Tag: machine learning

Data is the fuel for AI; modern data is even more important for generative AI and advanced data analytics, producing more accurate, relevant, and impactful results. Modern data comes in various forms: real-time, unstructured, or user-generated. Each form requires a different solution. AWS’s data journey began with Amazon Simple Storage Service (Amazon S3) in 2006, […]

A data-driven approach empowers businesses to make informed decisions based on accurate predictions and forecasts, leading to improved operational efficiency and resource optimization. Machine learning (ML) systems have the remarkable ability to continuously learn and adapt, improving their performance over time as they are exposed to more data. This self-learning capability ensures that organizations can […]

Generative artificial intelligence (generative AI) is a type of AI used to generate content, including conversations, images, videos, and music. Generative AI can be used directly to build customer-facing features (a chatbot or an image generator), or it can serve as an underlying component in a more complex system. For example, it can generate embeddings […]

Today, we are delighted to introduce the latest version of the AWS Well-Architected Machine Learning (ML) Lens whitepaper. The AWS Well-Architected Framework provides architectural best practices for designing and operating ML workloads on AWS. It is based on six pillars: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and—a new addition to this revision—Sustainability. The […]

This blog post helps customers in mitigating distributed denial-of-service (DDoS) using AWS Shield Advanced, AWS WAF, and data science. We explore how to use these services along with machine learning (ML) to detect and mitigate DDoS attacks. Bad actors conduct DDoS attacks using botnets. Through botnets, attackers look for zero-day vulnerabilities—specifically on network devices such […]

Enterprises perform quality control to ensure products meet production standards and avoid potential brand reputation damage. As the cost of sensors decreases and connectivity increases, industries adopt real-time imagery analysis to detect quality issues. At the same time, artificial intelligence (AI) advancements enable advanced automation, reduce overall cost and project time, and produce accurate defect […]

It’s hard to imagine a world without computer chips. They are at the heart of the devices that we use to work and play every day. Currently, Amazon Web Services (AWS) is offering customers the next generation of computer chip, with lower cost, higher performance, and a reduced carbon footprint. This edition of Let’s Architect! […]

Though it seems like something out of a sci-fi movie, machine learning (ML) is part of our day-to-day lives. So often, in fact, that we may not always notice it. For example, social networks and mobile applications use ML to assess user patterns and interactions to deliver a more personalized experience. However, AWS services provide […]

Running machine learning (ML) inference on large datasets is a challenge faced by many companies. There are several approaches and architecture patterns to help you tackle this problem. But no single solution may deliver the desired results for efficiency and cost effectiveness. In this blog post, we will outline a few factors that can help […]

Customers from startups to enterprises observe increased revenue when personalizing customer interactions. Still, many companies are not yet leveraging the power of personalization, or, are relying solely on rule-based strategies. Those strategies are effort-intensive to maintain and not effective. Common reasons for not launching machine learning (ML) based personalization projects include: the complexity of aggregating […]