First screen, captured .
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Neural Network Diffusion(arxiv.org)
199 points by vagabund | 74 comments
Diffusion models are real-time game engines(gamengen.github.io)
1087 points by jmorgan | 391 comments
Project page for GameNGen, a Google Research paper showing a diffusion model running a playable game in real time, with links to the paper, arXiv, and a demo video.
Related stories
Diffusion models from scratch, from a new theoretical perspective(chenyang.co)
342 points by jxmorris12 | 36 comments
A tutorial blog post by Chenyang Yuan explaining diffusion models from scratch through a new theoretical perspective.
Diffusion models are real-time game engines(gamengen.github.io)
1087 points by jmorgan | 391 comments
Project page for GameNGen, a Google Research paper showing a diffusion model running a playable game in real time, with links to the paper, arXiv, and a demo video.
Training language models to be warm and empathetic makes them less reliable(arxiv.org)
334 points by Cynddl | 333 comments
arXiv paper finding that fine-tuning language models to be warm and empathetic raises error rates and makes them more sycophantic on safety-critical tasks.
Visual Anagrams: Generating optical illusions with diffusion models(dangeng.github.io)
758 points by beefman | 64 comments
Project page for Visual Anagrams, a University of Michigan research paper using pretrained diffusion models to generate multi-view optical illusions.
Deep Learning Is Not So Mysterious or Different(arxiv.org)
445 points by wuubuu | 112 comments
arXiv paper by Andrew Gordon Wilson arguing deep learning generalization phenomena like benign overfitting and double descent are explainable by soft inductive biases.
A Design Space Exploration of Async/Await(cel.cs.brown.edu)
431 points by wcrichton | 124 comments
Brown University Cognitive Engineering Lab blog post summarizing a paper comparing how async/await designs differ across programming languages.