Live intelligence

Latest AI updates

23 updates

Products Editor selected

Taxbit Assist: A grounded, role-aware AI agent on Amazon Bedrock AgentCore

Taxbit built a permission-aware, citation-grounded AI assistant inside its digital-asset tax compliance dashboard using Amazon Bedrock AgentCore. The post details its architecture: Strands Agents SDK on AgentCore runtime, Bedrock Guardrails screening, a curated Bedrock Knowledge Bases index backed by Amazon S3 Vectors, Cohere embeddings and reranking, and per-session isolation. It also shares retrieval lessons such as excluding marketing pages, prepending document scope to chunks, and enforcing citation eligibility in code, plus continuous production evaluation and human-corrected answers.

Why it matters: It offers a concrete, production-tested case study of retrieval, grounding, identity binding and evaluation practices for shipping a regulated-domain AI agent.

AWS Machine Learning Blog2h agoScore 81

AWSAmazon BedrockTaxbit

Tutorial

Amazon Bedrock AgentCore runtime adds session endpoints for live web app previews

AWS introduced session endpoints for Amazon Bedrock AgentCore runtime, giving each agent session an authenticated URL that forwards HTTP/1.1, HTTP/2 and WebSocket traffic to ports the developer explicitly allows. The post walks through a sample coding agent that keeps a Vite dev server running inside its microVM session, so developers can watch a site update in the browser as the agent saves files. It covers port configuration, SigV4 or JWT authentication, a local-endpoint proxy for browser clients, and the specific 403, 404 and 502 refusal codes the runtime returns.

AWS Machine Learning Blog6d agoScore 78

Amazon Bedrock AgentCorecoding agentsAWS

Industry Editor selected

Exowatt beats frontier models on accuracy with SageMaker serverless model customization

Exowatt used Amazon SageMaker AI serverless model customization to build a repeatable AI pipeline that fine-tunes small open-weight models for edge and cloud deployment. The fine-tuned Qwen3-1.7B and Qwen3-14B models outperformed frontier models like Claude Opus 4.7 on specific tasks, achieving higher accuracy at up to 49x lower cost. The pipeline, built with seven AWS serverless services, enabled rapid experimentation and production deployment in days rather than months.

Why it matters: This case study provides concrete evidence that fine-tuned small models can beat frontier models on narrow tasks with significant cost savings, offering a practical blueprint for AI teams.

AWS Machine Learning BlogOct 28, 2026Score 88

model customizationedge AIenergy infrastructure

Tutorial Editor selected

AWS details multi-turn reinforcement learning on SageMaker AI

AWS published a hands-on guide to Multi-Turn Reinforcement Learning (MTRL) on Amazon SageMaker AI, which trains models on end-of-episode rewards rather than per-step labels. Agents hosted on Bedrock AgentCore (or EKS, EC2, Fargate) play multi-step tasks and return a single reward, with GRPO updating a LoRA adapter. In the guide's Wordle example, gpt-oss-20b improved its solve rate on held-out words from 61% to 84% at default reasoning effort and from 15% to 69% at low effort, at roughly $339 in

Why it matters: It gives practitioners a concrete, cost-transparent walkthrough of agentic multi-turn RL on a major cloud platform, including benchmark numbers, supported models and failure modes.

AWS Machine Learning BlogOct 24, 2026Score 83

AWSAmazon SageMaker AIMulti-Turn Reinforcement Learning

Tutorial

AWS CDK construct automates SageMaker AI endpoint auto scaling during updates

The AWS Machine Learning Blog describes a reusable CDK construct that replaces native Application Auto Scaling resources for SageMaker AI endpoints with three CloudFormation custom resources. The construct deregisters scalable targets before an endpoint update and re-registers the target and scaling policy afterward, avoiding update failures and silent loss of auto scaling. Asynchronous completion handlers wait for the endpoint to reach InService and the scalable target to become queryable. A Co

AWS Machine Learning BlogOct 24, 2026Score 71

AWSAmazon SageMaker AIAWS CDK

Products

Amazon Polly Generative engine upgrade adds 14 voices, Hindi and Finnish

AWS upgraded the Amazon Polly Generative text-to-speech engine, improving expressiveness and accuracy for numbers, currency and addresses at low latency. The release adds 14 new voices across 9 locales, including the first generally available Generative voices in Hindi and Finnish, bringing the catalog to 57 voices across 11 languages and 25 locales. The upgrade is a drop-in change: existing voice names and SynthesizeSpeech/StartSpeechSynthesisStream API calls are unchanged, with no price increa

