Amazon Bedrock provides you with an easy way to build and scale generative AI applications with leading foundation models (FMs). Continued pre-training in Amazon Bedrock is a new capability that allows you to train Amazon Titan Text Express and Amazon Titan Text Lite FMs and customize them using your own unlabeled data, in a secure and managed environment. As models are continually pre-trained on data spanning different topics, genres, and contexts over time, they become more robust and learn to handle out-of-domain data better by accumulating wider knowledge and adaptability, creating even more value for your organization.

Amazon Bedrock is an easy way to build and scale generative AI applications with leading foundation models (FMs). Amazon Bedrock now supports fine-tuning for Meta Llama 2 and Cohere Command Light, along with Amazon Titan Text Lite and Amazon Titan Text Express FMs, so you can use labeled datasets to increase model accuracy for particular tasks.

Today, we are announcing Guardrails for Amazon Bedrock in preview that enables customers to implement safeguards across foundation models (FMs) based on their use cases and responsible AI policies. Customers can create multiple guardrails tailored to different use cases and apply them across multiple FMs, providing a consistent user experience and standardizing safety controls across generative AI applications.

Now generally available, fully managed Knowledge Bases for Amazon Bedrock securely connects foundation models (FMs) to internal company data sources for Retrieval Augmented Generation (RAG) to deliver more relevant, context-specific, and accurate responses. Knowledge bases extend the FM’s powerful capabilities to make it more knowledgeable about your business, customers, and offerings.

We are excited to announce the public preview of Amazon Q in AWS Chatbot, which provides summarized and concise answers to customers’ AWS-related queries in a conversational experience in Microsoft Teams and Slack. Customers receive concise and trustworthy answers to their questions to accelerate their understanding of the AWS services, architect solutions, and troubleshoot issues.

Today, Amazon QuickSight announces three new natural language capabilities enabled by Amazon Q for business users. Launching in preview, these capabilities can summarize dashboards, generate mini dashboards to answer data questions, and build stories explaining data.

Amazon Web Services (AWS) is announcing the public preview of Amazon Q in the AWS Console Mobile Application. AWS customers using the AWS Console Mobile App for Android can now use Amazon Q, the generative AI assistant in the AWS Console Mobile App to ask questions about AWS services, and receive concise, reliable answers in a mobile-friendly user interface with voice input and output capabilities.

Amazon Connect now supports two-way Short Messaging Service (SMS) capabilities, making it easy for you to resolve customer issues via text messaging. SMS offers a ubiquitous and convenient channel for customers to get help, while enabling you to deliver personalized experiences at a lower cost.

Amazon Connect now provides in-app and web voice and video calling capabilities, making it easier to deliver more personalized voice and video experiences in your websites and mobile applications. These voice and video capabilities allow customers to contact you without having to leave your website or mobile application. You can use these capabilities to pass contextual information to Amazon Connect, enabling you to personalize the customer experience based on attributes such as the customer’s profile, authentication status, or actions previously taken within the app.

Amazon Connect Customer Profiles now provides a generative AI powered customer data mapping capability that significantly reduces the time needed to create unified profiles, enabling companies to help provide more personalized customer experiences faster.