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Sacks claims DeepSeek exploited OpenAI’s intellectual property to boost its own AI systems, drawing a line between ethical innovation and outright theft in the competitive AI landscape.
David Sacks, a prominent figure in the tech and cryptocurrency sectors and known as Trump's AI and crypto "czar," has made a bold claim on Fox News. He asserts that there is "substantial evidence" indicating Chinese AI company DeepSeek used knowledge from OpenAI’s models to train its own systems, a process he likens to intellectual property theft.
The allegation of IP theft in the AI sector carries significant implications for both technological innovation and geopolitical relations. If substantiated, this claim could:

David Sacks did not provide specific sources or detailed evidence to support his claims during the Fox News interview. However, he suggested that DeepSeek used responses from OpenAI’s models to "distill" knowledge, a process akin to reverse engineering. This method involves using outputs from one model to train another, which can be seen as a form of intellectual property theft.
The AI community has responded with a mix of skepticism and concern. While some experts agree that the use of one company's models to train another’s is unethical and potentially illegal, others caution against jumping to conclusions without concrete evidence. OpenAI itself has not yet commented on Sacks' allegations.
David Sacks’ claims about DeepSeek’s alleged misuse of OpenAI’s technology underscore the complex challenges in protecting intellectual property in the rapidly evolving AI sector. As the investigation into these allegations unfolds, it will be crucial to balance innovation with ethical and legal considerations to ensure a fair and competitive landscape.
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Marcus began tracking AI's market implications in 2016, noticing AI-related patent filings accelerating ahead of earnings upgrades before most of the sell-side had caught on. A former fixed-income quantitative analyst, he spent two decades building models that priced risk across emerging markets before pivoting to cover the economic impact of AI full-time. His writing translates opaque technical developments into clear risk/reward terms — and he's rarely diplomatic about the gap between AI valuations and underlying fundamentals. He believes most market participants still underestimate AI's long-run deflationary effect on knowledge work.
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4 February 2025
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