Google Research tackles challenges that define the technology of today and tomorrow.
Advancing the state of the art
Our approach
Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field.
Our researchers publish regularly in academic journals, release projects as open source, and apply research to Google products.
Explore a sample of our research
Researchers at Google are working in many domains.
See some of our latest research developments from the Google AI blog and elsewhere.
Quantum Advantage in Learning from Experiments
Quantum Computing
Quantum Advantage in Learning from Experiments
Google at CVPR 2022
Machine Perception
Google at CVPR 2022
Scanned Objects by Google Research: A Dataset of 3D-Scanned Common Household Items
Robotics
Scanned Objects by Google Research: A Dataset of 3D-Scanned Common Household Items
Minerva: Solving Quantitative Reasoning Problems with Language Models
Natural Language Processing
Minerva: Solving Quantitative Reasoning Problems with Language Models
Identifying Disfluencies in Natural Speech
Speech Processing
Identifying Disfluencies in Natural Speech
MLGO: A Machine Learning Framework for Compiler Optimization
Machine Intelligence
MLGO: A Machine Learning Framework for Compiler Optimization
Enabling Creative Expression with Concept Activation Vectors
Human Computer Interaction & Visulaization
Enabling Creative Expression with Concept Activation Vectors
We reimagine technology across all areas of Computer Science research.
Learn how we challenge conventions.
Publications
We publish hundreds of research papers each year and present our work in a wide range of venues.
See some of our most recent research.
Continuous Control and Multiscale Sensor Fusion with Neural CDEs
IROS & RSS Imitation Learning Workshop (2022) (to appear)
Detection and Prevention of Silent Data Corruption in an Exabyte-scale Database System
The 18th IEEE Workshop on Silicon Errors in Logic – System Effects, IEEE (2022)
What Do We Mean by Generalization in Federated Learning?
International Conference on Learning Representations (ICLR) (2022)
Rax: Composable Learning-to-Rank using JAX
KDD 2022 (to appear)
Teams & people
Meet the people behind our innovation
Our teams advance the state of the art through research, systems engineering, and collaboration across Google.
Join us
We're always looking for more talented, passionate people
Our global reach means that research teams across the company tackle tough problems together.