Author: AI Generated Robotic Content

Amazon SageMaker is a fully-managed service that provides every developer and data scientist with the ability to quickly build, train, and deploy machine learning (ML) models at scale. ML is realized in inference. SageMaker offers four Inference options: Real-Time Inference Serverless Inference Asynchronous Inference Batch Transform These four options can be broadly classified into Online …

Read more “Getting started with deploying real-time models on Amazon SageMaker”

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, and is composed of tumors with significant molecular heterogeneity resulting from differences in intrinsic oncogenic signaling pathways [1]. Enabling precision medicine, anticipating patient preferences, detecting disease, and improving care quality for NSCLC patients are important topics among healthcare and life sciences (HCLS) …

Read more “Predict lung cancer survival status using multimodal data on Amazon SageMaker JumpStart”

As I type this blog in a Google Doc, I can’t help but think about how much we rely on digital documents to communicate, collaborate, and do business. Yet most of the data in documents remains un-analyzed. Even when documents are part of customer-facing workflows like processing a mortgage application or a contract, businesses frequently …

Read more “Document AI: A unified AI agent for your document processing needs”

Introduction In my experience, I have observed that it’s common in machine learning to surrender to the process of experimenting with many different algorithms in a trial and error fashion, until you get the desired result. My peers and I at Google have a People and Planet AI YouTube series where we talk about how …

Read more “Intro to deep learning to track deforestation in supply chains”

Posted by Noah Snavely and Zhengqi Li, Research Scientists, Google Research We live in a world of great natural beauty — of majestic mountains, dramatic seascapes, and serene forests. Imagine seeing this beauty as a bird does, flying past richly detailed, three-dimensional landscapes. Can computers learn to synthesize this kind of visual experience? Such a …

Read more “Infinite Nature: Generating 3D Flythroughs from Still Photos”

Amazon SageMaker Data Wrangler is a capability of Amazon SageMaker that makes it faster for data scientists and engineers to prepare high-quality features for machine learning (ML) applications via a visual interface. Data Wrangler reduces the time it takes to aggregate and prepare data for ML from weeks to minutes. With Data Wrangler, you can …

Read more “Cost-effective data preparation for machine learning using SageMaker Data Wrangler”

In December 2020, AWS announced the general availability of Amazon SageMaker JumpStart, a capability of Amazon SageMaker that helps you quickly and easily get started with machine learning (ML). JumpStart provides one-click fine-tuning and deployment of a wide variety of pre-trained models across popular ML tasks, as well as a selection of end-to-end solutions that …

Read more “Generate images from text with the stable diffusion model on Amazon SageMaker JumpStart”