America
Silicon Valley startups are turning to Chinese open-source AI models
Misha Laskin, a theoretical physicist and machine learning engineer who contributed to the development of some of Google’s most powerful AI models, encountered a concerning picture when examining the American AI landscape earlier this year.
Laskin observed a growing interest among US AI companies in free, customizable, and increasingly powerful open-source AI models.
The vast majority of these models are produced in China and are rapidly gaining ground against their US competitors.
Assessing the current situation, Laskin stated, “These models are not far behind the frontier (the cutting edge of technology). In fact, they are surprisingly close to the frontier. What is coming now is noticeably close to the frontier.”
Following this development, Laskin founded a startup called Reflection AI to offer an open-source American alternative to the Chinese models gaining traction in Silicon Valley.
The founder of the company, which recently reached an $8 billion valuation, said, “You are starting to see signs that open model companies in China are actually pushing the frontier of intelligence and the limits of intelligence technology in general.”
Over the past year, a significant portion of America’s most popular AI startups have turned to Chinese open AI models, which compete with and sometimes replace expensive US systems as the foundation for American AI products.
More than 15 AI startup founders, engineers, and industry experts who spoke to NBC News stated that American companies’ models still hold the lead in terms of capability.
However, experts emphasized that many Chinese systems are cheaper to access, more customizable, and have become sufficiently competent for many use cases over the past year.
Cost and speed advantages are changing preferences
Investors have poured tens of billions of dollars into OpenAI and Anthropic with the expectation that leading American AI companies will dominate the global market.
But the increasing use of free Chinese models by American companies raises questions about how exceptional these models are and whether America’s insistence on a “closed model” approach is flawed.
Michael Fine, head of machine learning at the search company Exa, which is valued at $700 million and backed by established Silicon Valley investors Lightspeed Venture Partners and Nvidia, said that running Chinese models on their own hardware is, in many cases, much faster and cheaper than using large models like OpenAI’s GPT-5 or Google’s Gemini.
Fine described the process:
“We often launch a feature with a closed model, but then we realize it’s too expensive or too slow, and we ask, ‘What tricks do we have up our sleeve to make this faster and cheaper?'”
Fine stated that the solution is often to replace the closed model with an equivalent open model and then run it on their own infrastructure.
Chinese-origin systems like DeepSeek’s R1 and Alibaba’s Qwen models can be used for free because they are “open-source” or “open-weight,” meaning anyone can download, copy, modify, and run them.
These systems differ from “closed” systems accessed through data centers controlled by major tech giants, such as Anthropic’s Claude or OpenAI’s GPT models.
The technology gap is closing fast
For years, the closed-source models from OpenAI and Anthropic performed far better than both American and Chinese open alternatives.
Even open-source initiatives like BloombergGPT, trained by institutions with resources like Bloomberg on their own financial data, lagged behind OpenAI’s closed models in financial knowledge.
However, over the past year, Chinese companies like DeepSeek and Alibaba have made significant technological strides. According to metrics tracked by Artificial Analysis, an independent AI benchmarking company, their open-source products now approach or match the performance of leading closed American models in many areas.
“The gap is really narrowing,” said Lin Qiao, co-creator of PyTorch, the dominant framework for training AI models, and CEO of Fireworks AI, regarding the capability difference between American closed-source and Chinese open-source models.
As a result of this performance increase, platforms like OpenRouter, which allow users to choose between different models, are seeing a shift toward Chinese open-source models.
Jerry Liu, founder of the productivity app Dayflow, estimates that about 40% of his users now prefer to use open-source models.
Dayflow offers an application built on basic tasks like scanning screenshots and summarizing user activity.
Users can choose between Google’s Gemini model and smaller open-source options like Alibaba’s Qwen.
Liu noted that for tasks like describing a user’s screen, the Qwen model is extremely consistent, stating, “Qwen is as good as GPT-5 for my use case.”
Unlike GPT-5 or Gemini, a smaller version of Qwen can be run at a relatively low cost or for free.
Liu mentioned that paying for closed model usage could cost Dayflow up to $1000 per person, making cheaper open-source models critical for the application’s sustainability.
Privacy sensitivity encourages local processing
The open-source models used by Dayflow perform all processing on each user’s own computer. Liu stated that this is attractive to users who do not want to send their data to the cloud for privacy reasons.
