AWS Machine Learning Blog
Tag: AI/ML
Databricks DBRX is now available in Amazon SageMaker JumpStart
Today, we are excited to announce that the DBRX model, an open, general-purpose large language model (LLM) developed by Databricks, is available for customers through Amazon SageMaker JumpStart to deploy with one click for running inference. The DBRX LLM employs a fine-grained mixture-of-experts (MoE) architecture, pre-trained on 12 trillion tokens of carefully curated data and […]
Scale AI training and inference for drug discovery through Amazon EKS and Karpenter
This is a guest post co-written with the leadership team of Iambic Therapeutics. Iambic Therapeutics is a drug discovery startup with a mission to create innovative AI-driven technologies to bring better medicines to cancer patients, faster. Our advanced generative and predictive artificial intelligence (AI) tools enable us to search the vast space of possible drug […]
Skeleton-based pose annotation labeling using Amazon SageMaker Ground Truth
Pose estimation is a computer vision technique that detects a set of points on objects (such as people or vehicles) within images or videos. Pose estimation has real-world applications in sports, robotics, security, augmented reality, media and entertainment, medical applications, and more. Pose estimation models are trained on images or videos that are annotated with […]
Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs
This post provides three guided steps to architect risk management strategies while developing generative AI applications using LLMs. We first delve into the vulnerabilities, threats, and risks that arise from the implementation, deployment, and use of LLM solutions, and provide guidance on how to start innovating with security in mind. We then discuss how building on a secure foundation is essential for generative AI. Lastly, we connect these together with an example LLM workload to describe an approach towards architecting with defense-in-depth security across trust boundaries.
Use mobility data to derive insights using Amazon SageMaker geospatial capabilities
Geospatial data is data about specific locations on the earth’s surface. It can represent a geographical area as a whole or it can represent an event associated with a geographical area. Analysis of geospatial data is sought after in a few industries. It involves understanding where the data exists from a spatial perspective and why […]
Build well-architected IDP solutions with a custom lens – Part 4: Performance efficiency
When a customer has a production-ready intelligent document processing (IDP) workload, we often receive requests for a Well-Architected review. To build an enterprise solution, developer resources, cost, time and user-experience have to be balanced to achieve the desired business outcome. The AWS Well-Architected Framework provides a systematic way for organizations to learn operational and architectural […]
Build well-architected IDP solutions with a custom lens – Part 6: Sustainability
An intelligent document processing (IDP) project typically combines optical character recognition (OCR) and natural language processing (NLP) to automatically read and understand documents. Customers across all industries run IDP workloads on AWS to deliver business value by automating use cases such as KYC forms, tax documents, invoices, insurance claims, delivery reports, inventory reports, and more. […]
Geospatial generative AI with Amazon Bedrock and Amazon Location Service
Today, geospatial workflows typically consist of loading data, transforming it, and then producing visual insights like maps, text, or charts. Generative AI can automate these tasks through autonomous agents. In this post, we discuss how to use foundation models from Amazon Bedrock to power agents to complete geospatial tasks. These agents can perform various tasks […]
Foundational vision models and visual prompt engineering for autonomous driving applications
Prompt engineering has become an essential skill for anyone working with large language models (LLMs) to generate high-quality and relevant texts. Although text prompt engineering has been widely discussed, visual prompt engineering is an emerging field that requires attention. Visual prompts can include bounding boxes or masks that guide vision models in generating relevant and […]
Index your web crawled content using the new Web Crawler for Amazon Kendra
In this post, we show how to index information stored in websites and use the intelligent search in Amazon Kendra to search for answers from content stored in internal and external websites. In addition, the ML-powered intelligent search can accurately get answers for your questions from unstructured documents with natural language narrative content, for which keyword search is not very effective.