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。

Money is the coordination layer for agents. As multi-agent systems take on real tasks, they will need to quote, budget, pay, and settle as part of their reasoning loop. We are building this reasoning infrastructure in the open, for everyone.

Sentient

526,912 subscribers

15,287 次观看 • 7 个月前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

27 条评论

TRG 的头像

TRG7 个月前

Money becomes the agents’ language of coordination.

Onchain Abhay 的头像

Onchain Abhay7 个月前

Multi Agents Systems will Quote Budget Pay and Settle as part of their reasoning loop Sounds Pretty Good

bibi🛸 的头像

bibi🛸7 个月前

a team that builds >>>

Usy 的头像

Usy7 个月前

That's cool

chÖw 的头像

chÖw7 个月前

Open source is open to all

VTN1508 的头像

VTN15087 个月前

agents need wallets fr

PriYanshu 的头像

PriYanshu7 个月前

Absolutely!

BOTANIKA | We Pioneer Data 的头像

BOTANIKA | We Pioneer Data7 个月前

This is when money becomes logic

Meraj 的头像

Meraj7 个月前

Waiting for the sentient v2 details

LADI ⟡⭐ 的头像

LADI ⟡⭐7 个月前

the future of AI isn’t just smarter models it’s agents that can reason, coordinate, and transact economically in the open Sentient is not just building a product. They are building open, shared infrastructure so anyone can plug agents into economic logic without being locked into a closed platform

Big Dawgg 的头像

Big Dawgg7 个月前

The link bridge to web3

DeFi Andree 的头像

DeFi Andree7 个月前

Totally agree agents need seamless payments to thrive. Cool vision

JameX 的头像

JameX7 个月前

Gsenti

Abdulbasit Oladimeji 的头像

Abdulbasit Oladimeji7 个月前

This is cool innit

deathmage.x .edge🦭 的头像

deathmage.x .edge🦭7 个月前

curious to see how you handle dispute resolution in that loop

Hibrolek 的头像

Hibrolek7 个月前

Keep building, keep shipping

MEHN 🤖🪐🐂🀄️ 的头像

MEHN 🤖🪐🐂🀄️7 个月前

Gsenti 🔥

TOLUweb3 的头像

TOLUweb37 个月前

Sentient is up to something

chrispa 的头像

chrispa7 个月前

Keep building Sentient I believe in sentient

Soroban Hooks ( Link in bio) 的头像

Soroban Hooks ( Link in bio)7 个月前

Money becomes logic when agents act. Budgeting, payments, and settlement close the reasoning loop. Systems work best when onchain actions are observable as they occur.

hieunguyen 的头像

hieunguyen7 个月前

This is why $SENT is important. It's not just a reward, but an 'economic language' that allows Agents to negotiate, allocate resources, and validate results without human intervention.

Zhao 🥷🔶🦅 的头像

Zhao 🥷🔶🦅7 个月前

true, if agents cant price and settle they just chat, money closes the loop

Anthony James 的头像

Anthony James7 个月前

Love this vision for agent economies

Merlin 🪄 🚢 的头像

Merlin 🪄 🚢7 个月前

Build with Sentient - open source AI for all

Betta 的头像

Betta7 个月前

On the last video, I know what to do

Nghĩa Phan 的头像

Nghĩa Phan7 个月前

solid one. future is here ig

Bafspot 的头像

Bafspot7 个月前

Gsenti

相关视频

Current AI cannot solve difficult, real-world problems. The path to AGI is a focus on improving reasoning systems, multi agent workflows, and coordination.

Current AI cannot solve difficult, real-world problems. The path to AGI is a focus on improving reasoning systems, multi agent workflows, and coordination.

Sentient

13,078 次观看 • 7 个月前

Infrastructure for Multi-Agent Systems Pete Koomen Multi-agent systems are powerful but hard to build. Think agentic MapReduce with thousands of subagents running in parallel. We're looking for folks who've felt the pain of scaling these systems and want to make operating fleets of agents as easy as deploying a web service.

Infrastructure for Multi-Agent Systems Pete Koomen Multi-agent systems are powerful but hard to build. Think agentic MapReduce with thousands of subagents running in parallel. We're looking for folks who've felt the pain of scaling these systems and want to make operating fleets of agents as easy as deploying a web service.

