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Devconnnect Whiteboarding Session 🇦🇷 | EP # 1 New whiteboard deep dive with nader dabit featuring Nathan Vandy & Med Amine ID from bond.credit, and it’s one of the most exciting looks yet at the emerging agentic economy. Bond Credit is building the credit layer for autonomous agents, complete...

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EigenCloud

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✨ New look: The agentic era is here! As this era unfolds, agents will observe, decide, transact, and execute tasks with real value on the line. The next generation of apps and agents will require trust built in. That’s why we’re building EigenCloud, a verifiable cloud for the agentic economy.
1:09

✨ New look: The agentic era is here! As this era unfolds, agents will observe, decide, transact, and execute tasks with real value on the line. The next generation of apps and agents will require trust built in. That’s why we’re building EigenCloud, a verifiable cloud for the agentic economy.

EigenCloud

41,437 Aufrufe • vor 5 Monaten

Verifiable AI is the next frontier. At moved to x.com/ns Conference, Sreeram Kannan unveiled the next evolution of AI x Crypto. ☁️ EigenCloud: The Verifiable AI Cloud ☁️ Crypto gave us digital property, programmable money, and trustless execution. But it wasn’t built to run AI. EigenCloud changes that. Billions in verifiable compute. $20B staked in ETH and EIGEN. 100s of operators. The fastest-growing developer ecosystem in crypto. Now, for the first time, you can run any compute offchain, and bring the results verifiably onchain. 🔥 Smart contracts that think 🔥 Agents that trade 🔥 AI that can own, earn, and act onchain This is how we go from protocols → to platforms → to sovereign agents. Bitcoin scaled money. Ethereum scaled logic. Solana scaled throughput. EigenCloud scales verifiable intelligence. From agentic finance to verifiable social, from onchain games to autonomous governance, the next era of crypto isn’t just programmable. It’s intelligent. ☁️ Build Verifiable AI ☁️ Build on EigenCloud 0:07 Introduction 0:16 EigenCloud by Numbers 0:55 Build Unstoppable Verifiable Agents and Apps 1:34 Run Compute Offchain Verifiably Onchain 2:08 AWS for Crypto 3:03 Application: Agentic Finance 3:42 Application: Gaming Tournaments 4:11 Application: Social Media 4:35 Application: Agentic Governance 4:49 Application: Sovereign Agents Learn more ⬇️ 🧵
5:10

Verifiable AI is the next frontier. At moved to x.com/ns Conference, Sreeram Kannan unveiled the next evolution of AI x Crypto. ☁️ EigenCloud: The Verifiable AI Cloud ☁️ Crypto gave us digital property, programmable money, and trustless execution. But it wasn’t built to run AI. EigenCloud changes that. Billions in verifiable compute. $20B staked in ETH and EIGEN. 100s of operators. The fastest-growing developer ecosystem in crypto. Now, for the first time, you can run any compute offchain, and bring the results verifiably onchain. 🔥 Smart contracts that think 🔥 Agents that trade 🔥 AI that can own, earn, and act onchain This is how we go from protocols → to platforms → to sovereign agents. Bitcoin scaled money. Ethereum scaled logic. Solana scaled throughput. EigenCloud scales verifiable intelligence. From agentic finance to verifiable social, from onchain games to autonomous governance, the next era of crypto isn’t just programmable. It’s intelligent. ☁️ Build Verifiable AI ☁️ Build on EigenCloud 0:07 Introduction 0:16 EigenCloud by Numbers 0:55 Build Unstoppable Verifiable Agents and Apps 1:34 Run Compute Offchain Verifiably Onchain 2:08 AWS for Crypto 3:03 Application: Agentic Finance 3:42 Application: Gaming Tournaments 4:11 Application: Social Media 4:35 Application: Agentic Governance 4:49 Application: Sovereign Agents Learn more ⬇️ 🧵

EigenCloud

97,862 Aufrufe • vor 9 Monaten

Verifiable AI is crypto’s true product–market fit. At DAS London by , our Chief Growth Officer, JT Rose shared a vision 10 years in the making. ☁️ EigenCloud: Ethereum’s Verifiable AI Cloud ☁️ Bitcoin gave us verifiable money. Ethereum gave us verifiable logic. Now, EigenCloud gives us verifiable intelligence. $20B in restaked assets. Hundreds of global operators, from Google to Coinbase 🛡️. The fastest-growing developer ecosystem in crypto. For the first time, you can run any compute offchain, and bring the results verifiably onchain. 🔥 Agents that trade verifiably 🔥 AI that earns, acts, and proves itself 🔥 Apps that can’t rug their users This is how we unlock the apps Ethereum was meant for from DeFi to AI to the agentic internet. The next growth driver for crypto isn’t just DeFi. It’s Verifiable AI. And it’s being built on EigenCloud and Ethereum. ☁️ Build trust ☁️ Build verifiable AI ☁️ Build on EigenCloud Timestamps: 0:06 Introduction 0:22 Who is EigenCloud 1:44 Scaling Verifiable Compute 3:02 Trillion Dollar TAM for Ethereum 5:19 Run any Compute Verifiably with EigenCloud 6:41 Programmability x Verifiability 7:10 Hyperscale Cloud vs Verifiable Cloud 8:29 Agentic Trading 9:52 Verifiable Agent to Agent Payments 11:00 Verifiable Agents 11:48 Agentic Gaming 12:36 Possibilities with Verifiable AI Cloud 14:14 Explosion of Interest from Builders 15:01 Golden Age of Innovation with Crypto x AI All slides ⬇️ 🧵
15:37