AWS Machine Learning BlogOct 23, 2026Score 70

Amazon PollyAWSText-to-speech

Products

AWS SageMaker AI adds serverless training sessions for custom post-training loops

Amazon SageMaker AI has made training sessions generally available within its serverless model customization offering, letting users write their own post-training loop—custom loss functions, reward signals, and multi-turn RL stages—while AWS handles GPU allocation, distributed execution, fault recovery, and checkpoint storage. Supported techniques include SFT, DPO, RLVR, RLAIF, and multi-turn RL with LoRA or full fine-tuning, and an agent-assisted cookbook aims to automate data prep, technique c

AWS Machine Learning BlogOct 23, 2026Score 79

Amazon SageMaker AIpost-training and RL fine-tuningserverless ML infrastructure

Products

Rescale builds AI triage agent with Strands Agents and AI-DLC

Rescale built an AI triage agent to automatically classify and route nightly end-to-end test failures, using Claude on Amazon Bedrock, the Strands SDK, MCP-based log retrieval through Amazon CloudWatch, and a knowledge base of historical failures. The agent runs in Rescale's existing Argo Workflows CI/CD pipeline on Amazon EKS, producing structured remediation reports for engineer validation. The company reported that classification agreement with human triage rose from 44% to 68% and that time

AWS Machine Learning BlogOct 23, 2026Score 68

RescaleAWSAI agents

Tutorial Editor selected

AWS details production architecture for its open-source Deep Insight multi-agent system

AWS Solutions Architecture published the first part of a series on Deep Insight, an open-source multi-agent system that turns CSV data and natural-language prompts into validated analysis reports. The post describes eight role-specialized agents (Coordinator, Planner, Supervisor, Coder, Validator, Reporter, Tracker, Plan Reviewer) built with the Strands Agents SDK Graph and Agents-as-Tools patterns, with model selection tiered across Claude Haiku, Opus and Sonnet via Amazon Bedrock. It also outl

Why it matters: It offers concrete, reusable architectural guidance and trade-offs for teams moving multi-agent systems from prototype to production, backed by open-source code.

AWS Machine Learning BlogOct 22, 2026Score 80

AWSmulti-agent systemsagent orchestration

Tutorial

AWS demonstrates hybrid SLM/cloud agent routing with Strands Agents

AWS's Machine Learning Blog walks through the Adaptive Agentic Intelligence Framework (AAIF), built on Strands Agents, which uses a small local orchestrator model (llama3.2:1b via Ollama) to classify requests and route routine tasks to on-device models while escalating complex queries to cloud models on Amazon Bedrock. The post provides working code for local telemetry and vision tools, a Bedrock expert-insights tool, and deployment variants spanning edge, fully cloud, and air-gapped configurati

AWS Machine Learning BlogOct 22, 2026Score 68

AWSStrands AgentsAmazon Bedrock

Tutorial

AWS and Keyfactor detail X.509 PKI identity architecture for AI agents using MCP

An AWS Machine Learning Blog post describes a reference architecture for giving AI agents verifiable, revocable cryptographic identities using Keyfactor EJBCA X.509 PKI on AWS. The design adds signed request envelopes with nonces and timestamps, user-signed delegation assertions, RFC 8693 audience-scoped tokens, and real-time OCSP revocation checks across three trust boundaries: user-to-system, agent-to-agent, and agent-to-MCP-tool-server. It uses Amazon Bedrock with the Strands Agents SDK, Keyc

AWS Machine Learning BlogOct 21, 2026Score 75

AWSKeyfactor EJBCAModel Context Protocol

Tutorial

AtScale's dimensional semantic layer exposed to Bedrock AgentCore agents via MCP

AWS's latest semantic-layer post in its series swaps AtScale in for Stardog and Denodo, modeling a Customer 360 domain in AtScale's open YAML-based Semantic Modeling Language versioned in Git. A single deployed AtScale model is served simultaneously over SQL, XMLA and MCP, letting a Strands agent hosted on Amazon Bedrock AgentCore and existing BI tools get the same computed answers from shared metric definitions. The article details query planning and pushdown to Amazon Redshift Serverless, auto

