HELIX: Semantic Compression for AI Systems | 10x Smaller, Near-Lossless скачать в хорошем качестве

HELIX: Semantic Compression for AI Systems | 10x Smaller, Near-Lossless

0:00 Intro 0:07 Problem 1:01 What is helix 1:20 Helix illustration 1:33 Encode Demo 1:59 Materialization Demo 2:06 12MB file Quality Vs 1.3MB file quality(comparison) 2:15 Our API HELIX — A Semantic Storage Layer for AI Systems and Data Storage 🧠 What is HELIX? HELIX is a Semantic Codec that extracts key features, structures, and patterns from images — then uses AI to perfectly reconstruct them when needed. This enables up to 10x smaller file sizes while maintaining visual quality that's often indistinguishable from the original. 🎯 The Problem We Solve AI training datasets are exploding. Storage costs scale linearly. Carbon footprints grow. And traditional compression forces a painful tradeoff: quality vs. size. 💡 Our Solution Instead of storing raw pixels, HELIX stores the "recipe" — the semantic blueprint of an image. When you need it back, we use Gemini 3's multimodal intelligence to recreate it at any resolution, with near-lossless reconstruction. 🚀 Features • 2-5x (up to 10x) compression ratio • Near-lossless identity preservation • PyTorch/TensorFlow compatible for ML training • REST API & Python SDK for developers • Cross-platform HLX v2 format