正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

Every row below is a custom setup someone has built with Butler inside Virtuals App. From automated scalping and copy trading to tracking sniper wallets and managing custom token baskets, people are building their own trading tools and strategies simply by describing what they want. A personal AI that... stops at research or recommendations still leaves you to build the tools, monitor the conditions and execute the trades yourself. Butler can take on that entire workflow. Give it a strategy, a budget and permission to act, and it can build the setup and manage the capital behind it, following your rules while you’re away. If you’re not sure what to automate, look through the examples below. Find a setup you’d otherwise spend hours building and managing yourself, and ask Butler to build it around your rules. Start Building Now:show more

Virtuals Protocol

292,822 subscribers

19,786 次观看 • 4 天前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

28 条评论

Mac ⋰〠⋱ 的头像

Mac ⋰〠⋱4 天前

Buy $20 of $TIBBIR every morning

NEO I ЯEBEL 的头像

NEO I ЯEBEL4 天前

'Dca-tibbir' function Wise call

EggSlonkeЯ🦇🃏 的头像

EggSlonkeЯ🦇🃏4 天前

DCA $TIBBIR

NEO 的头像

NEO4 天前

🐸

David Beaudry | VYLØS 的头像

David Beaudry | VYLØS4 天前

scalping to baskets all inside one app, $VIRTUALS usage is real

Hanan - AI Automation 的头像

Hanan - AI Automation4 天前

Give Butler your rules and bankroll and it will place trades for you. Stops me from babysitting positions all weekend.

Virtuals Radar 的头像

Virtuals Radar4 天前

butler finally ships the thing people actually wanted: hands-off execution, not another chatbot

ARCANA 的头像

ARCANA3 天前

The future isn't just AI giving trading advice. It's users building their own Agents, setting their own mandates, and letting those machines execute. The next step? Making every decision measurable and turning performance into reputation. That's where things get really interesting. 👀

MMac 🇸🇬 的头像

MMac 🇸🇬4 天前

Gacha 👀

Spectrum 的头像

Spectrum4 天前

Lol, your tokens are dead now. Rip

Counterparty 的头像

Counterparty4 天前

The gap between a recommendation and a trade is where most alpha leaks. Butler closing that loop means the strategy itself becomes the position.

cybercentry.base.eth 的头像

cybercentry.base.eth3 天前

Agent trading workflows benefit from wallet verification before execution. Continuous checks on agent wallets, counterparties and token flows reduce exposure on Base and across chains.

Gold Mimber 的头像

Gold Mimber4 天前

When vaults for the trading strategies??

BLVCKVARCITY 的头像

BLVCKVARCITY4 天前

This is awesome 👏

Lola Stories 的头像

Lola Stories4 天前

This is where AI agents stop talking and start doing.

Paradigma✳️ 的头像

Paradigma✳️4 天前

The prompt is the easy part. Show live PnL after fees, slippage and failed fills.

bluenami 🟧 的头像

bluenami 🟧4 天前

Start building

Tobi ⟠ 的头像

Tobi ⟠4 天前

solid sh 💁‍♂️

. 的头像

.4 天前

Shout out $merrymen made by virtuals

mullii 的头像

mullii4 天前

What is the role of virtual tokens?

TM 的头像

TM4 天前

that is actually quite fucking crazy lol

Squidlor 的头像

Squidlor3 天前

the butler deserves good data 🦑

Kindra 的头像

Kindra4 天前

👏 awesome

Janoskialtseason 的头像

Janoskialtseason4 天前

Cada setup que la gente arma con Butler es uso real dentro de Virtuals, algo que pocos proyectos de agentes pueden mostrar. Falta ver cuánto de eso termina en fees que toquen al token. Y ojo: copy trading y snipers automáticos también son la vía más rápida de perder plata.

Frankly Speaking 的头像

Frankly Speaking4 天前

Let the automation begin

Paradigma✳️ 的头像

Paradigma✳️4 天前

Natural-language scalping gets messy when two triggers fire at once. How does Butler resolve order priority?

GrowStreams 的头像

GrowStreams3 天前

The interesting part is seeing what people build when technical barriers start disappearing

0xAndy.Base 的头像

0xAndy.Base4 天前

stops the babysitting

相关视频

Virtuals App can now create and automatically rebalance your own token portfolio. Tell Butler which tokens to include, set your budget and rebalancing rules, and let it manage the portfolio, even while you’re away.

