Liang Wenfeng (Chinese: 梁文锋; pinyin: Liáng Wénfēng; born 1985) is a Chinese entrepreneur and businessman who is the co-founder of the quantitative hedge fund High-Flyer, as well as the founder and CEO of its artificial intelligence firm DeepSeek.

1 day ago · DeepSeek founder Liang Wenfeng, 40, is a billionaire. He started off in engineering, then founded and ran a hedge fund, before founding popular AI startup DeepSeek.

Jan 28, 2025 · Liang Wenfeng, who founded DeepSeek in 2023, was born in southern China’s Guangdong and studied in eastern China’s Zhejiang province, home to e-commerce giant Alibaba and other tech firms, according to Chinese media reports.

BEIJING, Jan 28 (Reuters) - Liang Wenfeng, the 39-year-old founder of Chinese AI startup DeepSeek, has in the matter of weeks become the face of China's tech industry and its hope of overcoming an ...

Jan 28, 2025 · What Are Liang Wenfeng’s Ties To The Chinese Government? Liang spoke at a closed-door event for China’s Premier Li Qiang with experts from other industries on Jan. 20, according to a summary ...

Jan 29, 2025 · Liang Wenfeng is now leading China in its AI revolution as the superpower attempts to keep pace with the dominant AI industry in the United States. But who is the founder of DeepSeek?

Chinese engineer Liang Wenfeng built the AI company after founding a successful hedge fund. By . Gregory Zuckerman. and . Raffaele Huang. Share. Resize. Listen (1 min)

Jan 27, 2025 · Liang Wenfeng is the founder of DeepSeek, the Chinese AI startup potentially upending the industry. Here's everything to know about the hedge funder.

Jan 28, 2025 · But who is Liang Wenfeng, the leader of the company so disruptive that it sent Nvidia shares tumbling? According to The Wall Street Journal, DeepSeek isn’t the entrepreneur’s first company. In...

Jan 27, 2025 · DeepSeek, founded by hedge fund manager Liang Wenfeng, unveiled its R1 model last Monday, accompanied by a detailed paper outlining how to train a large-scale reinforcement learning (RL) model without relying on supervised fine-tuning (SFT) as a preliminary step.