All the articles with the tag "computer-vision".
A high level view on how modern vision-language models connect pixels and prose, from CLIP and BLIP to Flamingo, MiniGPT-4, Kosmos, and Gemini.
A deep dive into the physics and probability of diffusion models. Learn how reversing a stochastic process became the foundation for modern generative AI, from Stable Diffusion to robotics and protein design.
The evolution of image diffusion architectures. Learn how we moved from convolutional U-Nets to scalable Diffusion Transformers (DiT), and why treating images like language changed everything.
Exploring the state-of-the-art in video generation. Learn how Sora and Veo use Spatiotemporal Transformers to simulate the physical world, and the challenges of achieving perfect motion fidelity.
How to train a world-class diffusion model. Covers the complete lifecycle: from large-scale pre-training on noisy web data to specialized post-training, alignment, and aesthetic fine-tuning.
How to move from visual imitation to law-governed motion. Deep dive into injecting PDEs into neural networks, implicit physics extraction, and LLM-guided physical reasoning.