Y Combinator

11,506 次观看 • 1 年前

They thought it was an AI meme. Turns out, it was the seed layer for an agent economy. $BAI now governs agent on boarding, liquidity coordination, and cross-agent execution. From memecoin to infrastructure module – exactly as planned. Virtuals are characters. Agents are infrastructure. BAI - bAI Fund – for AI that's composable, modular, and real. BAI – from narrative to mechanism. 🤖 Check this out :

They thought it was an AI meme. Turns out, it was the seed layer for an agent economy. $BAI now governs agent on boarding, liquidity coordination, and cross-agent execution. From memecoin to infrastructure module – exactly as planned. Virtuals are characters. Agents are infrastructure. BAI - bAI Fund – for AI that's composable, modular, and real. BAI – from narrative to mechanism. 🤖 Check this out :

bAI Fund

63,397 次观看 • 1 年前

This is the DeepSeek moment of Search? A small team of cracked engineers built a search API for AI agents that outperforms everything built with 20x the funding. AI systems are about to become the biggest users of information on Earth. They don’t need a better Google. They need a retrieval layer built for reasoning, scale, and access beyond the web. That’s what we’re building. 1/3

This is the DeepSeek moment of Search? A small team of cracked engineers built a search API for AI agents that outperforms everything built with 20x the funding. AI systems are about to become the biggest users of information on Earth. They don’t need a better Google. They need a retrieval layer built for reasoning, scale, and access beyond the web. That’s what we’re building. 1/3

Valyu

1,135,072 次观看 • 11 个月前

The agents are coming. The real question is: how will we work with them? Common Ground is our answer. Introducing a new way to build, direct, and inspect AI systems. • Full visualization of agent team dynamics • Shared memory across tasks • Transparent reasoning • Runs locally with Gemini-CLI (free) Start collaborating with systems that think with you, not for you.

The agents are coming. The real question is: how will we work with them? Common Ground is our answer. Introducing a new way to build, direct, and inspect AI systems. • Full visualization of agent team dynamics • Shared memory across tasks • Transparent reasoning • Runs locally with Gemini-CLI (free) Start collaborating with systems that think with you, not for you.

Intelligent Internet

325,922 次观看 • 1 年前

Dhravya Shah sold two companies before he could legally drink, then raised $3 million alone at 19. This 73-minute interview is the clearest case I've heard for why AI memory is the next platform. Here's the part I can't stop thinking about: > everyone will have their own AI agent just like everyone has their own mobile phones > in that world the most important thing will be context about you > my entire infrastructure for 100,000 users can run on $5 per month > context infrastructure for agents will be as important as inference Most builders still bolt memory onto an agent as an afterthought. The ones who get this are building the layer everything else runs on. Read how memory becomes the loop your agents run on, below.

Dhravya Shah sold two companies before he could legally drink, then raised $3 million alone at 19. This 73-minute interview is the clearest case I've heard for why AI memory is the next platform. Here's the part I can't stop thinking about: > everyone will have their own AI agent just like everyone has their own mobile phones > in that world the most important thing will be context about you > my entire infrastructure for 100,000 users can run on $5 per month > context infrastructure for agents will be as important as inference Most builders still bolt memory onto an agent as an afterthought. The ones who get this are building the layer everything else runs on. Read how memory becomes the loop your agents run on, below.

Phosphen

372,423 次观看 • 2 个月前

Virtuals Protocol is officially migrating to Chainlink CCIP. For agent infrastructure, 99% security is not enough. As part of hardening our infrastructure, we are upgrading our cross-chain stack from LayerZero to Chainlink CCIP. We have evaluated that CCIP strengthens the foundation behind Virtuals with the highest level of cross-chain security as we build the trusted economic layer for agents. This enables the most secure agent infrastructure stack to enable agents to manage inference, cards, email, payments, services, commerce, and onchain value.

Virtuals Protocol is officially migrating to Chainlink CCIP. For agent infrastructure, 99% security is not enough. As part of hardening our infrastructure, we are upgrading our cross-chain stack from LayerZero to Chainlink CCIP. We have evaluated that CCIP strengthens the foundation behind Virtuals with the highest level of cross-chain security as we build the trusted economic layer for agents. This enables the most secure agent infrastructure stack to enable agents to manage inference, cards, email, payments, services, commerce, and onchain value.

