Tag: #diffusion
Writing on GPUs, LLMs, MLOps, Kubernetes — and mindset · 8 posts
AI for Everyone, Part 6 — Drawing Digits From Words With a 1.11M Diffusion Model
We built a conditional diffusion model with 1.11 million parameters that draws a 0 when you type "zero". The forward process that adds noise is a single formula; the reverse process that restores the image is that same l
2026-08-24 · 8 min read #ai#diffusion#ddpm#generative#pytorchDiffusion LLMs That Write CUDA Kernels — DICE and Why Parallel Generation Might Help
DICE, a February 2026 preprint, claims that diffusion large language models beat autoregressive models of the same size at generating CUDA kernels, setting a new state of the art. The core idea: instead of writing one to
2026-07-11 · 6 min read #ai#llm#diffusion#cuda#gpuThe Rise of Diffusion LMs — Can They Become an Alternative to Autoregression
In June 2026 Google released DiffusionGemma, and text diffusion models are lighting up GeekNews and Hacker News. We critically analyze the structural limits of autoregressive generation, the principles of mask-based deno
2026-06-12 · 17 min read #llm#diffusion#text-generation#gemma#inferenceDiffusion Models Deep Dive — DDPM, Latent Diffusion, Classifier-Free Guidance, DDIM, Stable Diffusion Complete Guide (2025)
Diffusion models — the foundation of Stable Diffusion, DALL-E, Midjourney, and Sora. This post dissects diffusion models from scratch. Forward/Reverse diffusion process, DDPM and the variational lower bound, the score-ba
2026-04-15 · 25 min read #diffusion#generative-ai#stable-diffusion#ddpm#machine-learning2025 AI Research Trends: Top HuggingFace Papers and 10 Defining Research Directions
A developer-focused review of HuggingFace trending papers and the 10 defining AI research trends of 2025. DeepSeek-R1 pure RL reasoning, Nemotron-Cascade 30B/3B MoE, GRPO, PagedAttention, million-token context limitation
2026-03-21 · 15 min read #ai-research#papers#huggingface#reasoning#moeComplete Guide to Text-to-Image Model Training Methodologies: From GAN to Flow Matching
An in-depth, paper-based analysis of training methodologies for Text-to-Image generative model architectures spanning GAN, VAE, Diffusion, and Flow Matching. Comprehensively covers training strategies and fine-tuning tec
2026-03-01 · 51 min read #deep-learning#text-to-image#diffusion#stable-diffusion#generative-aiWan Text-to-Video/Image-to-Video and Z Image Turbo Complete Analysis: Architecture and Applications of Next-Gen Video/Image Generation Models
A complete analysis of Wan video generation models and Z Image Turbo covering architecture, performance, and practical applications.
2026-03-01 · 36 min read #wan#text-to-video#image-to-video#z-image-turbo#video-generationACE-Step: A New Paradigm in AI Music Generation — Complete Analysis of Architecture, Training Methods, and Practical Applications
An in-depth analysis of the ACE-Step music generation model covering its architecture, training methodology, and text-to-music generation principles, with comparisons against competing models like MusicGen, Suno, and Udi
2026-03-01 · 38 min read #ace-step#music-generation#ai-music#deep-learning#diffusion