Verifiable AI is crypto’s true product–market fit. At DAS London by , our Chief Growth Officer, JT Rose shared a vision 10 years in the making. ☁️ EigenCloud: Ethereum’s Verifiable AI Cloud ☁️ Bitcoin gave us verifiable money. Ethereum gave us verifiable logic. Now, EigenCloud gives us verifiable intelligence. $20B in restaked assets. Hundreds of global operators, from Google to Coinbase 🛡️. The fastest-growing developer ecosystem in crypto. For the first time, you can run any compute offchain, and bring the results verifiably onchain. 🔥 Agents that trade verifiably 🔥 AI that earns, acts, and proves itself 🔥 Apps that can’t rug their users This is how we unlock the apps Ethereum was meant for from DeFi to AI to the agentic internet. The next growth driver for crypto isn’t just DeFi. It’s Verifiable AI. And it’s being built on EigenCloud and Ethereum. ☁️ Build trust ☁️ Build verifiable AI ☁️ Build on EigenCloud Timestamps: 0:06 Introduction 0:22 Who is EigenCloud 1:44 Scaling Verifiable Compute 3:02 Trillion Dollar TAM for Ethereum 5:19 Run any Compute Verifiably with EigenCloud 6:41 Programmability x Verifiability 7:10 Hyperscale Cloud vs Verifiable Cloud 8:29 Agentic Trading 9:52 Verifiable Agent to Agent Payments 11:00 Verifiable Agents 11:48 Agentic Gaming 12:36 Possibilities with Verifiable AI Cloud 14:14 Explosion of Interest from Builders 15:01 Golden Age of Innovation with Crypto x AI All slides ⬇️ 🧵

EigenCloud

88,278 Aufrufe • vor 9 Monaten

What does Verifiable AI mean? Turning “trust me” outputs into cryptographic proof, so agents can manage money, sign agreements and act with guarantees. 🎥 nader dabit breaks it down in less than 3 mins and shows how to start building ⬇️
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What does Verifiable AI mean? Turning “trust me” outputs into cryptographic proof, so agents can manage money, sign agreements and act with guarantees. 🎥 nader dabit breaks it down in less than 3 mins and shows how to start building ⬇️

