Microsoft’s ambitious push to build a commercially useful quantum computer by 2029 is facing renewed scrutiny after a fresh critique published in the journal Nature challenged key elements of the company’s scientific claims.

The debate goes beyond an academic disagreement. It strikes at the heart of Microsoft’s strategy to leapfrog rivals such as IBM and Quantinuum by pursuing a radically different approach based on elusive particles known as Majoranas.

The controversy comes at a time when quantum computing has become a strategic priority for governments and technology companies. The Trump administration recently committed $2 billion to accelerate quantum research and set a goal of achieving a scientifically useful quantum system by 2028. The technology is viewed as a potential game changer capable of solving problems in materials science, drug discovery, logistics, artificial intelligence, and cryptography that remain beyond the reach of even the most powerful conventional computers.

At the center of the dispute is Microsoft’s long-running effort to build what are known as topological qubits. Unlike the qubits used by competitors, Microsoft’s design relies on Majorana particles, theoretical quantum states that could potentially produce more stable and less error-prone quantum systems. If successful, the approach could dramatically reduce one of quantum computing’s biggest challenges: error correction.

The problem is that Microsoft’s scientific journey toward proving the existence and practical usefulness of Majoranas has been controversial for years. Several earlier papers connected to Majorana research were retracted after questions emerged about the interpretation of experimental data. Critics have noted that those setbacks have left significant gaps in the scientific foundation supporting Microsoft’s current roadmap.

The latest challenge comes from Henry Legg, a quantum physicist at the University of St. Andrews, whose peer-reviewed critique in Nature focuses on a February 2025 paper that remains central to Microsoft’s quantum program. That paper did not directly claim the discovery of a Majorana particle. Instead, it described software designed to identify a tiny energy gap in a highly conductive wire, a signal Microsoft believes helps identify conditions suitable for creating Majorana-based quantum devices.

Legg’s critique questions whether the evidence presented in the paper adequately supports Microsoft’s interpretation of the results. While the paper itself has not been retracted, the challenge adds to broader skepticism among some researchers who argue that Microsoft has not yet provided definitive experimental proof that its topological approach works as advertised.

The debate is growing because Microsoft used the February paper as part of the scientific foundation for subsequent announcements, including its recent assertion that it expects to have a working quantum system by 2029.

Microsoft has strongly defended its work.

In its formal response published by Nature, the company argued that the software described in the paper serves as a practical tool for configuring quantum devices and identifying optimal operating conditions. Microsoft maintains that the tool is already being used in its laboratories to support functioning quantum operations.

Chetan Nayak, who leads Microsoft’s quantum hardware program, pushed back against critics in comments to Reuters, arguing that the technology is already delivering practical results inside the company’s research facilities.

“It’s almost like arguing, is flight possible or not? And then you’re standing next to an airplane,” Nayak said. “Well, why don’t you hop in and take a ride?”

His defense is part of Microsoft’s broader position that the discussion has moved beyond theoretical possibility toward engineering execution. However, the defense has failed to quell skepticism, which remains widespread within parts of the quantum research community.

Sergey Frolov, a physicist at the University of Pittsburgh and one of Microsoft’s most prominent, believes that Microsoft’s approach lacks the extensive experimental validation accumulated by competing technologies. According to Frolov, companies such as IBM and Quantinuum have spent years steadily demonstrating progress through a series of increasingly sophisticated experiments, creating a more transparent path toward scalable quantum systems.

“Neither Microsoft nor anyone else has laid a foundation where it is clear that these (Majorana-based) advances are plausible, through a series of reliable experiments,” Frolov said. “On the contrary, we have a series of papers that keep being challenged at the very basic level, by different people.”

IBM, Quantinuum, and several other major players rely on more established qubit architectures that have demonstrated measurable performance improvements over time, even though they require extensive error correction. Microsoft is betting that a riskier but potentially more transformative topological approach could ultimately produce more reliable systems with fewer engineering challenges.

The debate has piqued the interest of investors and policymakers, given the enormous stakes. Quantum computing is increasingly viewed as the next major computing platform after artificial intelligence. Success could unlock trillion-dollar economic opportunities while reshaping national security, particularly in cryptography and defense. Governments in the United States, China, and Europe are racing to secure leadership in the field.

