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Embeddings play a key role in natural language processing (NLP) and machine learning (ML). Text embedding refers to the process of transforming text into numerical representations that reside in a high-dimensional vector space. This technique is achieved through the use of ML algorithms that enable the understanding of the meaning and context of data (semantic …

Getting started with Amazon Titan Text Embeddings Read More »

Improving how users discover new content is critical to increase user engagement and satisfaction on media platforms. Keyword search alone has challenges capturing semantics and user intent, leading to results that lack relevant context; for example, finding date night or Christmas-themed movies. This can drive lower retention rates if users can’t reliably find the content …

Build a movie chatbot for TV/OTT platforms using Retrieval Augmented Generation in Amazon Bedrock Read More »

This post was co-written with Ricardo Perdigao, Solution Architecture Manager at Mendix, a Siemens business. Mendix, a Siemens business, offers the low-code platform with the vision and execution designed for today’s complex software development challenges. Since 2005, we’ve helped thousands of organizations worldwide reimagine how they develop applications with our platform’s cutting-edge capabilities. Mendix allows …

How Mendix is transforming customer experiences with generative AI and Amazon Bedrock Read More »

In the first part of this three-part series, we presented a solution that demonstrates how you can automate detecting document tampering and fraud at scale using AWS AI and machine learning (ML) services for a mortgage underwriting use case. In this post, we present an approach to develop a deep learning-based computer vision model to …

Train and host a computer vision model for tampering detection on Amazon SageMaker: Part 2 Read More »

Circle to Search is now available on select premium Android smartphones — here are some helpful ways to use it.

With the advent of generative AI, today’s foundation models (FMs), such as the large language models (LLMs) Claude 2 and Llama 2, can perform a range of generative tasks such as question answering, summarization, and content creation on text data. However, real-world data exists in multiple modalities, such as text, images, video, and audio. Take …

Talk to your slide deck using multimodal foundation models hosted on Amazon Bedrock and Amazon SageMaker – Part 1 Read More »

When deploying a large language model (LLM), machine learning (ML) practitioners typically care about two measurements for model serving performance: latency, defined by the time it takes to generate a single token, and throughput, defined by the number of tokens generated per second. Although a single request to the deployed endpoint would exhibit a throughput …

Benchmark and optimize endpoint deployment in Amazon SageMaker JumpStart  Read More »

We’re publishing an AI Opportunity whitepaper to help ASEAN governments tap into AI’s vast potential.