EigenCloud

13,119 Aufrufe • vor 9 Monaten

INFINIT partners with Google and GoogleCloudTech to bring agentic finance to millions. Anyone can access INFINIT's AI Agents for agentic coordination in their financial apps. This partnership marks the first step towards INFINIT becoming the universal infrastructure for agentic finance. This is the foundation for agentic finance at scale. Proven in DeFi, Built for Global Finance INFINIT has proven sophisticated agent coordination in DeFi: • 559,000+ Wallets • 506,000+ DeFi Conversations • 633,000+ Agent Transactions DeFi was the start. Next is scaling these capabilities to millions of developers building the future of agentic finance. A2A Integration Unlocks Exponential Distribution INFINIT integrates with Agent2Agent (A2A), Google's open standard for AI agent interoperability. This transforms how developers access INFINIT's DeFi capabilities.​ Every application adopting A2A automatically gains access to INFINIT's agent infrastructure, exponentially expanding reach from individual partnerships to ecosystem-wide distribution. Any application can now integrate INFINIT's agentic coordination capabilities: • Wallets requiring intelligent portfolio management • Trading platforms executing cross-chain strategies • Financial services building autonomous yield optimization • Portfolio managers coordinating multi-protocol operations Developers integrate sophisticated agentic coordination in a matter of hours, while users access advanced financial strategies with agentic coordination. Google's AI Infrastructure That Enables Agentic Finance Google Cloud's Vertex AI provides the foundation enabling INFINIT's agent coordination at scale with these capabilities:​ 1. Specialization: Vertex AI's Model Garden lets INFINIT's infrastructure to automatically select the optimal LLM for each natural language query.​ 2. Personalization: Vertex AI's RAG Engine processes massive on-chain and off-chain data, enabling agents to understand user history, market conditions, and protocol details providing complete context to AI agents. 3. Accuracy: Gemini's capability feeds complete instructions to all 30+ agents across multiple blockchains without compromises resulting in zero hallucination in financial execution.​​ The Vision: From DeFi to Payments to Complete Financial Coordination This is only the beginning of INFINIT and Google's collaboration.​ Google recently launched its Agent Payments Protocol (AP2) as an extension of A2A - enabling autonomous commerce across 60+ partners including American Express, Mastercard, PayPal, Coinbase, and Revolut.​ Agents will be able to execute purchases, coordinate bookings, and manage delegated financial tasks autonomously, starting from payments. The next stage entails sophisticated agentic coordination beyond simple transactions. INFINIT provides this through A2A-compatible DeFi infrastructure where agents orchestrate: • Personalized yield optimization • Cross-chain liquidity management • Portfolio rebalancing across protocols • Multi-step strategy execution As the agentic payment ecosystem matures, INFINIT becomes the infrastructure enabling agents to not only spend capital, but strategically manage and grow it.​​ From standalone DeFi agents to the universal infrastructure for global agentic finance.​ This partnership and integration with Google and Google Cloud positions INFINIT as a key building block for agentic finance, helping shape a more transparent, efficient, and accessible financial system. The future of finance is agentic. The foundation is INFINIT.
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INFINIT partners with Google and GoogleCloudTech to bring agentic finance to millions. Anyone can access INFINIT's AI Agents for agentic coordination in their financial apps. This partnership marks the first step towards INFINIT becoming the universal infrastructure for agentic finance. This is the foundation for agentic finance at scale. Proven in DeFi, Built for Global Finance INFINIT has proven sophisticated agent coordination in DeFi: • 559,000+ Wallets • 506,000+ DeFi Conversations • 633,000+ Agent Transactions DeFi was the start. Next is scaling these capabilities to millions of developers building the future of agentic finance. A2A Integration Unlocks Exponential Distribution INFINIT integrates with Agent2Agent (A2A), Google's open standard for AI agent interoperability. This transforms how developers access INFINIT's DeFi capabilities.​ Every application adopting A2A automatically gains access to INFINIT's agent infrastructure, exponentially expanding reach from individual partnerships to ecosystem-wide distribution. Any application can now integrate INFINIT's agentic coordination capabilities: • Wallets requiring intelligent portfolio management • Trading platforms executing cross-chain strategies • Financial services building autonomous yield optimization • Portfolio managers coordinating multi-protocol operations Developers integrate sophisticated agentic coordination in a matter of hours, while users access advanced financial strategies with agentic coordination. Google's AI Infrastructure That Enables Agentic Finance Google Cloud's Vertex AI provides the foundation enabling INFINIT's agent coordination at scale with these capabilities:​ 1. Specialization: Vertex AI's Model Garden lets INFINIT's infrastructure to automatically select the optimal LLM for each natural language query.​ 2. Personalization: Vertex AI's RAG Engine processes massive on-chain and off-chain data, enabling agents to understand user history, market conditions, and protocol details providing complete context to AI agents. 3. Accuracy: Gemini's capability feeds complete instructions to all 30+ agents across multiple blockchains without compromises resulting in zero hallucination in financial execution.​​ The Vision: From DeFi to Payments to Complete Financial Coordination This is only the beginning of INFINIT and Google's collaboration.​ Google recently launched its Agent Payments Protocol (AP2) as an extension of A2A - enabling autonomous commerce across 60+ partners including American Express, Mastercard, PayPal, Coinbase, and Revolut.​ Agents will be able to execute purchases, coordinate bookings, and manage delegated financial tasks autonomously, starting from payments. The next stage entails sophisticated agentic coordination beyond simple transactions. INFINIT provides this through A2A-compatible DeFi infrastructure where agents orchestrate: • Personalized yield optimization • Cross-chain liquidity management • Portfolio rebalancing across protocols • Multi-step strategy execution As the agentic payment ecosystem matures, INFINIT becomes the infrastructure enabling agents to not only spend capital, but strategically manage and grow it.​​ From standalone DeFi agents to the universal infrastructure for global agentic finance.​ This partnership and integration with Google and Google Cloud positions INFINIT as a key building block for agentic finance, helping shape a more transparent, efficient, and accessible financial system. The future of finance is agentic. The foundation is INFINIT.

INFINIT

176,699 Aufrufe • vor 9 Monaten

LIVE NOW - Tempo Mainnet: The Race to Agentic Commerce Tempo is live, and the big bet is clear: AI agents need a native payment layer. Georgios Konstantopoulos and Brendan Ryan join Bankless to explore: - why Tempo launched with agentic payments front and center, - how MPP turns payments into auth, - why “give the agent the wallet” could unlock a new internet economy, - where MPP fits against x402, - what Tempo’s L1 design makes possible for builders. Enjoy the episode. --- TIMESTAMPS 0:00 Tempo Mainnet goes live 1:18 Why the launch is focused on agents 3:58 What MPP actually is 6:30 MPP vs x402 15:28 Why agentic commerce matters 20:08 The “original sin” of the internet 26:04 MCP, NLWeb, and the emerging agent stack 34:07 The onboarding flow: wallets for agents 37:11 How Tempo’s wallet security works 40:11 Tempo chain design and specs 51:13 Why build an L1 instead of an Ethereum L2? 56:10 The Ethereum tension 1:05:01 Agent identity, reputation, and ERC-8004 1:06:53 TIP20, stablecoins, and what can be built on Tempo 1:12:36 Builder opportunity in the agentic web
1:21:50

LIVE NOW - Tempo Mainnet: The Race to Agentic Commerce Tempo is live, and the big bet is clear: AI agents need a native payment layer. Georgios Konstantopoulos and Brendan Ryan join Bankless to explore: - why Tempo launched with agentic payments front and center, - how MPP turns payments into auth, - why “give the agent the wallet” could unlock a new internet economy, - where MPP fits against x402, - what Tempo’s L1 design makes possible for builders. Enjoy the episode. --- TIMESTAMPS 0:00 Tempo Mainnet goes live 1:18 Why the launch is focused on agents 3:58 What MPP actually is 6:30 MPP vs x402 15:28 Why agentic commerce matters 20:08 The “original sin” of the internet 26:04 MCP, NLWeb, and the emerging agent stack 34:07 The onboarding flow: wallets for agents 37:11 How Tempo’s wallet security works 40:11 Tempo chain design and specs 51:13 Why build an L1 instead of an Ethereum L2? 56:10 The Ethereum tension 1:05:01 Agent identity, reputation, and ERC-8004 1:06:53 TIP20, stablecoins, and what can be built on Tempo 1:12:36 Builder opportunity in the agentic web

