On Monday, Nvidia Corp. experienced the largest single-day market cap loss in U.S. history, shedding $593 billion, according to Dow Jones Market Data. The trigger? A breakthrough attributed to Liang Wenfeng, co-founder of High-Flyer Quant and its AI-focused subsidiary, DeepSeek.
DeepSeek, a cutting-edge AI model, was developed by High-Flyer Quant, one of China’s leading quantitative trading firms. While it’s not uncommon for Wall Street quant veterans to venture into technology, DeepSeek’s rise has been anything but ordinary.
High-Flyer, a major player in China’s financial markets, employs sophisticated algorithms and models to execute trades. Its AI lab, DeepSeek, gained global attention over the weekend by launching its newest model, available in the U.S. via a smartphone app. By late Sunday, the app had surged to the top of Apple’s download charts. Social media buzzed with comparisons between DeepSeek’s model and offerings from Western giants like OpenAI and Anthropic.
DeepSeek’s innovation has been remarkable, competing effectively with high-profile AI models while operating on a fraction of their budgets. The company claims to have achieved this with fewer than 10,000 Nvidia A100 GPUs—an assertion met with skepticism by figures like Tesla CEO Elon Musk. This efficiency sent ripples through the market on Monday, as investors reconsidered the U.S.’s AI leadership and Nvidia’s dominance in powering AI advancements. Nvidia’s stock plunged 16.9%, wiping out $588.9 billion in market capitalization.
The upheaval also affected shares of Microsoft, Alphabet, and Amazon, as questions arose about the sustainability of massive AI infrastructure investments. Despite a projected $1 trillion in AI spending by U.S. tech giants in the next year, as forecast by Goldman Sachs strategists, the cost-revenue gap is expected to hit $600 billion by late 2024, according to Sequoia’s David Cahn.
Who is Liang Wenfeng?
Born in Guangdong province, Liang studied electronics and computer vision at Zhejiang University. In 2015, he co-founded High-Flyer with two college friends. His growing prominence in China’s AI industry was highlighted by his attendance at a symposium hosted by Premier Li Qiang.
High-Flyer, which reportedly manages $8 billion, initially built its AI capabilities with Nvidia chips. Liang is among a lineage of finance professionals leveraging quant skills to innovate in tech, echoing figures like Jeff Bezos, David Siegel, and David E. Shaw, who transitioned between finance and technology with remarkable success.
The Convergence of Quant and AI
The overlap between quantitative finance and AI research is significant. Gareth Shepherd, co-head of Voya Machine Learning Intelligence, noted that techniques like reinforcement learning, deep learning, and Bayesian networks are foundational to both fields.
The shift of talent between finance and AI reflects the growing allure of the AI sector. For years, hedge funds were lucrative destinations for top tech talent. However, as AI’s importance has grown, companies like OpenAI have begun aggressively hiring, offering competitive compensation to attract experts.
Liang’s journey from quant trading to AI exemplifies how competitive and lucrative AI has become, reshaping industries and challenging assumptions about technological leadership.
