Amazon unveils Q chatbot

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Amazon has unveiled Q, an AI-powered chatbot designed for businesses. Announced at Amazon's re:Invent conference, Q is integrated into the AWS Management Console and existing chat and business apps like Slack. It is designed to answer questions, generate content, and take actions based on an understanding of a company's systems, data repositories, and operations1. Q is trained on 17 years' worth of AWS knowledge and can provide a list of potential solutions to queries, along with reasons for considering each proposal. It can understand the nuances of app workloads, suggesting AWS solutions and products for specific needs. For example, it can recommend the best EC2 instance for an app that requires high performance for video encoding and transcoding, taking into account performance and cost considerations1. In addition to answering questions, Q can troubleshoot issues like network connectivity problems by analyzing network configurations and providing remediation steps. It can also generate tests to benchmark software within a supported IDE, such as Amazon's own CodeCatalyst, drawing on knowledge of a customer's code. Q can create draft plans for implementing new features in software, transforming code, and upgrading code packages, repositories, and frameworks1. Q is designed to help employees with daily tasks, such as summarizing strategy documents, filling out internal support tickets, and answering questions about company policy. It is built to be more secure and private than a consumer chatbot, with the ability to emulate the same security permissions that business customers have already set up for their users2. Amazon Q is not built on a specific AI model. Instead, it uses an Amazon platform known as Bedrock, which connects several AI systems together, including Amazon’s own Titan as well as ones developed by Anthropic and Meta2. The chatbot is currently available to AWS users in select parts of the US, with one tier costing $20 per month per user and another tier that includes extra features for technical staff costing $25 per month per user3.
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