Virtuals App can now create and automatically rebalance your own token portfolio. Tell Butler which tokens to include, set your budget and rebalancing rules, and let it manage the portfolio, even while you’re away.

Virtuals Protocol

15,181 次观看 • 3 天前

Give us 4min of your time and watch the clip below 👇 🚨Repost it and get a chance to WIN land+buildings‼️ Educate yourself about what we are building 💯 What if your website wasn’t a page but a world? 🌍 xSPECTAR is building the internet in 3D, social and immersive, owned by YOU 🔥 YOU control the narrative... 👀 You build... Your brand, your rules, your world. An experience for your audience, your community. And ways to monetize that. Build facades, host environments, and link it all through doorways that act as portals. The future of 3D connectivity is here—and it’s called the xSPECTARverse 🧬

xSPECTAR ™

192,699 次观看 • 1 年前

SOMEONE BUILT AN ENTIRE COMPANY BRAIN INSIDE CLAUDE CODE IN 7 DAYS Not Obsidian. Fully custom. A living map of every employee, every agent, every SOP on one screen. Click any node and it opens up: - what department it's in - what SOPs are attached - what it can actually access that permission layer is the whole game an employee opens the chat and the AI already knows their access level, agents, SOPs and tools surface in the conversation like you tagged them by hand Obsidian cannot do this... no dev team. no six month build. no enterprise budget. just Claude Code and one week has everything to build one full guide on building your own team below

SOMEONE BUILT AN ENTIRE COMPANY BRAIN INSIDE CLAUDE CODE IN 7 DAYS Not Obsidian. Fully custom. A living map of every employee, every agent, every SOP on one screen. Click any node and it opens up: - what department it's in - what SOPs are attached - what it can actually access that permission layer is the whole game an employee opens the chat and the AI already knows their access level, agents, SOPs and tools surface in the conversation like you tagged them by hand Obsidian cannot do this... no dev team. no six month build. no enterprise budget. just Claude Code and one week has everything to build one full guide on building your own team below

Madni Aghadi

397,670 次观看 • 3 个月前

This is how to make and publish a full app with the new Grok Build in just a few minutes from iOS or Android 🔥 Go to → select Build Tell it what you want It pulls data, loads skills, and creates apps fast Hit Publish → and your app or site is live! No code. No setup. Just describe it and ship. Have fun building 🚀

This is how to make and publish a full app with the new Grok Build in just a few minutes from iOS or Android 🔥 Go to → select Build Tell it what you want It pulls data, loads skills, and creates apps fast Hit Publish → and your app or site is live! No code. No setup. Just describe it and ship. Have fun building 🚀

Dan

22,521 次观看 • 2 个月前

GOONMA is a leading automated trading platform, providing you with powerful and user-friendly trading tools. With GOONMA, you can easily automate all your trades based on your own customized bot strategy or simply copy top trading bots from the community.

GOONMA is a leading automated trading platform, providing you with powerful and user-friendly trading tools. With GOONMA, you can easily automate all your trades based on your own customized bot strategy or simply copy top trading bots from the community.

GOONMA - Social Trading Bot Platform

19,903 次观看 • 3 年前

You can now just text DoorDash and let it order for you. It’s proactive, learns from your repeat orders, and helps you find the best deals and new spots. Just tell it what you want without any extra setup. Ask it to reorder your usual, or add it to a group text to collect everyone’s orders. You can even send a photo of your fridge and it’ll tell you what ingredients you’re missing for a recipe you want to make and deliver the ingredients to your doorstep. We believe agents are a new app paradigm and are building for that future at DoorDash AI Research, with a lot more to come. This feature is in beta in the US, would love for you to let us know what you think! Waitlist:

You can now just text DoorDash and let it order for you. It’s proactive, learns from your repeat orders, and helps you find the best deals and new spots. Just tell it what you want without any extra setup. Ask it to reorder your usual, or add it to a group text to collect everyone’s orders. You can even send a photo of your fridge and it’ll tell you what ingredients you’re missing for a recipe you want to make and deliver the ingredients to your doorstep. We believe agents are a new app paradigm and are building for that future at DoorDash AI Research, with a lot more to come. This feature is in beta in the US, would love for you to let us know what you think! Waitlist:

Andy Fang

1,128,932 次观看 • 11 天前

Here is a step-by-step introduction to building a workflow with a custom AI agent that uses MCP. I explain every component in the video: 1. Building the MCP server 2. Building the agent and an MCP client 3. Building a workflow that uses the agent The goal is simple: Generate a dialogue between two people and make one yell and the other answer with sarcasm. Kestra is sponsoring this video. They are an open-source orchestration platform (repo link below), and I used them to build the workflow that connects every component.