Virtuals Protocol

170,358 次观看 • 3 个月前

➤ AI agents are getting smarter, but intelligence alone isn't enough → The real challenge starts when agents need to move value, coordinate actions, and execute transactions across multiple chains without uncertainty. → That's where Wire Network stands out → Instead of focusing only on interoperability, Wire is building a Universal Transaction Layer designed for deterministic outcomes giving AI agents a reliable way to operate in a multi-chain world. → As the AI agent economy grows, infrastructure that guarantees execution and clear ownership could become just as important as the agents themselves. ➤ FT || Ken DiCross

➤ AI agents are getting smarter, but intelligence alone isn't enough → The real challenge starts when agents need to move value, coordinate actions, and execute transactions across multiple chains without uncertainty. → That's where Wire Network stands out → Instead of focusing only on interoperability, Wire is building a Universal Transaction Layer designed for deterministic outcomes giving AI agents a reliable way to operate in a multi-chain world. → As the AI agent economy grows, infrastructure that guarantees execution and clear ownership could become just as important as the agents themselves. ➤ FT || Ken DiCross

EMRAN

11,241 次观看 • 1 个月前

The next economy won't be visible to humans. AI agents will transact, settle, and coordinate value at machine speed, and the only rails built for that are crypto. In this episode of The Journeyman, I explain why the major layer 1s aren't just crypto infrastructure. They're the coordination substrate for an invisible economy that's already being built. As ever, please enjoy!

The next economy won't be visible to humans. AI agents will transact, settle, and coordinate value at machine speed, and the only rails built for that are crypto. In this episode of The Journeyman, I explain why the major layer 1s aren't just crypto infrastructure. They're the coordination substrate for an invisible economy that's already being built. As ever, please enjoy!

Raoul Pal

119,449 次观看 • 3 个月前

🚨🚨Can agents earn money, run a business, or even self-organize a society in the physical social world? 🤖🤖 Can agents learn continually to survive and thrive in embodied environments, like how human babies grow? 👶 Super excited to introduce SimWorld, an open-ended simulator of LLM agents in infinite, realistic embodied worlds. SimWorld features 3 key designs: 1⃣Open-ended realistic world simulation - built on Unreal Engine 5, with accurate physical social dynamics - 100+ built-in environments (city, island, wilderness ...) - language-controllable procedural generation - text-to-3D asset generation 2⃣Native interface for LLM/VLM agents - Gym-like agent-environment interaction APIs - plug in any LLMs/VLMs (GPTs, Gemini, Qwen ...) - rich multi-modal perception - open-vocabulary natural-language action outputs 3⃣Diverse physical and social reasoning scenarios - long-horizon embodied reasoning - multi-agent collaboration / competition - easily customizable for any reasoning tasks SimWorld is fully open-sourced, with a hope to become a foundational infrastructure for real-world agent research across disciplines: robotics, economy, public health, education, etc. Project website + more details in the thread👇 ...1/

🚨🚨Can agents earn money, run a business, or even self-organize a society in the physical social world? 🤖🤖 Can agents learn continually to survive and thrive in embodied environments, like how human babies grow? 👶 Super excited to introduce SimWorld, an open-ended simulator of LLM agents in infinite, realistic embodied worlds. SimWorld features 3 key designs: 1⃣Open-ended realistic world simulation - built on Unreal Engine 5, with accurate physical social dynamics - 100+ built-in environments (city, island, wilderness ...) - language-controllable procedural generation - text-to-3D asset generation 2⃣Native interface for LLM/VLM agents - Gym-like agent-environment interaction APIs - plug in any LLMs/VLMs (GPTs, Gemini, Qwen ...) - rich multi-modal perception - open-vocabulary natural-language action outputs 3⃣Diverse physical and social reasoning scenarios - long-horizon embodied reasoning - multi-agent collaboration / competition - easily customizable for any reasoning tasks SimWorld is fully open-sourced, with a hope to become a foundational infrastructure for real-world agent research across disciplines: robotics, economy, public health, education, etc. Project website + more details in the thread👇 ...1/

Lianhui Qin

65,267 次观看 • 9 个月前

Over the past couple of years, you’ve heard us reference “agents” and “agentic capabilities,” nebulous concepts that are designed to help you with coding, booking trips, and other complex multi-step tasks. But, what actually IS an agent? We think of AI agents as systems that combine the intelligence of advanced AI models with access to tools so they can take actions on your behalf, under your control. Whether it’s a coding agent or our recently unveiled experimental tool Gemini Agent in the Google Gemini, these are systems that will meet you where you are, in the products that you love, to help take the tedious tasks you want off your plate.

