Google Just Made AI 8× More Efficient With One Breakthrough Tool

Google Just Shrunk 31GB of AI Memory Down to 4GB — What TurboVec Means for the Future of AI Infrastructure The AI Infrastructure Problem Nobody Talks About Everyone is obsessed with bigger models. GPT-5.5. Gemini. Claude. Open-source giants with hundreds of billions of parameters. But there is another problem quietly becoming one of the biggest cost drivers in AI: Memory. Not GPU memory for training. Not VRAM for inference. The memory required to store and search billions of vector embeddings powering Retrieval-Augmented Generation (RAG), AI agents, semantic search engines, recommendation syst…