Zhipu’s founder makes the case for open frontier AI


The founder of China’s most prominent AI lab has made an unambiguous case for openness. Frontier AI should stay broadly accessible rather than controlled by a select few, Zhipu’s Tang Jie wrote in an internal memo reviewed by Bloomberg.

His argument inverts the usual security logic. Real safety comes from broad participation, sharing, and oversight, he said, not from technological barriers.

Zhipu has backed that with product. It released GLM-5.2 under an open-source licence, free to download and commercialise.

The awkward timing

Tang made the comments shortly after Reuters reported that Beijing is considering the opposite. Chinese officials are weighing limits on overseas access to the country’s most advanced open models.

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That puts Zhipu’s founder at odds with the direction of travel in his own capital. Openness has been China’s strategic advantage, and now its government is wondering whether it gave away too much.

The company has commercial reasons to want the door open. Its models have spread globally precisely because they are free, and cheap Chinese models are now closing in on the US frontier labs.

That does not make the argument wrong. It does mean the person making it stands to benefit from it, which is true of nearly everyone in this debate.

The case he is making

The open-source security argument is not fringe. Its logic is that many independent eyes on a system find flaws faster than a small team behind a wall.

Defenders make the same point. When Washington restricted a frontier model, 100 cybersecurity experts signed an open letter arguing the ban hurt defenders more than attackers.

Attackers, they argued, will obtain capable models regardless. The people locked out are the researchers and security teams trying to keep up.

The case against

The closed camp has a straightforward reply. An open-weight model cannot be recalled, patched, or switched off once it is downloaded.

Publishing frontier capabilities means publishing them to everyone, including people building bioweapons or industrial-scale cyberattacks. Safeguards trained into a model can be stripped out by anyone with the weights and a modest budget.

Both sides are describing real risks. The disagreement is about which risk is larger, and there is no clean empirical answer yet.

Why it matters now

Zhipu is no longer a curiosity. It has raised billions, listed in Hong Kong, and its share sale drew heavy demand from investors betting Chinese AI fills the gap left by restricted US models.

So the question is no longer academic. If China does restrict its open models, the world’s main source of free frontier-class AI closes at the same time as America’s.

Tang is arguing against that outcome from inside the country most likely to cause it. Whether anyone in Beijing is listening is the part he cannot control.



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TL;DR

India debates sovereign AI after the US forced Anthropic to kill Fable 5, with proposals for a $5B fund and calls to embrace open-source models.

When the US government ordered Anthropic to shut down Fable 5 and Mythos 5 on 12 June, the export control directive was aimed at restricting foreign nationals from accessing America’s most capable AI. In India, Anthropic’s second-largest market, it landed as a warning shot about what happens when your AI infrastructure runs on someone else’s politics.

The suspension cut off Indian developers and enterprises from Claude’s most advanced models overnight. India’s Claude run-rate revenue had doubled since October 2025, and Tata Consultancy Services had announced a partnership just one day earlier, on 11 June, to train 50,000 employees on Claude and build a dedicated Anthropic business unit. That deal is now in limbo.

The timing has turned what was already a simmering debate about AI sovereignty into a full strategic reckoning. Proposals that sounded ambitious a week ago now sound urgent.

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Mohandas Pai, former Infosys CFO and one of India’s most prominent tech investors, has called for a ₹50,000 crore (roughly $5 billion) annual sovereign AI fund. He has also proposed a ₹2 lakh crore (approximately $21 billion) credit guarantee to finance cloud infrastructure, hardware procurement, and semiconductor development. The figures dwarf the government’s existing commitment.

India approved its IndiaAI Mission in March 2024 with a budget of ₹10,372 crore, approximately $1.25 billion. The programme has deployed around 38,000 GPUs so far. Pai’s proposal would quadruple annual spending and add a credit backstop an order of magnitude larger.

Sridhar Vembu, the founder of Zoho, has gone further. He argued that India should embrace smaller and open-source models, including Chinese ones, rather than depend on American frontier systems that can be switched off by executive order. “Technology is the ultimate weapon,” Vembu said. “Globalization is dead and Bharat must find her own way ahead.

The argument has teeth because the suspension demonstrated exactly the vulnerability Vembu is describing. Amazon’s CEO reportedly triggered the government crackdown by telling Treasury Secretary Scott Bessent that researchers had used Fable 5 to obtain information that could be used in cyberattacks. Anthropic called the action disproportionate, but compliance was immediate and global.

Policy expert Prasanto Roy put it bluntly: “American AI models are bound to American geopolitics.” For Indian enterprises that had built workflows around Claude, the lesson was that access to frontier AI is a privilege that can be revoked without notice, without consultation, and without regard for the commercial relationships it disrupts.

The Indian startup ecosystem is already adapting. Sarvam, a Bengaluru-based AI company, released 30-billion and 105-billion parameter open-source models at the India AI Impact Summit in 2026. Krutrim, founded by Ola’s Bhavish Aggarwal, has pivoted from building foundational models to providing cloud and AI infrastructure services, reporting ₹3 billion in revenue for fiscal year 2026.

Neither company is close to matching the capabilities of Fable 5 or Mythos 5. But the argument for sovereign AI was never about matching frontier performance immediately. It is about ensuring that the floor does not fall out when Washington makes a unilateral decision about who gets to use which models.

Aakrit Vaish, founder of the AI startup Activate, said the suspension “completely changes things” for the sovereign AI debate. Vijay Rayapati, CEO of Atomicwork, raised concerns about what the precedent means for Indian companies with multi-country teams that depend on American AI providers. If the US can shut off model access to enforce export controls, any country that relies on American AI is one policy decision away from disruption.

Not everyone agrees that India needs to build its own frontier models. Hemant Mohapatra, a partner at Lightspeed Venture Partners, argued that talent and compute access matter more than capital for building competitive AI. India has the engineering workforce, but the compute gap is significant, and closing it requires either massive domestic investment or continued access to foreign cloud infrastructure.

Anthropic opened a Bengaluru office as part of its India expansion, and the TCS partnership was designed to be a cornerstone of its enterprise strategy in the country. Whether those plans survive the suspension intact depends on how quickly Anthropic can restore access and whether Indian enterprises still trust a provider whose most capable models can vanish overnight.

The broader pattern is unmistakable. The US has spent four years tightening controls on AI technology, from chip export restrictions to model-level interventions. Each escalation pushes more countries toward the conclusion that dependence on American AI infrastructure carries political risk. India, with its 1.4 billion people and rapidly growing technology sector, is now asking whether it can afford that risk, and what it would cost to eliminate it.

The Opendoor layoffs in June 2026, which shut the company’s India office and affected roughly 250 employees, added another dimension. CEO Kaz Nejatian cited AI-native teams as the reason, suggesting that some US companies are using AI to reduce their reliance on Indian engineering talent at the same time that India is debating its reliance on American AI. The relationship is becoming less complementary and more competitive.

For now, the sovereign AI proposals remain proposals. Pai’s fund has no legislative vehicle, Vembu’s call for open-source adoption has no coordinated policy framework, and the IndiaAI Mission’s GPU deployment is still in early stages.

But the Anthropic suspension has done something that years of policy papers and conference speeches could not: it has given the sovereign AI movement a concrete, recent, and viscerally felt example of why dependence on foreign AI is a strategic liability. The debate is no longer theoretical.



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