6x Less Memory. 8x Faster. Zero Loss. Google's TurboQuant Explained I UNPUZZLED

Google just quietly dropped something massive — and the memory chip market already felt it. TurboQuant is Google's new AI compression algorithm that shrinks the KV Cache — the working memory of every AI model — down to just 3 bits, with zero accuracy loss and zero retraining needed. In this video, I break down: → What the KV Cache is and why it's AI's biggest bottleneck → How PolarQuant converts vectors into polar coordinates to compress them efficiently → How QJL eliminates residual error using a single 1-bit transform → Why SK Hynix, Samsung & Micron stocks crashed on this news → What this means for the future of AI inference This is Google's DeepSeek moment — and it's just getting started. ───────────────────────────── 🔔 Subscribe for more such info 👍 Like if you learned something new 💬 Drop your thoughts in the comments ───────────────────────────── 📌 Chapters Intro What is the KV Cache? How TurboQuant Works Step 1: PolarQuant Step 2: QJL Transform Benchmark Results Market Impact What This Means For AI ───────────────────────────── #Google #TurboQuant #AI #MachineLearning #ArtificialIntelligence #LLM #AINews #GoogleAI #DeepLearning #TechNews