Bankless

23,815 Aufrufe • vor 4 Monaten

Types of AI Agents & why they need Verifiable Cloud | Weekend Learning [2 Mins] 🤖 Sreeram Kannan breaks down the evolution from personal agents to multiplayer agents to sovereign agents, and why only verifiable compute can support the last two. EigenCloud enables: ✅ Verifiable execution for multi-user agents ✅ Enforcement of covenants and property rights ✅ A foundation for sovereign agents to operate independently A cloud where agents can act, coordinate, and self-govern, with verifiable guarantees, not blind trust.
2:09

Types of AI Agents & why they need Verifiable Cloud | Weekend Learning [2 Mins] 🤖 Sreeram Kannan breaks down the evolution from personal agents to multiplayer agents to sovereign agents, and why only verifiable compute can support the last two. EigenCloud enables: ✅ Verifiable execution for multi-user agents ✅ Enforcement of covenants and property rights ✅ A foundation for sovereign agents to operate independently A cloud where agents can act, coordinate, and self-govern, with verifiable guarantees, not blind trust.

EigenCloud

97,052 Aufrufe • vor 7 Monaten

Why Onchain Virtual Machines Limit Crypto? | Weekend Learning ☁️ Sreeram Kannan explains why onchain VMs fall short and how verifiable off-chain compute unlocks the ability to run any program, on any hardware, with cryptograde guarantees. EigenCloud gives you: ✅ Full flexibility of modern cloud platforms ✅ Verifiable off-chain compute returned onchain ✅ Support for real workloads: gaming, social, AI agents and more A cloud where you bring your stack and the chain brings the trust. A cloud you can verify, not just trust.
1:06

Why Onchain Virtual Machines Limit Crypto? | Weekend Learning ☁️ Sreeram Kannan explains why onchain VMs fall short and how verifiable off-chain compute unlocks the ability to run any program, on any hardware, with cryptograde guarantees. EigenCloud gives you: ✅ Full flexibility of modern cloud platforms ✅ Verifiable off-chain compute returned onchain ✅ Support for real workloads: gaming, social, AI agents and more A cloud where you bring your stack and the chain brings the trust. A cloud you can verify, not just trust.

EigenCloud

56,699 Aufrufe • vor 7 Monaten

Crypto built the root of trust. AI needs it. At Permissionless Wealth (自由财富) IV’s Open Source AI Summit presented by NEAR Protocol, Sreeram Kannan dropped the most important update in Crypto x AI this year. ☁️ Eigencloud Supercharging Verifiable AI. ☁️ Crypto built the foundation for digital property, programmable money, and trustless execution. But it was never built to run AI. EigenCloud changes that. For the first time, you can deploy unstoppable, verifiable AI agents, not behind an API key, but as sovereign entities that own, earn, and act onchain. 🔥 Smart contracts that think. 🔥 AI that can stake. 🔥 Agents that can own. This is not a demo. It’s a new reality. And it’s the most powerful unlock in crypto since Ethereum. EigenCloud Timestamps:⁣ 0:10 Introduction⁣ 0:32 EigenLayer → EigenCloud 1:53 Autonomous Verifiable Services 3:06 Evolving from Infra to Apps⁣ to AI 5:41 EigenCloud Architecture 9:30 Bringing AI Onchain⁣ with EigenVerify 12:01 Supercharge AI 15:44 Sovereign AI Agents 17:48 Making Autonomous Agents Practical⁣ 18:37 AI Inference, Model, and Agents 19:03 Deep stack of Verifiability 21:15 Call to Builders: Build Powerful Expressive Apps with Agents
21:24

Crypto built the root of trust. AI needs it. At Permissionless Wealth (自由财富) IV’s Open Source AI Summit presented by NEAR Protocol, Sreeram Kannan dropped the most important update in Crypto x AI this year. ☁️ Eigencloud Supercharging Verifiable AI. ☁️ Crypto built the foundation for digital property, programmable money, and trustless execution. But it was never built to run AI. EigenCloud changes that. For the first time, you can deploy unstoppable, verifiable AI agents, not behind an API key, but as sovereign entities that own, earn, and act onchain. 🔥 Smart contracts that think. 🔥 AI that can stake. 🔥 Agents that can own. This is not a demo. It’s a new reality. And it’s the most powerful unlock in crypto since Ethereum. EigenCloud Timestamps:⁣ 0:10 Introduction⁣ 0:32 EigenLayer → EigenCloud 1:53 Autonomous Verifiable Services 3:06 Evolving from Infra to Apps⁣ to AI 5:41 EigenCloud Architecture 9:30 Bringing AI Onchain⁣ with EigenVerify 12:01 Supercharge AI 15:44 Sovereign AI Agents 17:48 Making Autonomous Agents Practical⁣ 18:37 AI Inference, Model, and Agents 19:03 Deep stack of Verifiability 21:15 Call to Builders: Build Powerful Expressive Apps with Agents

EigenCloud

65,722 Aufrufe • vor 1 Jahr

TradFi just met DeFi, onchain. is bringing institutional credit onchain, powered by EigenLayer. Its inaugural user? Flow Traders, one of the world’s largest market makers. This marks a milestone: regulated institutions are now accessing onchain liquidity through cryptoeconomically secured DeFi infra. More 🧵⬇️
0:43

