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The latest research from Google

Leveraging transfer learning for large scale differentially private image classification

Large deep learning models are becoming the workhorse of a variety of critical machine learning (ML) tasks. However, it has been shown that without any protection it is plausible for bad actors to attack a variety of models, across modalities, to reveal information from individual training examples. As such, it’s essential to protect against this sort of information leakage.

PRESTO – A multilingual dataset for parsing realistic task-oriented dialogues

Detecting novel systemic biomarkers in external eye photos

Visual language maps for robot navigation

Vid2Seq: a pretrained visual language model for describing multi-event videos

Responsible AI at Google Research: The Impact Lab

Learning from deep learning: a case study of feature discovery and validation in pathology

PaLM-E: An embodied multimodal language model

The BirdCLEF 2023 Challenge: Pushing the frontiers of biodiversity monitoring

Announcing the ICDAR 2023 Competition on Hierarchical Text Detection and Recognition

Universal Speech Model (USM): State-of-the-art speech AI for 100+ languages