Tag: #vision-language
Writing on GPUs, LLMs, MLOps, Kubernetes — and mindset · 4 posts
Analyzing SOTA Multimodal LLMs — One Model to See, Hear, and Speak
How did a language model trained purely on text come to understand and generate images, audio, and video? This post walks through modality encoders and projectors, the unified token space, the any-to-any flow, native mul
2026-06-30 · 22 min read #multimodal-llm#any-to-any#vision-language#audio#architectureMultimodal Tokenization and Fusion — Turning Images and Audio Into Tokens
A deep look at how images, audio, and video become tokens and get woven into one sequence with text. We cover patch and VQ image tokenization, discrete-codec audio tokenization, frame sampling, interleaving and separator
2026-06-26 · 14 min read #llm#multimodal#tokenization#vision-language#q-formerMultimodal AI Training Methods — Many Senses in One Model
A walkthrough of how multimodal AI learns to handle images, text, audio, and video in a single model. We cover modality alignment and contrastive learning, fusion strategies, shared embedding spaces, pretraining and fine
2026-06-26 · 15 min read #ai-papers#multimodal#clip#vision-language#contrastive-learningMultimodal AI Complete Guide: Master CLIP, LLaVA, GPT-4V, and Gemini Vision
A complete guide to mastering multimodal AI from fundamentals to the latest vision-language models. Learn CLIP, BLIP-2, LLaVA, InstructBLIP, GPT-4V, Gemini Vision, and Claude Vision with practical code, plus Multimodal R
2026-03-17 · 25 min read #multimodal#vision-language#clip#llava#gpt-4v