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://youtu.be/TfqioNAP1W4?si=BaUNulKcAGQq1axA In this video, I’ll show you the simplest method to equip your AI agents with tools in seconds, using nothing but natural language! With this approach, you can spin up advanced AI agents in minutes, allowing them to take action, retrieve data, and automate workflows effortlessly. Whether you're a beginner or more advanced, this method makes building AI agents easier than ever.

https://www.promptingguide.ai/agents/introduction In this guide, we refer to an agent as an LLM-powered system designed to take actions and solve complex tasks autonomously. Unlike traditional LLMs, AI agents go beyond simple text generation. They are equipped with additional capabilities, including: Planning and reflection: - AI agents can analyze a problem, break it down into steps, and adjust their approach based on new information. - Tool access: They can interact with external tools and resources, such as databases, APIs, and software applications, to gather information and execute actions. - Memory: AI agents can store and retrieve information, allowing them to learn from past experiences and make more informed decisions. This lecture discusses the concept of AI agents and their significance in the realm of artificial intelligence.

https://www.loom.com/share/7a169d8cd05d4eba8a662adc53d6ab65?t=0 I'm so excited to see you here! Now, you have full access to the AI with Armand newsletter. My mission is to help you become a better AI practitioner – even a professional AI expert if you aspire to that. There are steps you can take right now... 1. AI Agents in 10 days Join my 10-day AI Agents email course and master the essentials in just 5 minutes a day. Each concise lesson focuses on practical applications to boost your AI knowledge. Your first email arrives tomorrow! 2. Learn the Basics of AI in 15 days Join my 15-day Generative AI email course, and learn with just 5 minutes a day. You'll receive concise daily lessons focused on practical business applications. It is perfect for quickly learning and applying core AI concepts.

https://browser-use.com Browser Use is the easiest way to connect your AI agents with the browser. It makes websites accessible for AI agents by providing a powerful, yet simple interface for browser automation.

https://scrimba.com/the-ai-engineer-path-c02v Build apps powered by generative AI - an essential 2024 skill for product teams at startups, agencies, and large corporations. Welcome to the AI Engineer Path This course isn't focused on complex AI research or model training. It's a practical, JavaScript-powered track designed for intermediate and advanced web developers who are eager to use the latest AI tech to elevate their skills. Many experts believe that the "AI Engineer" will be the most sought-after engineering role of the next decade! So by completing this course you'll be positioning yourself at the forefront of technological innovation. Along the way you'll complete many exciting Solo Projects. These are your chance to independently build your own apps, test your new AI knowledge, and gain the muscle memory you need to be a genuinely effective AI Engineer. Are you ready to embark on this thrilling adventure into AI engineering? Let's do this! Course breakdown Discover the following technologies: 1 OpenAI API A powerful tool to build applications that can understand and generate human-like text. 2 HuggingFace The Hugging Face Hub works as a central place where anyone can share, explore, discover, and experiment with open-source ML. 3 Embeddings and vector databases Infuse your apps with specialized knowledge that standard models can only dream of. 4 AI Agents Interact with the world and use AI to solve problems and complete tasks. 5 OpenAI's Assistants API Your trusty sidekick for seamlessly integrating AI models into your apps. 6 Langchain Effortlessly enhance your sites and apps with powerful AI language capabilities, and with a focus on your context.

https://www.paymanai.com/ Imagine work for and getting paid by AI ??? The Financial Layer for AI Agents Payman provides the critical financial infrastructure that lets AI Agents handle money safely and securely. Build AI applications that can receive deposits, manage balances, and send payments - all with built-in compliance and controls. Payman is the financial infrastructure that empowers AI Agents to move money securely and efficiently. With built-in compliance, human oversight, and seamless integration, it's got all developers need to trust AI with money.

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://www.pythagora.ai/ Build. Debug. Deploy. All in one tool. Prompt, run, edit and deploy full-stack web apps. Pythagora is a VS Code / Cursor extension powered by fourteen different AI agents that work together to plan, write code, review it, build tests, debug, and deploy full-stack web applications with ease. Pythagora uses a combination of advanced language models from providers such as OpenAI and Anthropic. THis platform is backed by Y-combinator.

https://www.vccafe.com/2024/09/26/ai-agents-the-evolution-of-rpa/?amp This article discusses the AI Agent Frameworks for 2024. The 2024 AI Agent Ecosystem framework provides a useful categorisation of the emerging layers in AI development: Ecosystem Layer: Foundational models (like OpenAI’s GPT) and enterprise tools form the bedrock. Application Layer: Thousands of companies will build agent apps, leveraging multimodal capabilities and no-code tools. Management Layer: Critical functions include managing AI agents, securing permissions, and enabling payments. Data Layer: AI agents will rely on both exclusive private data and public datasets.

Stay updated with the latest developments in AI agents, tools, and frameworks. Our curated news coverage keeps you informed about the most important advances in artificial intelligence. https://ai-agents.news/news