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The New PayPal Mafia: 10 Interns Building a $100 Billion Business Empire

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A group of Olympiad prodigies who once interned at the same quantitative firm have, a decade later, become central figures in the AI and crypto worlds.

Original title: "The New PayPal Mafia: 10 Interns, $100 Billion"
Original author: Xiaobing | Shenchao TechFlow

On October 19, 2026, Meta Chief AI Officer Alexandr Wang posted a selfie on X with just seven words: got the HRT gang back together!

The comments section exploded.

This seemingly casual group photo hides one of the most absurd facts in today's tech world: the three people in the photo, plus a few former classmates not present, all participated in the inaugural internship program at Wall Street quantitative trading giant Hudson River Trading in the winter of 2015 — a program that admitted only 10 people in total.

Ten years later, the companies founded or led by these 10 interns have a combined valuation exceeding $100 billion.

On the right of the photo is Wang himself, 29, founder of Scale AI, who was recruited by Zuckerberg last year at a cost of $14.3 billion to join Meta as Chief AI Officer, helming Meta's Superintelligence Labs.

On the left is Jeff Yan, founder of Hyperliquid, a decentralized trading platform built by an 11-person team with zero funding, which posted $900 million in profit last year and has a project market cap of $76 billion.

In the middle is Scott Wu, founder and CEO of Cognition, whose AI coding agent Devin is growing enterprise customers at a rate of 50% per month, with the company's latest valuation at $48 billion.

The last time all three appeared in the same room was probably that winter of 2015, in the trading firm's office by the Hudson River.

Winter by the Hudson

The bond among these geniuses began back in high school.

Both Jeff Yan and Scott Wu won gold medals at the International Olympiad in Informatics (IOI), with Wu winning gold three times and achieving a perfect score in 2014. Alexandr Wang was a regular at the US Computing Olympiad and Mathematical Olympiad. They crossed paths repeatedly at various summer camps and training squads — that circle was so small that almost everyone knew each other.

In the winter of 2015, these young competitors scattered across Harvard and MIT were brought together by a common name: Hudson River Trading.

HRT is one of the world's top quantitative trading firms, headquartered in New York, with daily trading volume once accounting for more than 15% of the U.S. stock market.

In the winter of 2015, HRT attempted to recruit interns for the first time. The quota was extremely small—only 10 in total. Jeff Yan was a junior at Harvard at the time, Scott Wu was a freshman, and Alexandr Wang was a freshman at MIT.

The design of this internship program was itself very "quantitative": it lasted three weeks and was conducted in a competition format, with rankings in every round. According to Jeff Yan's later recollection, the top two in every round were always him and Scott Wu.

But the most historically significant moment of this internship may not have been the trading competition itself. According to an in-depth interview with Jeff Yan by Colossus magazine, it was during his internship at HRT that Yan first heard about Bitcoin from the introductions of two former partners. Although he did not act immediately at the time, he soon found Ethereum's yellow paper and read a description: a computer run jointly by the whole world that no one can shut down. That seed grew into Hyperliquid years later.

Also that winter, the 19-year-old Alexandr Wang, at his own birthday party, said something to the Harvard and MIT classmates sitting around the table that was later quoted repeatedly:

"Why can't it be us?"

Three paths, one origin

After walking out of HRT's office, these young people chose completely different tracks. But they shared one common underlying logic: using algorithmic thinking to reconstruct a traditional industry.

Alexandr Wang: From data labeling to Zuckerberg's AI brain

After leaving HRT, Wang made a decision that surprised everyone: he dropped out of MIT.

In 2016, at age 19, he co-founded Scale AI with Lucy Guo. What the company did sounded not sexy at all—labeling data for AI training. But Wang's judgment was extremely precise: he skipped specific AI applications and bet directly on the "shovels" of the entire AI industry.

As the AI wave sweeps the globe, Scale AI has become a core supplier to giants like OpenAI, Meta, and the U.S. Department of Defense. In 2021, the company's valuation soared to $7.3 billion, and 24-year-old Wang became the world's youngest self-made billionaire. In its 2024 funding round, Scale AI reached a valuation of $13.8 billion, backed by Nvidia, Amazon, and Meta.

