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what happens to trading if AI keeps getting better? Dwarkesh Patel asked Jane Street's head of technology the obvious question: if we get AGI, can't it just replace what you do? his answer: "trading feels to me like AGI-complete." "all of the different problems of the world end up...

57,388 görüntüleme • 3 ay önce •via X (Twitter)

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At the BNB Chain hackathon, CZ 🔶 BNB made several very important points about AI trading (Everything in parentheses is my own view and judgment.) He first said that AI will be involved in trading everywhere. Trading itself is already a huge market: there are 300 million users on Binance alone, and if you add the decentralized ecosystems, that number is not small either. In such a mass-market environment, many different trading strategies can work, with countless different coins, different projects, and different ways to play. But there is a big problem here: building commercial AI trading platforms for retail users is actually very hard. If a trading strategy works very well for one person, once a billion people start using the same strategy, that strategy “might still work, or might stop working.” Take copy trading / follow trading as an example: if you buy first and everyone follows you, the first buyer will perform very well, but the last person to follow may not end up with good results. So, with the exact same strategy and the exact same copy logic, the outcomes can be completely different for different people. (On top of that, every strategy also has its own capital capacity limits.) Teams that can really build strong AI are, with high probability, going to trade with their own money. In today’s world, money itself is already somewhat like a “commodity”; many people have a lot of capital, and it’s actually not that hard to raise funds. If you truly have an algorithm that can make a lot of money, it’s not hard to get money and run your own book. There is really only one situation where you would sell this algorithm to mass-market users: for example, if you charge a $10 monthly subscription and can sell it to one million users, then your $10 million monthly subscription revenue is higher than the profit you could make by trading the strategy yourself. (Here this touches one of our earlier theses: as training AI models becomes relatively easier and the supply of models increases, model companies have more incentive to open-source. By analogy, as the production process of trading strategies is increasingly simplified by AI and the supply of strategies explodes, traders will have stronger incentives to monetize by expanding their influence in other words, by “open-sourcing” their strategies.) Of course, CZ did not say that this model can never work. Another path is to build an AI trading platform that lets users tune different AI algorithms, or very easily assemble their own structures and strategies, so that what each person ends up running is different and better tailored to themselves. Some people will make money, some people will lose money, but the platform still has value because it’s very hard for most people to build an AI trading algorithm from scratch. So there are a lot of trade-offs here; it’s not as simple as saying “once AI shows up, everything automatically gets better.” (This is exactly what we presented at the hackathon: you describe your own strategy in natural language, and the AI automatically generates a workflow. The parameters in that workflow, the models used, the logical structure, the APIs it calls, and even the algorithms it invokes are all customizable. The reasons we think workflows are a good way to do this include: controllable execution paths, Lego-like modular nodes, and better visualization that makes it easier for users to build and adjust their workflows.) Finally, his conclusion was very clear: it’s not that AI will definitely make trading better, and it’s not that AI will definitely make things worse. Rather, no matter what, in the future a huge number of people will use AI to trade. This will be a very large field, and whoever can build the best algorithms will make a lot of money.

Tykoo

25,535 görüntüleme • 8 ay önce

Sam Altman told the world exactly what skills will matter when AI takes over 30 to 40 percent of the global economy. He was asked what his own kids should do to survive it. His answer was surprisingly human. He said the single most valuable thing anyone can build right now is the meta-skill of learning how to learn. Not a degree or a certification but the raw ability to adapt when everything around you changes. He also said learning to understand what other people actually want and building useful things for them will be more valuable than almost any technical knowledge. That skill has never been automated and is not close to being automated. He said human creativity and the desire to express it are, in his words, limitless. Every major technological revolution increased the demand for creative, curious, and socially intelligent people, not decreased it. The Industrial Revolution is the clearest parallel. Machines replaced physical labor and people were terrified. The next generation took those machines and built industries, art forms, and institutions nobody had conceived of before. The people who thrived were not the ones who competed with the machines. They were the ones who learned to direct them toward something new. That dynamic is already playing out right now with AI. The practical implication is this, depth in a single rigid skill is becoming less valuable. The ability to move across domains, pick up new tools quickly, and apply judgment in ambiguous situations is becoming more valuable. Altman also pointed to something most career advice ignores entirely, learning how to interact with the world, build relationships, and earn trust from other people. Those are things AI can simulate but cannot replace. The honest opportunity in this moment is not to outrun AI. It is to focus on the things that make you irreducibly human. Curiosity, judgment, empathy and the ability to ask the right question before anyone knows what the right question is. The people who will matter most in an AI-driven economy are not necessarily the ones who understand the technology deepest. They are the ones who can figure out what the technology should actually be used for. Altman has spent his career betting on human potential in the face of technological disruption. Based on every historical precedent, that is still the right bet to make.

StockMarket.News

376,873 görüntüleme • 5 ay önce

"You can either produce excellence or you can avoid criticism. But you cannot do both of those. The reason that you don't have certain excellence that you want is because you are afraid of getting criticized. You are afraid of the judgment that comes with it. You are afraid of standing out. You are afraid of being alone. You are afraid of people looking at you. You are worried about what people think of you. There are 2 categories of things in this world: 1) Things that are up to you 2) Things that are not up to you Which category does your reputation sit in? Your reputation is not up to you. I'm the one who associates your reputation with something, not you. You just do things. What's up to you? How you act. Your decisions. Your actions. That is up to you. Your reputation is not up to you. Here's how I know that: You all have a reputation about me and it's not in my control. I get to say and do whatever I say and do up here. I am in control of saying it. I am in control of doing it. The moment words leave my lips, who has control over what is done with those words? You! You are in control of what you think of me. And there's no way everybody in this room is going to think the exact same thing about me. No way. When it comes to exceptional, what we've got to understand is you can spend your whole life trying to avoid criticism and earn reputation, and it still won't be in your control. We can waste a lot of time missing out on excellence we could have been producing if we were just simply LESS trying to engineer what we wanted other people to think about us."

Brian Kight

308,812 görüntüleme • 1 yıl önce