All news with #amazon bedrock tag

🧠 Amazon Quick Suite now adds memory to its chat agents, enabling personalized responses based on prior conversations and stated preferences. The feature stores inferred user preferences—such as response format, acronyms, dashboards, and integrations—and lets users view and remove any remembered items. Users may also choose Private Mode, in which chats are not used to infer memories. Memory is currently available in US East (N. Virginia) and US West (Oregon).

🤖 Amazon GameLift Servers now offers AI-powered assistance within the AWS Console, leveraging Amazon Q Developer to deliver tailored guidance for game developers. The integrated assistant helps with game server integration, fleet configuration, and performance optimization by surfacing in-console recommendations and troubleshooting steps. It is intended to streamline decision making, reduce troubleshooting time, and improve resource utilization for cost savings and better player experiences. The feature is available in all supported regions except AWS China.

📣 Amazon Bedrock now offers TwelveLabs Pegasus 1.2 via Global cross-Region inference, expanding availability by 23 new Regions in addition to the seven where it was already supported. You can also access the model in all EU Regions using Geographic cross-Region inference to meet data-residency requirements. Pegasus 1.2 is a video-first model for long-form video-to-text generation and temporal understanding, enabling lower latency and simplified architecture for video-intelligence applications.

🚀 Amazon Bedrock now exposes an OpenAI-compatible Responses API on new service endpoints, enabling asynchronous inference for long-running workloads, streaming and non-streaming modes, and automatic stateful conversation reconstruction so developers no longer must resend full histories. The endpoints provide Chat Completions with reasoning-effort support for models served by Mantle, Amazon’s distributed inference engine. Integration requires only a base URL change for OpenAI SDK–compatible code, and support starts today for OpenAI’s GPT OSS 20B and 120B models, with additional models coming soon.

🔧 Amazon Bedrock now supports reinforcement fine-tuning, enabling developers to improve model accuracy without deep ML expertise or large labeled datasets. The service automates the reinforcement fine-tuning workflow and trains models by learning from feedback on multiple candidate responses, improving model judgment about what makes a good reply. AWS reports an average 66% accuracy gain over base models, allowing teams to deploy smaller, faster, and more cost-effective variants while maintaining quality. At launch the feature supports Amazon Nova 2 Lite, and it can be accessed via the Bedrock console or APIs.

🛠️ AWS announced the Apache Spark upgrade agent, a capability that automates and accelerates Spark version upgrades for Amazon EMR on EC2 and EMR Serverless. The agent performs automated code analysis across PySpark and Scala, identifies API and behavioral changes for Spark 2.4→3.5, and suggests precise code transformations. Engineers can invoke the agent from SageMaker Unified Studio, the Kiro CLI, or any MCP-compatible IDE, interact via natural-language prompts, review proposed edits, and approve implementations. Functional correctness is validated through data quality checks to help maintain processing accuracy during migration.

🤖AWS has introduced Amazon Nova 2, a next-generation family of foundation models now available in Amazon Bedrock. The release includes Nova 2 Lite, optimized for fast, cost-effective reasoning for everyday workloads, and Nova 2 Pro (Preview), designed for complex, multistep tasks. Both models support step-by-step reasoning, three thinking intensity levels, built-in tools such as code interpreter and web grounding, remote MCP tool support, and a one-million-token context window. Nova 2 Lite supports supervised fine-tuning on Bedrock and SageMaker; full fine-tuning is available on SageMaker. Nova 2 Pro is available in preview for Amazon Nova Forge customers with global cross-region inference.

🚀 Amazon Bedrock expanded its model catalog with 18 new fully managed open-weight models, the largest single addition to date. The offering includes Gemma 3, Mistral Large 3, NVIDIA Nemotron Nano 2, OpenAI gpt-oss variants and other vendor models. Through a unified API, developers can evaluate, switch, and adopt these models in production without rewriting applications or changing infrastructure. Models are available in supported AWS Regions.

🎙️ Amazon announced Amazon Nova 2 Sonic, a speech-to-speech model for natural, real-time conversational AI available via Amazon Bedrock. The model delivers streaming speech understanding robust to background noise and diverse speaking styles, expressive polyglot voices, turn-taking controllability, asynchronous tool calling, and a one‑million token context window. Developers can integrate Nova 2 Sonic with Amazon Connect, leading telephony providers, open-source frameworks, and Bedrock’s bidirectional streaming API; it’s initially available in select AWS Regions.

🚀 AWS AI Factories are now available to deploy high-performance AWS AI infrastructure inside customer data centers, combining AWS Trainium, NVIDIA GPUs, low-latency networking, and optimized storage. The service integrates Amazon Bedrock and Amazon SageMaker to provide immediate access to foundation models without separate provider contracts. AWS manages procurement, setup, and operations while customers supply space and power, enabling isolated, sovereign deployments that accelerate AI initiatives.

