Favorite Digital experience interruptions can harm customer satisfaction and business performance across industries. Application failures, slow load times, and service unavailability can lead to user frustration, decreased engagement, and revenue loss. The risk and impact of outages increase during peak usage periods, which vary by industry—from ecommerce sales events to

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Shared by AWS Machine Learning December 4, 2024

Favorite Amazon Q Business is a generative AI-powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in your enterprise systems. Although generative AI is fueling transformative innovations, enterprises may still experience sharply divided data silos when it comes to enterprise

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Shared by AWS Machine Learning December 4, 2024

Favorite Today, the Accounts Payable (AP) and Accounts Receivable (AR) analysts in Amazon Finance operations receive queries from customers through email, cases, internal tools, or phone. When a query arises, analysts must engage in a time-consuming process of reaching out to subject matter experts (SMEs) and go through multiple policy

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Shared by AWS Machine Learning December 3, 2024

Favorite Chronos-Bolt is the newest addition to AutoGluon-TimeSeries, delivering accurate zero-shot forecasting up to 250 times faster than the original Chronos models [1]. Time series forecasting plays a vital role in guiding key business decisions across industries such as retail, energy, finance, and healthcare. Traditionally, forecasting has relied on statistical

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Shared by AWS Machine Learning December 3, 2024

Favorite In Part 1 of this series, we introduced Amazon SageMaker Fast Model Loader, a new capability in Amazon SageMaker that significantly reduces the time required to deploy and scale large language models (LLMs) for inference. We discussed how this innovation addresses one of the major bottlenecks in LLM deployment: the

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Shared by AWS Machine Learning December 3, 2024

Favorite The generative AI landscape has been rapidly evolving, with large language models (LLMs) at the forefront of this transformation. These models have grown exponentially in size and complexity, with some now containing hundreds of billions of parameters and requiring hundreds of gigabytes of memory. As LLMs continue to expand,

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Shared by AWS Machine Learning December 3, 2024

Favorite Today at AWS re:Invent 2024, we are excited to announce the new Container Caching capability in Amazon SageMaker, which significantly reduces the time required to scale generative AI  models for inference. This innovation allows you to scale your models faster, observing up to 56% reduction in latency when scaling

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Shared by AWS Machine Learning December 3, 2024

Favorite Today at AWS re:Invent 2024, we are excited to announce a new feature for Amazon SageMaker inference endpoints: the ability to scale SageMaker inference endpoints to zero instances. This long-awaited capability is a game changer for our customers using the power of AI and machine learning (ML) inference in

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Shared by AWS Machine Learning December 3, 2024

Favorite This post is co-written with Abhishek Sawarkar, Eliuth Triana, Jiahong Liu and Kshitiz Gupta from NVIDIA.  At re:Invent 2024, we are excited to announce new capabilities to speed up your AI inference workloads with NVIDIA accelerated computing and software offerings on Amazon SageMaker. These advancements build upon our collaboration

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Shared by AWS Machine Learning December 3, 2024

Favorite As developers gear up for re:Invent 2024, they again face the unique challenges of physical racing. What are the obstacles? Let’s have a look. In this blog post, I will look at what makes physical AWS DeepRacer racing—a real car on a real track—different to racing in the virtual

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Shared by AWS Machine Learning December 2, 2024