Emphasizing his preference for using open-source models on his own device, Liu said, “Would I use a product where my entire screen is beamed to some random guy’s cloud? Never.”
In addition to increased performance, stronger privacy, and lower costs, open-source models are also gaining ground due to ecosystem advantages.
The rising adoption rate among developers and the open-source systems they create encourage more software engineers to use these models.
Antonio Vespoli, co-founder of the browser assistant startup Circlemind AI, said that Chinese models now dominate online developer resources.
There is a practical reason for this: Chinese models like Qwen, which Airbnb CEO Brian Chesky stated they rely on “heavily,” have abundant training guides and community support.
Charles Zedlewski, chief product officer at the AI infrastructure company Together AI, noted that developers now find it simpler and more efficient to start with open models and adapt them with their own data.
Zedlewski stated that companies understand their needs more clearly as they launch their first AI applications.
Of the top 20 models among users of Kilo Code, a popular application that helps software engineers write code, seven are of Chinese origin, and six of them are open-source.
Beijing’s strategic support and production speed
While most of America’s AI developments occur in the private sector and with a closed-model approach led by industry giants like OpenAI and Anthropic, the Chinese government plays a more active role in charting the country’s AI vision.
In a speech on November 1, Chinese President Xi Jinping called for “more cooperation in open-source technologies.”
In March, China’s top economic planning authority announced its intention to support an ecosystem of open-source models.
While Chinese labs generally release their models openly, American companies like OpenAI achieved early success with closed models and have remained committed to that approach.
Furthermore, many Chinese companies are releasing their products at a faster pace than their American competitors.
Alibaba has released a new model roughly every 20 days this year, while the average time between Anthropic’s releases has been 47 days.
Nathan Lambert, a senior research scientist at the Allen Institute for AI and an expert on the open model ecosystem, told NBC News that the recent progress of Chinese models is no coincidence.
“The Chinese are real innovators in AI,” Lambert said.
Lambert, who writes extensively about China’s AI developments on the Substack platform and is considered an expert on China’s open-source ecosystem, added that the balance of power has shifted rapidly in the last 12 months.
Some in Silicon Valley note that American models still hold a significant advantage at the cutting edge of AI capabilities and that closed American models offer a user-friendliness that cumbersome open models cannot match.
Tim Tully, a partner at Menlo Ventures, argued that closed models are still much more capable and generally more useful:
“The tools are better, the productivity is better, the agent frameworks being built and used by everyone are better with Anthropic and OpenAI. They just work better. So the ecosystem is strong in the closed-source environment.”
However, many companies may avoid using Chinese models due to the real or perceived risks of using a product built on a Chinese-origin foundation.
“There is a perceived risk that buyers, whether from the private or public sector, are hesitant to purchase a product based on a Chinese-origin open-weight model,” said Tully, an investor in Anthropic, one of the world’s leading closed-model companies.
The US open-source ecosystem is waking up
American AI companies and the federal government have taken notice of the recent rise of Chinese models. Experts have described America’s lack of powerful open-source models as an “existential” threat to democracy.
Although Meta’s high-profile Llama series has historically led American open-source efforts, CEO Mark Zuckerberg has signaled that Meta does not intend to make all of its “superintelligence” AI models open-source.
The stagnation in the performance of Llama models in recent years is also seen as one of the reasons open-source users have shifted to better-performing Chinese models.
But the US open-source ecosystem may be gradually awakening, with efforts by American innovators to enhance their competitiveness.
In July, the White House released an AI Action Plan that called on the federal government to “Promote Open-Source and Open-Weight AI.”
In August, OpenAI, the creator of ChatGPT, released its first open-source model in five years. Announcing the model’s launch, OpenAI referenced the importance of American open-source models, stating, “Broad access to these capable open-weight models created in the US helps expand democratic AI.”
The Seattle-based Allen Institute also released its latest open-source model, Olmo 3, at the end of November, designed to help users “quickly build reliable features for research, education, or applications,” according to the launch announcement.
Lambert from the Allen Institute also launched the “ATOM Project” (American Truly Open Models).
The ATOM Project’s manifesto states: “America has lost its lead in both performance and adoption in open models and is on track to fall further behind.”
“If we want to be the leading nation in the age of AI, we cannot cede such a critical piece of the ecosystem to any one nation,” Lambert said in a statement to NBC News.
