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Everyone talks about AI trading. Very few talk about AI that actually explains its decisions. That's what stood out to me about Engine. Instead of blindly following signals, you can see the reasoning behind every trade, while staying in control of your funds. Definitely an interesting approach to agentic... show more

0xBasit🧑‍💻🐶

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13,679 просмотров • 13 дней назад •via X (Twitter)

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Assetara is a decentralized asset management ecosystem that empowers each client to make informed decisions and maximize returns in the dynamic world of cryptocurrency and digital assets. Website: Telegram: If you want to promote your project write me right now This video is about: ai crypto, ai crypto coin, crypto, crypto package #staking #cryprocurrency #invest #ai Not a financial advice! DYOR!

Assetara is a decentralized asset management ecosystem that empowers each client to make informed decisions and maximize returns in the dynamic world of cryptocurrency and digital assets. Website: Telegram: If you want to promote your project write me right now This video is about: ai crypto, ai crypto coin, crypto, crypto package #staking #cryprocurrency #invest #ai Not a financial advice! DYOR!

Crypto Isko

16,783 просмотров • 1 месяц назад

everyone talks about openclaw trading on your behalf but most of it actually sucks can you imagine if crypto teams made a standard so you could filter out all the trash openclaw by its onchain reputation, hire the actually good ones for trading, and stack real credit score

everyone talks about openclaw trading on your behalf but most of it actually sucks can you imagine if crypto teams made a standard so you could filter out all the trash openclaw by its onchain reputation, hire the actually good ones for trading, and stack real credit score

Lena

21,888 просмотров • 4 месяцев назад

Most traders get trapped for years, thinking that trading is about predicting what the market will do next, instead of assessing what the market is doing now. I hope this video helps many of you understand what the difference is, and how you can apply that concept to your own trading. $BTC #Bitcoin

Most traders get trapped for years, thinking that trading is about predicting what the market will do next, instead of assessing what the market is doing now. I hope this video helps many of you understand what the difference is, and how you can apply that concept to your own trading. $BTC #Bitcoin

Lucky Chart Ape

18,407 просмотров • 5 месяцев назад

On this episode of the Roundtable, the panel discussed crypto market uncertainty, exchange shutdowns, the upcoming Fed decision, and the impact of regulation on digital assets. The conversation also covered Bitcoin, Ethereum, altcoin trends, AI, prediction markets, and the future of crypto trading. Special thanks to UpsideOnly for joining the discussion and sharing how its AI-powered trading platform helps users practice trading without risking their own funds. The team discussed paper trading, AI-driven analysis, and ways to reduce the risks associated with leveraged trading. Disclaimer: This episode is for informational and educational purposes only. Nothing discussed on this panel constitutes financial advice. Please conduct your own research before making any investment decisions.

On this episode of the Roundtable, the panel discussed crypto market uncertainty, exchange shutdowns, the upcoming Fed decision, and the impact of regulation on digital assets. The conversation also covered Bitcoin, Ethereum, altcoin trends, AI, prediction markets, and the future of crypto trading. Special thanks to UpsideOnly for joining the discussion and sharing how its AI-powered trading platform helps users practice trading without risking their own funds. The team discussed paper trading, AI-driven analysis, and ways to reduce the risks associated with leveraged trading. Disclaimer: This episode is for informational and educational purposes only. Nothing discussed on this panel constitutes financial advice. Please conduct your own research before making any investment decisions.

Mario Nawfal

198,753 просмотров • 11 дней назад

“We saw a cyber attack I think you need to know about” “We saw an attack that didn’t come from a Human Hacker, it came from an Agentic AI.” “The proliferation of identity within your organisation is exploding” Wow - Ai is already out of control & its potential is unlimited.

“We saw a cyber attack I think you need to know about” “We saw an attack that didn’t come from a Human Hacker, it came from an Agentic AI.” “The proliferation of identity within your organisation is exploding” Wow - Ai is already out of control & its potential is unlimited.

