Parse notes
A great summary of the language modeling industry. There are good discussions here on safety, capabilities, chips, and more. The predictions around AI filmmaking, capital costs, and AI-fueled IPOs are interesting.
Using iterative re-embedding and treating embedding inversion as a conditional generation problem allows attackers to successfully recreate 92% of the embedded texts just with access to the dense vectors.
Researchers have improved the segmentation of specific targets in optical coherence tomography angiography (OCTA) images with a method called SAM-OCTA.
Researchers studied how to produce high-quality images at large sizes using pre-trained diffusion models trained on smaller images. They discovered issues with repeated patterns in the bigger images and pinpointed the problem to the limited perception of the model's structures.
Researchers are improving how we communicate with text-to-image models, like Midjourney and Stable Diffusion, which currently require complex prompts for generating images. They've introduced "interactive text to image", allowing people to naturally interact with Large Language Models for better image creation and related tasks.
Framework to enable agent system deployment.