Meshup is a tool I created with Kevin Dunnell at the MIT Media Lab’s Viral Communications Group to accelerate synthesizing complex ideas. We trained a GAN model on images of cars, creating a machine learning model that understood images of cars and could generate new images of cars.

What’s the combination of a red sports car and a blue truck?

It's a simple question you and I both understand. But how do we reach a shared understanding of our answer. Drawing + 3D modeling cars are time consuming processes. Meshup is an attempt to use generative AI to accelerate visualizing a shared idea.

Meshup is a tool designed to facilitate collaborative, accelerated idea generation. It leverages a machine learning model, specifically a Generative Adversarial Network (GAN), trained on a large dataset of car images. The result is a model capable of generating realistic images of cars that don't actually exist yet.

The interface allows users to upload images of existing cars, which are then projected into the latent space of the generative model. This latent space is a low-dimensional space where car images can be represented as a vector of numbers, essentially coordinates where similar looking cars exist.

These uploaded images appear in the user interface as targets. Team members can select these targets to "steer" the output design towards a car with similar characteristics. As the team iteratively chooses different targets, the output becomes a synthesis of these selections. The influence of each target on the synthesized design can be seen from the width of the line connecting the target to the output - a wider line corresponds to a stronger influence.

This tool allows for the quick generation of a starting point for design, serving as a working model for the entire team to visualize and immediately share an understanding around. The goal is not for the computer to do the creating, but rather to augment the ability of humans by offering inspiration and a starting point for further human refinement.

Above is a demo of 2 simulated users generating a new image at the same time. The site uses web sockets so multiple people can generate and "steer" outputs at the same time.