Google Research
 | |
| Founded | 2000 |
|---|---|
| Founder | |
| Type | Division |
| Location | |
| Services | Computer science, Artificial intelligence |
Parent organization | Alphabet Inc. |
| Website | research.google |
Google Research (also known as Research at Google) is the research division of Google, a subsidiary of Alphabet. According to its official website, Google Research publishes findings, releases open-source software, and applies research results within Google products and services as well as within the wider scientific community.[1]
Notable contributions
[edit]- The 2017 landmark paper Attention Is All You Need, which introduced the Transformer architecture, which has subsequently been used to build modern large language models.[2]
- Advances in neural machine translation powering Google Translate.[3]
- Time series forecasting.[4]
- Development of scalable learning systems and infrastructure for large-model training.[5][additional citation(s) needed]
- Flood forecasting.[6]
- Research into computational discovery via Google Accelerated Science including demonstrating the first below-threshold quantum calculations.[7]
See also
[edit]References
[edit]- ↑ "Research at Google". Google Research. Retrieved 10 October 2025.
- ↑ Maxwell, Hugh; Langley, Thomas. "Google's top AI researchers, including all the authors behind a landmark paper, have left for competitors. Here's where they are now". Business Insider. Retrieved 2025-10-13.
- ↑ Wu, Yonghui; et al. (2016), Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation, doi:10.48550/ARXIV.1609.08144, retrieved 2026-09-17
- ↑ "google-research/timesfm". GitHub. GitHub, Inc. Retrieved 14 October 2025.
- ↑ Kurian, George; et al. (2025), Scalable Machine Learning Training Infrastructure for Online Ads Recommendation and Auction Scoring Modeling at Google, doi:10.48550/ARXIV.2501.10546
- ↑ "Flood Forecasting". Google Research. Google LLC. Retrieved 14 October 2025.
- ↑ Castelvecchi, Davide (2024-12-09). "'A truly remarkable breakthrough': Google's new quantum chip achieves accuracy milestone". Nature. 636 (8043): 527–528. Bibcode:2024Natur.636..527C. doi:10.1038/d41586-024-04028-3. ISSN 1476-4687. PMID 39653720.
