Anthropic AI Hackathon

You have one last chance to register for the event, and be the first to meet Claude from Anthropic

 Closing of Registration

Welcome to the 7 days of creation with TOP model on the market! We will start with intro from lablab.ai team!

Hackathon Opening

We will dive into the rules to get an access to Anthropic. Stay tuned!

Rules and API access

The tech overview on the Claude AI Assistant and tech tutorials recommendations for you.

Meet Anthropic's Claude

We will go through profile creation, team formation, communication with Mentors and more.

Getting around Discord and the Platform

Join OpenVoice Channel for Mentorship session about business strategy, bringing first users, fin strategy and more.

Mentor Session: Pawel Czech

Hurry up! That's the last time to be able to get access to Claude AI Assistant!

Deadline to submitting access form

It's the deadline to submit your projects!

The time is OVER!

Some cool things about intelligence geek!
Create an ecology based on large language generative models and diffusion models to help self-media practitioners conveniently design interesting pictures in various fields.

Geek1024

Vincent Chen


The concept hinges on the use of the Language to Language Model (LLM) command to generate prompts for the Stable Diffusion (SD) process, which then creates images. The LLM command converts linguistic instructions into AI-compatible formats, guiding the SD process. SD, a common AI technique, spreads information through a system until a stable state is achieved, making it effective for image generation.

The LLM command creates prompts that direct the SD process to create specific images. These prompts, which are linguistic instructions, are designed and coded strategically to guide the image generation process towards a desired outcome, like an image of a sunset over a calm lake.

Once the SD process starts with these prompts, it gradually transforms the initial state (a noise pattern or blank canvas) into a complex image that aligns with the prompts. This diffusion process ensures the image evolves in a stable, controlled manner, closely following the instructions in the prompts. The outcome is an image that accurately reflects the original LLM instructions.

This isn't the end, however. The image can then be used as input for further LLM commands, which create 'img2img' prompts for another round of SD, further transforming the image based on new instructions. This enables the creation of a variety of images, each interpreting the LLM-generated prompts uniquely.

This approach, combining the linguistic versatility of LLM commands with SD's transformation capabilities, creates a cycle of image generation and transformation. This cycle opens up extensive possibilities for creative expression and AI-assisted design, with each cycle potentially birthing a new artistic creation.

stable diffusion prompts generated by llm command, and after the img generated by SD, still can use the img2img prompts generated by llm command.

"Geek1024 team on Anthropic AI Hackathon Hackathon"

Team Idea

Submission