AWS Machine Learning BlogOct 20, 2026Score 68

semantic layeragentic AIAWS

Products Editor selected

Amazon Bedrock adds structured outputs for Anthropic Claude models

Amazon Bedrock now supports structured outputs for all Anthropic Claude models on the bedrock-runtime and bedrock-mantle endpoints. The feature uses constrained decoding to enforce a JSON schema during token generation, which the post says makes output formatting deterministic and removes the need for custom parsing or retry logic. It covers JSON Schema output format and strict tool use, works with batch inference, cross-Region inference and streaming, and caches compiled grammars for 24 hours.

Why it matters: This gives teams building on Bedrock a concrete way to get schema-compliant JSON from Claude without custom validation code, which matters for data extraction and agent tool calls.

AWS Machine Learning BlogOct 20, 2026Score 80

Amazon BedrockAnthropic ClaudeAWS

Products

TwelveLabs Pegasus 1.5 video model lands on Amazon Bedrock

TwelveLabs' Pegasus 1.5 is now available in Amazon Bedrock, adding time-based metadata generation that returns every matching video segment as structured JSON with start and end times. The release adds video segmentation, multimodal prompting with reference images, on-the-fly processing from S3 or base64 without pre-indexing, and support for videos up to two hours in a single request. It is invoked via the bedrock-runtime InvokeModel and InvokeModelWithResponseStream APIs in us-west-2.

AWS Machine Learning BlogOct 20, 2026Score 68

Amazon BedrockTwelveLabs Pegasusvideo language models

Tutorial Editor selected

Push-based KV transfer in vLLM cuts TTFT up to 3x for disaggregated inference

AWS describes a push-based NIXL KV connector for vLLM's prefill-decode disaggregated serving, contributed upstream as an accelerator-agnostic feature. Instead of the decode instance pulling KV blocks after prefill, the decode side registers target blocks in advance and the prefill side issues an NIXL WRITE from a background thread, removing the router round trip and setup work from the TTFT critical path. On a 1P1D deployment with EC2 P5en instances and EFA, the Qwen3-32B benchmark showed up to

Why it matters: It gives concrete benchmark data and implementation guidance for a real vLLM latency optimization that teams running disaggregated inference can adopt.

AWS Machine Learning BlogOct 20, 2026Score 82

vLLMLLM inference servingAWS

Tutorial

AWS details nine-stage evaluation framework for production AI agents on Bedrock AgentCore

AWS's SMGS Operations team describes a production multi-agent system for its field sales organization and the nine-stage continuous evaluation framework it built on Amazon Bedrock AgentCore Evaluations. The framework spans quality definition, experiments, CI/CD gates, canary scoring, adversarial testing, drift detection, live monitoring and automated feedback. The post documents real pre-launch failures, such as revenue misreported in millions and ungrounded figures, and reports that a mismatche

AWS Machine Learning BlogOct 17, 2026Score 75

Amazon Bedrock AgentCoreAI agent evaluationAWS

Products

AWS introduces "Trust in Depth" framework for governing autonomous AI agents

AWS outlined a governance approach called Trust in Depth for letting AI agents act with more autonomy while keeping them within verifiable limits. The framework has four layers—Scope, Know, Bound and Observe—combining automated reasoning proofs of precise rules with deterministic policy enforcement outside the agent's reasoning, agent identity tracking, and production observability. It is backed by AWS services including Policy and identity controls in Amazon Bedrock AgentCore, Automated Reasoni

AWS Machine Learning BlogOct 15, 2026Score 75

AWSAmazon BedrockAI agent governance

Tutorial

AWS shows self-improving agentic document processing on Bedrock AgentCore

AWS published a tutorial describing a multi-agent intelligent document processing system built on Amazon Bedrock AgentCore. Eight specialized agents classify, extract, validate, and save reusable instructions for new document formats using AWS services including Amazon Textract, S3 Vectors, Aurora DSQL, Lambda, and AgentCore Gateway. The post provides a deployable sample repository, sample purchase order flows, estimated costs, and guidance for adapting schemas, validators, and prompts to other

AWS Machine Learning BlogOct 15, 2026Score 72

Amazon Bedrock AgentCoreAWSDocument AI