Post by The AI Compass

🔹 Running large AI models is expensive. Google just made it dramatically cheaper. Here's how; TurboQuant unveiled at ICLR 2026 — slashes the memory overhead of large context windows using two-step compression: PolarQuant + Quantized Johnson-Lindenstrauss. Translation? Powerful models now run faster, cheaper, and on smaller hardware. This could flip the economics of enterprise AI deployment overnight. 📍 What this means for data and AI teams: → On-device AI just became significantly more viable → Data centre costs for running LLMs could drop considerably → Efficiency, not just scale is becoming the new AI moat Raw power is no longer the only edge. Efficiency is the new competitive weapon. 📌 ♻️ Repost if AI infrastructure cost is on your roadmap. Follow us to stay updated on Ai and Data trends #TheAICompass #TurboQuant #AIInfrastructure #GoogleAI #DataScience