Many people saw that OpenAI just used AI to disprove the Exponential Time Hypothesis (ETH). So does that mean @OpenAI is about to destroy the existing social order? Does it mean that if we just have enough tokens, we can solve any problem in the future? Today’s hot OpenAI paper on the ETH solution has led a lot of people to believe two things: 1. The P vs NP problem has been solved, so the era of AI solving everything has arrived. 2. The Great Acceleration is here, every problem can now be computed. I spent an hour carefully reading the paper and found it’s actually not as exaggerated as most people think. Here’s a simple explanation of the key concepts: --- First, what is the P vs NP problem? When I started learning algorithms around age 16, I was obsessed with P vs NP. Why? Bc if it were solved, it would mean that with enough computing power, you could instantly get the answer to almost anything in the universe. Simply put, the core question is: “Are problems that can be verified in polynomial time equal to problems that can be solved in polynomial time?” What is polynomial time? Any algorithm can basically be reduced to forms like O(n), O(n^2), etc. Here n is the size of the input, and the big-O notation tells you roughly how long the computation will take as n grows. If P = NP, then essentially everything becomes computable. Humanity would have obtained the “cheat code” of the universe. From that point on, with enough tokens: - We could instantly reverse-engineer drugs that cure any disease. - AI could exhaustively search and find the perfect rocket launch trajectory in seconds. - Logistics optimization, AI training, weather forecasting… all of it could be solved in seconds by throwing more tokens at it. --- However, if the mainstream scientific view is correct and P ≠ NP, then many problems cannot be solved in polynomial time; they require exponential time. What is exponential time? Exponential time means the complexity is not O(n^c), but something like O(2^n). Every time n increases by 1, the amount of computation roughly doubles. Problems that require exponential time and cannot be reduced to polynomial time mean that no matter how many tokens you burn, you may never get the answer in any practical timeframe. In reality, protein folding for new drug discovery and the RSA encryption that protects your online banking are both classic exponential-time hard problems. Even if you burned all the computing power on Earth, you still wouldn’t get the answer before the solar system dies. If P = NP were true, exponential-time problems could be converted into polynomial-time ones through algorithmic engineering. Humans could create almost anything with AI, or destroy and break almost anything. --- So what’s the connection between this ETH result and P vs NP? A lot of people are saying: “ETH showed that 3-SAT (an exponential-time problem) has a better solution, so P vs NP is basically solved.” That’s not actually the case. Even if this particular exponential-time case (3-SAT) has been refuted under ETH, P vs NP remains unsolved. Why? Bc what happened here is that O(2^n) exponential time was improved to 2^{O(n/sqrt(log n))} — which is sub-exponential time, but still not polynomial time. As n gets larger, the complexity still explodes, just not quite as fast as pure exponential. In essence, AI shortened the time from “hundreds of billions of years” to something like “hundreds of millions of years.” That said, this is still worth paying attention to. AI has already come up with a way to reduce exponential time that humans hadn’t thought of before. As AI continues to advance, many classic hard problems that we had basically written off as “impossible to compute faster” are now open questions again. In other words, the assumption that “exponential time cannot become polynomial time” still has a chance of being overturned — just not yet. It’s similar to what Vitalik Buterin @VitalikButerin (the other “ETH”) said recently about the possibility of AI breaking ECDSA: > In any mathematical structure, “there exists a hidden 4th solution” is more likely than “there are exactly 3 solutions.”

Some of you may have noticed has been running a bit differently lately. Yes. Back in late September, right after I posted that insiders was getting hard to keep running, a senior I met earlier this year, someone I trust, reached out and offered to take over my operating role at insiders along with my equity. So since early October, insiders has been transitioning to the new team. That also gave me time to see whether their way of running things actually holds up. People will call this an exit, but it's closer to walking away with nothing. Apart from me and @dakshbigshit putting in over 50% of our personal assets, insiders never brought in real revenue. If anything, it ended up wiping out everything we'd saved through 2024 and 2025. All equity and tokens are being transferred for free. The only condition is that he funds insiders out of his own pocket and keeps it running to see if crypto prediction markets come back. He'll also look at what more $IN can be used for. A few engineers and interns will stay on to help. I did a lot of DD myself. The person taking over is trustworthy and has real operating experience. Even if it keeps losing money and has to shut down, every user's funds on insiders will be returned ahead of time, the same way @fireplacegg handled it. On the bright side, he's building his own trading platform, so there's a real chance of a rebrand or a merger with another platform. So from today, @dakshbigshit and I are moving into the next stage of exploring and learning. More reflecting, more searching for direction, and maybe some work outside Web3, like AI and real-world businesses. If anyone on here has a good opportunity, feel free to reach out. At the very least, we took insiders to millions in trading volume and 300 paying users at its peak. Looking back, insiders had two perfect exit windows, and we missed both. 1. January last year. If we'd stopped shipping updates then, we could have kept most of our capital. Had we just kept running it as it was instead of expanding in the wrong direction without PMF, it still had a decent shot. 2. April last year. A platform much bigger than us proposed a merger. We were proud and thought the terms weren't good enough, and the talks fell apart. So after half a year of grinding, we've ended up barely able to afford dinner. The good part is I learned a lot. A lot, a lot. I lost a lot of money and I'm ready to start over from zero and climb back up from the bottom. Still, I'm grateful to insiders. It showed me my own limits, and how far I can take a product when I go all in. Time to keep pushing. A while ago I read The Hard Thing About Hard Things by the @a16z founder. When I got to the part about the failed IPO, the setbacks that kept coming after it, and how he finally survived and sold the company, I couldn't hold it in and cried on the train. And I haven't even been through 1% of what's in that book. At some point in the next month or two I'll probably write a long-form post on the whole rise and fall of Next week I'll wrap up the handover and get ready for whatever comes next.

Talking about prediction markets at @TaipeiWeek with fellow founders. - @chessxyz from @bagel_win - @itsmaximilian from @meleemarkets Huge thanks to the mod - @Alvin0617 from @CryptoWesearch Next big update on @insidersdotbot soon!

Kudos to fireplace 🫡 Fireplace is, until today, one of the best prediction markets terminal I used. When building @insidersdotbot , we really learnt a lot from good products like @fireplacegg , @bagel_win and more. Market today is tough. Kudos to every founders who struggle to survive in this market.

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What a match! Even though with this unexpected turn of events, the winnings are around -30% for this match. Unfortunate but here are the @insidersdotbot next prediction: Hoping to make it back with this one! Let's go! @MrRyanChi what are your bets?

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