AWS for Industries

Category: Amazon SageMaker

Applying carbon value modeling to achieve net-zero

Climate change is one of the most pressing issues of our time, and it’s becoming increasingly clear that we need to take rapid action to reduce our carbon emissions. To be carbon-neutral by 2050 and keep the Earth’s mean temperature below 2° C of preindustrial levels, the world must curb emissions by 7.6 percent per […]

The Next Frontier: Generative AI for Financial Services

Generative artificial intelligence (AI) applications like ChatGPT have captured the headlines and imagination of the public. Generative AI is a type of AI that can create new content and ideas, including conversations, stories, images, videos, and music. Like all AI, generative AI is powered by machine learning (ML) models—very large models (known as Large Language […]

How Generative AI will transform manufacturing

Introduction Artificial intelligence (AI) and machine learning (ML) have been a focus for Amazon for decades, and we’ve worked to democratize ML and make it accessible to everyone who wants to use it, including more than 100,000 customers of all sizes and industries. This includes manufacturing companies who are looking beyond AI/ML to generative AI […]

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Generative AI for Telcos: taking customer experience and productivity to the next level

According to a recent Gartner® CEO survey – The Pause and Pivot Year, what is the “top new technology that CEOs believe will significantly impact their industry over the next three years”? You guessed it: Artificial Intelligence. “21% of CEO’s say AI is the top disruptive technology.”i Telcos are not alone in recognizing the immense […]

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How AWS is helping thredUP revolutionize the resale model for brands

Like global landfills, the fashion industry waste problem is growing by the second. Retailers are struggling to address an enormous (and pressing) concern: what happens to their products after point-of-sale and what are the environmental implications? In the United States, companies spend an estimated $50 billion on product returns. These returned goods are responsible for […]

How to manage and bill structured energy contracts on AWS

Energy companies are still using architectures based on monolithic systems when managing and billing energy service contracts. Architectures where the billing processes have been built using stored procedures inside a database are common. These architectures limit the capabilities of the business units to create, manage, and invoice contracts based on new products and services, especially […]

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The positive impact Generative AI could have for Retail

Since it was released back in November 2022, the internet has been buzzing about ChatGPT. Since then, retailers having been asking two main questions: what is it, and how will it impact my business? Let’s dive into both, staying high-level, and see if we can make sense of all the hype. What is Generative AI? […]

TC Energy innovates using AWS to improve document consistency and asset management

TC Energy operates one of North America’s largest energy infrastructure portfolios, delivering the energy that millions of people rely on to power their lives in a sustainable way. TC Energy’s portfolio includes three complimentary energy infrastructure businesses: A 93,300 km network of natural gas pipelines that supplies more than 25 percent of the daily clean-burning […]

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Top re:Invent 2022 takeaways for the advertising and marketing technology industry

There were a large number of new service announcements as well as partner and solution announcements that came out of AWS re:Invent 2022. To make it easy for advertising and marketing technology customers, we have identified a list of top announcements specific to this industry. Session summaries and access details to content on demand is […]

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How Machine Learning on AWS can help customers predict the risk of Automotive Part Recalls

This blog focuses on a potential method to use Long Short Term Memory (LSTM) machine learning models to help customers predict parts that are likely to become defects or recalls. Specifically, we show how predictions generated from an LSTM may provide customers with early indicators that generally out-perform existing manual processes and can help assist […]