Silicon

A wealthy young Silicon Valley venture capitalist hopes to recruit statewide and congressional candidates and launch an affordable-housing ballot measure in 2018 because he says California’s leaders are failing to address flaws in the state’s governance that are killing opportunities for future generations.

Sam Altman, 32, said in May that he was considering a run for governor. But he said in an interview with The Times this week that he has no plans to run for office — at the moment — and will instead roll out an effort Wednesday to enlist candidates around a shared set of policy priorities — including tackling how automation is going to affect the economy and the cost of housing in California — and is willing to put his own money behind the effort.

“I think we have a fundamental breakdown of the American social contract and it’s desperately important that we fix it,” he said. “Even if we had a very well-functioning government, it would be a challenge, and our current government functions so badly it is an extra challenge.”

Altman is the president of Y Combinator, a technology incubator that has provided start-up funding to hundreds of Silicon Valley companies, notably Airbnb, Dropbox and Stripe. He first made his mark by co-founding a social media app called Loopt when he was 19 that later sold for $43 million.

He said he hopes to recruit a slate of four candidates to run for office — possibly for governor, lieutenant governor, mayor of a major city in California and Congress — and could provide technology platforms and seed money for their campaigns.

Though Altman said he is not specifically targeting Democratic politicians, he made clear he is not happy with incumbents such as Sen. Dianne Feinstein or the current gubernatorial field, which includes Lt. Gov. Gavin Newsom and former Los Angeles Mayor Antonio Villaraigosa.

“I’m not satisfied with the current choices,” Altman said. “I don’t want to make this about dumping on specific people, [but] I don’t think any of the current candidates are the best we could do.”

He would not be the first wealthy Silicon Valley entrepreneur to try to shake up California politics based on his tech resume. Among them are former eBay chief Meg Whitman, who spent $144 million of her own money on an unsuccessful gubernatorial run in 2010, and former Hewlett-Packard Chief Executive Carly Fiorina, who ran for Senate in 2010 before running for president in 2016.

In recent years, tech industry executives have played notable roles helping candidates get elected to top office, including Google parent company Alphabet Inc. CEO Eric Schmidt, who backed former President Obama, and PayPal co-founder Peter Thiel, who supported President Trump.

Altman declined to say how much he was willing to spend on his effort but said he would prefer to invest heavily on a cause rather than underwriting individual campaigns.

“That’s always felt gross to me,” he said. “I’m happy to spend a lot of money supporting the movement.”

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Over the years, Altman has been registered as a Democrat and as having no party preference, and his political donations swing between liberal and center-left.

Last year, he donated $100,000 to a San Francisco group working to elect moderates to the county Board of Supervisors, and $50,000 to an Airbnb committee that backed an increase in the city sales tax. He has also spent thousands of dollars backing Obama and national and local Democratic groups, as well as congressional, legislative and local candidates.

On a website that launches Wednesday, Altman lays out his concerns and policy goals. He argues that the state’s priorities have become unbalanced, resulting in inequality, stalled growth and declining opportunity. And it will only become worse because of an upcoming economic shift driven by automation, he says.

“We need to figure out a new social contract, and to ensure that everyone benefits from the coming changes,” Altman writes on the site.

Altman lays out 10 principles including lowering the cost of housing, creating single-payer healthcare, increasing clean energy use, improving education, reforming taxes and rebuilding infrastructure.

He has few specific policy edicts, and floats proposals that will generate controversy, such as creating a universal basic income for all Americans in an effort to equalize opportunity, public funding for the media and increasing taxes on property that is owned by foreigners, is unoccupied or has been “flipped” by investors seeking a quick return on an investment.

Altman said he recognizes he faces an uphill battle.

“Maybe this will go nowhere,” he said. “There’s always the possibility I put this out and there’s exactly one person who believes in this stuff and it’s me.”

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Updates on California politics

China’s AI models are quickly gaining traction in Silicon Valley, becoming integral to the operations of American companies and earning the praise of a growing list of tech leaders.

Their rapid ascent has highlighted the competitive edge that Chinese developers such as Alibaba, Z.ai, Moonshot, and MiniMax have been able to gain by offering so-called “open” language models at much lower costs than their rivals in the United States.

The trend has also cast a critical glare on the US’s efforts to stunt China’s tech sector with export controls on advanced chips, which have not stopped Chinese developers from approaching the capabilities of Silicon Valley’s tech giants.

Airbnb CEO Brian Chesky generated headlines in October when he revealed that the short-term rental platform had opted for Alibaba’s Qwen over OpenAI’s ChatGPT, praising the Chinese model as “fast and cheap”.

