Artificial Intelligence

Category: Announcements

Reduce LLM latency with prefix-aware routing on Amazon SageMaker Inference

Reduce LLM latency with prefix-aware routing on Amazon SageMaker Inference

Amazon SageMaker Inference now offers prefix-aware routing, a routing strategy that sends requests sharing the same prompt prefix to the same instance so the KV cache stays warm. In benchmarks on Llama 3.1 70B, it reduced P50 time-to-first-token by up to 77% and raised KV cache hit rates from about 25% to over 80%.

Reduce inference cold starts on Amazon SageMaker HyperPod with model caching

Reduce inference cold starts on Amazon SageMaker HyperPod with model caching

Amazon SageMaker HyperPod now supports model caching for inference, which pre-loads model weights and container images onto cluster nodes so pods read from local NVMe storage instead of downloading over the network. Learn how model caching cuts cold starts from tens of minutes to seconds, how it works, and how to enable it.

Video and image search in Amazon Bedrock Knowledge Base using Marengo 3.0

Video and image search in Amazon Bedrock Knowledge Base using Marengo 3.0

TwelveLabs Marengo Embed 3.0 is now generally available as an embedding model in Amazon Bedrock Knowledge Bases, bringing fully managed natural language search to video, image, and audio content. This walkthrough shows how to build a knowledge base powered by Marengo 3.0 and run semantic queries against your media.

Amazon Quick is now generally available on desktop

Your teams get an AI assistant that handles real work while your data stays in your environment and your conversations stay private Today, the Amazon Quick desktop application is generally available on macOS and Windows. We’re also adding a new activity feed to the mobile experience on iOS and Android that consolidates email, calendar, CRM, […]

Pathway’s brain-inspired architecture development on Amazon SageMaker HyperPod

Pathway’s brain-inspired architecture development on Amazon SageMaker HyperPod

Pathway’s Baby Dragon Hatchling (BDH) is a brain-inspired, post-transformer architecture that reasons in latent space instead of emitting chain-of-thought tokens. See how Pathway develops and scales BDH on Amazon SageMaker HyperPod, and how BDH-CQ set a new cost-efficiency mark on the ARC-AGI-1 benchmark.

Amazon SageMaker Feature Store introduces UpdateRecord for feature-level writes

Amazon SageMaker Feature Store introduces UpdateRecord for feature-level writes

Amazon SageMaker Feature Store now supports feature-level writes. With the new UpdateRecord API, you can update one or more feature values in a single call without reading or rewriting the entire record. It is available for both the Standard (Amazon DynamoDB) and In-Memory (Amazon ElastiCache) online store tiers.

Govern models with MLflow and Amazon SageMaker AI Model Registry sync part 2

Govern models with MLflow and Amazon SageMaker AI Model Registry sync: Part 2

Governing models across accounts is the next step after automatic model registration. This post extends managed MLflow and Amazon SageMaker AI Model Registry sync to two cross-account governance topologies: a hub-and-spoke pattern that centralizes governance with AWS RAM, and a hybrid pattern that keeps development accounts isolated.

Govern models with MLflow and Amazon SageMaker AI Model Registry sync part 1

Govern models with MLflow and Amazon SageMaker AI Model Registry sync: Part 1

Managed MLflow on Amazon SageMaker AI now syncs richer model metadata (training metrics, evaluation results, inference specs, and lineage) into the SageMaker AI Model Registry, with lifecycle stage promotion. Part 1 shows how to govern candidate models in a single account using IAM guardrails.