The renewed scrutiny does not mean Microsoft’s quantum program is in immediate jeopardy. The February paper remains published, the company continues to invest heavily in the technology, and no formal scientific body has rejected its latest findings. However, the controversy underpins a persistent challenge facing Microsoft: convincing a skeptical scientific community that its unconventional path can deliver on promises that have remained elusive for more than a decade.

Anthropic has accused Chinese technology giant Alibaba of carrying out what it describes as the largest known attempt to illicitly extract its artificial intelligence capabilities, escalating tensions in the increasingly fierce global battle over advanced AI models and intellectual property.

In a letter sent to the U.S. Senate Committee on Banking, Housing, and Urban Affairs, the AI company alleged that operators linked to Alibaba and its AI research division conducted a large-scale “distillation attack” aimed at replicating Anthropic’s technology through millions of interactions with its models.

The allegations follow Alibaba’s recent lawsuit against the U.S. Department of Defense over its designation as a company linked to China’s military, and add another layer to growing concerns in Washington that Chinese firms are seeking to accelerate AI development by leveraging American breakthroughs.

The June 10 letter, addressed to Senate Banking Committee Chairman Sen. Tim Scott and ranking member Sen. Elizabeth Warren, accused Alibaba of attempting to extract proprietary capabilities from Anthropic’s frontier AI systems through what the company described as a coordinated and fraudulent operation.

According to Anthropic, operators affiliated with Alibaba and its AI laboratory conducted approximately 28.8 million exchanges with Anthropic models between April 22 and June 5 using roughly 25,000 fraudulent accounts.

The company characterized the activity as “brazen” and “illicit,” describing it as the largest distillation effort it has identified to date.

Distillation is a widely used AI development technique in which a smaller model is trained using outputs generated by a larger and more advanced model. While distillation itself is a legitimate machine-learning practice, AI developers increasingly distinguish between authorized distillation conducted with permission and unauthorized efforts designed to replicate proprietary capabilities.

Anthropic argues that the alleged activity crossed that line.

Why Distillation Has Become a Major Battleground

The dispute highlights one of the most significant challenges facing leading AI companies. Training frontier AI models requires enormous investments in computing infrastructure, talent, and data. Companies such as Anthropic, OpenAI, and Google spend billions of dollars developing advanced systems.

Once released, however, those models can potentially be queried repeatedly to generate training data for competing systems.

Industry executives increasingly fear that unauthorized distillation could allow competitors to reproduce key model capabilities at a fraction of the original cost. The issue has become particularly sensitive as Chinese and American firms race to dominate artificial intelligence development.

Several AI companies have privately warned policymakers that model extraction and distillation could become one of the most important intellectual property battles of the AI era, potentially rivaling disputes over semiconductors and advanced manufacturing technologies.

Anthropic used the letter not only to detail its allegations but also to urge policymakers to take a more active role in protecting U.S. AI leadership.

“We believe combating the threat of illicit distillation requires coordinated action between government and industry, and we will continue working with Congress and the Administration to maintain American AI leadership,” an Anthropic spokesperson said.

The appeal reflects growing pressure from leading AI firms for stronger legal protections and clearer enforcement mechanisms against model theft and unauthorized replication. Unlike traditional intellectual property disputes, AI model extraction can be difficult to detect and prove, particularly when interactions occur through publicly accessible interfaces and cloud services.

Alibaba Faces Mounting Scrutiny

Alibaba has not publicly responded to the allegations. A representative for the company did not immediately provide comment following publication of the report.

The accusations arrive at a difficult moment for the Chinese technology giant. Just days earlier, Alibaba filed a lawsuit against the U.S. government seeking removal from a Pentagon list of companies allegedly connected to China’s military. The company has argued that the designation has no factual basis and unfairly damages its reputation and business relationships.

Now, the Anthropic allegations risk reinforcing concerns among U.S. lawmakers about Chinese access to advanced American AI technologies.

Washington has already imposed restrictions on advanced semiconductor exports to China and tightened controls on access to high-performance computing technologies needed to train frontier AI systems. As those restrictions expand, concerns are increasingly shifting from hardware access to model access.

U.S. officials fear that Chinese firms could narrow the AI gap through model extraction techniques rather than through direct access to advanced chips. For AI companies, the concern is that if frontier models can be replicated through large-scale distillation efforts, the economics underpinning billions of dollars in AI investment could be undermined.