The crypto circle is going to have to copy homework now.
Family, who understands this! The 'iron rice bowl' in academia can't even compete with the AI wave? Yesterday I came across the news that the big shot from the University of Virginia's mathematics department, Ken Ono, took a naked resignation from his tenured position, and I almost spilled my coffee on the keyboard. This 'living fossil' who has won numerous awards in the mathematics world actually went to work for his 24-year-old former student!
Don't get me wrong, this isn't the kind of sci-fi script where a 7-year-old wins a Nobel Prize. It's about Ken Ono, who is nearing seventy and has solved the lingering problems left by Ramanujan, a tough character known in the industry as the 'mathematical magician.' In the crypto circle, it would be equivalent to Satoshi Nakamoto suddenly announcing they are joining a new public chain project as the chief technical advisor, the shock level would be off the charts. The one who poached him is his Chinese student Carina Hong, a genius girl who is only 24 years old, with an undergraduate degree from MIT and dual PhDs from Stanford.
As someone who has been watching the AI + crypto track for three years, I have to say this is definitely not as simple as 'master-student affection'; the signals hidden behind are more important than announcements from major exchanges. Let me first lay out the 'hardcore resumes' of these two, so you can see how outrageous this combination is.
Ken Ono is not just a bookworm who can only write formulas; early in his career, he applied number theory to the field of physics. This ability to 'theorize to application' is more valuable than gold in today's AI scene. The most critical point is that this old man publicly criticized 'AI doing mathematics is just a gimmick' a couple of years ago, but after witnessing Hong LeLan's team's model last year, he immediately changed his tune — it is said that the model completed a number theory reasoning that had troubled his team for half a year, with steps even more rigorous than those of humans. This kind of 'old-timer turning the page' decisively is far more clear-headed than those stubbornly sticking to traditional tracks in the crypto space.
Looking again at this 24-year-old founder Hong LeLan, a typical 'hexagonal warrior'. With a foundation in mathematics from MIT, a JD + PhD from Stanford, and having been nominated for the highest honor in undergraduate mathematics, this level of prestige in the crypto space is equivalent to having independently completed the underlying code of a public chain right after graduation. Even more impressive is her cross-industry intuition; while doing AI mathematical reasoning at Meta, she discovered that the 'reasoning bottleneck' of large models is essentially the same problem as the 'security verification bottleneck' in the crypto field: both require an absolutely rigorous logical closed loop. So when she started her business, she gathered a group of former AI elites from Meta and directly raised $64 million in funding at a speed that outpaced this year's popular MEME coins.
Speaking of this, there must be some brothers asking: what does this have to do with us crypto players? Don't worry, the key points are coming. Hong LeLan's company is called Axiom Math, and its goal is to create an 'AI mathematician' with three core capabilities: mathematical reasoning, automated proof, and formal verification. These three terms translate to the crypto world as three gold mines:
First, smart contract auditing. Current contract audits either rely on manual time or simple scripts to scan for vulnerabilities; when faced with complex nested logic, they can fail. But AI mathematicians can verify each step of the contract's logic like solving a math problem, making future encounters with 'rug pulls' potentially 'mathematically impossible'.
Second, upgrade of quantitative strategies. Most current quantitative strategies are based on 'historical data backtesting', which essentially is 'inductive reasoning'. When encountering a black swan, they can fail. However, an AI mathematician can use 'deductive reasoning' to derive strategies, for instance by calculating the optimal opening point based on the mathematical model of market liquidity, which is a thousand times more reliable than guessing.
Third, breakthroughs in underlying technology. Many underlying technologies in the crypto field, such as zero-knowledge proofs and elliptic curve encryption, are essentially mathematical problems. An AI mathematician might help us find more efficient encryption algorithms, making doubled transfer speeds and halved gas fees no longer a fantasy.
To be honest, Ken Ono's cross-industry move is like when internet tycoons jumped into the crypto space; it's traditional elites 'voting with their feet' on new tracks. We used to say 'AI changes crypto', but now it seems that it’s not that AI is insufficient, but rather that there’s a lack of knowledgeable mathematicians to steer the ship. Follow Yangyang.