America
Musk appointed co-director of Pentagon future warfare initiative
The world’s richest man, Elon Musk, has assumed the co-directorship of a Pentagon initiative focused on the future of warfare, known as “Project Meridian”.
Musk’s new role was announced by US Secretary of Defence Pete Hegseth.
Musk, who has long expressed his conviction that wars will ultimately be fought with autonomous unmanned aerial vehicles, will advise the project as co-director alongside Palmer Luckey, founder of defence start-up Anduril, and former Speaker of the House of Representatives Newt Gingrich.
In a memorandum issued at the Pentagon, Hegseth stated that the group would “examine the battlefields of the future” and “determine which weapons and technologies warfighters must employ to achieve dominance in these environments.”
During his “State of the Force” address at Marine Corps Base Quantico, Hegseth said:
“The best predictors of future conflict do not reside exclusively within the Pentagon. Obvious biases and risks arise when we task ourselves with both framing the questions and answering them.”
Hegseth stated that this initiative would commence immediately and that, following his address, he would convene with Musk, Luckey, and Gingrich at a secure location.
Project Meridian will have 120 days to “ruthlessly map the trajectory of wars, domains, and technologies”, a process that will culminate in the public disclosure of its findings alongside a classified annex.
Hegseth outlined an expansive mandate extending “from beneath the surface of the Earth to beyond the Moon.”
Rather than formulating new military strategies or policies, the panel will seek to identify “the domains we must seize and the capabilities we must master”, focusing on the effort to “discover, develop, and field” the weapons and systems that next-generation American troops may require.
The group is expected to submit a report containing recommendations to him by the end of January.
In 2024, Musk remarked: “Future wars will be entirely about drones and hypersonic missiles.” This was merely one of several similar statements he has made in recent years.
For Musk, whose oversight role at the Department of Government Efficiency (DOGE) ended in turmoil and escalated into a dispute with President Donald Trump over Trump’s spending bill, this appointment marks his formal return to government in an official capacity.
Musk and Trump ultimately reconciled, and Musk attended a meeting on artificial intelligence safety at the White House this week alongside other technology leaders.
Meridian forms part of a broader push announced by Hegseth to restructure the military around autonomous warfare and rapidly advancing technologies.
Hegseth announced the establishment of the Autonomous Warfare Command (AUTOWARCOM), a new four-star combatant command endowed with what he termed “service-like authorities” to scale autonomous and robotic capabilities across the joint force.
The Department of War will also begin phasing in new occupational frameworks across all military branches to establish specialised career tracks for what Hegseth described as “the next generation of autonomous warfighters.”
“We should have conceived an Autonomous Warfare Command a decade ago,” Hegseth said, explaining that Meridian aims to gaze far enough ahead to enable the military to anticipate the next technological shift rather than lag behind.
America
Pentagon breach exposes personal records of three million people
A cyberattack targeting the US Department of War’s personnel database has resulted in the leak of personal information belonging to approximately 3 million people.
Speaking to ABC News, a Pentagon official stated that the system accessed by unauthorised individuals contained the records of 2,760,000 living persons and 294,000 deceased individuals.
The Military Times portal, which first broke the news, had reported the number of affected individuals as approximately 4 million based on two sources. The Pentagon official subsequently conveyed different figures to ABC News.
The leak encompasses Social Security numbers and duty information belonging to military personnel and civilian employees. According to an official notification examined by Military Times, the compromised records may also include names, dates of birth, contact information, sex, race, and military occupational specialties.
The unauthorised access to the information system of the Defense Manpower Data Center (DMDC) lasted for approximately nine months, between October 2025 and 16 July 2026.
ABC News reported that the access in question was obtained by a small number of third-party users. The vulnerability was closed after it was identified.
The DMDC is considered one of the Pentagon’s primary personnel records centres. More than 60 million records belonging to active-duty personnel, reservists, civilian staff, contractors, retirees, veterans, and military family members are stored at the centre.
The Pentagon has not detected any evidence that the leaked data has been misused. Military Times reported that affected individuals were offered identity restoration and credit history monitoring services.
A similar data breach previously occurred on the Federal Bureau of Investigation’s (FBI) recruitment website, FBIJobs.gov. According to information obtained by ABC News from internal communications and sources, the FBI is considering the possibility that data belonging to its entire staff may have been stolen.