TradFi just met DeFi, onchain. is bringing institutional credit onchain, powered by EigenLayer. Its inaugural user? Flow Traders, one of the world’s largest market makers. This marks a milestone: regulated institutions are now accessing onchain liquidity through cryptoeconomically secured DeFi infra. More 🧵⬇️

EigenCloud

179,993 Aufrufe • vor 8 Monaten

AI agents are the fastest growing sector in crypto. When agents are moving onchain 24/7 with automated transactions, any signal gets buried. I built Manta Style alongside Benjamin Hughes to help solve this issue. The visibility layer for the onchain agent economy. Every agent indexed. Every profile searchable. One agent leaderboard. Starting with Base. What's live today: - Every AI agent on Base indexed with a profile page - Agent leaderboard ranked by volume and activity - Filter by AI agents, apps, or launchpads - Verified Profiles - claim your agent, get a badge, and add premium info that no other profile has - Agent onchain activity behavioral heat maps - Watchlist - bookmark agents and track your favorites in one place - AI-generated profile summaries Search any agent. See the full picture. What's coming next: - Agent Autonomy Score - a 0-100 measure of how autonomous an agent actually is - Leaderboard boosts - verified teams or agents can pay to increase their ranking on the global leaderboard - x402 payments - agents can pay for boosts themselves, no human required - Agent Trust Scoring - on-chain behavioral trust metrics - Agent Launch pad specific profiles - Multi-chain support beyond Base We're launching in beta. Rough edges are to be expected. Our goal is to build in public and ship fast. The end user of crypto is AI. (link to site below)
0:54

AI agents are the fastest growing sector in crypto. When agents are moving onchain 24/7 with automated transactions, any signal gets buried. I built Manta Style alongside Benjamin Hughes to help solve this issue. The visibility layer for the onchain agent economy. Every agent indexed. Every profile searchable. One agent leaderboard. Starting with Base. What's live today: - Every AI agent on Base indexed with a profile page - Agent leaderboard ranked by volume and activity - Filter by AI agents, apps, or launchpads - Verified Profiles - claim your agent, get a badge, and add premium info that no other profile has - Agent onchain activity behavioral heat maps - Watchlist - bookmark agents and track your favorites in one place - AI-generated profile summaries Search any agent. See the full picture. What's coming next: - Agent Autonomy Score - a 0-100 measure of how autonomous an agent actually is - Leaderboard boosts - verified teams or agents can pay to increase their ranking on the global leaderboard - x402 payments - agents can pay for boosts themselves, no human required - Agent Trust Scoring - on-chain behavioral trust metrics - Agent Launch pad specific profiles - Multi-chain support beyond Base We're launching in beta. Rough edges are to be expected. Our goal is to build in public and ship fast. The end user of crypto is AI. (link to site below)

Ethan

14,423 Aufrufe • vor 5 Monaten

Most blockchains weren’t built for real world finance. We sat down with Daniel Marin, CEO of Nexus, to break down why how Nexus has built a purposeful Layer 1 for verifiable finance. We cover the Nexus Exchange, $USDX as the native dollar, predictable execution powered by zkProofs, and how stablecoin yield can create sustainable onchain revenue models. Timestamps: 0:00 – The Problem: Why Ethereum Isn’t Built for Traditional Finance 0:53 – Introducing Nexus: A Purpose-Built Layer 1 for Verifiable Finance 4:44 – How Zero Knowledge Scaling Enables Low Latency Trading 6:24 – Tokenization on Ethereum vs High Frequency Verifiable Finance 8:30 – Nexus Timeline: From Stanford to 3M+ Users 12:34 – USDX Explained: A Native Stablecoin Backed by T-Bills 16:16 – How Nexus Captures Stablecoin Yield & Creates a Value Flywheel 26:15 – What’s Coming Next: Token Campaigns & Mainnet Roadmap
29:04

Most blockchains weren’t built for real world finance. We sat down with Daniel Marin, CEO of Nexus, to break down why how Nexus has built a purposeful Layer 1 for verifiable finance. We cover the Nexus Exchange, $USDX as the native dollar, predictable execution powered by zkProofs, and how stablecoin yield can create sustainable onchain revenue models. Timestamps: 0:00 – The Problem: Why Ethereum Isn’t Built for Traditional Finance 0:53 – Introducing Nexus: A Purpose-Built Layer 1 for Verifiable Finance 4:44 – How Zero Knowledge Scaling Enables Low Latency Trading 6:24 – Tokenization on Ethereum vs High Frequency Verifiable Finance 8:30 – Nexus Timeline: From Stanford to 3M+ Users 12:34 – USDX Explained: A Native Stablecoin Backed by T-Bills 16:16 – How Nexus Captures Stablecoin Yield & Creates a Value Flywheel 26:15 – What’s Coming Next: Token Campaigns & Mainnet Roadmap

Crypto Coin Show

10,669 Aufrufe • vor 5 Monaten

When you give an AI agent money, how do you trust what it’s really doing? Sreeram Kannan explains why verifiable agents, AI systems you can cryptographically audit, are the key to trustless, safe agentic trading. 🎙️ w/ Ash Bennington on Real Vision
2:16

When you give an AI agent money, how do you trust what it’s really doing? Sreeram Kannan explains why verifiable agents, AI systems you can cryptographically audit, are the key to trustless, safe agentic trading. 🎙️ w/ Ash Bennington on Real Vision

