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AITech

The war between competing AI models could end up more like Apple vs. Android than VHS vs. Betamax

Jason Ma
By
Jason Ma
Jason Ma
Weekend Editor
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Jason Ma
By
Jason Ma
Jason Ma
Weekend Editor
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July 27, 2026, 12:13 PM ET
The VHS format prevailed because JVC licensed it broadly, allowing a self-reinforcing ecosystem to develop around it.
The VHS format prevailed because JVC licensed it broadly, allowing a self-reinforcing ecosystem to develop around it.Getty Images
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The tech world has been consumed recently by the debate over open-weight and closed AI models, but it doesn’t have to be a zero-sum game.

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The arguments cut across business, political, and safety issues. For example, lower-cost open models could take market share from closed rivals, like Anthropic and OpenAI, and reduce demand for chips.

U.S. AI companies also warn that Chinese open models are quickly closing the performance gap, potentially translating to a military edge, while also accusing China of stealing technology via illegal “distillation.”

In addition, critics of open models warn they lack safety guardrails that would prevent them from being misused to develop nuclear, biological, or cyber weapons.

But closed models have their downsides, too. Safety regulations could reduce competition and protect providers of closed models.

Limiting access to the most advanced models also leaves users vulnerable to regulatory risk, as when the U.S. government effectively banned Anthropic’s most powerful Claude models for several weeks owing to security concerns.

But Deutsche Bank analyst Adrian Cox put the AI debate into a more historical perspective, drawing parallels with the fight between direct current and alternating current in the 1880s during the emergence of electrical technology.

In a note last week, he also recalled the battle between VHS and Betamax videocassette players in the late 1970s and early 1980s. While Betamax was considered the superior technology, it’s been relegated to the dustbin of history.

The VHS format prevailed because JVC licensed it broadly, allowing a self-reinforcing ecosystem to develop around it, Cox wrote. Similarly, open-source AI doesn’t have to beat closed rivals on performance, but can merely be good enough, cheaper and ubiquitous.

“However, while the contest between open and proprietary AI is often presented as a winner-takes-all format war, the most likely outcome is a combination of the two,” he predicted.

Instead of resembling VHS vs. Betamax, Cox thinks the future of AI could instead look more like today’s smartphones, which run on Apple’s operating system and Google’s Android.

Both have found success, and Apple’s controlled premium ecosystem now coexists with a larger, more customizable one, according to Cox.

Open and closed AI will also “exert a positive gravitational force on each other,” he said, explaining that open models will force closed competitors to curb prices and remain flexible, while closed models will continue setting the bar on quality and safety.

Nvidia CEO Jensen Huang echoed this argument on Friday, saying the world needs both frontier closed models and frontier open models.

He also posted a letter his company signed—along with Google, Meta, Microsoft, and even OpenAI—that also looked back to the 1980s.

It said the development of open-source software at that time not only lowered costs but also “created a shared foundation of knowledge on which generations of American engineers and entrepreneurs built their institutional sovereignty.”

The letter added that U.S. leadership in AI shouldn’t be measured by a single frontier model, but by whether the country builds a broad, open ecosystem.

It acknowledged that open models carry security risks, but said the answer is maintaining access to them to bolster defenses rather than cutting off access.

“Open weights also strengthen competition, and competition is what keeps the gains of AI broadly shared rather than concentrated in a few hands,” the letter said. “By allowing many organizations to build, adapt, and deploy advanced models, open weights create rivalry not only among model developers but across cloud chips, applications, and services. That competition spurs innovation, drives down costs, and distributes the benefits of AI broadly across our economy.”

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About the Author
Jason Ma
By Jason MaWeekend Editor

Jason Ma is the weekend editor at Fortune, where he covers markets, the economy, finance, and housing.

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