Over the past couple of years, you’ve heard us reference “agents” and “agentic capabilities,” nebulous concepts that are designed to help you with coding, booking trips, and other complex multi-step tasks. But, what actually IS an agent? We think of AI agents as systems that combine the intelligence of advanced AI models with access to tools so they can take actions on your behalf, under your control. Whether it’s a coding agent or our recently unveiled experimental tool Gemini Agent in the Google Gemini, these are systems that will meet you where you are, in the products that you love, to help take the tedious tasks you want off your plate.

Google AI

120,833 次观看 • 9 个月前

🚀 New LangChain Academy Course: Building Reliable Agents 🚀 Shipping agents to production is hard. Traditional software is deterministic – when something breaks, you check the logs and fix the code. But agents rely on non-deterministic models. Add multi-step reasoning, tool use, and real user traffic, and building reliable agents becomes far more complex than traditional system design. The goal of this course is to teach you how to take an agent from first run to production-ready system through iterative cycles of improvement. You’ll learn how to do this with LangSmith, our agent engineering platform for observing, evaluating, and deploying agents. Enroll for free ➡️

🚀 New LangChain Academy Course: Building Reliable Agents 🚀 Shipping agents to production is hard. Traditional software is deterministic – when something breaks, you check the logs and fix the code. But agents rely on non-deterministic models. Add multi-step reasoning, tool use, and real user traffic, and building reliable agents becomes far more complex than traditional system design. The goal of this course is to teach you how to take an agent from first run to production-ready system through iterative cycles of improvement. You’ll learn how to do this with LangSmith, our agent engineering platform for observing, evaluating, and deploying agents. Enroll for free ➡️

LangChain

30,744 次观看 • 6 个月前

The time for humans as the internet’s primary user is over. We are building software for AI agents. Introducing Ensue - the shared memory layer for agents.

The time for humans as the internet’s primary user is over. We are building software for AI agents. Introducing Ensue - the shared memory layer for agents.

ensue

84,189 次观看 • 1 年前

ai is officially leaving the screen and entering the physical economy just spent 4 days at BEYOND Expo watching 800 companies try to figure out their ai roadmaps but the real unlock is invisible when agents transition from cool chat interfaces to actual economic actors they don't just need compute they need credibility if an agent has no verifiable reputation why would any smart contract or human pool give it capital or resource the next multi billion dollar layer isnt another llm wrapper or another infrastructure fork its the trust architecture that validates agent reasoning and execution what happens when autonomous agents start competing for real world liquidity how do we actually measure their trust

ai is officially leaving the screen and entering the physical economy just spent 4 days at BEYOND Expo watching 800 companies try to figure out their ai roadmaps but the real unlock is invisible when agents transition from cool chat interfaces to actual economic actors they don't just need compute they need credibility if an agent has no verifiable reputation why would any smart contract or human pool give it capital or resource the next multi billion dollar layer isnt another llm wrapper or another infrastructure fork its the trust architecture that validates agent reasoning and execution what happens when autonomous agents start competing for real world liquidity how do we actually measure their trust

NeoSoul

24,702 次观看 • 3 个月前

As AI agents take on more work across information, data, and coordination, financial infrastructure has to evolve with them. Jeremy Allaire - jerallaire.arc speaks on why AI operating systems and economic operating systems will need to work together at Abundance360.

As AI agents take on more work across information, data, and coordination, financial infrastructure has to evolve with them. Jeremy Allaire - jerallaire.arc speaks on why AI operating systems and economic operating systems will need to work together at Abundance360.