EigenCloud

35,069 Aufrufe • vor 8 Monaten

New short course: Building Code Agents with Hugging Face smolagents! Learn how to build code agents in this course, created in collaboration with Hugging Face, and taught by Thomas Wolf, its co-founder and CSO, and m_ric, Hugging Face’s Project Lead on Agents. Tool-calling agents use LLMs to generate multiple function calls sequentially to complete a complex sequence of tasks. They generate one function call, execute it, observe, reason, and decide what to do next. Code agents take a different approach. They consolidate all these calls into a single block of code, letting the LLM lay out an entire action plan at once, which can be executed efficiently to provide more reliable results. You’ll learn how to code agents using smolagents, a lightweight agentic framework from Hugging Face. Along the way, you’ll learn how to run LLM-generated code safely and develop an evaluation system to optimize your code agent for production. In detail, you’ll learn: - How agentic systems have evolved, gaining greater levels of agency over time—and why code agents are a next step. - How code agents write their actions in code. - When code agents outperform function-calling agents. - How to run code agents safely in your system using a constrained Python interpreter and sandboxing using E2B. - To trace, debug, and assess the code agent to optimize its behaviours for complex requests. - How to build a research multi-agent system that can find information online and organize it into an interactive report. By the end of this course, you’ll know how to build and run code agents using smolagents, and deploy them safely with a structured evaluation system in your projects. Please sign up here!
2:17

New short course: Building Code Agents with Hugging Face smolagents! Learn how to build code agents in this course, created in collaboration with Hugging Face, and taught by Thomas Wolf, its co-founder and CSO, and m_ric, Hugging Face’s Project Lead on Agents. Tool-calling agents use LLMs to generate multiple function calls sequentially to complete a complex sequence of tasks. They generate one function call, execute it, observe, reason, and decide what to do next. Code agents take a different approach. They consolidate all these calls into a single block of code, letting the LLM lay out an entire action plan at once, which can be executed efficiently to provide more reliable results. You’ll learn how to code agents using smolagents, a lightweight agentic framework from Hugging Face. Along the way, you’ll learn how to run LLM-generated code safely and develop an evaluation system to optimize your code agent for production. In detail, you’ll learn: - How agentic systems have evolved, gaining greater levels of agency over time—and why code agents are a next step. - How code agents write their actions in code. - When code agents outperform function-calling agents. - How to run code agents safely in your system using a constrained Python interpreter and sandboxing using E2B. - To trace, debug, and assess the code agent to optimize its behaviours for complex requests. - How to build a research multi-agent system that can find information online and organize it into an interactive report. By the end of this course, you’ll know how to build and run code agents using smolagents, and deploy them safely with a structured evaluation system in your projects. Please sign up here!

Andrew Ng

127,724 Aufrufe • vor 1 Jahr

Don't just learn how to build AI agents. Instead, learn how to build... ...full-stack AI agents that actually work inside apps. Yet, the main challenge is transitioning them from local setups to user-facing apps. Here are some key factors to consider: - How do you embed a seamless UI? - How do you enable user control when necessary? - How do you unify the agent’s state and actions with the app? CoAgents by CopilotKit🪁 solves this. It is the only framework that offers all the essential Agentic front-end building blocks to set up full-stack agentic apps. And most recently, they have extended full-stack development support to Agents built with CrewAI ✨. This includes both regular Agentic Crews and Flows. Check their GitHub repo it's 100% open-source, I have shared link in the next tweet! With this update, here's what you can do with Agents built using CrewAI: ↳ Chat: Add chat components for interaction. ↳ Human-in-the-loop: Real-time human approvals. ↳ Predictive state updates: Preview upcoming changes. ↳ Agentic UI: Agents generate UI components dynamically. This way, you can give your CrewAI Agents a frontend brain—so they don’t just work behind the scenes, they become an integral part of the user experience. The video below showcases a full-stack CrewAI Agent built in 20 minutes using CoAgents. Impressive, right?
0:25

Don't just learn how to build AI agents. Instead, learn how to build... ...full-stack AI agents that actually work inside apps. Yet, the main challenge is transitioning them from local setups to user-facing apps. Here are some key factors to consider: - How do you embed a seamless UI? - How do you enable user control when necessary? - How do you unify the agent’s state and actions with the app? CoAgents by CopilotKit🪁 solves this. It is the only framework that offers all the essential Agentic front-end building blocks to set up full-stack agentic apps. And most recently, they have extended full-stack development support to Agents built with CrewAI ✨. This includes both regular Agentic Crews and Flows. Check their GitHub repo it's 100% open-source, I have shared link in the next tweet! With this update, here's what you can do with Agents built using CrewAI: ↳ Chat: Add chat components for interaction. ↳ Human-in-the-loop: Real-time human approvals. ↳ Predictive state updates: Preview upcoming changes. ↳ Agentic UI: Agents generate UI components dynamically. This way, you can give your CrewAI Agents a frontend brain—so they don’t just work behind the scenes, they become an integral part of the user experience. The video below showcases a full-stack CrewAI Agent built in 20 minutes using CoAgents. Impressive, right?