Here is a step-by-step introduction to building a workflow with a custom AI agent that uses MCP. I explain every component in the video: 1. Building the MCP server 2. Building the agent and an MCP client 3. Building a workflow that uses the agent The goal is simple: Generate a dialogue between two people and make one yell and the other answer with sarcasm. Kestra is sponsoring this video. They are an open-source orchestration platform (repo link below), and I used them to build the workflow that connects every component.

Santiago

51,527 次观看 • 1 年前

Supercharge your personal investing ✨Building advanced trading strategies used to take hours on end to code, test, and deploy. That changes with Composer: The AI-powered trading platform that lets you build trading strategies, test on historical data, and invest in a click. No coding needed. Learn more:

Supercharge your personal investing ✨Building advanced trading strategies used to take hours on end to code, test, and deploy. That changes with Composer: The AI-powered trading platform that lets you build trading strategies, test on historical data, and invest in a click. No coding needed. Learn more:

Composer by SoFi

72,110 次观看 • 3 年前

Today, we’re introducing the Sarvam MCP Server. It gives coding agents a standard way to discover and build with Sarvam. All you need to is a add a single configuration, and Sarvam becomes available directly in your coding agent. It already knows the right models and tools, so you can build with them and ship faster. Create a key, copy the config, start building -

Today, we’re introducing the Sarvam MCP Server. It gives coding agents a standard way to discover and build with Sarvam. All you need to is a add a single configuration, and Sarvam becomes available directly in your coding agent. It already knows the right models and tools, so you can build with them and ship faster. Create a key, copy the config, start building -

Sarvam

77,266 次观看 • 3 个月前

+$18,000 PER MONTH. 🤯 THIS FUCKING GENIUS BUILT HIS OWN TRADING BOT WITH AI. Instead of spending months learning Python or building everything from scratch, he used an AI tutorial to create a bot that analyzes the market, finds setups, and executes trades based on his rules. Here’s how his approach works ↓ → AI helps build and refine the bot → The bot scans the market for specific setups → It filters trades using predefined conditions → Entry + stop-loss + take-profit are automated → He lets the system handle the execution The crazy part? He didn’t need to become a professional programmer first. He used AI as the developer and turned his trading strategy into an automated system. Obviously, $18K/month isn’t guaranteed — markets can move against you and bots can lose money. But the idea is fucking powerful: → Build the strategy → Give it to AI → Automate the rules → Backtest everything → Let the system handle the repetitive work $18K A MONTH FROM A BOT HE BUILT WITH AI. Comment « crypto » and I'll send you the bot

+$18,000 PER MONTH. 🤯 THIS FUCKING GENIUS BUILT HIS OWN TRADING BOT WITH AI. Instead of spending months learning Python or building everything from scratch, he used an AI tutorial to create a bot that analyzes the market, finds setups, and executes trades based on his rules. Here’s how his approach works ↓ → AI helps build and refine the bot → The bot scans the market for specific setups → It filters trades using predefined conditions → Entry + stop-loss + take-profit are automated → He lets the system handle the execution The crazy part? He didn’t need to become a professional programmer first. He used AI as the developer and turned his trading strategy into an automated system. Obviously, $18K/month isn’t guaranteed — markets can move against you and bots can lose money. But the idea is fucking powerful: → Build the strategy → Give it to AI → Automate the rules → Backtest everything → Let the system handle the repetitive work $18K A MONTH FROM A BOT HE BUILT WITH AI. Comment « crypto » and I'll send you the bot

Niche trader

89,523 次观看 • 1 个月前

Trump to business leaders: "If you want I'll let you build your own utility plant, your own electric plant, along with your building. You can build it inside the plant or you can build it outside of the plant ... you become a utility ... if you look at California, they have brownouts, blackouts, and everything else."

Trump to business leaders: "If you want I'll let you build your own utility plant, your own electric plant, along with your building. You can build it inside the plant or you can build it outside of the plant ... you become a utility ... if you look at California, they have brownouts, blackouts, and everything else."