🚀 Amazon S3 Vectors is now generally available, delivering native, purpose-built vector storage and query capabilities in cloud object storage. It supports up to two billion vectors per index, 10,000 indexes per vector bucket, and offers up to 90% lower costs to upload, store, and query vectors. S3 Vectors integrates with Amazon Bedrock, SageMaker Unified Studio, and OpenSearch Service, supports SSE-S3 and optional SSE-KMS encryption with per-index keys, and provides tagging for ABAC and cost allocation.

🚀 Amazon Bedrock now offers Mistral Large 3 and the Ministral 3 family alongside additional Mistral AI checkpoints, giving customers early access to open-weight multimodal models. Mistral Large 3 employs a granular Mixture-of-Experts architecture with 41B active and 675B total parameters and supports a 256K context window for long-form comprehension and agentic workflows. The Ministral 3 series (14B, 8B, 3B) plus Voxtral and Magistral small models let developers choose scales optimized for production assistants, RAG systems, single-GPU edge deployment, or low-resource environments.

🔁 Amazon Bedrock AgentCore Runtime now supports bi-directional streaming, enabling real-time, continuous conversations where agents listen and respond simultaneously and handle interruptions or context shifts mid-turn. This removes stop-start friction in voice and text agents and preserves context across exchanges. Built into AgentCore Runtime, the capability reduces months of engineering work required to implement streaming infrastructure, letting developers focus on agent experiences rather than plumbing. Available in nine AWS Regions with consumption-based pricing.

🤖 Amazon API Gateway now supports the Model Context Protocol (MCP) via a proxy, enabling organizations to expose existing REST APIs to AI agents and MCP clients without modifying their applications. Integrated with Amazon Bedrock AgentCore's Gateway, the feature performs protocol translation, indexes APIs for semantic tool discovery, and eliminates the need to host additional intermediary infrastructure. It also enforces dual authentication to verify agent identities for inbound requests while managing secure outbound connections to REST endpoints. The capability is available in nine AWS Regions and follows Amazon Bedrock AgentCore pricing.

🔐 CrowdStrike integrates NVIDIA Nemotron via Amazon Bedrock to advance agentic security across the Falcon platform, enabling defenders to reason and act autonomously at scale. Falcon Fusion SOAR leverages Nemotron for adaptive, context-aware playbooks that prioritize alerts, understand relationships, and execute complex responses. Charlotte AI AgentWorks uses Bedrock-delivered models to create task-specific agents with real-time environmental awareness. The serverless Bedrock architecture reduces infrastructure overhead while preserving governance and analyst controls.

📘 Amazon Connect now supports connecting existing Amazon Bedrock Knowledge Bases directly to AI agents and allows multiple knowledge bases per agent. You can attach Bedrock KBs in a few clicks with no additional setup or data duplication, and leverage Bedrock connectors such as Adobe Experience Manager, Confluence, SharePoint, and OneDrive. With multiple KBs per agent, AI agents can query several sources in parallel for more comprehensive responses. This capability is available in all AWS Regions where both services are offered.

🤖 Amazon SageMaker Catalog now provides automated data classification that suggests business glossary terms during dataset publishing to reduce manual tagging and improve metadata consistency. The capability leverages Amazon Bedrock language models to analyze table metadata and schema and recommend relevant business and sensitive-data terms from organizational glossaries. Data producers receive AI-generated suggestions they can accept or modify before publishing, helping standardize vocabulary and improve data discoverability. The feature is available in multiple AWS regions and can be managed via SageMaker Unified Studio, the AWS CLI, or SDKs.

🚀 AWS announced a major expansion of its AI Competency, validating 60 partners across three new Agentic AI categories: Agentic AI Tools, Agentic AI Applications, and Agentic AI Consulting Services. The launch includes an AI agent in AWS Partner Central to provide immediate feedback and speed specialization approvals. Validated partners demonstrate production-grade capabilities using services such as Amazon Bedrock AgentCore, Strands Agents, and Amazon SageMaker AI, and must meet AWS standards for security, reliability, and responsible AI.

🧭 Amazon CloudWatch launched an AI-powered incident report generator that guides teams through a Five Whys root-cause analysis using a chat-based workflow powered by Amazon Q. The feature combines human inputs and automated analysis of incident data to recommend specific remediation and prevention measures. It is available at no additional cost in multiple AWS regions. To use it, create a CloudWatch investigation, click "Incident report," then select "Guide Me" in the Five Whys section.

🤖 AWS has launched the AWS AI League 2026 Championship, expanding its flagship AI tournament with new challenge tracks and a doubled prize pool of $50,000 to drive builder innovation. The program pairs a brief orientation with two competition tracks: a Model Customization track using Amazon SageMaker AI to fine-tune foundation models for domain-specific tasks, and an Agentic AI track using Amazon Bedrock AgentCore to build planning and execution agents. Enterprises can apply to host internal tournaments and receive AWS credits to run team competitions, while individual developers can compete at AWS Summits to test skills and build with AWS AI services.