Researchers translate brain waves into scarily accurate images using Stable Diffusion AI

pcgamer.com:

Imagine having the ability to recall your memories with near perfect precision. As we move into an ever more AI-centric future, that dream looks set to come true. With researchers now having used Stable Diffusion to reconstruct pretty damn accurate, high resolution images by reading human brain waves, we could one day be pulling up images from the annals of our minds without having taken a single photograph.

Researchers Yu Takagi and Shinji Nishimoto, from the Graduate School of Frontier Biosciences at Osaka University, recently wrote a paper outlining how it's possible to reconstruct high res images(opens in new tab) (PDF) using latent diffusion models, by reading human brain activity gained from functional Magnetic Resonance Imaging (fMRI), «without the need for training or fine-tuning of complex deep generative models» (via Vice(opens in new tab)).

Considering we don't fully understand how the underlying translation happens in the brain, the results from this research are incredible. The fact Takagi and Nishimoto were able to coax high resolution images from the latent space using human brain waves is astonishing.

Alright, they say high resolution, but we're talking 512 x 512 pixels. Still, it's a darn sight better than the 256p the competition had managed, and with a much higher «semantic fidelity», too. In other words, the translations are actually vaguely recognisable, and representative of the original images participants had been shown.

Previous studies involved «training and possibly fine-tuning of generative models, such as GANs, with the same dataset used in the fMRI experiments», the researchers explain. It's challenging as these generative models are not only awkward as heck to work with, but the training