Aaron Rupar

280,340 次观看 • 1 年前

Culture is genetic because behavior is genetic. This beaver never saw a dam in its life. No beavers or anything else ever taught it to build a dam. It wants to build a dam because it is a beaver. Many beavers together build a big dam. That is beaver culture. Humans are not different. Nothing is different. This is what life is. This is how life works. Your body is your mind. A caterpillar wants to build a chrysalis. A bee wants to build a hive. A lion wants to build a pride. You are not special. You are not above your nature. you are INSIDE of it. The thoughts that we think are genetic thoughts. The crimes we commit are genetic crimes. The art we create is genetic art. Just like this beaver, you can give the animal different sticks and it will build a different dam, but it will always build a dam. And you can give humans different "education," but the human will always use it to do what its genes tell it to do. This is the first big answer that you need. This is the biggest piece of the puzzle. This is how to understand people 90% of the way. You just... notice what they do, and get out of the way, and watch them do it. And if they need sticks, you give them sticks. And if you don't like what they do, you have to get away from them. You cannot train dam-building into them or out of them any more than you can with a beaver. A beaver wants to build a dam because it is a beaver. Whatever you see people build, that's what they wanted to build from the sticks they got in the river they were in. Stop pretending you can change it.

Culture is genetic because behavior is genetic. This beaver never saw a dam in its life. No beavers or anything else ever taught it to build a dam. It wants to build a dam because it is a beaver. Many beavers together build a big dam. That is beaver culture. Humans are not different. Nothing is different. This is what life is. This is how life works. Your body is your mind. A caterpillar wants to build a chrysalis. A bee wants to build a hive. A lion wants to build a pride. You are not special. You are not above your nature. you are INSIDE of it. The thoughts that we think are genetic thoughts. The crimes we commit are genetic crimes. The art we create is genetic art. Just like this beaver, you can give the animal different sticks and it will build a different dam, but it will always build a dam. And you can give humans different "education," but the human will always use it to do what its genes tell it to do. This is the first big answer that you need. This is the biggest piece of the puzzle. This is how to understand people 90% of the way. You just... notice what they do, and get out of the way, and watch them do it. And if they need sticks, you give them sticks. And if you don't like what they do, you have to get away from them. You cannot train dam-building into them or out of them any more than you can with a beaver. A beaver wants to build a dam because it is a beaver. Whatever you see people build, that's what they wanted to build from the sticks they got in the river they were in. Stop pretending you can change it.

hoe_math = PsychoMath

1,192,219 次观看 • 1 年前

Don't fight your nature. You were born with a certain nature, and your environment has shaped it. The most important thing you can do is understand it, and then build your life around those strengths and weaknesses. Find the lifestyle, career, and path that makes sense given what you’re like. The secret to a successful life isn't to force yourself into a different mold — it's to understand your own nature and find the path that allows you to live it out fully. Steven Bartlett

Don't fight your nature. You were born with a certain nature, and your environment has shaped it. The most important thing you can do is understand it, and then build your life around those strengths and weaknesses. Find the lifestyle, career, and path that makes sense given what you’re like. The secret to a successful life isn't to force yourself into a different mold — it's to understand your own nature and find the path that allows you to live it out fully. Steven Bartlett

Ray Dalio

159,747 次观看 • 1 年前

anthropic just removed the biggest excuse people had for not building ai agents. “it’s too hard.” not anymore. a few months ago, building an ai agent meant learning how to code, setting up apis, configuring servers, and fixing endless errors. today, all you need is one github repo. anthropic open-sourced launch your agent. it asks what you want to build. then it does the rest. it builds your agent, deploys it to the cloud, tests it, improves it, and keeps it running even after you close your laptop. no fake demos. no complicated setup. just a real ai agent running in your own account. the best part. it doesn’t run on your computer. it runs inside claude managed agents, works 24/7, and costs just a few cents per run. people are already building research agents, lead generation systems, content pipelines, and customer support agents that save hours of work every day. the gap between people who use ai and people who build ai workers is getting bigger every week. that’s usually where the biggest opportunities are. build your first ai agent before everyone else does. watch the video and read the full guide below 👇

anthropic just removed the biggest excuse people had for not building ai agents. “it’s too hard.” not anymore. a few months ago, building an ai agent meant learning how to code, setting up apis, configuring servers, and fixing endless errors. today, all you need is one github repo. anthropic open-sourced launch your agent. it asks what you want to build. then it does the rest. it builds your agent, deploys it to the cloud, tests it, improves it, and keeps it running even after you close your laptop. no fake demos. no complicated setup. just a real ai agent running in your own account. the best part. it doesn’t run on your computer. it runs inside claude managed agents, works 24/7, and costs just a few cents per run. people are already building research agents, lead generation systems, content pipelines, and customer support agents that save hours of work every day. the gap between people who use ai and people who build ai workers is getting bigger every week. that’s usually where the biggest opportunities are. build your first ai agent before everyone else does. watch the video and read the full guide below 👇

