AWS Machine Learning Blog

Category: Best Practices

Designing generative AI workloads for resilience

Resilience plays a pivotal role in the development of any workload, and generative AI workloads are no different. There are unique considerations when engineering generative AI workloads through a resilience lens. Understanding and prioritizing resilience is crucial for generative AI workloads to meet organizational availability and business continuity requirements. In this post, we discuss the […]

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.

Build enterprise-ready generative AI solutions with Cohere foundation models in Amazon Bedrock and Weaviate vector database on AWS Marketplace

This post discusses how enterprises can build accurate, transparent, and secure generative AI applications while keeping full control over proprietary data. The proposed solution is a RAG pipeline using an AI-native technology stack, whose components are designed from the ground up with AI at their core, rather than having AI capabilities added as an afterthought. We demonstrate how to build an end-to-end RAG application using Cohere’s language models through Amazon Bedrock and a Weaviate vector database on AWS Marketplace.

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 […]

Host the Whisper Model on Amazon SageMaker: exploring inference options

OpenAI Whisper is an advanced automatic speech recognition (ASR) model with an MIT license. ASR technology finds utility in transcription services, voice assistants, and enhancing accessibility for individuals with hearing impairments. This state-of-the-art model is trained on a vast and diverse dataset of multilingual and multitask supervised data collected from the web. Its high accuracy […]

Build financial search applications using the Amazon Bedrock Cohere multilingual embedding model

Enterprises have access to massive amounts of data, much of which is difficult to discover because the data is unstructured. Conventional approaches to analyzing unstructured data use keyword or synonym matching. They don’t capture the full context of a document, making them less effective in dealing with unstructured data. In contrast, text embeddings use machine […]

Build an Amazon SageMaker Model Registry approval and promotion workflow with human intervention

This post is co-written with Jayadeep Pabbisetty, Sr. Specialist Data Engineering at Merck, and Prabakaran Mathaiyan, Sr. ML Engineer at Tiger Analytics. The large machine learning (ML) model development lifecycle requires a scalable model release process similar to that of software development. Model developers often work together in developing ML models and require a robust […]

Create a document lake using large-scale text extraction from documents with Amazon Textract

AWS customers in healthcare, financial services, the public sector, and other industries store billions of documents as images or PDFs in Amazon Simple Storage Service (Amazon S3). However, they’re unable to gain insights such as using the information locked in the documents for large language models (LLMs) or search until they extract the text, forms, […]

Mixtral-8x7B is now available in Amazon SageMaker JumpStart

Today, we are excited to announce that the Mixtral-8x7B large language model (LLM), developed by Mistral AI, is available for customers through Amazon SageMaker JumpStart to deploy with one click for running inference. The Mixtral-8x7B LLM is a pre-trained sparse mixture of expert model, based on a 7-billion parameter backbone with eight experts per feed-forward […]

How AWS Prototyping enabled ICL-Group to build computer vision models on Amazon SageMaker

This is a customer post jointly authored by ICL and AWS employees. ICL is a multi-national manufacturing and mining corporation based in Israel that manufactures products based on unique minerals and fulfills humanity’s essential needs, primarily in three markets: agriculture, food, and engineered materials. Their mining sites use industrial equipment that has to be monitored […]