Social Capital CEO Chamath Palihapitiya revealed the same month that his company had migrated much of its work to Moonshot’s Kimi K2 as it was “way more performant” and “a ton cheaper” than models from OpenAI and Anthropic.

Programmers on social media also recently highlighted evidence that two popular US-developed coding assistants, Composer and Windsurf, were built on Chinese models.

The assistants’ developers, Cursor and Cognition AI, have not publicly confirmed their use of Chinese technology and did not respond to requests for comment, though Z.ai has said the speculation aligns with its “internal findings.”

Nathan Lambert, a machine learning researcher who founded the Atom Project, an initiative to promote open models in the US, said such public examples were the “tip of the iceberg”.

“Chinese open models have become a de facto standard among startups in the US,” Lambert told Al Jazeera.

“I’ve personally heard of many other high-profile cases, where the most valued and hyped American AI startups are starting training models on the likes of Qwen, Kimi, GLM or DeepSeek,” Lambert said, adding that many US firms have been reluctant to publicly disclose their use of Chinese technology.

While it is not possible to precisely quantify the usage of different AI models, industry data points to the rising popularity of Chinese offerings.

Chinese AI tools, including MiniMax’s M2, Z.ai’s GLM 4.6 and DeepSeek’s V3.2, took up seven spots among the 20 models with the most usage last week, according to data from OpenRouter, a platform that connects developers with AI models.

Among the top 10 models used for programming, four were developed by Chinese firms, according to OpenRouter.

In the open model space, China’s clear lead is evident, with cumulative downloads surpassing 540 million as of October, according to an Atom Project analysis of data from hosting platform Hugging Face.

Rui Ma, the founder of Tech Buzz China, said Chinese models are particularly attractive to fledgling startups, while “high-resource organisations” have gravitated towards premium US models.

“These are typically cost-conscious early-stage companies that experiment widely, and many of them will not survive,” Ma told Al Jazeera.

Unlike leading US platforms such as ChatGPT, China’s open-weight large language models make their trained parameters – called weights – publicly available.

While open-weight models do not generate licensing or subscription fees, running them at enterprise scale requires large amounts of computing power, which creators can offer to users at a cost.

Developers such as Beijing-based Z.ai and Hangzhou-based DeepSeek have reported using older-generation chips that are not subject to US export controls, in relatively small quantities, dramatically reducing training and hardware costs compared with their Silicon Valley rivals.

“The success of these Chinese models demonstrates the failure of export controls to limit China,” Toby Walsh, an expert in AI at the University of New South Wales, told Al Jazeera.

“Indeed, they’ve actually encouraged Chinese companies to be more resourceful and build better models that are smaller and are trained on and run on older generation hardware. Necessity is the mother of invention.”

With lower input costs, Chinese firms have been able to offer their services far more cheaply than their US peers.

In an analysis published by AllianceBernstein in February, DeepSeek’s pricing for its models at the time was estimated to be up to 40 times cheaper than OpenAI’s, for instance.

“I do think China’s AI progress has been underestimated, partly because the signal is fragmented,” Greg Slabaugh, a professor who studies AI at Queen Mary University of London, told Al Jazeera.

“Much of the uptake of Chinese models is in China. China’s scale in AI publications and patents has long been visible; the emergence of open-weight models simply makes that capability more globally consumable.”

Some industry analysts have likened China’s approach to AI to the strategy undertaken by Chinese firms in other industries, such as solar panels, that flooded markets with cheap goods.

“This is the solar panel playbook running on software,” Poe Zhao, a Beijing-based tech analyst, wrote last week in his Substack newsletter, Hello China Tech.

But while Chinese AI models have made inroads with their low cost, US tech giants are in a strong position to dominate the high-end market and highly regulated sectors where considerations such as national security are paramount, according to analysts.

Ma, the Tech Buzz China founder, said the development of AI could end up following a similar trajectory to the Android and iPhone platforms, the former of which has about three times as many users worldwide.

“Over the longer term – likely faster than what we saw in the mobile era – it’s entirely possible that AI adoption might follow similar economic dynamics. There are simply more users in the world who prioritise affordability than those who choose premium options,” Ma said.

“But that doesn’t mean the greatest margins or market capitalisation will exist at the low end; value may still concentrate where differentiation, performance and trust command a premium.”

“In Fortune 500 and regulated sectors, widespread adoption is probably not imminent,” said Slabaugh, the Queen Mary University of London professor, referring to the uptake of Chinese models.

“If there is a ‘rude awakening’, it may come on the pricing and flexibility front rather than from a sudden displacement of US models.”