has demanded that OpenAI stop using its members’ copyrighted material to train its video generation model, Sora 2.

The letter, first reported by Automaton, accuses OpenAI of using Japanese creative works without authorization, calling the act of replication during the machine learning process a potential “copyright infringement.” CODA argued that the company’s generative AI system, which has produced numerous clips and visuals bearing a strong resemblance to Japanese animation and gaming characters, has crossed legal lines.

“CODA considers that the act of replication during the machine learning process may constitute copyright infringement,” the organization said.

The complaint follows the September 30 launch of Sora 2, which quickly became a global sensation for its lifelike AI-generated videos — many of which adopted the visual language and style of beloved Japanese animation studios. In response, Japan’s Ministry of Economy, Trade, and Industry reportedly asked OpenAI to stop replicating Japanese artwork, underlining the rising alarm among Japanese creators about generative AI’s impact on cultural property.

This controversy marks one of several global confrontations between AI developers and copyright owners. Over the past year, a wave of “cease and desist” letters has been issued to major AI companies, including OpenAI, Stability AI, and Midjourney, over their alleged use of copyrighted material without permission. Many of these warnings have escalated into full-scale lawsuits.

In the United States, The New York Times filed a landmark lawsuit against OpenAI and Microsoft in December 2023, accusing them of using millions of its articles to train GPT models without authorization. The Times alleged that the AI systems could reproduce entire paragraphs from its reporting, potentially replacing its journalism in search results and chat interfaces. Similarly, several prominent authors — including George R.R. Martin, John Grisham, and Jodi Picoult — sued OpenAI, claiming the company’s large language models were trained on pirated copies of their books. Getty Images also sued Stability AI in both the U.S. and the U.K., accusing it of using more than 12 million copyrighted photos to train its image generator, Stable Diffusion.

The rising volume of legal challenges has forced AI companies to rethink their approach to data sourcing. In an effort to secure lawful access to training data, OpenAI has begun signing content partnerships with major platforms. Earlier this year, it struck deals with Reddit, Stack Overflow, the Associated Press, and Axel Springer, the parent company of Business Insider and Politico, to license their data for model training. These partnerships mark a shift in strategy as AI firms face increasing scrutiny from regulators and creators worldwide.

However, CODA insists that OpenAI’s reliance on “opt-out” systems — where content owners must explicitly request exclusion from training — violates Japan’s copyright regime.

“Under Japan’s copyright system, prior permission is generally required for the use of copyrighted works, and there is no system allowing one to avoid liability for infringement through subsequent objections,” the association said in its statement.

The group urged OpenAI to “respond sincerely” to its members’ concerns and immediately cease using Japanese intellectual property without prior authorization. The association also hinted that it could pursue legal or diplomatic action if the company fails to comply.

The growing number of copyright disputes highlights a widening fault line between AI innovation and intellectual property protection. As AI models become more advanced and capable of mimicking human artistry, creative industries across the world — from Hollywood to Tokyo — are mobilizing to safeguard their work from unauthorized digital reproduction.

It is believed that Japan’s pushback could become a defining test of how nations with robust copyright protections adapt to the AI age. With AI-generated content blurring the lines between inspiration and imitation, OpenAI and its rivals face an increasingly urgent challenge: balancing technological progress with the rights of the creators who supply the culture that fuels it.

OpenAI has struck a landmark seven-year, $38 billion agreement with Amazon.com Inc. to purchase cloud services, marking its first major infrastructure move since last week’s restructuring that granted the ChatGPT maker greater operational and financial independence.

The deal cements Amazon Web Services (AWS) as a central player in OpenAI’s bid to expand computing power for the next generation of artificial intelligence models.

Under the agreement, OpenAI will gain access to hundreds of thousands of Nvidia GPUs through AWS to train and deploy its frontier AI systems — a move that underscores the industry’s growing hunger for computing resources. OpenAI CEO Sam Altman said the deal represents a significant step toward achieving the company’s ambitious target of developing 30 gigawatts of computing power, roughly enough to power 25 million U.S. homes.

“This is a hugely significant deal and clearly a strong endorsement of AWS compute capabilities to deliver the scale needed to support OpenAI,” said Paolo Pescatore, analyst at PP Foresight.

Altman echoed that sentiment, emphasizing reliability and scale as critical to AI advancement.

“Scaling frontier AI requires massive, reliable compute,” he said. “Our partnership with AWS strengthens the broad compute ecosystem that will power this next era and bring advanced AI to everyone.”

AWS will begin provisioning capacity immediately, with all systems expected to go live by the end of 2026, and more expansions planned through 2027. Amazon will deploy Nvidia’s newest GB200 and GB300 AI accelerators across vast data centers to power OpenAI’s training workloads and the conversational capabilities behind ChatGPT.

The announcement comes as Amazon’s cloud unit regains investor confidence following strong growth in the September quarter. AWS had faced concerns that it was losing ground to Microsoft Azure and Google Cloud in the AI infrastructure race, but Monday’s deal pushed Amazon shares to a record high, adding nearly $140 billion to its market capitalization. The stock surged 5% during trading, following a 10% rally the previous Friday.

The partnership also highlights OpenAI’s diversification strategy. Despite its long-standing alliance with Microsoft — which began in 2019 and saw the software giant take a multibillion-dollar stake — OpenAI has increasingly sought to reduce dependence on a single provider. In addition to AWS, the company has inked a $300 billion cloud supply deal with Oracle and is working with Google Cloud to expand its compute network.

The new arrangement effectively sidelines Microsoft’s exclusive cloud rights, which were removed during last week’s restructuring. OpenAI’s revised governance framework allows the company to seek external investors and explore an initial public offering, which puts the value of the AI leader at up to $1 trillion, according to a Reuters report.

However, the eye-popping spending commitments, estimated at over $1 trillion in total compute investments, have fueled concerns on Wall Street that the AI sector is edging toward a financial bubble. Analysts warn that the enormous infrastructure costs could weigh heavily on OpenAI’s profitability, even as its annualized revenue run rate is projected to reach $20 billion by year-end.

OpenAI’s partnerships with Amazon, Microsoft, Oracle, and Google now make it one of the most cloud-diversified AI firms in the world. Yet, questions remain about how the company will finance such extraordinary expansion. The firm is still loss-making, and its capital demands — including Altman’s ambition to add 1 gigawatt of compute capacity per week — are unprecedented in tech history.

The OpenAI deal is seen as a symbolic and financial victory for Amazon, solidifying AWS’s relevance in a hyper-competitive AI arms race. It positions the e-commerce giant’s cloud business as a foundational layer for the most advanced AI systems in development, reaffirming that even as AI models grow more sophisticated, cloud infrastructure remains the backbone of the intelligence revolution.