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Introducing ASCII Magic v2 ✨ - A completely restructured interface focused on discoverability and performance - 100+ styles & shaders - Unique animations for each effect - 171 AI generative presets - 4K export - New stackable post processing effects - A new way to create ft. node editor... show more

Kailash

14,088 subscribers

16,689 Aufrufe • vor 1 Monat •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

32 Kommentare

Profilbild von Kailash

Kailashvor 1 Monat

Check it out at

Profilbild von abhidev

abhidevvor 1 Monat

Wooahh .. lets Gooo 🔥🔥🔥

Profilbild von Kailash

Kailashvor 1 Monat

🔥🔥

Profilbild von Sweta

Swetavor 1 Monat

Woahh!!! Crazyy🔥🫶🏻

Profilbild von Kailash

Kailashvor 1 Monat

yass thank you!!

Profilbild von The Boring Developer

The Boring Developervor 1 Monat

171 presets is a lot of ways to make text look weird in the best way, bookmarking this for when i inevitably need to procrastinate

Profilbild von Kailash

Kailashvor 1 Monat

Thanks!

Profilbild von Kailash

Kailashvor 1 Monat

🚀

Profilbild von Pratik

Pratikvor 1 Monat

banger video bro!

Profilbild von Kailash

Kailashvor 1 Monat

Thanks so much bro 👊

Profilbild von Arpit

Arpitvor 1 Monat

Will try all

Profilbild von Kailash

Kailashvor 1 Monat

letsgo! let me know how your experience was

Profilbild von Neelakshi

Neelakshivor 1 Monat

Looks so sick! Also the video is so damn smooth 🔥

Profilbild von Kailash

Kailashvor 1 Monat

Thanks so muchh🔥😇

Profilbild von Basit A. Khan

Basit A. Khanvor 1 Monat

that's amazing work bro

Profilbild von Kailash

Kailashvor 1 Monat

Thanks Basit🫶🔥

Profilbild von Deep

Deepvor 1 Monat

It is going to go huge miles for suree..... the beast asciiiii.....

Profilbild von Kailash

Kailashvor 1 Monat

yessir! it should. for the amount of effort put in

Profilbild von Kanha Meher

Kanha Mehervor 1 Monat

Bro's GOAT for a reason! 🔥

Profilbild von Kailash

Kailashvor 1 Monat

Hahah thanks so much man!

Profilbild von hashim

hashimvor 1 Monat

@BenjaminUIX Can’t wait for the mcp!

Profilbild von Kailash

Kailashvor 1 Monat

@BenjaminUIX dropping in a couple days!

Profilbild von Shubh

Shubhvor 1 Monat

letsgoo! keep em coming

Profilbild von Kailash

Kailashvor 1 Monat

Thanks brother🔥🔥🙏 Yes lots more coming soon

Profilbild von Putri Karunia

Putri Karuniavor 1 Monat

woo this is sick!! these look really good! ❤️‍🔥

Profilbild von Kailash

Kailashvor 1 Monat

Thank you so much Putri✨

Profilbild von BenjaminUIX

BenjaminUIXvor 1 Monat

Looks super cool 😎

Profilbild von Kailash

Kailashvor 1 Monat

Thanks bro🔥🙏

Profilbild von dudu

duduvor 1 Monat

Absolute banger of a launch video for a banger product! the MCP server will be game changing

Profilbild von Kailash

Kailashvor 1 Monat

Yesss! Thanks bro MCP coming soon

Profilbild von Adam 🌿 Unroot.design

Adam 🌿 Unroot.designvor 1 Monat

congrats, looks great. what got cut going from v1 to v2?

Profilbild von Hammermann

Hammermannvor 1 Monat

Been waiting for this!

