Tesla has disbanded its Dojo supercomputer team, with team leader Peter Bannon departing amid a shift in AI strategy. Resources are being reallocated to other company data centres and computing projects.
The supercomputer was initially intended to process large volumes of vehicle data and video to train its autonomous‑driving systems. The team had recently lost around 20 members to the start‑up DensityAI.
Tesla plans to rely more on external partners for compute and chip supply. Strategic collaborations with Nvidia, AMD and Samsung Electronics are being pursued to bolster capacity.
The company focuses on integrating AI, including robotics and self‑driving technologies, across its business. A recent $16.5 billion agreement with Samsung aims to support services like robotaxi, humanoid robots and data‑centre operations.
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Tesla has reportedly shut down its Dojo supercomputer project following multiple high-profile departures, including that of project head Peter Bannon. CEO Elon Musk ended the AI chip programme, reassigning the remaining staff to other data centre projects.
Dojo aimed to process vehicle data for autonomous driving and reduce Tesla’s reliance on Nvidia and AMD. The project faced delays, with leaders such as Jim Keller, Ganesh Venkataramanan, and Bannon departing before its closure.
About 20 former Dojo employees have joined DensityAI, a stealth startup founded by ex-Tesla staff, which is expected to work on AI chips for robots and data centres. Tesla will now rely more on Nvidia, AMD, and Samsung.
Samsung recently secured a $16.5 billion deal to supply AI chips for Tesla’s self-driving cars, robots, and data centres. Musk said Samsung’s Texas factory will produce Tesla’s AI6 chips, with AI5 chips to be made in 2026.
Musk suggested that combining AI5 and AI6 chips could form a ‘Dojo 3’ system, while Dojo 2 would not launch. The shutdown comes as Tesla restructures, with executive exits, job cuts, and renewed focus on AI integration across Musk’s companies.
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NVIDIA has publicly rejected calls to embed kill switches or backdoors in its AI chips amid growing political pressure. The statement follows proposals from US lawmakers and accusations by Chinese authorities.
Chief Security Officer David Reber Jr. said any such backdoor would endanger global digital infrastructure and open doors for hackers. He reaffirmed NVIDIA’s commitment to fixing vulnerabilities, not creating them.
The controversy arises as the chipmaker navigates strict US export controls while maintaining its foothold in China with the H20 chip. A Chinese agency recently claimed these chips already contain hidden controls.
Reber distinguished transparent, user-controlled tools like remote wipe from covert backdoors, arguing they serve customers without risking the system integrity of the chips.
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Apple is increasing its domestic investment by an additional $100 billion, bringing its total commitment to US manufacturing to $600 billion over the next four years.
The announcement was made by CEO Tim Cook during a joint appearance with President Donald Trump at the White House, as the administration signals plans to impose steep tariffs on foreign-made semiconductors.
The investment includes a new American Manufacturing Program aimed at expanding US production of key Apple components, such as AI servers and rare earth magnets. Facilities are already under development in states including Texas, Kentucky, and Arizona.
Apple says the initiative will support 450,000 jobs across all 50 states and reduce reliance on overseas supply chains.
Apple’s expanded spending arrives amid criticism of its slow progress in AI. With its ‘Apple Intelligence’ software struggling for traction, and the recent departure of foundation model head Rouming Pang to Meta, the company is now shifting focus.
Cook confirmed that investment in AI infrastructure is accelerating, with data centres expanding in five states.
While Apple’s move has drawn praise for supporting American jobs, it has also stirred controversy. Some users expressed discontent with Cook’s public alignment with Trump, despite the strategic importance of avoiding tariffs.
Trump stated that companies investing in the US would not face the proposed import charges.
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South Korea’s Trade Minister said Samsung and SK Hynix will avoid the 100% US tariffs on semiconductor imports. The exemption follows both companies’ significant investments in US chip manufacturing facilities.
Trump had warned that countries failing to produce semiconductors domestically would incur steep tariffs but offered relief for those building factories in the US.
Samsung operates two chip fabrication plants in Texas, supported by the CHIPS and Science Act. Meanwhile, SK Hynix is building a packaging plant in Indiana with government grants and loans.
Samsung’s partnership with Apple will see chips manufactured at its Texas facility supply the iPhone line, particularly image sensors for next-generation models. Analysts expect this collaboration to boost Samsung’s semiconductor sales.
Apple also announced plans to invest an additional $100 billion in US operations over the next four years, highlighting the growing importance of domestic chip production.
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Two Chinese nationals have been charged in the US with illegally exporting millions of dollars’ worth of advanced Nvidia AI chips to China, violating the export controls.
