SayTap: Language to quadrupedal locomotion

Favorite Posted by Yujin Tang and Wenhao Yu, Research Scientists, Google Simple and effective interaction between human and quadrupedal robots paves the way towards creating intelligent and capable helper robots, forging a future where technology enhances our lives in ways beyond our imagination. Key to such human-robot interaction systems is

Read More
Shared by Google AI Technology August 29, 2023

MLOps for batch inference with model monitoring and retraining using Amazon SageMaker, HashiCorp Terraform, and GitLab CI/CD

Favorite Maintaining machine learning (ML) workflows in production is a challenging task because it requires creating continuous integration and continuous delivery (CI/CD) pipelines for ML code and models, model versioning, monitoring for data and concept drift, model retraining, and a manual approval process to ensure new versions of the model

Read More
Shared by AWS Machine Learning August 29, 2023

RO-ViT: Region-aware pre-training for open-vocabulary object detection with vision transformers

Favorite Posted by Dahun Kim and Weicheng Kuo, Research Scientists, Google The ability to detect objects in the visual world is crucial for computer vision and machine intelligence, enabling applications like adaptive autonomous agents and versatile shopping systems. However, modern object detectors are limited by the manual annotations of their

Read More
Shared by Google AI Technology August 28, 2023

Announcing the Preview of Amazon SageMaker Profiler: Track and visualize detailed hardware performance data for your model training workloads

Favorite Today, we’re pleased to announce the preview of Amazon SageMaker Profiler, a capability of Amazon SageMaker that provides a detailed view into the AWS compute resources provisioned during training deep learning models on SageMaker. With SageMaker Profiler, you can track all activities on CPUs and GPUs, such as CPU

Read More
Shared by AWS Machine Learning August 25, 2023

Responsible AI at Google Research: Perception Fairness

Favorite Posted by Susanna Ricco and Utsav Prabhu, co-leads, Perception Fairness Team, Google Research Google’s Responsible AI research is built on a foundation of collaboration — between teams with diverse backgrounds and expertise, between researchers and product developers, and ultimately with the community at large. The Perception Fairness team drives

Read More
Shared by Google AI Technology August 25, 2023

Teaching language models to reason algorithmically

Favorite Posted by Hattie Zhou, Graduate Student at MILA, Hanie Sedghi, Research Scientist, Google Large language models (LLMs), such as GPT-3 and PaLM, have shown impressive progress in recent years, which have been driven by scaling up models and training data sizes. Nonetheless, a long standing debate has been whether

Read More
Shared by Google AI Technology August 24, 2023

Announcing Amazon S3 access point support for Amazon SageMaker Data Wrangler

Favorite We’re excited to announce Amazon SageMaker Data Wrangler support for Amazon S3 Access Points. With its visual point and click interface, SageMaker Data Wrangler simplifies the process of data preparation and feature engineering including data selection, cleansing, exploration, and visualization, while S3 Access Points simplifies data access by providing

Read More
Shared by AWS Machine Learning August 23, 2023