This post is co-written with Mark Ross from Atos. Organizations pursuing AI transformation can face a familiar challenge: how to upskill their workforce at scale in a way that changes …
AWS AI League: Atos fine-tunes approach to AI education Read More »
AI is moving fast, and for most of our customers, the real opportunity isn’t in experimenting with it—it’s in running AI in production where it drives meaningful business outcomes. This …
AWS and NVIDIA deepen strategic collaboration to accelerate AI from pilot to production Read More »
This is Part II of a two-part series from the AWS Generative AI Innovation Center. If you missed Part I, refer to Operationalizing Agentic AI Part 1: A Stakeholder’s Guide. …
Agentic AI in the Enterprise Part 2: Guidance by Persona Read More »
We thank Greg Pereira and Robert Shaw from the llm-d team for their support in bringing llm-d to AWS. In the agentic and reasoning era, large language models (LLMs) generate …
Introducing Disaggregated Inference on AWS powered by llm-d Read More »
This post is cowritten with Ilija Subanovic and Michael Rice from Workhuman. Workhuman’s customer service and analytics team were drowning in one-time reporting requests from seven million users worldwide—a common …
Building and managing machine learning (ML) features at scale is one of the most critical and complex challenges in modern data science workflows. Organizations often struggle with fragmented feature pipelines, …
EAGLE is the state-of-the-art method for speculative decoding in large language model (LLM) inference, but its autoregressive drafting creates a hidden bottleneck: the more tokens that you speculate, the more …
P-EAGLE: Faster LLM inference with Parallel Speculative Decoding in vLLM Read More »
As organizations scale their generative AI workloads on Amazon Bedrock, operational visibility into inference performance and resource consumption becomes critical. Teams running latency-sensitive applications must understand how quickly models begin …
Deploying AI agents safely in regulated industries is challenging. Without proper boundaries, agents that access sensitive data or execute transactions can pose significant security risks. Unlike traditional software, an AI …
Secure AI agents with Policy in Amazon Bedrock AgentCore Read More »
This post shows you how to build a scalable multimodal video search system that enables natural language search across large video datasets using Amazon Nova models and Amazon OpenSearch Service. …
Multimodal embeddings at scale: AI data lake for media and entertainment workloads Read More »