Then came the June 2025 deal that shook Silicon Valley. Meta acquired 49% of Scale AI for $14.3 billion, at an overall valuation of $29 billion. As a core condition of the deal, Zuckerberg required Wang himself to join Meta as Chief AI Officer, leading the newly established "Meta Superintelligence Labs."

A 28-year-old young man became the overall commander of the AI strategy for the world's largest social media empire.

Jeff Yan: From Quantitative Trader to Builder of On-Chain Financial Infrastructure

If Wang chose the "picks and shovels" business of AI, Jeff Yan chose the hardest path in the crypto world: rebuilding trading infrastructure.

After graduating from Harvard, Yan did not rush into entrepreneurship. He worked at Google and then at a self-driving car company, while never stopping his observation of the crypto world. In 2020, he founded Chameleon Trading, a cryptocurrency market maker. This experience gave him a deep understanding of the structural flaws of centralized trading platforms, and the collapse of FTX gave him the decisive push.

In 2022, Yan disbanded the Chameleon team and began building Hyperliquid with his own funds—a decentralized perpetual contract trading platform running on the blockchain. No VC investment, no token presale, an 11-person team, starting from scratch.

This "anti-VC" path is almost unheard of in the crypto industry. Yan's confidence came from the trading profits accumulated at Chameleon, and even more from a quantitative trader's relentless pursuit of product excellence: low latency, high throughput, and a user experience approaching or even surpassing centralized trading platforms.

ICE CEO Jeffrey Sprecher once said that Hyperliquid's trading activity "exceeded Nasdaq's."

Today, Hyperliquid is one of the most profitable companies per capita in the world. Last year, the company's mere 11 employees generated over $900 million in profit. Founded just four years ago, the company has reached a market valuation of $76 billion.

Scott Wu: The Man Who Lets AI Write Its Own Code

Scott Wu has the most intimidating competition record among this group. Three IOI gold medals, winning with a perfect score in 2014, a MathCounts national champion, and third place at Google Code Jam. After studying at Harvard for two years, he dropped out and co-founded the AI social networking platform Lunchclub.

But what truly made him famous in Silicon Valley was Cognition, co-founded in late 2023 with Steven Hao and Walden Yan (the three hold a combined 5 IOI gold medals). In March 2024, Cognition released Devin, billed as "the world's first AI software engineer," capable of independently planning, writing, testing, and deploying code.

Devin sparked enormous controversy in the tech world, but the market gave its own answer: Cognition's valuation soared from $350 million in early 2024 to $10.2 billion in September 2025, and then to $26 billion in May 2026 (raising $1 billion), with annualized revenue surging from $5.4 million in mid-2024 to nearly $500 million in mid-2026.

By September 2026, annualized revenue had approached $1 billion, and the latest valuation was reportedly $48 billion. Wu himself says that over 90% of Cognition's internal code is now written by Devin itself.

A three-year-old startup whose valuation went from $350 million to $48 billion — a more than 130-fold increase.

More Than Three People

Today's selfie shows only three people, but this circle is far larger than one photo can contain.

According to Scott Wu himself, the HRT internship program was not the starting point of this group's friendship. As early as high school, many of them had already met through various olympiad competitions. And the names extending from that small circle each occupy a place on today's tech landscape.

Jesse Zhang, one of the HRT interns in the same cohort. His previously founded social gaming company Lowkey was acquired by Niantic (the developer of "Pokémon Go"). In 2023, he founded the AI customer service agent company Decagon, focusing on using AI to replace enterprise customer service. Less than three years after its founding, the company's valuation has reached $4.5 billion, with clients including giants such as Duolingo and Hertz, and was selected for Forbes 30 Under 30 in 2026.

Johnny Ho, a three-time IOI gold medalist and Harvard alumnus. He met Scott Wu and Jeff Yan in high school. In a 2013 photo of the U.S. IOI team, he stood shoulder to shoulder with Steven Hao and Scott Wu.

After leaving the competitive programming circle, Ho worked as a quantitative trader at Tower Research Capital, then joined Quora as an engineer. In 2022, he co-founded the AI search engine Perplexity with Aravind Srinivas and others, and currently serves as co-founder and Chief Strategy Officer. Perplexity's latest funding round reportedly values the company at approximately $30 billion, and it is redefining the trillion-dollar search engine market.

