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

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.

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.

How Venture Capital Can Help Create Startup Fraud

Fraud Is Often A System Problem, Not Just A Founder Problem

A new report from Imperial College London and Emlyon Business School examines how venture capital-backed founders commit fraud and how investors can unintentionally create the conditions for it.

Published in June, the study draws on cases pursued by the U.S. Securities and Exchange Commission and the Department of Justice between 2000 and 2023. Its central conclusion is that fraud is not solely a founder problem, but can also stem from the incentives, expectations and governance structures surrounding startups.

High Expectations, Higher Risks

Several high-profile cases, including Charlie Javice of Frank, Gökçe Güven of Kalder, Do Kwon of Terraform Labs, and Alexander and Valerie Lau Beckman of GameOn, have intensified debate over where ambitious fundraising ends and fraud begins.

“Fraud is much more common and normalized in the startup world than we are ready to admit and accept,” Tim Weiss, one of the report’s authors, told TechCrunch.

Weiss also cited a University of Toronto study covering 654 fraud cases involving U.S. venture-backed startups between 2000 and 2023. Although fraud remained relatively rare, venture-backed companies were more likely to face fraud charges than non-VC-backed firms, while startups launched during overheated investment markets were 19% more likely to commit fraud later.

According to Weiss, pressure from investors and boards to deliver rapid growth can encourage misconduct, particularly in fast-moving sectors such as artificial intelligence.

The Three Stages Of “Façading”

The report, co-authored by Weiss and Nevena Radoynovska, identifies a three-stage process the authors call “façading.”

Surface façading begins with exaggerated claims about a company’s progress or traction. Reinforced façading involves creating evidence to support those claims, including fabricated contracts, invoices or revenue records. Deep façading extends the deception to the product itself through fake demonstrations and staged proof points.

Rather than beginning with a single act of fraud, the report argues that misconduct often develops gradually as founders attempt to sustain increasingly unrealistic expectations.

Investors Also Shape The Conditions For Fraud

One of the report’s central arguments is that investors are not always passive victims of founder misconduct. In some cases, they help create the conditions in which fraud becomes more likely.

According to the researchers, venture capital can “co-create fraud” by continuing to back founders who have previously been accused of misconduct, signaling that such behavior carries few long-term consequences. A separate University of Toronto study found little evidence that founders accused of fraud struggle to raise funding for new ventures, even when earlier cases attracted significant media attention.

“New investors and the broader VC market do not penalize past misconduct,” the report said, linking that pattern to Silicon Valley’s long-standing tolerance for failure.

Governance Plays A Critical Role

The University of Toronto study also identified governance as a key factor. Startups with founder-controlled boards were twice as likely to commit fraud as companies with investor-controlled or shared-control boards.

It also found that venture-backed companies going public were more likely to face securities class-action lawsuits within two years than private equity-backed firms. As startups remain private for longer while raising larger funding rounds, Weiss argues that governance has not kept pace with their growing scale.

“Founders do not have a professional body or association that could govern or enforce rules of entrepreneurial and investor conduct on how to be a good founder and what reasonable growth expectations are,” he said.

Calls For Stronger Oversight

Weiss argues that regulators should take a more proactive approach by introducing routine investigations and formal audits once startups reach significant funding thresholds, rather than waiting for whistleblower complaints or investor lawsuits.

The report also calls on investors to accept greater responsibility when aggressive growth targets contribute to governance failures. According to the authors, stronger oversight by both regulators and investors would help reduce the conditions in which fraud can develop.

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