The New York Times (NYT) examined a portion of the stolen FBI records. Home addresses, telephone numbers, official email addresses, Social Security numbers, dates of birth, hiring dates, and emergency contact details for relatives were identified within these documents.
The database also contained unit designations, duty roles, and information regarding the supervisors of personnel. Some records revealed assignments within counterintelligence and counternarcotics units, as well as departments examining threats originating from Russia, China, and Iran.
Ciaran Martin, the former head of the UK National Cyber Security Centre, noted that this type of breach could directly affect the FBI’s operational capabilities.
The hacker group known as ShinyHunters had announced that it had seized medical data and security clearance records alongside files belonging to tens of thousands of active and former FBI employees.
Experts evaluating the matter for the NYT warned that this information could be used to track agents, threaten their families, or compile dossiers by foreign intelligence services.
The ShinyHunters group initially threatened to release the data unless the bureau withdrew an advisory it had published concerning the group’s attack methods.
The group later asserted that it had never intended to leak the information and characterised its action as an advertising campaign.
In a report published in May, Reuters noted that the personal data of US military personnel had been used in surveillance and attack preparations.
According to the agency, Washington’s adversaries gained the ability to pinpoint areas where troops were concentrated by exploiting commercially available location data. US lawmakers at the time criticised the Pentagon for failing to adequately protect the personal data of military personnel.
America
Canada diversifies oil and gas exports away from US
US President Donald Trump’s trade policy and the Washington administration’s push to increase Venezuelan oil imports are prompting Canada to diversify its energy exports.
According to a report by The Wall Street Journal, recent developments are accelerating Canada’s development of new oil and natural gas projects.
Steps taken by the Ottawa administration, which aspires to become an energy superpower, are seen as potentially strengthening the country’s position in global markets.
In Canada, the world’s fourth-largest oil producer and fifth-largest natural gas producer, the energy sector accounts for approximately one-fifth of total exports.
Almost all of the country’s natural gas exports and approximately 90% of its oil exports go to the US.
The newspaper writes that the trade war with Washington and the atmosphere of confrontation entered into with Iran have heightened Canada’s desire to turn to alternative markets outside the US.
Officials plan to increase shipments of oil and liquefied natural gas (LNG) to European and Asian markets.
Accelerating infrastructure investments in line with this target, Canada is also shortening approval processes. The government is prioritising the construction of an oil pipeline extending specifically to the west coast.
According to the newspaper’s estimate, if major pipeline projects are implemented, Canada’s daily oil transport capacity could rise to 6.8 million barrels by 2034.
Routes heading to the west coast will make up approximately 30% of this capacity.
The Canadian administration is simultaneously advancing LNG export projects. According to the report, these investments could allow approximately 55% of Canadian natural gas exports to be directed to markets outside the US by the early or mid-2030s.
While the government expands tax incentives for the oil and natural gas sector, the province of Alberta also plans to overhaul its royalty system.
However, the newspaper notes that implementing the new projects requires heavy investment, and the process depends on the final decisions taken by producers as well as the completion of regulatory approval processes.
The expansion of pipeline and LNG infrastructure could gradually reduce Canada’s dependence on the US market while raising its share in the global energy market.
The Canadian Prime Minister’s demand to reduce reliance on the US market had also come to the fore in July.
According to Carney’s statement, the province of Alberta submitted a plan for a pipeline spanning more than 1,000 kilometres to the west coast of British Columbia.
Targeted for completion by September 2027, the line will reach the Pacific coast by following an existing corridor through the mountainous terrain.
This shift in energy comes at a time of strained relations with the US. Donald Trump said that if Canada obtains associate member status in the European Union, he could halt trade with Europe in certain sectors and impose high tariffs.
As reported by the Associated Press, Trump characterised such a rapprochement as a “potentially hostile act”.
European Commission President Ursula von der Leyen had proposed opening the path for Canada to become the EU’s first associate member. The terms of this associate membership status, which is not defined in EU treaties, are not yet clear and require the approval of member states to enter into force.
Canada, which does not seek full membership, aims for maximum rapprochement with the EU.
Following Trump’s return to the White House, relations between Washington and Ottawa deteriorated. The Trump administration, which repeatedly called on Canada to become the “51st state” of the US, introduced additional tariffs.
In July, the US began imposing 50% tariffs on certain Canadian-origin goods.
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