AWS Machine Learning Blog
Query structured data from Amazon Q Business using...
In this post, we show how Amazon Q Business integrates with QuickSight to enable users to query both structured and unstructured data in a unified way. The integration allows users to connect to over 20 structured data sources like...
Elevate customer experience by using the Amazon Q ...
The New Relic AI custom plugin for Amazon Q Business creates a unified solution that combines New Relic AI’s observability insights and recommendations and Amazon Q Business’s Retrieval Augmented Generation (RAG) capabilities, in and a natural language interface for...
Amazon SageMaker launches the updated inference op...
Today, Amazon SageMaker is excited to announce updates to the inference optimization toolkit, providing new functionality and enhancements to help you optimize generative AI models even faster.In this post, we discuss these new features of the toolkit in more...
Syngenta develops a generative AI assistant to sup...
In this post, we explore how Syngenta collaborated with AWS to develop Cropwise AI, a generative AI assistant powered by Amazon Bedrock Agents that helps sales representatives make better seed product recommendations to farmers across North America. The solution...
Speed up your AI inference workloads with new NVID...
At re:Invent 2024, we are excited to announce new capabilities to speed up your AI inference workloads with NVIDIA accelerated computing and software offerings on Amazon SageMaker. In this post, we will explore how you can use these new...
Unlock cost savings with the new scale down to zer...
Today at AWS re:Invent 2024, we are excited to announce a new feature for Amazon SageMaker inference endpoints: the ability to scale SageMaker inference endpoints to zero instances. This long-awaited capability is a game changer for our customers using...
Supercharge your auto scaling for generative AI in...
Today at AWS re:Invent 2024, we are excited to announce the new Container Caching capability in Amazon SageMaker, which significantly reduces the time required to scale generative AI models for inference. This innovation allows you to scale your models...
Introducing Fast Model Loader in SageMaker Inferen...
Today at AWS re:Invent 2024, we are excited to announce a new capability in Amazon SageMaker Inference that significantly reduces the time required to deploy and scale LLMs for inference using LMI: Fast Model Loader. In this post, we...
Introducing Fast Model Loader in SageMaker Inferen...
In this post, we provide a detailed, hands-on guide to implementing Fast Model Loader in your LLM deployments. We explore two approaches: using the SageMaker Python SDK for programmatic implementation, and using the Amazon SageMaker Studio UI for a...
Fast and accurate zero-shot forecasting with Chron...
Chronos models are available for Amazon SageMaker customers through AutoGluon-TimeSeries and Amazon SageMaker JumpStart. In this post, we introduce Chronos-Bolt, our latest FM for forecasting that has been integrated into AutoGluon-TimeSeries.
How Amazon Finance Automation built a generative A...
Amazon Finance Automation developed a large language model (LLM)-based question-answer chat assistant on Amazon Bedrock. This solution empowers analysts to rapidly retrieve answers to customer queries, generating prompt responses within the same communication thread. As a result, it drastically...
Cohere Rerank 3.5 is now available in Amazon Bedro...
We are excited to announce the availability of Cohere’s advanced reranking model Rerank 3.5 through our new Rerank API in Amazon Bedrock. This powerful reranking model enables AWS customers to significantly improve their search relevance and content ranking capabilities....
AWS DeepRacer: How to master physical racing?
In this blog post, I will look at what makes physical AWS DeepRacer racing—a real car on a real track—different to racing in the virtual world—a model in a simulated 3D environment. I will cover the basics, the differences...
Easily deploy and manage hundreds of LoRA adapters...
The new efficient multi-adapter inference feature of Amazon SageMaker unlocks exciting possibilities for customers using fine-tuned models. This capability integrates with SageMaker inference components to allow you to deploy and manage hundreds of fine-tuned Low-Rank Adaptation (LoRA) adapters through...
Improve the performance of your Generative AI appl...
Today, we are excited to announce the availability of Prompt Optimization on Amazon Bedrock. With this capability, you can now optimize your prompts for several use cases with a single API call or a click of a button on...
Search enterprise data assets using LLMs backed by...
In this post, we present a generative AI-powered semantic search solution that empowers business users to quickly and accurately find relevant data assets across various enterprise data sources. In this solution, we integrate large language models (LLMs) hosted on...
Embodied AI Chess with Amazon Bedrock
In this post, we demonstrate Embodied AI Chess with Amazon Bedrock, bringing a new dimension to traditional chess through generative AI capabilities. Our setup features a smart chess board that can detect moves in real time, paired with two...
Efficiently train models with large sequence lengt...
In this post, we demonstrate how the Amazon SageMaker model parallel library (SMP) addresses this need through support for new features such as 8-bit floating point (FP8) mixed-precision training for accelerated training performance and context parallelism for processing large...