Lucidly: Text and Image Art Symposium

Project Statement
One statement: Letting the model generate its own story through prompt generation with context and sound meaning.
My last iteration on this project aimed at generating multiple interpretations off a text prompt and engineering animations between them smoothly compiled as GIFs. This one would focus on the research of how to make the model interrogate itself, i.e generate prompts for itself on the go and in context with what happened before it. Core to the research would be finding a way mathematically to generate cohesive meaningfulness to human mind.

[My results from last model] (Lucidly – Google Drive). They were generated with one liner prompts.

Research report and Analysis on how to generate coherent text prompts and hence meaningful visual stories with animation.

Amit Singh (metamyth)
R&D, Paperplane Technology
Researcher, Active Inference Lab

Discord: metamyth #8558
USDC Wallet Address: 0x0159af752e0220ed3eef439bef36f982cc0a6fbf


This sounds really exciting. It can really help in interpreting the model’s predictions. Did you plan any experiments and test benchmark to test you approaches?

Yeah sure it does. My approaches will measure context in consecutive frames. You can think of this in transformer vocab as attention over frames/model outputs. More to be worked for sure, would love to know if you have something in mind.