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Time for the weekend Long Read suggestions and look this was the week of Deep Seq, right? So two different profiles of Deep Seq founder Liang Wen Fang, a math geek who in 2015 founded hedge fund High Flyer, which somehow Deepseek was incubated inside of. This first one is from the journal Quote Some call him China's Sam Altman. Others compare him to Jim Simmons, the pioneer of quantitative investing. Liang Wen Feng shares a lot with both innovators, but his impact might end up being as Great Born in 1985, Liang grew up in Zhangjiang, one of the port cities on the southern Chinese coast that have traded with the world for centuries. He was a straight A student in school and began studying calculus on his own in junior high school before going on to China's prestigious Zhejiang University as a student, Liang started writing AI algorithms to pick stocks in 2013. A few years after graduation, he started Jacobi, an investment firm named after German mathematician Karl Jacoby. In 2015, he founded High Flyer with two college friends. It was a pioneer in China in applying newer AI techniques so computers could absorb many types of data, not just market prices, and tease out significant patterns. Unlike high frequency traders, who try to get a jump of a few milliseconds on others, Liang and and his colleagues have focused on medium frequency trading, where positions can be held longer. Lang drew inspiration from Simmons, a mathematician and pioneer in quantitative finance who founded the Long island hedge fund Renaissance Technologies and was using machine learning techniques. In the 1980s, Liang wrote the introduction to the Chinese version of the man who Solved the Market, a book about Simmons and his team. Whenever I encounter difficulties at work, I recall Simmons words. There must be a way to model prices, liang wrote. Over the past five years, at least five funds High Flyer managed produced average excess returns of more than 20% compared with market benchmarks, according to financial data provider Simu Pai Paiwang. But there have been bumpy patches, too. In 2021, High Flyer apologized to its investors for poor performance, saying it misread which sectors of the market would perform well. Another rough spot occurred last year, when China's financial regulator clamped down on quants, accusing them of herd behavior that exacerbated volatility. Richard Dewey, a technology executive and former hedge fund manager, said DeepSeq's AI development strategy of doing more with less a smaller team, less money and fewer chips reminded him of quant traders. They seem to have focused on wringing a lot of signal out of a relatively small amount of data, which is similar in spirit to what's required in quantitative trading, dewey said. Like some other quants, Liang prefers to be thought of as an engineer rather than a trader, according to people close to him. In 2019, Liang's team started building computing systems with Nvidia graphics processing units. By late 2022, when OpenAI released ChatGPT, only a few Chinese companies had more 10,000 Nvidia high end chips in hand, and High Flyer was among them. It's like buying a piano, liang told at Chinese tech publication 36Kr in 2023, talking about the chip purchases. Firstly, it's because you can afford it, and secondly it's because you have a group of people who are eager to play music on it. One of Liang's biggest decisions was to make his code open source, meaning anyone can access it, he said. He wanted Deepseek to break the monopoly of big tech companies. And this is BusinessWeek's profile. DeepSeek's research was funded by High Flyer's R&D budget, Liang said. Previously it drew computing resources from the quant fund, which had amassed 10,000 Nvidia GPUs in 2021. Prior to US bans on exports of sophisticated Nvidia chips and other graphics processing units, Liang recruited engineering talent almost exclusively from China. Many were fresh out of top universities, interns in their final leg of doctoral studies and Olympiad medal holders, Wang said. L. Yang ran many experiments on his own and DeepSeq operated much like a research lab. It started small, but as they got real progress, they started to get excited, he said. The startup began periodically releasing models seemingly impervious to even stirred up by the US ban on exports of cutting edge AI accelerator chips. Deepseek released its R1 advanced AI reasoning model on January 20, the same day Donald Trump was sworn in as America's 47th president. Earlier that Monday, Liang attended a closed door business symposium in Beijing that was hosted by Chinese Premier Li Qiang. Their experts in technology, science, education and other fields offered their opinions and suggestions for a draft government work report, according to the official news agency. Video footage on YouTube shows Liang sitting across the table from Li and speaking with the Chinese leader, nodding attentively. Liang is assumed to own 51% of High Flyer. That would give him a stake worth $71 million, based on a comparative analysis, according to the Bloomberg Billionaires Index. If Deepseek reaches the same potential as OpenAI valued at roug $150 billion, the founder could potentially be in line for a massive windfall. Some have questioned whether Lang's Deep Seek is as promising as it appears. Shortcomings include the startup's infrastructure's ability to handle global traffic, waiting to try its service, or the app's handling of sensitive subjects, such as the 1989 protests in Tiananmen Square and queries on Chinese leader Xi Jinping. Experts have also questioned the assumption that Deepseek was building with 10,000 A100 Nvidia chips, with analysts like like Dylan Patel speculating that DeepSeq needs at least 50,000 of Nvidia's far more powerful chips. The H1 hundreds meta platforms, for instance, operates the equivalent of 600,000 Nvidia H1 hundreds, end quote. Yeah, on that. And finally this week, the great site Semianalysis has a deeply detailed look at Deepseek and the contours of their operation, which again is estimated to have access to around 500,000 Hopper GPUs, a total server capex of 1.3 billion doll, and a GPU spend of more than $500 million over its history quote Deepseek took the world by storm. For the last week, Deepseek has been the only topic that anyone in the world wants to talk about. As it currently stands, Deep Seek daily traffic is now much higher than Claude, Perplexity and even Gemini. But to close watchers of the space, this is not exactly new news. We have been talking about Deepseek for months. Each link is an example. The company is not new, but the obsessive hype is. Semianalysis has long maintained that Deepseek is extremely talented and the broader public in the United States has not cared. When the world finally paid attention, it did so in an obsessive hype that doesn't reflect reality. We want to highlight that the narrative has flipped from last month when scaling laws were broken. We dispelled this myth. Now algorithmic improvement is too fast and this is too somehow bad for Nvidia and GPUs. The narrative now is that Deepseek is so efficient that we don't need more compute and everything has now massive overcapacity because of the model changes. While Jevons paradox 2 is overhyped, Jevons is closer to reality. The models have already induced demand with tangible effects to H100 and H200 pricing. We believe the most interesting implications is specifically on margins and what that means for the entire ecosystem. Below we have a view of the future pricing structure of the entire AI industry and we detail why we think Deepseek is subsidizing price, as well as why we see early signs that Jevons Paradox is carrying the day. We comment on the implications, implications on export controls, how the CCP might react with added deep, seek dominance, and more. As I say, it's in depth, it's technical, it's worth reading. This weekend I've got a bonus episode that looks at something we don't talk about all that much. You, you know, you create a startup, you enter a market, you attack a problem, all with a set of assumptions set in a specific period of time. And then the world changes. Maybe there's a global recession, maybe there's a global pandemic, maybe there's a, I don't know, meteor strike. Or as in the case of the company we're profiling this weekend, there is a change in political administrations and suddenly the market you were targeting might have to face headwinds you didn't need to even worry about a year or so ago. It's an interesting look at as an interesting startup problem that doesn't get discussed very often. Listen to that. Talk to you on Monday.