AWS News Blog
Category: Artificial Intelligence
AWS Weekly Roundup: Advanced capabilities in Amazon Bedrock and Amazon Q, and more (July 15, 2024).
July 16, 2024: Updated link for “IDE workspace context awareness in Amazon Q Developer chat” As expected, there were lots of exciting launches and updates announced during the AWS Summit New York. You can quickly scan the highlights in Top Announcements of the AWS Summit in New York, 2024. My colleagues and fellow AWS News […]
Vector search for Amazon MemoryDB is now generally available
Store, index, retrieve, and search vectors with in-memory performance for use cases like retrieval augmentation, semantic caching, and anomaly detection through single-digit millisecond queries.
Build enterprise-grade applications with natural language using AWS App Studio (preview)
Effortlessly build apps with AI-powered low-code tools, enabling organizations to create secure custom apps in minutes without dev teams – streamlining processes like claims, inventory, and approvals.
Amazon Q Apps, now generally available, enables users to build their own generative AI apps
Craft generative AI apps from conversations using natural language and approved data sources. Customize securely shared apps, specifying data sources per card and new APIs for programmatic app management.
Agents for Amazon Bedrock now support memory retention and code interpretation (preview)
Agents for Amazon Bedrock now offer Memory to retain user context and Code Interpreter to dynamically execute code snippets—whether for data analysis, visualization, or complex problem-solving.
Guardrails for Amazon Bedrock can now detect hallucinations and safeguard apps built using custom or third-party FMs
Guardrails for Amazon Bedrock adds hallucination detection and an independent API to fortify generative AI applications with customized guardrails across any model, ensuring responsible and trustworthy outputs.
Knowledge Bases for Amazon Bedrock now supports additional data connectors (in preview)
Enhance company knowledge bases with new Amazon Bedrock connectors for Confluence, Salesforce, SharePoint, and web domains – empowering RAG models with contextual data for more accurate and relevant responses.
Introducing Amazon Q Developer in SageMaker Studio to streamline ML workflows
Streamline your ML workflows with this generative AI assistant providing tailored guidance, code generation, and error troubleshooting, to build, train, and deploy models efficiently.