AWS Machine Learning Blog
Category: Artificial Intelligence
Demystifying machine learning at the edge through real use cases
October 2023: Starting in April 26th, 2024, you can no longer access Amazon SageMaker Edge Manager. For more information about continuing to deploy your models to edge devices, see SageMaker Edge Manager end of life. Edge is a term that refers to a location, far from the cloud or a big data center, where you […]
Text summarization with Amazon SageMaker and Hugging Face
In this post, we show you how to implement one of the most downloaded Hugging Face pre-trained models used for text summarization, DistilBART-CNN-12-6, within a Jupyter notebook using Amazon SageMaker and the SageMaker Hugging Face Inference Toolkit. Based on the steps shown in this post, you can try summarizing text from the WikiText-2 dataset managed […]
Take your intelligent search experience to the next level with Amazon Kendra hierarchical facets
Unstructured data continues to grow in many organizations, making it a challenge for users to get the information they need. Amazon Kendra is a highly accurate, intelligent search service powered by machine learning (ML). Amazon Kendra uses deep learning and reading comprehension to deliver precise answers, and returns a list of ranked documents that match […]
Easily customize your notifications while using Amazon Lookout for Metrics
We are excited to announce that you can now add filters to alerts and also edit existing alerts while using Amazon Lookout for Metrics. With this launch, you can add filters to your alerts configuration to only get notifications for anomalies that matter the most to you. You can also modify existing alerts as per […]
Use a pre-signed URL to provide your business analysts with secure access to Amazon SageMaker Canvas
Agility and security have historically been two aspects of IT of paramount importance for any company. With the simplification of access to advanced IT technologies thanks to low-code and no-code (LCNC) tools, an even bigger number of people must be enabled to access resources, without impacting security. For many companies, the solution has been to […]
Enable business analysts to access Amazon SageMaker Canvas without using the AWS Management Console with AWS SSO
IT has evolved in recent years: thanks to low-code and no-code (LCNC) technologies, an increasing number of people with varying backgrounds require access to tools and platforms that were previously a prerogative to more tech-savvy individuals in the company, such as engineers or developers. Out of those LCNC technologies, we have recently announced Amazon SageMaker […]
Create, train, and deploy a billion-parameter language model on terabytes of data with TensorFlow and Amazon SageMaker
The increasing size of language models has been one of the biggest trends in natural language processing (NLP) in recent years. Since 2018, we’ve seen unprecedented development and deployment of ever-larger language models, including BERT and its variants, GPT-2, T-NLG, and GPT-3 (175 billion parameters). These models have pushed the boundaries of possible architectural innovations. […]
Identify potential root cause in business-critical anomalies using Amazon Lookout for Metrics
We are excited to launch a causal contribution analysis capability in Amazon Lookout for Metrics that helps you to understand the potential root causes for the business-critical anomalies in the data. Previously, you were only given the root causes for a single anomaly per measure. You had to analyze to determine if causal relationships existed […]
Use AWS AI and ML services to foster accessibility and inclusion of people with a visual or communication impairment
AWS offers a broad set of artificial intelligence (AI) and machine learning (ML) services, including a suite of pre-trained, ready-to-use services for developers with no prior ML experience. In this post, we demonstrate how to use such services to build an application that fosters the inclusion of people with a visual or communication impairment, which […]
How service providers can use natural language processing to gain insights from customer tickets with Amazon Comprehend
Today, customers can raise support tickets through multiple channels like – web, mobile, chat-bots, emails, or phone calls. When a support ticket is raised by a customer, it is processed and assigned to a category based on the information provided in the ticket. It is then routed to the support group for resolution according to […]