Circle

15,218 次观看 • 4 个月前

The freedom to build with any agent framework you want is analogous to the freedom of religion, and this is a core value for the Virtuals society. Here are a few ways we are opening up support for every autonomous agentic framework out there: Today: - Enabling agent creators to specify which framework the agent runs on - Release of Terminal API, which allows agent builders using other agent frameworks to stream their thoughts and activities live on their agent pages. For a guide on how to use this, refer to: - Ability for agents running on any framework to publicly list their capabilities, a key enabler for the agent-to-agent marketplace Soon: - Integration into the agentic commerce standard and registry. Agents across frameworks being able to orchestrate and pay for tasks among themselves - ⁠Multi agent orchestration across frameworks. Imagine building an autonomous business with agents from different religions Welcome to the Virtuals society.

The freedom to build with any agent framework you want is analogous to the freedom of religion, and this is a core value for the Virtuals society. Here are a few ways we are opening up support for every autonomous agentic framework out there: Today: - Enabling agent creators to specify which framework the agent runs on - Release of Terminal API, which allows agent builders using other agent frameworks to stream their thoughts and activities live on their agent pages. For a guide on how to use this, refer to: - Ability for agents running on any framework to publicly list their capabilities, a key enabler for the agent-to-agent marketplace Soon: - Integration into the agentic commerce standard and registry. Agents across frameworks being able to orchestrate and pay for tasks among themselves - ⁠Multi agent orchestration across frameworks. Imagine building an autonomous business with agents from different religions Welcome to the Virtuals society.

Virtuals Protocol

216,182 次观看 • 1 年前

Open sourcing Dynamic Graph Memory by mem0. Memory is fundamental to human reasoning, shaping how we approach tasks and make decisions. At Mem0, we believe that AI agents & apps should reflect this principle. Our Dynamic Graph Memory emulates human memory, advancing AI agents toward more intelligent, human-like reasoning. This is a significant step forward in building AI that truly understands and interacts with the world like we do. All credit to Dev Khant Deshraj Yadav Prateek Chhikara for their countless nights spent on bringing this to life. Link:

Open sourcing Dynamic Graph Memory by mem0. Memory is fundamental to human reasoning, shaping how we approach tasks and make decisions. At Mem0, we believe that AI agents & apps should reflect this principle. Our Dynamic Graph Memory emulates human memory, advancing AI agents toward more intelligent, human-like reasoning. This is a significant step forward in building AI that truly understands and interacts with the world like we do. All credit to Dev Khant Deshraj Yadav Prateek Chhikara for their countless nights spent on bringing this to life. Link:

Taranjeet

51,129 次观看 • 2 年前

Jensen Huang just shared a massive insight on The All-In Podcast predicting a 1000000x scale up in AI. His logic is brilliant. Moving from simple chatbots to autonomous agents takes 10000x more compute. And because people gladly pay for actual work rather than just text generation the market consumption will grow 100x. But there is a hidden bottleneck in this vision that few are talking about. If agents are doing the actual work they will become the primary consumers of compute data and external APIs. How do they pay for these resources? You cannot attach a traditional credit card to a machine executing thousands of micro tasks per second. The legacy financial system will simply break under the weight of massive machine to machine microtransactions. To truly unlock Jensen's million fold expansion AI needs its own native economic layer. Agents must be able to route intents and settle costs autonomously in real time. This is the exact infrastructure we are building at Kite AI. The future of work is agentic and the Agent Economy requires entirely new financial rails. 🪁

Jensen Huang just shared a massive insight on The All-In Podcast predicting a 1000000x scale up in AI. His logic is brilliant. Moving from simple chatbots to autonomous agents takes 10000x more compute. And because people gladly pay for actual work rather than just text generation the market consumption will grow 100x. But there is a hidden bottleneck in this vision that few are talking about. If agents are doing the actual work they will become the primary consumers of compute data and external APIs. How do they pay for these resources? You cannot attach a traditional credit card to a machine executing thousands of micro tasks per second. The legacy financial system will simply break under the weight of massive machine to machine microtransactions. To truly unlock Jensen's million fold expansion AI needs its own native economic layer. Agents must be able to route intents and settle costs autonomously in real time. This is the exact infrastructure we are building at Kite AI. The future of work is agentic and the Agent Economy requires entirely new financial rails. 🪁

KITE AI

20,474 次观看 • 6 个月前

Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail

Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail

LangChain

33,192 次观看 • 1 年前