Google Research introduce PASTA, a reinforcement learning agent that refines text-to-image output over multiple turns of interaction with a user by learning their unique preferences. This process is made possible by a novel user simulation technique. You have a perfect image in your mind. You enter a prompt, hit generate, and the result is close […]
A collaborative approach to image generation : PASTA Read More »
Voice Search is now powered by our new Speech-to-Retrieval engine, which gets answers straight from your spoken query without having to convert it to text first, resulting in a faster, more reliable search for everyone. Voice-based web search has been around a long time and continues to be used by many people, with the underlying
Speech-to-Retrieval (S2R): A new approach to voice search Read More »
XR Blocks is an open-source framework to help you develop immersive experiences for the web, featuring XR realism, XR interaction, and AI + XR applications with live demos in xrblocks.github.io. The combination of artificial intelligence (AI) and extended reality (XR) has the potential to unlock a new paradigm of immersive intelligent computing. However, a significant gap
Introducing Coral NPU, a full-stack, open-source platform designed to address the core performance, fragmentation, and privacy challenges that limit powerful, always-on AI with low-power edge devices and wearables. Generative AI has fundamentally reshaped our expectations of technology. We’ve seen the power of large-scale cloud-based models to create, reason and assist in incredible ways. However, the
DeepSomatic is an AI-powered tool that identifies cancer-related mutations in a tumor’s genetic sequence to help pinpoint what’s driving the cancer. Cancer is fundamentally a genetic disease in which the genetic controls on cell division go awry. Many types of cancer exist, and each poses unique challenges as it can have distinct genetic underpinnings. A
Using AI to identify genetic variants in tumors with DeepSomatic Read More »
We present LAVA, a new scheduling algorithm that continuously re-predicts and adapts to the actual lifetimes of virtual machines to optimize resource efficiency in large cloud data centers. Imagine a puzzle game similar to Tetris with pieces rapidly falling onto a stack. Some fit perfectly. Others don’t. The goal is to pack the blocks as
Solving virtual machine puzzles: How AI is optimizing cloud computing Read More »
In a publication in Nature Astronomy, we show how Google’s Gemini model can be transformed into an expert astronomy assistant that classifies cosmic events with high accuracy and explains its reasoning in plain language, achieving 93% accuracy across three datasets by learning from just 15 annotated examples per survey. Modern astronomy is a treasure hunt
Teaching Gemini to spot exploding stars with just a few examples Read More »
We introduce a method for generating differentially private synthetic photo albums that uses an intermediate text representation and produces the albums in a hierarchical fashion. Differential privacy (DP) provides a powerful, mathematically rigorous assurance that sensitive individual information in a dataset remains protected, even when a dataset is used for analysis. Since DP’s inception nearly two decades
In our latest Nature publication, we introduce a new quantum computational task measuring Out-of-Time-Order Correlators (OTOCs). This work demonstrates a verifiable quantum advantage and paves the way for solving real-world problems like Hamiltonian learning in Nuclear Magnetic Resonance (NMR). Nature is brimming with chaos, a phenomenon characterized by the high sensitivity of a system toward small perturbations.
Google Earth AI is our family of geospatial AI models and reasoning agents that provides users with actionable insights, grounded in real-world understanding. Today, we’re sharing our latest Earth AI innovations and expanding access to these new capabilities on Google Earth and Google Cloud. For years, Google has developed AI models that enhance our understanding
