Google launches free Gemini-powered Data Science Agent on its Colab Python platform AI agents are making waves, but what about one dedicated to analyzing, organizing, and interpreting massive datasets? Enter Google’s data science agent: a cutting-edge, Gemini 2.0-powered AI assistant designed to automate data analysis. This innovative tool is now free and accessible to users aged 18 and older in select countries and languages. The assistant is seamlessly integrated into Google Colab, the company’s robust, eight-year-old platform that enables users to execute Python code live online. Leveraging Google’s advanced hardware, including GPUs and proprietary tensor processing units (TPUs), it delivers unparalleled computational performance for data-driven tasks. https://venturebeat.com/ai/google-launches-free-gemini-powered-data-science-agent-on-its-colab-python-platform/

AI Agent Store - Here you'll find a comprehensive AI agent marketplace, top AI agents directory, and a new AI Agency list for all your AI automation needs. Think of it as a store filled with specialized AI assistants, each designed to help in different ways. Buy or find a free AI agent suitable for the job which needs to be done. Browse curated collection which includes: - Ready-to-use AI agents - Top tools and frameworks to build your own agents - Platforms that help you create and manage agents https://aiagentstore.ai/

https://x.com/AndrewYNg/status/1882125891821822398 Our first short course with @AnthropicAI! Building Towards Computer Use with Anthropic. This teaches you to build an LLM-based agent that uses a computer interface by generating mouse clicks and keystrokes. Computer Use is an important, emerging capability for LLMs that will let AI agents do many more tasks than were possible before, since it lets them interact with interfaces designed for humans to use, rather than only tools that provide explicit API access. I hope you will enjoy learning about it! This course is taught by Anthropic's Head of Curriculum, @Colt_Steele. You'll learn to apply image reasoning and tool use to "use" a computer as follows: a model processes an image of the screen, analyzes it to understand what's going on, and navigates the computer via mouse clicks and keystrokes. This course goes through the key building blocks, and culminates in a demo of an AI assistant that uses a web browser to search for a research paper, downloads the PDF, and finally summarizes the paper for you. In detail, you’ll: - Learn about Anthropic's family of models, when to use which one, and make API requests to Claude - Use multi-modal prompts that combine text and image content blocks, and also work with streaming responses - Improve your prompting by using prompt templates, using XML to structure prompts, and providing examples - Implement prompt caching to reduce cost and latency - Apply tool-use to build a chatbot that can call different tools to respond to queries - See all these building blocks come together in Computer Use demo Please sign up here: https://deeplearning.ai/short-courses/building-towards-computer-use-with-anthropic

https://github.com/cline/cline Meet Cline, an AI assistant that can use your CLI and Editor. Cline can handle complex software development tasks step-by-step. With tools that let him create & edit files, explore large projects, use the browser, and execute terminal commands (after you grant permission), he can assist you in ways that go beyond code completion or tech support. Cline can even use the Model Context Protocol (MCP) to create new tools and extend his own capabilities. While autonomous AI scripts traditionally run in sandboxed environments, this extension provides a human-in-the-loop GUI to approve every file change and terminal command, providing a safe and accessible way to explore the potential of agentic AI. Enter your task and add images to convert mockups into functional apps or fix bugs with screenshots. Cline starts by analyzing your file structure & source code ASTs, running regex searches, and reading relevant files to get up to speed in existing projects. By carefully managing what information is added to context, Cline can provide valuable assistance even for large, complex projects without overwhelming the context window. Once Cline has the information he needs, he can: Create and edit files + monitor linter/compiler errors along the way, letting him proactively fix issues like missing imports and syntax errors on his own. Execute commands directly in your terminal and monitor their output as he works, letting him e.g., react to dev server issues after editing a file. For web development tasks, Cline can launch the site in a headless browser, click, type, scroll, and capture screenshots + console logs, allowing him to fix runtime errors and visual bugs. When a task is completed, Cline will present the result to you with a terminal command like open -a "Google Chrome" index.html, which you run with a click of a button. Usefull Links: https://marketplace.visualstudio.com/items?itemName=saoudrizwan.claude-dev https://github.com/cline/cline/blob/main/README.md https://github.com/cline/cline https://www.youtube.com/watch?v=8jpWHRRzyiE&ab_channel=TheMetaverseGuy