Author: AI Generated Robotic Content

The challenges of keeping health data private — and why lineage-aware data deletion matters The global COVID-19 crisis, the first pandemic of its kind in recent history, brought about an unprecedented set of challenges. Faced with a public health crisis, governments around the world established far-reaching emergency measures in an attempt to “flatten the curve” and protect citizens. …

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Posted by Weicheng Kuo and Anelia Angelova, Research Scientists, Google Research, Brain Team Natural language enables flexible descriptive queries about images. The interaction between text queries and images grounds linguistic meaning in the visual world, facilitating a better understanding of object relationships, human intentions towards objects, and interactions with the environment. The research community has …

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Amazon SageMaker Data Wrangler reduces the time that it takes to aggregate and prepare data for machine learning (ML) from weeks to minutes in Amazon SageMaker Studio, the first fully integrated development environment (IDE) for ML. With Data Wrangler, you can simplify the process of data preparation and feature engineering, and complete each step of …

Read more “Configure a custom Amazon S3 query output location and data retention policy for Amazon Athena data sources in Amazon SageMaker Data Wrangler”

Pharmaceutical companies seeking approval from regulatory agencies such as the US Food & Drug Administration (FDA) or Japanese Pharmaceuticals and Medical Devices Agency (PMDA) to sell their drugs on the market must submit evidence to prove that their drug is safe and effective for its intended use. A team of physicians, statisticians, chemists, pharmacologists, and …

Read more “Use RStudio on Amazon SageMaker to create regulatory submissions for the life sciences industry”

Amazon SageMaker provides a suite of built-in algorithms, pre-trained models, and pre-built solution templates to help data scientists and machine learning (ML) practitioners get started on training and deploying ML models quickly. These algorithms and models can be used for both supervised and unsupervised learning. They can process various types of input data, including tabular, …

Read more “Churn prediction using Amazon SageMaker built-in tabular algorithms LightGBM, CatBoost, TabTransformer, and AutoGluon-Tabular”

Many machine learning (ML) use cases, like fraud detection, ad targeting, and recommendation engines, require near real-time predictions. The performance of these predictions is heavily dependent on access to the most up-to-date data, with delays of even a few seconds making all the difference. But it’s difficult to set up the infrastructure needed to support …

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New cloud services to support AI workflows and the launch of a new generation of GeForce RTX GPUs featured today in NVIDIA CEO Jensen Huang’s GTC keynote, which was packed with new systems, silicon, and software. “Computing is advancing at incredible speeds, the engine propelling this rocket is accelerated computing, and its fuel is AI,” …

Read more “Keynote Wrap-Up: NVIDIA CEO Unveils Next-Gen RTX GPUs, AI Workflows in the Cloud”

Recommender systems, the economic engines of the internet, are getting a new turbocharger: the NVIDIA Grace Hopper Superchip. Every day, recommenders serve up trillions of search results, ads, products, music and news stories to billions of people. They’re among the most important AI models of our time because they’re incredibly effective at finding in the …

Read more “Why the New NVIDIA Grace Hopper Superchip Is Ideal for Next-Gen Recommender Systems”