This post is part of an ongoing series about governing the machine learning (ML) lifecycle at scale. To view this series from the beginning, start with Part 1. This post dives deep into how to set up data governance at scale using Amazon DataZone for the data mesh. The dataContinue Reading
In today’s data-intensive business landscape, organizations face the challenge of extracting valuable insights from diverse data sources scattered across their infrastructure. Whether it’s structured data in databases or unstructured content in document repositories, enterprises often struggle to efficiently query and use this wealth of information. In this post, we exploreContinue Reading
This post is co-written with Kaustubh Kambli from DXC Technology. DXC Technology is an IT services leader with more than 130,000 employees supporting 6,000 customers in over 70 countries. DXC builds offerings across industry verticals to deliver accelerated value to their customers. One of the sectors DXC has deep expertiseContinue Reading
Generative AI has transformed customer support, offering businesses the ability to respond faster, more accurately, and with greater personalization. AI agents, powered by large language models (LLMs), can analyze complex customer inquiries, access multiple data sources, and deliver relevant, detailed responses. In this post, we guide you through integrating AmazonContinue Reading
In the modern, cloud-centric business landscape, data is often scattered across numerous clouds and on-site systems. This fragmentation can complicate efforts by organizations to consolidate and analyze data for their machine learning (ML) initiatives. This post presents an architectural approach to extract data from different cloud environments, such as GoogleContinue Reading
Machine learning (ML) helps organizations to increase revenue, drive business growth, and reduce costs by optimizing core business functions such as supply and demand forecasting, customer churn prediction, credit risk scoring, pricing, predicting late shipments, and many others. Conventional ML development cycles take weeks to many months and requires sparseContinue Reading
Have you ever faced the challenge of obtaining high-quality data for fine-tuning your machine learning (ML) models? Generating synthetic data can provide a robust solution, especially when real-world data is scarce or sensitive. For instance, when developing a medical search engine, obtaining a large dataset of real user queries andContinue Reading
Amazon SageMaker Ground Truth is a powerful data labeling service offered by AWS that provides a comprehensive and scalable platform for labeling various types of data, including text, images, videos, and 3D point clouds, using a diverse workforce of human annotators. In addition to traditional custom-tailored deep learning models, SageMakerContinue Reading
Customers across all industries are experimenting with generative AI to accelerate and improve business outcomes. Generative AI is used in various use cases, such as content creation, personalization, intelligent assistants, questions and answers, summarization, automation, cost-efficiencies, productivity improvement assistants, customization, innovation, and more. Generative AI solutions often use Retrieval AugmentedContinue Reading
Amazon Lookout for Vision, the AWS service designed to create customized artificial intelligence and machine learning (AI/ML) computer vision models for automated quality inspection, will be discontinuing on October 31, 2025. New customers will not be able to access the service effective October 10, 2024, but existing customers will beContinue Reading
