Categories: AI/ML News

Self-supervised AI learns physics to reconstruct microscopic images from holograms

Researchers have unveiled an artificial intelligence-based model for computational imaging and microscopy without training with experimental objects or real data. The team introduced a self-supervised AI model nicknamed GedankenNet that learns from physics laws and thought experiments. Informed only by the laws of physics that universally govern the propagation of electromagnetic waves in space, the researchers taught their AI model to reconstruct microscopic images using only random artificial holograms — synthesized solely from ‘imagination’ without relying on any real-world experiments, actual sample resemblances or real data.
AI Generated Robotic Content

Share
Published by
AI Generated Robotic Content

Recent Posts

What Illustrious models is everyone using?

I have experimented with many Illustrious models, with WAI, Prefect and JANKU being my favorites,…

1 hour ago

Large reasoning models almost certainly can think

Recently, there has been a lot of hullabaloo about the idea that large reasoning models…

2 hours ago

Too much screen time may be hurting kids’ hearts

More screen time among children and teens is linked to higher risks of heart and…

2 hours ago

I’m trying out an amazing open-source video upscaler called FlashVSR

Link : https://github.com/lihaoyun6/ComfyUI-FlashVSR_Ultra_Fast submitted by /u/Many-Ad-6225 [link] [comments]

1 day ago

Build reliable AI systems with Automated Reasoning on Amazon Bedrock – Part 1

Enterprises in regulated industries often need mathematical certainty that every AI response complies with established…

1 day ago

Cloud CISO Perspectives: AI as a strategic imperative to manage risk

Welcome to the second Cloud CISO Perspectives for October 2025. Today, Jeanette Manfra, senior director,…

1 day ago