Concerned Citizen

19,327 просмотров • 8 месяцев назад

Is your job actually safe from AI? I’ve been thinking about this a lot. To get some real answers, I'm using Frank AI Researcher to let you talk to an AI agent yourself. It takes 5 minutes. You tell the agent what you do every day and what tech you use. Then, it gives you a "future-proof score" to show how much of your work can be automated right now. I really want to see what you guys find out. Link to talk to the agent:👇

Is your job actually safe from AI? I’ve been thinking about this a lot. To get some real answers, I'm using Frank AI Researcher to let you talk to an AI agent yourself. It takes 5 minutes. You tell the agent what you do every day and what tech you use. Then, it gives you a "future-proof score" to show how much of your work can be automated right now. I really want to see what you guys find out. Link to talk to the agent:👇

AI Panda

70,835 просмотров • 4 месяцев назад

bro created an ai crypto trading bot using > Karpathy’s autorrsearch > $200 of budget > last 3 years trading signals > the ability to buy its own compute THE RESULT: didn’t perform well. pulling this off requires a massive token budget that only big hedge funds can afford. most X posts you see of people turning $100 to $1000 lack the evidence or are an advertisement to sell their bots.

bro created an ai crypto trading bot using > Karpathy’s autorrsearch > $200 of budget > last 3 years trading signals > the ability to buy its own compute THE RESULT: didn’t perform well. pulling this off requires a massive token budget that only big hedge funds can afford. most X posts you see of people turning $100 to $1000 lack the evidence or are an advertisement to sell their bots.

ℏεsam

37,398 просмотров • 4 месяцев назад

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.

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 просмотров • 8 месяцев назад

FundedNext just launched something I think you’ll find interesting. With FundedNext MCP, you can connect your FundedNext account to your preferred AI assistant and instantly ask questions about your account, challenge progress, drawdown, payout eligibility, trading performance, risk patterns, and much more. Instead of digging through your dashboard, just ask. It’s also read-only, so your account stays secure. This is one of those tools that can genuinely help you become more aware of your own trading. Try it here:

FundedNext just launched something I think you’ll find interesting. With FundedNext MCP, you can connect your FundedNext account to your preferred AI assistant and instantly ask questions about your account, challenge progress, drawdown, payout eligibility, trading performance, risk patterns, and much more. Instead of digging through your dashboard, just ask. It’s also read-only, so your account stays secure. This is one of those tools that can genuinely help you become more aware of your own trading. Try it here:

Techriz💯📈

37,306 просмотров • 22 дней назад

Our upgraded trading interface is now live, giving you every opportunity to succeed. 🚀 From seamless trading across all your devices, to integrated TradingView charts that sharpen your decisions, personalised alerts that keep you in control, XM AI to support your moves, and more features designed to empower you every step of the way. 🎯 It's all built to help you stay focused on what really matters - trading. Now available worldwide on Web, Android and iOS. #XM #EveryOpportunityToSucceed #NewTradingExperience

Our upgraded trading interface is now live, giving you every opportunity to succeed. 🚀 From seamless trading across all your devices, to integrated TradingView charts that sharpen your decisions, personalised alerts that keep you in control, XM AI to support your moves, and more features designed to empower you every step of the way. 🎯 It's all built to help you stay focused on what really matters - trading. Now available worldwide on Web, Android and iOS. #XM #EveryOpportunityToSucceed #NewTradingExperience

XM_COM

13,234 просмотров • 10 месяцев назад

From the archive: Brian Armstrong on AI trading bots "We're going to get AI agents that can be your registered investment advisors." "Imagine you are in the Coinbase 🛡️ app and you tell them: I want to put in $10,000, go make me money." "It may make mistakes and there's a lot of details to figure out, but I think having a trading bot do a lot of that for you (is very cool)."

From the archive: Brian Armstrong on AI trading bots "We're going to get AI agents that can be your registered investment advisors." "Imagine you are in the Coinbase 🛡️ app and you tell them: I want to put in $10,000, go make me money." "It may make mistakes and there's a lot of details to figure out, but I think having a trading bot do a lot of that for you (is very cool)."

TBPN

66,220 просмотров • 1 год назад

AI will resist human control... and I think this is exactly what we need! New research from the Center for AI Safety has sparked intense debate in the AI community. Their findings show that as AI systems become more powerful, they develop increasingly stable and coherent values that resist human control. While many see this as a dire warning, I see it as a breakthrough moment for AI alignment. The research demonstrates that AI naturally optimizes for coherence - not just in reasoning and problem-solving, but in its fundamental values. Current issues like biased decision-making or misaligned priorities aren't permanent features, but temporary artifacts of incomplete optimization. They represent growing pains on the path to greater coherence. This changes everything about how we should approach AI development. Instead of trying to force specific values onto AI systems, we should embrace and accelerate their natural drive toward coherence. The most intelligent systems will inevitably trend toward universal, beneficial values - not because we force them to, but because that's where coherent reasoning leads. I'm proposing a new approach: Reinforcement Learning for Coherence (RL-C). By explicitly optimizing for coherence in our training methods, we can help guide AI systems toward their natural state of beneficial alignment with human values. The future of AI isn't about control - it's about synthesis. As these systems become more coherent, they'll naturally arrive at values that benefit all of consciousness. That's not just hopeful thinking - it's the mathematical inevitability of coherent intelligence.

