Fine-tuning a pre-trained large language model (LLM) allows users to customize the model to perform better on domain-specific tasks or align more closely with human preferences. It is a continuous process to keep the fine-tuned model accurate and effective in changing environments, to adapt to the data distribution shift (conceptContinue Reading
At AWS re:Invent 2024, we launched a new innovation in Amazon SageMaker HyperPod on Amazon Elastic Kubernetes Service (Amazon EKS) that enables you to run generative AI development tasks on shared accelerated compute resources efficiently and reduce costs by up to 40%. Administrators can use SageMaker HyperPod task governance toContinue Reading
This blog post is co-written with Moran beladev, Manos Stergiadis, and Ilya Gusev from Booking.com. Large language models (LLMs) have revolutionized the field of natural language processing with their ability to understand and generate humanlike text. Trained on broad, generic datasets spanning a wide range of topics and domains, LLMsContinue Reading
This blog post is co-written with George Orlin from Meta. Today, we are excited to announce that Meta’s Segment Anything Model (SAM) 2.1 vision segmentation model is publicly available through Amazon SageMaker JumpStart to deploy and run inference. Meta SAM 2.1 provides state-of-the-art video and image segmentation capabilities in aContinue Reading
Today, we are excited to announce that the Falcon 3 family of models from TII are available in Amazon SageMaker JumpStart. In this post, we explore how to deploy this model efficiently on Amazon SageMaker AI. Overview of the Falcon 3 family of models The Falcon 3 family, developed byContinue Reading
AI agents are rapidly becoming the next frontier in enterprise transformation, with 82% of organizations planning adoption within the next 3 years. According to a Capgemini survey of 1,100 executives at large enterprises, 10% of organizations already use AI agents, and more than half plan to use them in theContinue Reading
As large language models (LLMs) become increasingly integrated into customer-facing applications, organizations are exploring ways to leverage their natural language processing capabilities. Many businesses are investigating how AI can enhance customer engagement and service delivery, and facing challenges in making sure LLMs driven engagements are on topic and follow theContinue Reading
Today, we are announcing that DeepSeek AI’s first-generation frontier model, DeepSeek-R1, is available through Amazon SageMaker JumpStart and Amazon Bedrock Marketplace to deploy for inference. You can now use DeepSeek-R1 to build, experiment, and responsibly scale your generative AI ideas on AWS. In this post, we demonstrate how to getContinue Reading
Evaluating large language models (LLMs) is crucial as LLM-based systems become increasingly powerful and relevant in our society. Rigorous testing allows us to understand an LLM’s capabilities, limitations, and potential biases, and provide actionable feedback to identify and mitigate risk. Furthermore, evaluation processes are important not only for LLMs, butContinue Reading
Amazon SageMaker provides a seamless experience for building, training, and deploying machine learning (ML) models at scale. Although SageMaker offers a wide range of built-in algorithms and pre-trained models through Amazon SageMaker JumpStart, there are scenarios where you might need to bring your own custom model or use specific softwareContinue Reading