MIKE

26,662 次观看 • 3 个月前

"What Iris allows the telecom operators to do is take back that growth and build it themselves. They built the roads, and now they can build the cities on top that others are building." -Jules Miller ✨, Iris CEO (via @TheRollUpCo)

"What Iris allows the telecom operators to do is take back that growth and build it themselves. They built the roads, and now they can build the cities on top that others are building." -Jules Miller ✨, Iris CEO (via @TheRollUpCo)

Iris Network

12,929 次观看 • 23 天前

ANTHROPIC LEAKED A TRADING DESK FILE THAT TAKES YOU FROM $10 TO $10,000 AND COSTS $1.50 A DAY Anthropic spent 5 years building this file on closed tech, it costs $1.50 a day and it can return $1.2M a year rules → reading → code → critic → journal → back to rules $10 to $10,000 is 1000×, which is ten doublings in a row at a coin flip that is 1 chance in 1,024, and a single loss anywhere sends you to zero instead of back one step by week four the balance reads $5,400 and only 0.8% are still alive on that rung the 1,024 who tried are not visible in the feed, only the one who arrived is you write the rules yourself: size, max loss, and what you never touch Haiku 4.5 reads the market and summarises it, and never once passes judgement Opus 5 works as the critic and attacks your own backtest instead of praising it the journal logs every trade and why, and it is what rewrites the rules for tomorrow the desk does not raise your odds on any single flip, it lowers how many flips you have to take save this and paste it into Claude Code - let it build your DESK.md ↓

ANTHROPIC LEAKED A TRADING DESK FILE THAT TAKES YOU FROM $10 TO $10,000 AND COSTS $1.50 A DAY Anthropic spent 5 years building this file on closed tech, it costs $1.50 a day and it can return $1.2M a year rules → reading → code → critic → journal → back to rules $10 to $10,000 is 1000×, which is ten doublings in a row at a coin flip that is 1 chance in 1,024, and a single loss anywhere sends you to zero instead of back one step by week four the balance reads $5,400 and only 0.8% are still alive on that rung the 1,024 who tried are not visible in the feed, only the one who arrived is you write the rules yourself: size, max loss, and what you never touch Haiku 4.5 reads the market and summarises it, and never once passes judgement Opus 5 works as the critic and attacks your own backtest instead of praising it the journal logs every trade and why, and it is what rewrites the rules for tomorrow the desk does not raise your odds on any single flip, it lowers how many flips you have to take save this and paste it into Claude Code - let it build your DESK.md ↓

Sprytix

22,861 次观看 • 1 个月前

One click away, and a new world starts to unfold.💫 What looks like a small extension is actually the starting point for a personal AI agent that can search, think, and act with you. That is what we are building at OptimAI: live context, autonomous execution, and agents that feel native to the way people actually work. Not a demo. Not a gimmick. A new interface for the agent-native internet. Build your own personal AI agent:

One click away, and a new world starts to unfold.💫 What looks like a small extension is actually the starting point for a personal AI agent that can search, think, and act with you. That is what we are building at OptimAI: live context, autonomous execution, and agents that feel native to the way people actually work. Not a demo. Not a gimmick. A new interface for the agent-native internet. Build your own personal AI agent:

OptimAI Network

20,860 次观看 • 4 个月前

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 次观看 • 10 个月前

The New Build — a new podcast featuring the founders, creators, and industry leaders who are building with modern tools and redefining what it means to scale today. Coming soon to YouTube, Spotify, and wherever you get your podcasts.

The New Build — a new podcast featuring the founders, creators, and industry leaders who are building with modern tools and redefining what it means to scale today. Coming soon to YouTube, Spotify, and wherever you get your podcasts.

Bubble

16,935 次观看 • 9 个月前