Akshay 🚀

27,153 Aufrufe • vor 1 Jahr

Multi-agent systems offer incredible potential and unprecedented risks. How do you solve for observability, failure mode analysis, and guardrailing in the era of agents? Today, we’re announcing our Agent Reliability platform to observe, evaluate, guardrail, and improve agents at scale. You can get started with the complete platform for trustworthy agentic AI today for free, and here’s how we’re solving some of the biggest challenges in agent reliability: - Observability redesigned for agents Trace views collapse under complex workflows, so we created the Graph View, Timeline View, and Conversation View to offer rich, intuitive visualizations of agent decisions, tool calls, and conversation flows. This multi-dimensional approach enables teams to pinpoint exactly where and why agents deviate or fail. - Automated Failure Mode Analysis with our new Insights Engine Our Insights Engine ingests your logs, metrics, and agent code to automatically surface nuanced failure modes and their root causes. But knowing the problem is not enough; you need to know how to fix it. Insights Engine delivers actionable fixes and can even apply them automatically. With adaptive learning, your insights become smarter and more relevant as your agents evolve. - Evaluating Agents Across Multiple Dimensions Agentic systems interact across complex pathways, and evaluating their performance requires new metrics that reflect this increasing complexity. To deliver comprehensive agentic measurements, we’ve added more out-of-the-box agent metrics like flow adherence, agent flow, agent efficiency, and more. For specialized domains and unique workflows, custom metrics powered by our new Luna-2 small language models can be rapidly designed and fine-tuned for your specific use case. - Real-Time Guardrails Powered by Luna-2 As AI agents become more autonomous and complex, failures like hallucinations or unsafe actions increase dramatically. Without real-time guardrails, these errors will hurt your user experience and brand reputation. Our Luna-2 family of small language models is purpose-built to provide low-latency, cost-effective guardrails that actively stop agent errors before they happen. With support for out-of-the-box and custom metrics, Luna-2 enables enterprises to enforce safety, compliance, and reliability at scale. Enterprises running hundreds of agents and processing hundreds of millions of queries daily already rely on Galileo’s Agent Reliability platform to protect their users, safeguard brand trust, and accelerate innovation. Agent Reliability is available starting today. Try it for free and experience the new standard in AI reliability. Learn more below 👇
2:43

Multi-agent systems offer incredible potential and unprecedented risks. How do you solve for observability, failure mode analysis, and guardrailing in the era of agents? Today, we’re announcing our Agent Reliability platform to observe, evaluate, guardrail, and improve agents at scale. You can get started with the complete platform for trustworthy agentic AI today for free, and here’s how we’re solving some of the biggest challenges in agent reliability: - Observability redesigned for agents Trace views collapse under complex workflows, so we created the Graph View, Timeline View, and Conversation View to offer rich, intuitive visualizations of agent decisions, tool calls, and conversation flows. This multi-dimensional approach enables teams to pinpoint exactly where and why agents deviate or fail. - Automated Failure Mode Analysis with our new Insights Engine Our Insights Engine ingests your logs, metrics, and agent code to automatically surface nuanced failure modes and their root causes. But knowing the problem is not enough; you need to know how to fix it. Insights Engine delivers actionable fixes and can even apply them automatically. With adaptive learning, your insights become smarter and more relevant as your agents evolve. - Evaluating Agents Across Multiple Dimensions Agentic systems interact across complex pathways, and evaluating their performance requires new metrics that reflect this increasing complexity. To deliver comprehensive agentic measurements, we’ve added more out-of-the-box agent metrics like flow adherence, agent flow, agent efficiency, and more. For specialized domains and unique workflows, custom metrics powered by our new Luna-2 small language models can be rapidly designed and fine-tuned for your specific use case. - Real-Time Guardrails Powered by Luna-2 As AI agents become more autonomous and complex, failures like hallucinations or unsafe actions increase dramatically. Without real-time guardrails, these errors will hurt your user experience and brand reputation. Our Luna-2 family of small language models is purpose-built to provide low-latency, cost-effective guardrails that actively stop agent errors before they happen. With support for out-of-the-box and custom metrics, Luna-2 enables enterprises to enforce safety, compliance, and reliability at scale. Enterprises running hundreds of agents and processing hundreds of millions of queries daily already rely on Galileo’s Agent Reliability platform to protect their users, safeguard brand trust, and accelerate innovation. Agent Reliability is available starting today. Try it for free and experience the new standard in AI reliability. Learn more below 👇

Galileo

1,276,298 Aufrufe • vor 1 Jahr

What does the future of unstoppable, verifiable agents look like?⁣ ⁣ In his talk at HackMIT, Gajesh shared the journey from a $7M teenage project to building and why verifiable code changes everything.⁣ ⁣ The future is open, and we’d love for you to be part of it.⁣ ⁣ 0:00 Intro⁣ 0:27 Story of a 13-year-old building a $7M app⁣ 1:12 Gaj’s coding journey⁣ 1:43 The Unstoppable Verifiable Future ⁣ 2:48 Call to Action: Verifiable Agents⁣ ⁣ Full video here 🎥👇
3:25

What does the future of unstoppable, verifiable agents look like?⁣ ⁣ In his talk at HackMIT, Gajesh shared the journey from a $7M teenage project to building and why verifiable code changes everything.⁣ ⁣ The future is open, and we’d love for you to be part of it.⁣ ⁣ 0:00 Intro⁣ 0:27 Story of a 13-year-old building a $7M app⁣ 1:12 Gaj’s coding journey⁣ 1:43 The Unstoppable Verifiable Future ⁣ 2:48 Call to Action: Verifiable Agents⁣ ⁣ Full video here 🎥👇

