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Nvidia Faces Historic Market Loss As DeepSeek Dents Confidence In AI’s Future

by THEFUTURE.TEAM

January 28, 2025

Nvidia experienced the largest single-day market cap drop in history on Monday, as its stock tumbled by 17%, shedding nearly $600 billion in value. This staggering loss is directly linked to a new development in the AI space—DeepSeek, a Chinese AI firm that unveiled its version of ChatGPT, raising concerns over the cost-efficiency and competitive positioning of U.S. AI companies.

Key Details

Nvidia’s shares experienced a severe decline, marking its worst daily percentage drop since March 2020, during the initial shock of the COVID-19 pandemic. On Monday, Nvidia lost a record-breaking $589 billion in market capitalization, more than doubling the previous one-day loss of $279 billion in September 2024. To put it into perspective, this is significantly more than Meta’s $251 billion market cap loss in February 2022.

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As a result, Nvidia’s market valuation dropped from $3.5 trillion to $2.9 trillion, slipping behind Apple and Microsoft as the world’s most valuable company. Nvidia’s dramatic fall led a broader retreat in U.S. stocks, with the S&P 500 losing 1.5% and the Nasdaq dropping 3.1%. Other major players in the AI industry, such as chipmakers Arm and Broadcom, alongside Oracle, saw their stocks plummet by at least 10%.

The DeepSeek Effect

The cause of Nvidia’s catastrophic loss lies in DeepSeek’s release of its large-language model, which has cast doubt on the continued dominance of U.S. companies in generative AI. Initially, this might not seem like a negative development for Nvidia, as DeepSeek’s model was also powered by Nvidia’s powerful graphics processing units (GPUs), just like many other AI technologies. However, DeepSeek revealed that it spent just $5.6 million on Nvidia’s technology to develop its model. While experts believe this figure is likely a significant underestimation, it still calls into question the very foundation of Nvidia’s meteoric stock rise.

In recent years, Nvidia’s profits have skyrocketed, with projections indicating net profits could soar from $4.8 billion in 2022 to $66.7 billion in 2024, largely due to the soaring demand for its high-priced GPUs, which can cost up to $25,000 each. U.S. tech giants such as Meta, Tesla, and OpenAI have been among Nvidia’s biggest customers. However, if companies like these can replicate DeepSeek’s cost-efficient approach by using cheaper GPUs, Nvidia could face significant challenges in maintaining its market dominance.

As Ed Yardeni of Yardeni Research pointed out, this shift could be an unwelcome development for Nvidia.

Surprising Statistic

Nvidia’s near-$600 billion market cap loss on Monday exceeds the market values of all but 13 American companies, surpassing industry giants like UnitedHealth, Exxon Mobil, and Costco.

CEO’s Losses

Nvidia CEO Jensen Huang saw his wealth take a massive hit, losing $21 billion in a single day. His net worth dropped from $124.4 billion to $103.1 billion, according to Forbes estimates. Huang remains the largest individual shareholder in Nvidia, owning a 3% stake in the company.

Nvidia’s colossal market cap loss highlights the growing uncertainties in the AI sector, as DeepSeek’s cost-effective alternative to American AI models threatens to disrupt the industry’s balance. With AI becoming an increasingly competitive and global field, Nvidia’s future may hinge on how it adapts to these emerging challenges.

The Future Forbes Realty Global Properties

by News Editor

August 24, 2026

Courts Are Still Applying Old Copyright Rules To AI

AI companies train models on enormous amounts of published material, including books, articles and academic research. Whether using that content without authors’ permission violates copyright law remains unresolved.

Much of the debate centres on fair use, which allows copyrighted material to be used without permission in certain circumstances. Courts consider factors such as the purpose of the use, how much material was involved and its impact on the original market.

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Anthropic Case Sets An Important Precedent

A major case involving Anthropic and a group of authors provided one of the clearest rulings so far. Judge William Alsup found that using copyrighted books to train AI models was lawful, comparing the process to people reading and studying literature before creating something new.

Anthropic was nevertheless ordered to pay $1.5 billion in a settlement. The penalty concerned books the company had obtained from illegal online libraries rather than the AI training itself.

For AI companies, that distinction could prove significant because it separates studying copyrighted material from directly copying it.

Competition Could Be The Key Issue

A case involving Thomson Reuters and Ross Intelligence offers a different perspective. A court ruled that Ross could not claim fair use after using Reuters’ copyrighted material to develop a competing AI-powered legal research platform.

The decision suggests courts may be less willing to consider AI training fair use when copyrighted content is used to build a product that directly competes with the original.

For authors, an unresolved question is whether AI-generated content should be considered competition for the works used to train these models.

The Law Has Yet To Catch Up

US copyright law predates generative AI by decades, leaving courts to apply old principles to new technology. Questions also remain over copyright protection for AI-generated works. In Thaler v. Perlmutter, a court ruled that material created entirely by AI cannot receive copyright protection.

Major AI companies remain involved in copyright litigation, and different courts could reach different conclusions. For now, there is no universal rule: the legality of AI training will depend on the circumstances of each case and how courts ultimately interpret copyright and fair use.