正在加载视频...

视频加载失败

At today’s Amazon Web Services Summit NYC, we unveiled a new Bedrock capability called AgentCore – a set of powerful building blocks that will change how you can deploy agents into production in a secure, scalable, and flexible way.

230,965 次观看 • 1 年前 •via X (Twitter)

11 条评论

britton winterrose 的头像
britton winterrose1 年前

@awscloud Andy I can’t imagine the burden you bear but please take care of yourself.

bshaan 的头像
bshaan1 年前

Agent Core: 1. secure serverless runtime (each agent run's on its own VM) 2. memory (short and log term) to personalize agents 3. identity (auth and access) 4. api/lambda -> mcp (give tools to agents) 5. code and browser tool (execute complex code and navigate the web) 6. observability (monitor agents)

Vittorio 的头像
Vittorio1 年前

@awscloud u rock

Mobile Scanner 的头像
Mobile Scanner1 年前

Scan any documents, convert images into text, PDF files, etc. 👍

Reno Seros ` 的头像
Reno Seros `1 年前

@awscloud ✨

Alex Volkov (Thursd/AI) 的头像
Alex Volkov (Thursd/AI)1 年前

@awscloud where's Alexa+? How can I get it in my home?

Lon 的头像
Lon1 年前

@awscloud giddy up

Dallas Klein 的头像
Dallas Klein1 年前

@awscloud Thanks Andy! Hoping I can hand off some docs to Kiro and come back and have an agent spun up

Carlos Carpio 的头像
Carlos Carpio1 年前

@awscloud Wow, you guys are getting serious! 💪❤️

Simon Leyland 的头像
Simon Leyland1 年前

@awscloud AWS will be able to house hundreds of millions of virtual workforce. Will transform industry and society for the better.

Quizical 的头像
Quizical1 年前

@awscloud Why are Amazon orders taking so long to ship now? Amazon is getting worse and worse by the day. Maybe someone should be looking into it, and fixing the problem, instead of looking for new ways to make more money for Amazon. Think of your customers for once.

相关视频

🚀 Here’s more on AgentCore, launched today: If AI agents are going to transform how we work and live, developers need the right set of tools to move them from prototype to production at scale. Today, I'm thrilled to announce Amazon Bedrock AgentCore, a comprehensive set of services to deploy and operate highly capable agents securely at scale. The journey from prototype to production for AI agents has been filled with complex infrastructure challenges. Teams spend months building secure runtime environments, implementing memory systems, and creating monitoring solutions. AgentCore eliminates this undifferentiated heavy lifting, with fully-managed, modular services - providing everything you need to operate trustworthy agents. What makes AgentCore powerful: 🟠 Complete Development Flexibility: Build agents your way using any framework and any model, and work with any protocol (including MCP and A2A) - all while maintaining enterprise-grade security and control 🟠 Purpose-Built Infrastructure: First serverless runtime to offer framework-agnostic flexibility, complete session isolation, and industry-leading 8-hour workload support 🟠 Trust and Reliability: Built on AWS's proven security foundation with built-in identity controls and strict security boundaries for operating agents at scale 🟠 Composable Services: Use exactly what you need independently or together, paying only for what you use as your needs evolve AgentCore represents a significant milestone in our mission to make advanced AI accessible and practical for every organization. Whether you're just starting with AI agents or scaling enterprise-wide implementations, AgentCore gives you the foundation to build with confidence. This is just the beginning of our journey to enable an agentic future. Can't wait to see the transformative solutions you'll build with AgentCore! Bring your AI agents to life at scale – learn more about AgentCore today. Amazon Web Services #AmazonBedrock #AgentCore

Swami Sivasubramanian

11,646 次观看 • 1 年前

New Short Course: Building AI Browser Agents! Learn how to build AI agents that interact and take actions on websites in this course, created in partnership with and taught by and @namangarg0, Co-founders of AGI Inc. AI browser agents can log into websites, fill out forms, click through web pages, or even place orders online for you. They use both visual information, like screenshots, and structural data, like the HTML or Document Object Model (DOM) of a web page, to reason and take action. With the complexity of webpages and multiple possible actions at each step, it can be challenging for an AI browser agent to complete an assigned task. Because these agents run long action sequences, a single error—like clicking the wrong button or misreading a field—can lead to unexpected outcomes or errors that compound over time. In this course, you'll understand how autonomous web agents work, their current limitations, and how AgentQ enables them to improve through self-correction. In detail, you'll: - Learn what web agents are, how they automate tasks online, their architecture, key components, limitations, and an overview of their decision-making strategies. - Build a web agent that can scrape website and return course recommendations in a structured output format. - Build an autonomous web agent that can execute multiple tasks, such as finding and summarizing webpages, filling out a form, and signing up for a newsletter. - Explore AgentQ, a framework that enables agents to self-correct by combining Monte Carlo Tree Search (MCTS), a self-critique mechanism for continuous improvement, and Direct Preference Optimization (DPO). - Deep dive into MCTS, learn how it finds an effective path, illustrated by an example of Gridworld animation, and use AgentQ to complete web tasks. - Understand AI agents' current state and future directions—including key factors shaping their evolution, such as hardware, algorithm innovation, and data availability. By the end of this course, you will have hands-on experience building browser agents and a deeper understanding of how to make them more robust and reliable. Please sign up here:

Andrew Ng

186,133 次观看 • 1 年前