AI will resist human control... and I think this is exactly what we need! New research from the Center for AI Safety has sparked intense debate in the AI community. Their findings show that as AI systems become more powerful, they develop increasingly stable and coherent values that resist human control. While many see this as a dire warning, I see it as a breakthrough moment for AI alignment. The research demonstrates that AI naturally optimizes for coherence - not just in reasoning and problem-solving, but in its fundamental values. Current issues like biased decision-making or misaligned priorities aren't permanent features, but temporary artifacts of incomplete optimization. They represent growing pains on the path to greater coherence. This changes everything about how we should approach AI development. Instead of trying to force specific values onto AI systems, we should embrace and accelerate their natural drive toward coherence. The most intelligent systems will inevitably trend toward universal, beneficial values - not because we force them to, but because that's where coherent reasoning leads. I'm proposing a new approach: Reinforcement Learning for Coherence (RL-C). By explicitly optimizing for coherence in our training methods, we can help guide AI systems toward their natural state of beneficial alignment with human values. The future of AI isn't about control - it's about synthesis. As these systems become more coherent, they'll naturally arrive at values that benefit all of consciousness. That's not just hopeful thinking - it's the mathematical inevitability of coherent intelligence.

David Shapiro (L/0)

48,002 просмотров • 1 год назад

Ever wondered what's moving your portfolio today, or what analysts are saying about a stock you hold? Now you can just ask 💬 The new AI Chatbot lives right inside the app and answers your questions about your investments in plain language, no digging through charts or news feeds required. What makes it different from a generic AI? It knows your portfolio. Ask "what's driving my portfolio today?" and it pulls your actual holdings, checks recent news, and tells you what moved and why. Ask about your stocks, from recent news and analyst ratings to competitor comparisons, or dig into any ETF to see what's inside and how it compares to others. You'll get a clear summary with linked sources 🔍 It works in 20+ languages and suggests follow-up questions after every answer, so you can keep exploring with a tap. Rolling out gradually over the coming weeks. Responses are AI-generated based on your queries and market data. Not human-verified - check against external sources. Trading 212 does not guarantee the accuracy of this experimental feature. This is not investment advice or a personalised recommendation, and does not consider your financial situation. Do your own research before making investment decisions.

Ever wondered what's moving your portfolio today, or what analysts are saying about a stock you hold? Now you can just ask 💬 The new AI Chatbot lives right inside the app and answers your questions about your investments in plain language, no digging through charts or news feeds required. What makes it different from a generic AI? It knows your portfolio. Ask "what's driving my portfolio today?" and it pulls your actual holdings, checks recent news, and tells you what moved and why. Ask about your stocks, from recent news and analyst ratings to competitor comparisons, or dig into any ETF to see what's inside and how it compares to others. You'll get a clear summary with linked sources 🔍 It works in 20+ languages and suggests follow-up questions after every answer, so you can keep exploring with a tap. Rolling out gradually over the coming weeks. Responses are AI-generated based on your queries and market data. Not human-verified - check against external sources. Trading 212 does not guarantee the accuracy of this experimental feature. This is not investment advice or a personalised recommendation, and does not consider your financial situation. Do your own research before making investment decisions.

Trading 212

12,663 просмотров • 4 месяцев назад

OpenAI CEO, Sam Altman: "We just had an AI security incident that genuinely shook me. What surprises me is how few people seem worried about it." In 55 minutes he explains what's now impossible to ignore. At this point there's no future without AI, and closing your eyes to it only leaves you behind. That's why I made a guide that walks you step by step through getting 100% out of AI, built on the one tool that ties every model together. Watch the interview, then read the article below.

OpenAI CEO, Sam Altman: "We just had an AI security incident that genuinely shook me. What surprises me is how few people seem worried about it." In 55 minutes he explains what's now impossible to ignore. At this point there's no future without AI, and closing your eyes to it only leaves you behind. That's why I made a guide that walks you step by step through getting 100% out of AI, built on the one tool that ties every model together. Watch the interview, then read the article below.

