Artificial Intelligence
Category: Customer Solutions
How Veritone uses Amazon Bedrock, Amazon Rekognition, Amazon Transcribe, and information retrieval to update their video search pipeline
This post is co-written with Tim Camara, Senior Product Manager at Veritone. Veritone is an artificial intelligence (AI) company based in Irvine, California. Founded in 2014, Veritone empowers people with AI-powered software and solutions for various applications, including media processing, analytics, advertising, and more. It offers solutions for media transcription, facial recognition, content summarization, object […]
Simple guide to training Llama 2 with AWS Trainium on Amazon SageMaker
Large language models (LLMs) are making a significant impact in the realm of artificial intelligence (AI). Their impressive generative abilities have led to widespread adoption across various sectors and use cases, including content generation, sentiment analysis, chatbot development, and virtual assistant technology. Llama2 by Meta is an example of an LLM offered by AWS. Llama […]
Improving inclusion and accessibility through automated document translation with an open source app using Amazon Translate
Organizations often offer support in multiple languages, saying “contact us for translations.” However, customers who don’t speak the predominant language often don’t know that translations are available or how to request them. This can lead to poor customer experience and lost business. A better approach is proactively providing information in multiple languages so customers can […]
Revolutionizing large language model training with Arcee and AWS Trainium
This is a guest post by Mark McQuade, Malikeh Ehghaghi, and Shamane Siri from Arcee. In recent years, large language models (LLMs) have gained attention for their effectiveness, leading various industries to adapt general LLMs to their data for improved results, making efficient training and hardware availability crucial. At Arcee, we focus primarily on enhancing […]
Scale AI training and inference for drug discovery through Amazon EKS and Karpenter
This is a guest post co-written with the leadership team of Iambic Therapeutics. Iambic Therapeutics is a drug discovery startup with a mission to create innovative AI-driven technologies to bring better medicines to cancer patients, faster. Our advanced generative and predictive artificial intelligence (AI) tools enable us to search the vast space of possible drug […]
Build an active learning pipeline for automatic annotation of images with AWS services
This blog post is co-written with Caroline Chung from Veoneer. Veoneer is a global automotive electronics company and a world leader in automotive electronic safety systems. They offer best-in-class restraint control systems and have delivered over 1 billion electronic control units and crash sensors to car manufacturers globally. The company continues to build on a […]
Understanding and predicting urban heat islands at Gramener using Amazon SageMaker geospatial capabilities
This is a guest post co-authored by Shravan Kumar and Avirat S from Gramener. Gramener, a Straive company, contributes to sustainable development by focusing on agriculture, forestry, water management, and renewable energy. By providing authorities with the tools and insights they need to make informed decisions about environmental and social impact, Gramener is playing a […]
Nielsen Sports sees 75% cost reduction in video analysis with Amazon SageMaker multi-model endpoints
This is a guest post co-written with Tamir Rubinsky and Aviad Aranias from Nielsen Sports. Nielsen Sports shapes the world’s media and content as a global leader in audience insights, data, and analytics. Through our understanding of people and their behaviors across all channels and platforms, we empower our clients with independent and actionable intelligence […]
Achieve DevOps maturity with BMC AMI zAdviser Enterprise and Amazon Bedrock
This blog post discusses how BMC Software added AWS Generative AI capabilities to its product BMC AMI zAdviser Enterprise. The zAdviser uses Amazon Bedrock to provide summarization, analysis, and recommendations for improvement based on the DORA metrics data.
The journey of PGA TOUR’s generative AI virtual assistant, from concept to development to prototype
This is a guest post co-written with Scott Gutterman from the PGA TOUR. Generative artificial intelligence (generative AI) has enabled new possibilities for building intelligent systems. Recent improvements in Generative AI based large language models (LLMs) have enabled their use in a variety of applications surrounding information retrieval. Given the data sources, LLMs provided tools […]









