BREAKING: Google says it has broken through a bottleneck that has held back quantum computing for 20 years. Quantum computers need special building blocks called "magic states" to run useful programs. They are so hard to make that up to 95% of a machine's capacity could go to making them. Google's new method cuts errors by about 40x on its Willow chip, with a record 99.99% accuracy. This is the first time a practical fix for this problem has worked on real hardware, according to Google's research published in Science today.

Today we are announcing our biggest bet yet on our own silicon. Starting next calendar year, we will scale our Maia family to multi-gigawatt deployments, making it the primary inference system for our own product and services. And we’re introducing Maia 300, which delivers 40% more tokens per watt compared to leading GPU-based systems. We are already deploying Maia 200 across the US, Europe, and Australia, delivering up to 1.7x more tokens per watt across experiences in Teams and Copilot. Our goal is to build on the full-stack efficiency gains we’ve already seen, while continuing to bring the latest innovations from across the ecosystem into our fleet.