U.S. Officials Target DeepSeek for Training New AI Model on Restricted Nvidia Chips
Another day, another regulatory showdown in the AI arms race.
The Chip Chase Gets Real
U.S. authorities are turning up the heat on AI development, setting their sights on DeepSeek. The allegation? The company trained its latest model using Nvidia hardware that sits firmly on the restricted list. This isn't about a simple licensing oversight—it's about accessing computational power deemed too sensitive for unfettered use.
Bypassing the Guardrails
The core of the issue cuts straight to supply chain control. Nvidia's most advanced chips are crown jewels of U.S. tech, with exports tightly managed. The implication is that DeepSeek found a way to get them, or their capabilities, anyway. It's a move that doesn't just challenge policy—it actively undermines a key strategic lever.
The Stakes for AI Sovereignty
This confrontation highlights the brutal truth: AI supremacy is built on silicon. Restricting chip access is America's primary tool for maintaining its lead. When a company allegedly circumvents those controls, it doesn't just build a better model—it punches a hole in a carefully constructed wall. The response from officials was predictably swift, signaling this will be a fight, not a fine.
A Costly Calculation
For DeepSeek, the gamble was clear: accelerated development versus regulatory wrath. They bet the value of a superior AI model outweighed the risk of getting caught. Now, they're facing the downside—a very public targeting that could freeze partnerships, spook investors, and attract even tighter scrutiny. It's a stark reminder that in tech, moving fast and breaking things applies to laws, too.
In the end, this is more than a compliance story. It's a power play. It reveals how the battle for AI dominance is fought not just in labs with algorithms, but in boardrooms and government offices over access to the physical hardware that makes it all run. And as usual, the finance guys are already pricing in the volatility—nothing like a good geopolitical spat to juice those trading fees.
Officials clash over chip sales and security rules
The Chinese embassy in Washington rejected the accusation. In a statement, it said China opposes “drawing ideological lines, overstretching the concept of national security, expansive use of export controls and politicizing economic, trade, and technological issues.”
On Tuesday, foreign ministry spokesperson Mao Ning told reporters she was not aware of the specific case. She added that China had already made its position clear on U.S. chip restrictions.
Export controls fall under the U.S. Commerce Department. Blackwell shipments to China are currently banned.
In August, Donald Trump signaled that Nvidia could sell a reduced Blackwell version to Chinese buyers. He later changed direction and said the company’s top chips should stay inside the United States.
In December, he allowed Chinese firms to purchase Nvidia’s second most advanced chip, the H200. That decision drew sharp criticism from lawmakers who take a hard line on China. Shipments of H200 chips are still paused because of approval guardrails.
White House AI czar David Sacks and Nvidia CEO Jensen Huang argue that allowing limited sales could slow the rise of Chinese rivals like Huawei. Some lawmakers disagree. They fear advanced chips could support military systems and weaken U.S. dominance in artificial intelligence.
The official also said the new DeepSeek model likely used “distillation” from leading U.S. AI systems built by Anthropic, Google, OpenAI, and xAI.
Distillation means a stronger model checks and grades the answers of a newer one. The smaller system then learns from those results. OpenAI and Anthropic have raised similar concerns before about Chinese developers using this method.
Hangzhou-based DeepSeek drew global attention early last year when it released models that rivaled leading U.S. systems. That release raised alarms in Washington about China closing the AI gap despite trade barriers.
Investors watch for Nvidia earnings and AI spending data
All this unfolds days before Nvidia reports fourth-quarter earnings on February 25. Last quarter, revenue beat guidance by almost $3 billion and showed $10 billion in sequential growth.
Despite those numbers, the stock fell from $186.52 on earnings day to $180.64 the next session. Shares had earlier peaked at $207.04 on October 29. They later dropped and closed at $171.88 on February 5 after a partial recovery.
Morgan Stanley analyst Joseph Moore expects strong Q4 results. Joseph said he sees at least $2 billion above the current $64 billion revenue guidance.
Consensus sits NEAR $72 billion. He said the ramp of the Vera Rubin chip should stay on schedule. He also noted demand for AI compute remains strong across DRAM, NAND, HDD, optical, CPU, and power supply chains.
Bank of America analyst Vivek Arya updated his outlook before earnings. Vivek said cloud capital spending could reach $748 billion in 2026 and $869 billion in 2027.
That represents growth of 56% and 16% year over year. He expects the data center systems market to expand 64% in 2026, while AI systems could grow close to 100% because of new accelerator deployments.
Even without Google, which uses its own TPUs, 2026 cloud capex may rise about 45% to $180 billion. Vendors are expected to pass higher HBM and DDR costs to customers to maintain margins as system sales increase.
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