Favorite Posted by Ellery Wulczyn and Yun Liu, Google Research When a patient is diagnosed with cancer, one of the most important steps is examination of the tumor under a microscope by pathologists to determine the cancer stage and to characterize the tumor. This information is central to understanding clinical
Favorite At The Check Up, we shared updates on our medical LLM research, partnerships and new ways AI can help with disease detection. View Original Source (blog.google/technology/ai/) Here.
Favorite Amazon SageMaker Ground Truth Plus is a managed data labeling service that makes it easy to label data for machine learning (ML) applications. One common use case is semantic segmentation, which is a computer vision ML technique that involves assigning class labels to individual pixels in an image. For
Favorite This post is co-written with Mahima Agarwal, Machine Learning Engineer, and Deepak Mettem, Senior Engineering Manager, at VMware Carbon Black VMware Carbon Black is a renowned security solution offering protection against the full spectrum of modern cyberattacks. With terabytes of data generated by the product, the security analytics team
Favorite Introducing new generative AI capabilities in Google Cloud and Google Workspace, plus PaLM API and MakerSuite for developers. View Original Source (blog.google/technology/ai/) Here.
Favorite There are only four generic barriers to KM. These are they, and all can be addressed. The Boston Square shown here maps the unwillingness and the inability that can affect the knowledge supplier, and the knowledge user. Any combination of these is a block to the transfer of knowledge from one
Favorite Online fraud has a widespread impact on businesses and requires an effective end-to-end strategy to detect and prevent new account fraud and account takeovers, and stop suspicious payment transactions. Detecting fraud closer to the time of fraud occurrence is key to the success of a fraud detection and prevention
Favorite In this two-part series, we demonstrate how to label and train models for 3D object detection tasks. In part 1, we discuss the dataset we’re using, as well as any preprocessing steps, to understand and label data. In part 2, we walk through how to train a model on
Favorite Amazon SageMaker Data Wrangler reduces the time it takes to aggregate and prepare data for machine learning (ML) from weeks to minutes in Amazon SageMaker Studio. Data Wrangler enables you to access data from a wide variety of popular sources (Amazon S3, Amazon Athena, Amazon Redshift, Amazon EMR and Snowflake)
Favorite Posted by Danny Driess, Student Researcher, and Pete Florence, Research Scientist, Robotics at Google Recent years have seen tremendous advances across machine learning domains, from models that can explain jokes or answer visual questions in a variety of languages to those that can produce images based on text descriptions.