The Department of Justice (DOJ) said Chuan Geng and Shiwei Yang operated California-based ALX Solutions, which allegedly shipped restricted hardware without the required licences over the past three years.
The DOJ claims that the company exported Nvidia’s H100 and GeForce RTX 4090 graphics processing units to China via transit hubs in Singapore and Malaysia, concealing their ultimate destination.
Payments for the shipments allegedly came from firms in Hong Kong and mainland China, including a $1 million transfer in January 2024.
Court documents state that ALX falsely declared shipments to Singapore-based customers, but US export control officers could not confirm the deliveries.
One 2023 invoice for over $28 million reportedly misrepresented the buyer’s identity. Neither Geng nor Yang had sought export licences from the US Commerce Department.
Yang was arrested on Saturday, and Geng surrendered soon after. Both appeared in a Los Angeles federal court on Monday and could face up to 20 years in prison if convicted.
Nvidia and Super Micro, a supplier, said they comply with all export regulations and will cooperate with authorities.
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The US is exploring how to build better location-tracking into advanced chips, as part of an effort to prevent American semiconductors from ending up in China.
Michael Kratsios, a senior official behind Donald Trump’s AI strategy, confirmed that software or physical updates to chips are being considered to support traceability.
Instead of relying on external enforcement, Washington aims to work directly with the tech industry to improve monitoring of chip movements. The strategy forms part of a broader national plan to counter smuggling and maintain US dominance in cutting-edge technologies.
Beijing recently summoned Nvidia representatives to address concerns over American proposals linked to tracking features and perceived security risks in the company’s H20 chips.
Although US officials have not directly talked with Nvidia or AMD on the matter, Kratsios clarified that chip tracking is now a formal objective.
The move comes even as Trump’s team signals readiness to lift certain export restrictions to China in return for trade benefits, such as rare-earth magnet sales to the US.
Kratsios criticised China’s push to lead global AI regulation, saying countries should define their paths instead of following a centralised model. He argued that the US innovation-first approach offers a more attractive alternative.
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Nvidia has firmly denied claims that its AI chips contain backdoors allowing remote control or tracking, following questioning by China’s top cybersecurity agency.
The investigation, which focuses on the H20 chip explicitly designed for the Chinese market, comes as Beijing intensifies scrutiny over foreign tech used in sensitive systems.
The H20 was initially blocked from export in April under US restrictions, but is now expected to return to Chinese shelves.
China’s Cyberspace Administration (CAC) summoned Nvidia officials to explain whether the chip enables unauthorised access or surveillance. The agency cited demands from US lawmakers for mandatory tracking features in advanced AI hardware as grounds for its concern.
In a statement, Nvidia insisted it does not include remote access capabilities in its products, reaffirming its commitment to cybersecurity.
Meanwhile, China’s state-backed People’s Daily questioned the company’s trustworthiness, stating that ‘network security is as vital as national territory’ and warning against reliance on what it described as ‘sick chips’.
The situation highlights Nvidia’s delicate position as it attempts to maintain dominance in China’s AI chip market while complying with mounting US export rules.
Tensions have escalated since similar actions were taken against other US firms, including a 2022 ban on Micron’s chips and recent antitrust scrutiny over Nvidia’s Mellanox acquisition.
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China’s top internet regulator has summoned Nvidia to explain alleged security concerns linked to its H20 computing chips.
The Cyberspace Administration of China stated that the chips, which are sold domestically, may contain backdoor vulnerabilities that could pose risks to users and systems.
Instead of ignoring the issue, Nvidia has been asked to submit technical documents and provide a formal response addressing these potential flaws.
The chips are part of Nvidia’s tailored product line for the Chinese market following US export restrictions on advanced AI processors.
The investigation signals tighter scrutiny from Chinese authorities on foreign technology amid ongoing geopolitical tensions and a global race for semiconductor dominance.
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Scientists in Australia have used quantum machine learning to model semiconductor properties more accurately, potentially transforming how microchips are designed and manufactured.
The hybrid technique combines AI with quantum computing to solve a long-standing challenge in chip production: predicting electrical resistance where metal meets semiconductor.
The Australian researchers developed a new algorithm, the Quantum Kernel-Aligned Regressor (QKAR), which uses quantum methods to detect complex patterns in small, noisy datasets, a common issue in semiconductor research.
By improving how engineers predict Ohmic contact resistance, the approach could lead to faster, more energy-efficient chips. It also offers real-world compatibility, meaning it can eventually run on existing quantum machines as the hardware matures.
The findings highlight the growing role of quantum AI in hardware design and suggest the method could be adopted in commercial chip production in the near future.
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