Demi Guo, a "genius girl" from Hangzhou and a 2015 IOI silver medalist. She holds a bachelor's degree in mathematics and a master's degree in computer science from Harvard, and was once the youngest full-time researcher at Meta AI Research. In 2023, she dropped out of her PhD program at Stanford and co-founded the AI video generation platform Pika with classmate Chenlin Meng. The company reached a valuation of $470 million, with more than 16 million users. She previously interned at HRT and Quora, and is part of the same circle.

Steven Hao, a 2014 IOI gold medalist and a graduate of MIT's mathematics department. He was an early core engineer at Scale AI during Alexandr Wang's time there, and later joined Scott Wu's Cognition as co-founder and CTO. According to Forbes estimates, the 30-year-old Hao's personal net worth has reached approximately $1.3 billion, making him the youngest American on the 2026 Forbes 400 list.

From Hao's trajectory, the "talent flow" within this circle is clearly visible: he brought the engineering experience and understanding of AI data accumulated at Scale AI into Cognition. And Cognition's three founders Wu, Hao, and Walden Yan collectively hold 5 IOI gold medals, directly infusing the algorithmic thinking honed in competitions into the core architecture of AI coding agents.

Why Have Quantitative Trading Firms Become Cradles for Founders?

This is no coincidence.

When Wang retweeted that 2015 intern group photo in early October this year, he added a note: "HRT 2015 intern class is the new-gen PayPal Mafia."

The story of the PayPal Mafia is well known. Elon Musk, Peter Thiel, Reid Hoffman, David Sacks, and others came out of the same company and went on to found Tesla, Palantir, LinkedIn, Yammer, and other companies, defining the tech landscape of the previous decade.

But the HRT cohort and the PayPal Mafia have a fundamental difference. The bond of the PayPal Mafia was a company and a shared entrepreneurial experience. The bond among the HRT group is earlier and deeper—what they share is a way of thinking.

What does it mean to come from a competition background?

It means they have been trained since their teens to approach problems with an optimal-solution mindset, with an almost obsessive pursuit of efficiency and an intuitive understanding of complex systems. Quantitative trading firms are a natural amplifier of this way of thinking: at HRT, they learned how to extract signals from massive noise, how to make decisions within millisecond-level time windows, and how to build systems capable of self-optimization.

Jesse Zhang wrote in an article: "The generation that grew up doing math, programming, and science competitions accounts for a disproportionately high share of today's founders."

Quantitative trading firms are precisely the key springboard for this group between the competition circle and the startup circle. Jane Street, Citadel, DE Shaw, Two Sigma—similar stories stand behind all these names, but the concentration of the HRT 2015 cohort is indeed unusually high.

10 interns, at least 4 of whom became unicorn founders, with their companies collectively valued at over $100 billion — this "talent conversion rate" surpasses that of tech giants like Google and Meta, which are renowned for producing AI talent.

The deeper reason may lie in this: what these quantitative trading firms offer is not just technical training, but also an instinctive understanding of market structure. Wang applied this understanding to AI data infrastructure, Yan to on-chain financial infrastructure, Wu to software engineering automation, Zhang to customer service reconstruction, and Ho to disrupting the search engine.

They solved different problems, but their approach to breaking them down was identical: find an inefficient system and rebuild it with algorithmic and engineering capabilities.

Geniuses always meet early. But what truly moves people about this story is not how smart they are. Competition gold medals have long proven their intelligence. What's moving is that the era has finally turned to the page that belongs to them.

Ten years ago, what was the portrait of this group? Math competition champions, programming geeks, invisible figures in social settings. In the hierarchy of any American high school, they were all lumped under one word: nerd. For a long time, that word was not a compliment — it meant eccentric, boring, out of step with the mainstream.

But the world after 2024 has given nerds an unprecedented stage.

When AI becomes the underlying operating system of all industries, when code itself begins to write code, the people who can harness all of this are precisely those who have lived inside algorithms and formulas since childhood.

Wang, Yan, Wu, Zhang, Ho, Guo, Hao — these Chinese surnames that are tongue-twisting for white people to pronounce — have walked from the olympiad arena to the center of the era's stage.

The once-despised nerd has finally ushered in their golden age.