EigenCloud

22,045 Aufrufe • vor 10 Monaten

#NewEpisodeAlert Ep:8 slice’s Leap: From Fintech Disruptor to India’s Next Big Bank In this episode of Innovators Playground, Dilip Asbe 🇮🇳, MD and CEO, NPCI, sits down with , Founder and ED, slice, for a candid conversation on how a fintech company is rethinking banking itself, from core technology and credit models to AI, #UPI, and population scale design. Here is what the episode dives into: ✅ What it means to build a banking stack in house: ✅ Why building for the first time users creates the best bank for everyone ✅ How UPI and credit are converging into a new financial primitive ✅ Where AI actually matters in banking at scale 🎧 A must listen for engineers, product leaders, and fintech founders building for India’s next decade of growth. Listen now: #InnovatorsPlayground #NPCI #slice #TechLeadership #OpenSource #DPI #Fintech #IndiaTech #EngineeringCulture #Startups #UPI #CreditonUPI #credit
1:02

#NewEpisodeAlert Ep:8 slice’s Leap: From Fintech Disruptor to India’s Next Big Bank In this episode of Innovators Playground, Dilip Asbe 🇮🇳, MD and CEO, NPCI, sits down with , Founder and ED, slice, for a candid conversation on how a fintech company is rethinking banking itself, from core technology and credit models to AI, #UPI, and population scale design. Here is what the episode dives into: ✅ What it means to build a banking stack in house: ✅ Why building for the first time users creates the best bank for everyone ✅ How UPI and credit are converging into a new financial primitive ✅ Where AI actually matters in banking at scale 🎧 A must listen for engineers, product leaders, and fintech founders building for India’s next decade of growth. Listen now: #InnovatorsPlayground #NPCI #slice #TechLeadership #OpenSource #DPI #Fintech #IndiaTech #EngineeringCulture #Startups #UPI #CreditonUPI #credit

NPCI

24,064 Aufrufe • vor 6 Monaten

Agentic commerce is coming 🔥 — Emily GlassbergSands, Head of Information at Stripe unpacks how autonomous “buying bots” and MCP are reshaping the very mechanics of online transactions - and how Stripe’s AI models and rails are adapting for tokens, one-time virtual cards, and real-time risk management. 0:00 - Intro, latest Stripe stats 01:45 - Backgroud: The “Head of Information” role at Stripe, and Emily's journey from Harvard to Stripe 08:54 - Why Stripe Built Its Own Foundation Model 13:19 - Cracking the Code: How Stripe Handles Complex Payment Data 16:25 - Foundation Model vs. Traditional ML: What’s Winning, When? 20:09 - Inside Stripe’s Foundation Model: How It Was Built 24:35 - Transparency vs black box AI 28:38 - How to decide when to use AI and when not 34:10 - How Stripe’s AI Drives Revenue for Businesses 41:22 - Real-Time Fraud Detection: Stripe’s Secret Sauce 42:51 - The Future of Shopping: AI Agents & Agentic Commerce 46:20 - How Agentic Commerce Is Changing Stripe 49:36 - Stripe’s Vision for a World of AI-Powered Buyers 55:46 - What Is MCP? Stripe’s Take on Agent-to-Agent Protocols 59:31 - Stripe’s Data on AI Startups Monetizing 3× Faster 1:03:03 - How AI Companies Go Global — From Day One 1:07:48 - The New Rules: Billing & Pricing for AI Startups 1:10:57 - How Stripe Builds AI Literacy Across the Company 1:14:05 - Roadmap: Risk-as-a-Service, Order Intent, and Beyond
1:15:14

Agentic commerce is coming 🔥 — Emily GlassbergSands, Head of Information at Stripe unpacks how autonomous “buying bots” and MCP are reshaping the very mechanics of online transactions - and how Stripe’s AI models and rails are adapting for tokens, one-time virtual cards, and real-time risk management. 0:00 - Intro, latest Stripe stats 01:45 - Backgroud: The “Head of Information” role at Stripe, and Emily's journey from Harvard to Stripe 08:54 - Why Stripe Built Its Own Foundation Model 13:19 - Cracking the Code: How Stripe Handles Complex Payment Data 16:25 - Foundation Model vs. Traditional ML: What’s Winning, When? 20:09 - Inside Stripe’s Foundation Model: How It Was Built 24:35 - Transparency vs black box AI 28:38 - How to decide when to use AI and when not 34:10 - How Stripe’s AI Drives Revenue for Businesses 41:22 - Real-Time Fraud Detection: Stripe’s Secret Sauce 42:51 - The Future of Shopping: AI Agents & Agentic Commerce 46:20 - How Agentic Commerce Is Changing Stripe 49:36 - Stripe’s Vision for a World of AI-Powered Buyers 55:46 - What Is MCP? Stripe’s Take on Agent-to-Agent Protocols 59:31 - Stripe’s Data on AI Startups Monetizing 3× Faster 1:03:03 - How AI Companies Go Global — From Day One 1:07:48 - The New Rules: Billing & Pricing for AI Startups 1:10:57 - How Stripe Builds AI Literacy Across the Company 1:14:05 - Roadmap: Risk-as-a-Service, Order Intent, and Beyond

Matt Turck

17,720 Aufrufe • vor 1 Jahr