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The AWS DeepRacer League is the world’s first autonomous racing league, open to everyone and powered by machine learning (ML). AWS DeepRacer brings builders together from around the world, creating a community where you learn ML hands-on through friendly autonomous racing competitions. As we celebrate the achievements of over 560,000 participants from more than 150 …

Celebrating the final AWS DeepRacer League championship and road ahead Read More »

News publishers want to provide a personalized and informative experience to their readers, but the short shelf life of news articles can make this quite difficult. In news publishing, articles typically have peak readership within the same day of publication. Additionally, news publishers frequently publish new articles and want to show these articles to interested …

Provide a personalized experience for news readers using Amazon Personalize and Amazon Titan Text Embeddings on Amazon Bedrock Read More »

The number of generative artificial intelligence (AI) features is growing within software offerings, especially after market-leading foundational models (FMs) became consumable through an API using Amazon Bedrock. Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and …

Implementing tenant isolation using Agents for Amazon Bedrock in a multi-tenant environment Read More »

Incorporating generative artificial intelligence (AI) into your development lifecycle can offer several benefits. For example, using an AI-based coding companion such as Amazon Q Developer can boost development productivity by up to 30 percent. Additionally, reducing the developer context switching that stems from frequent interactions with many different development tools can also increase developer productivity. …

Connect the Amazon Q Business generative AI coding companion to your GitHub repositories with Amazon Q GitHub (Cloud) connector Read More »

Organizations spend a lot of resources, effort, and money on running their customer care operations to answer customer questions and provide solutions. Your customers may ask questions through various channels, such as email, chat, or phone, and deploying a workforce to answer those queries can be resource intensive, time-consuming, and unproductive if the answers to …

Elevate customer experience through an intelligent email automation solution using Amazon Bedrock Read More »

Retrieval Augmented Generation (RAG) is a state-of-the-art approach to building question answering systems that combines the strengths of retrieval and generative language models. RAG models retrieve relevant information from a large corpus of text and then use a generative language model to synthesize an answer based on the retrieved information. The complexity of developing and …

Build an end-to-end RAG solution using Knowledge Bases for Amazon Bedrock and the AWS CDK Read More »

Amazon Q Business is a fully managed service that lets you build interactive chat applications using your enterprise data. These applications can generate answers based on your data or a large language model (LLM) knowledge. Your data is not used for training purposes, and the answers provided by Amazon Q Business are based solely on …

Index website contents using the Amazon Q Web Crawler connector for Amazon Q Business Read More »

With the advent of generative AI solutions, a paradigm shift is underway across industries, driven by organizations embracing foundation models to unlock unprecedented opportunities. Amazon Bedrock has emerged as the preferred choice for numerous customers seeking to innovate and launch generative AI applications, leading to an exponential surge in demand for model inference capabilities. Bedrock …

Getting started with cross-region inference in Amazon Bedrock Read More »

Several factors can make remediating security findings challenging. First, the sheer volume and complexity of findings can overwhelm security teams, leading to delays in addressing critical issues. Findings often require a deep understanding of AWS services and configurations and require many cycles for validation, making it more difficult for less experienced teams to remediate issues …

Building automations to accelerate remediation of AWS Security Hub control findings using Amazon Bedrock and AWS Systems Manager Read More »

The proliferation of large language models (LLMs) in enterprise IT environments presents new challenges and opportunities in security, responsible artificial intelligence (AI), privacy, and prompt engineering. The risks associated with LLM use, such as biased outputs, privacy breaches, and security vulnerabilities, must be mitigated. To address these challenges, organizations must proactively ensure that their use …

Secure RAG applications using prompt engineering on Amazon Bedrock Read More »