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Tom Krcha

66,914 Aufrufe • vor 3 Tagen

New course: MCP: Build Rich-Context AI Apps with Anthropic. Learn to build AI apps that access tools, data, and prompts using the Model Context Protocol in this short course, created in partnership with Anthropic Anthropic and taught by Elie Schoppik Elie Schoppik, its Head of Technical Education. Connecting AI applications to external systems that bring rich context to LLM-based applications has often meant writing custom integrations for each use case. MCP is an open protocol that standardizes how LLMs access tools, data, and prompts from external sources, and simplifies how you provide context to your LLM-based applications. For example, you can provide context via third-party tools that let your LLM make API calls to search the web, access data from local docs, retrieve code from a GitHub repo, and so on. MCP, developed by Anthropic, is based on a client-server architecture that defines the communication details between an MCP client, hosted inside the AI application, and an MCP server that exposes tools, resources, and prompt templates. The server can be a subprocess launched by the client that runs locally or an independent process running remotely. In this hands-on course, you'll learn the core architecture behind MCP. You’ll create an MCP-compatible chatbot, build and deploy an MCP server, and connect the chatbot to your MCP server and other open-source servers. Here’s what you’ll do: - Understand why MCP makes AI development less fragmented and standardizes connections between AI applications and external data sources - Learn the core components of the client-server architecture of MCP and the underlying communication mechanism - Build a chatbot with custom tools for searching academic papers, and transform it into an MCP-compatible application - Build a local MCP server that exposes tools, resources, and prompt templates using FastMCP, and test it using MCP Inspector - Create an MCP client inside your chatbot to dynamically connect to your server - Connect your chatbot to reference servers built by Anthropic’s MCP team, such as filesystem, which implements filesystem operations, and fetch, which extracts contents from the web as markdown - Configure Claude Desktop to connect to your server and others, and explore how it abstracts away the low-level logic of MCP clients - Deploy your MCP server remotely and test it with the Inspector or other MCP-compatible applications - Learn about the roadmap for future MCP development, such as multi-agent architecture, MCP registry API, server discovery, authorization, and authentication MCP is an exciting and important technology that lets you build rich-context AI applications that connect to a growing ecosystem of MCP servers, with minimal integration work. Please sign up here!

New course: MCP: Build Rich-Context AI Apps with Anthropic. Learn to build AI apps that access tools, data, and prompts using the Model Context Protocol in this short course, created in partnership with Anthropic Anthropic and taught by Elie Schoppik Elie Schoppik, its Head of Technical Education. Connecting AI applications to external systems that bring rich context to LLM-based applications has often meant writing custom integrations for each use case. MCP is an open protocol that standardizes how LLMs access tools, data, and prompts from external sources, and simplifies how you provide context to your LLM-based applications. For example, you can provide context via third-party tools that let your LLM make API calls to search the web, access data from local docs, retrieve code from a GitHub repo, and so on. MCP, developed by Anthropic, is based on a client-server architecture that defines the communication details between an MCP client, hosted inside the AI application, and an MCP server that exposes tools, resources, and prompt templates. The server can be a subprocess launched by the client that runs locally or an independent process running remotely. In this hands-on course, you'll learn the core architecture behind MCP. You’ll create an MCP-compatible chatbot, build and deploy an MCP server, and connect the chatbot to your MCP server and other open-source servers. Here’s what you’ll do: - Understand why MCP makes AI development less fragmented and standardizes connections between AI applications and external data sources - Learn the core components of the client-server architecture of MCP and the underlying communication mechanism - Build a chatbot with custom tools for searching academic papers, and transform it into an MCP-compatible application - Build a local MCP server that exposes tools, resources, and prompt templates using FastMCP, and test it using MCP Inspector - Create an MCP client inside your chatbot to dynamically connect to your server - Connect your chatbot to reference servers built by Anthropic’s MCP team, such as filesystem, which implements filesystem operations, and fetch, which extracts contents from the web as markdown - Configure Claude Desktop to connect to your server and others, and explore how it abstracts away the low-level logic of MCP clients - Deploy your MCP server remotely and test it with the Inspector or other MCP-compatible applications - Learn about the roadmap for future MCP development, such as multi-agent architecture, MCP registry API, server discovery, authorization, and authentication MCP is an exciting and important technology that lets you build rich-context AI applications that connect to a growing ecosystem of MCP servers, with minimal integration work. Please sign up here!

Andrew Ng

142,256 Aufrufe • vor 1 Jahr