https://modelcontextprotocol.io/quickstart/user#why-claude-for-desktop-and-not-claude-ai https://modelcontextprotocol.io/examples

Build reliable AI applications Prompt quality plays a significant role in how successful a model's responses are for a given task. The Anthropic Console already streamlines AI development with tools to write, evaluate, and optimize prompts more efficiently. Write prompts: Use the Workbench to structure your prompts effectively, incorporate examples, and integrate external tools, in an interactive environment for testing API calls. Automatically generate prompts: Describe what you want to achieve, and Claude will use prompt engineering techniques such as chain-of-thought reasoning to create an effective, precise, and reliable prompt. Evaluate model responses: Evaluate your prompts against real-world scenarios with automatic test case generation and side-by-side output comparison. Easily run test suites, grade response quality, and make data-driven decisions about which prompts to deploy. Improve prompts: Automatically refine prompts using advanced prompt engineering techniques. This is ideal for adapting prompts that were originally written for other AI models, as well as for optimizing hand-written prompts. https://www.anthropic.com/

Somebody please stop China they are on 🔥🔥. Wan from Alibaba Group has just open-sourced Wan 2.1 and it is better than OpenAI Sora - Text-to-Video - Image-to-Video - Video Editing - Text-to-Image - Video-to-Audio 10 wild examples and more details below! https://x.com/ai_for_success/status/1894415856467415140

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