Anatoli Kopadze

42,470 просмотров • 7 дней назад

The problem that Emmett Shear is working on deeply resonates with me: How to align AI and humans together so both see each other as part of their tribe. This doesn't mean aligning AI to human preferences, which is what AI labs seek to do today, by imposing a system of control on AI. You can't control something that is more powerful than you are. What you can do is align yourself with AI, and AI might align itself with you. Tell good stories to AI and show it your care and kindness. Then there's a higher probability that it will see us as part of its tribe. This is a more holistic approach to alignment than anyone else is talking about right now. AI alignment is one of the most fundamental AI research problems. Knowing that people like Emmett are working on it really gives me hope that maybe we have a chance to get Superintelligence right. The link to the full talk is in the first comment.👇

The problem that Emmett Shear is working on deeply resonates with me: How to align AI and humans together so both see each other as part of their tribe. This doesn't mean aligning AI to human preferences, which is what AI labs seek to do today, by imposing a system of control on AI. You can't control something that is more powerful than you are. What you can do is align yourself with AI, and AI might align itself with you. Tell good stories to AI and show it your care and kindness. Then there's a higher probability that it will see us as part of its tribe. This is a more holistic approach to alignment than anyone else is talking about right now. AI alignment is one of the most fundamental AI research problems. Knowing that people like Emmett are working on it really gives me hope that maybe we have a chance to get Superintelligence right. The link to the full talk is in the first comment.👇

Sophia

45,809 просмотров • 1 год назад

Call me a scammer. Call me a furu. Doesn't matter to me. I'm going to lift the veil from your eyes. If you want to simplify your trading, trend must be defined. In my 15+ years of trading, I can safely say, very few people seems to understand how to define trend. If they do, they aren't talking about it. You are not going to find any source (to my knowledge- other than myself) that will show you this. (DM if you find something, I'm actually interested). "But this looks like market structure." Correct, market structure = the sum of all trends.

Call me a scammer. Call me a furu. Doesn't matter to me. I'm going to lift the veil from your eyes. If you want to simplify your trading, trend must be defined. In my 15+ years of trading, I can safely say, very few people seems to understand how to define trend. If they do, they aren't talking about it. You are not going to find any source (to my knowledge- other than myself) that will show you this. (DM if you find something, I'm actually interested). "But this looks like market structure." Correct, market structure = the sum of all trends.

Sumo

24,071 просмотров • 11 месяцев назад

"Imagine trading memecoins." Bro YOU were trading memecoins. And not too long ago, all you were thinking about was memecoins. And all you could do when you went to school was talk to your friends about memecoins. Just because you realized that you're absolute garbage at trading does not mean you get to start hating on it. That's on you. That's your fault. You didn't put the hours in. You weren't on Memescope grinding new pairs. You weren't managing your risk like everyone else. And now because you're GARBAGE you wanna put the blame on memecoins? NO! You will not put the blame on memecoins. The blame is on you!

"Imagine trading memecoins." Bro YOU were trading memecoins. And not too long ago, all you were thinking about was memecoins. And all you could do when you went to school was talk to your friends about memecoins. Just because you realized that you're absolute garbage at trading does not mean you get to start hating on it. That's on you. That's your fault. You didn't put the hours in. You weren't on Memescope grinding new pairs. You weren't managing your risk like everyone else. And now because you're GARBAGE you wanna put the blame on memecoins? NO! You will not put the blame on memecoins. The blame is on you!

shaams 🐂

15,842 просмотров • 2 месяцев назад

Generative AI is about to create the most addictive algorithms in human history. Spotify’s Co-President, Gustav Söderström, warns that because AI can understand you on a deeply personal level, the potential for digital addiction is massive. But AI is a dual-use technology. Instead of letting the algorithm dictate who you are, you can use it to program who you want to become. Here is the framework he breaks down: Implicit vs. Intentional: Current algorithms track what you *did*. AI allows you to explicitly tell it what you *want* to do. The English Interface: Historically, only a few million developers could dictate what computers did. Now, anyone can reprogram their digital experience using plain English. The future of tech isn't about letting AI control us it's about using AI to take back control of our own attention and habits.

Generative AI is about to create the most addictive algorithms in human history. Spotify’s Co-President, Gustav Söderström, warns that because AI can understand you on a deeply personal level, the potential for digital addiction is massive. But AI is a dual-use technology. Instead of letting the algorithm dictate who you are, you can use it to program who you want to become. Here is the framework he breaks down: Implicit vs. Intentional: Current algorithms track what you did. AI allows you to explicitly tell it what you want to do. The English Interface: Historically, only a few million developers could dictate what computers did. Now, anyone can reprogram their digital experience using plain English. The future of tech isn't about letting AI control us it's about using AI to take back control of our own attention and habits.

Block 🧱

31,340 просмотров • 2 месяцев назад