Artificial Intelligence
Category: Amazon Machine Learning
Build a foundation model (FM) powered customer service bot with Amazon Bedrock agents
From enhancing the conversational experience to agent assistance, there are plenty of ways that generative artificial intelligence (AI) and foundation models (FMs) can help deliver faster, better support. With the increasing availability and diversity of FMs, it’s difficult to experiment and keep up-to-date with the latest model versions. Amazon Bedrock is a fully managed service […]
Principal Financial Group uses AWS Post Call Analytics solution to extract omnichannel customer insights
An established financial services firm with over 140 years in business, Principal is a global investment management leader and serves more than 62 million customers around the world. Principal is conducting enterprise-scale near-real-time analytics to deliver a seamless and hyper-personalized omnichannel customer experience on their mission to make financial security accessible for all. They are […]
Foundational vision models and visual prompt engineering for autonomous driving applications
Prompt engineering has become an essential skill for anyone working with large language models (LLMs) to generate high-quality and relevant texts. Although text prompt engineering has been widely discussed, visual prompt engineering is an emerging field that requires attention. Visual prompts can include bounding boxes or masks that guide vision models in generating relevant and […]
Flag harmful content using Amazon Comprehend toxicity detection
Online communities are driving user engagement across industries like gaming, social media, ecommerce, dating, and e-learning. Members of these online communities trust platform owners to provide a safe and inclusive environment where they can freely consume content and contribute. Content moderators are often employed to review user-generated content and check that it’s safe and compliant […]
Harness large language models in fake news detection
Fake news, defined as news that conveys or incorporates false, fabricated, or deliberately misleading information, has been around as early as the emergence of the printing press. The rapid spread of fake news and disinformation online is not only deceiving to the public, but can also have a profound impact on society, politics, economy, and […]
Explore advanced techniques for hyperparameter optimization with Amazon SageMaker Automatic Model Tuning
Creating high-performance machine learning (ML) solutions relies on exploring and optimizing training parameters, also known as hyperparameters. Hyperparameters are the knobs and levers that we use to adjust the training process, such as learning rate, batch size, regularization strength, and others, depending on the specific model and task at hand. Exploring hyperparameters involves systematically varying […]
Build a medical imaging AI inference pipeline with MONAI Deploy on AWS
In this post, we show you how to create a MAP connector to AWS HealthImaging, which is reusable in applications built with the MONAI Deploy App SDK, to integrate with and accelerate image data retrieval from a cloud-native DICOM store to medical imaging AI workloads. The MONAI Deploy SDK can be used to support hospital operations. We also demonstrate two hosting options to deploy MAP AI applications on SageMaker at scale.
Harnessing the power of enterprise data with generative AI: Insights from Amazon Kendra, LangChain, and large language models
Large language models (LLMs) with their broad knowledge, can generate human-like text on almost any topic. However, their training on massive datasets also limits their usefulness for specialized tasks. Without continued learning, these models remain oblivious to new data and trends that emerge after their initial training. Furthermore, the cost to train new LLMs can […]
Use generative AI to increase agent productivity through automated call summarization
Your contact center serves as the vital link between your business and your customers. Every call to your contact center is an opportunity to learn more about your customers’ needs and how well you are meeting those needs. Most contact centers require their agents to summarize their conversation after every call. Call summarization is a valuable tool that helps contact centers understand and gain insights from customer calls. Additionally, accurate call summaries enhance the customer journey by eliminating the need for customers to repeat information when transferred to another agent. In this post, we explain how to use the power of generative AI to reduce the effort and improve the accuracy of creating call summaries and call dispositions. We also show how to get started quickly using the latest version of our open source solution, Live Call Analytics with Agent Assist.
Bundesliga Match Facts Shot Speed – Who fires the hardest shots in the Bundesliga?
There’s a kind of magic that surrounds a soccer shot so powerful, it leaves spectators, players, and even commentators in a momentary state of awe. Think back to a moment when the sheer force of a strike left an entire Bundesliga stadium buzzing with energy. What exactly captures our imagination with such intensity? While there […]









