Artificial Intelligence
Category: Generative AI*
Build an agentic multimodal AI assistant with Amazon Nova and Amazon Bedrock Data Automation
In this post, we demonstrate how agentic workflow patterns such as Retrieval Augmented Generation (RAG), multi-tool orchestration, and conditional routing with LangGraph enable end-to-end solutions that artificial intelligence and machine learning (AI/ML) developers and enterprise architects can adopt and extend. We walk through an example of a financial management AI assistant that can provide quantitative research and grounded financial advice by analyzing both the earnings call (audio) and the presentation slides (images), along with relevant financial data feeds.
Effective cost optimization strategies for Amazon Bedrock
With the increasing adoption of Amazon Bedrock, optimizing costs is a must to help keep the expenses associated with deploying and running generative AI applications manageable and aligned with your organization’s budget. In this post, you’ll learn about strategic cost optimization techniques while using Amazon Bedrock.
Build an AI-powered document processing platform with open source NER model and LLM on Amazon SageMaker
In this post, we discuss how you can build an AI-powered document processing platform with open source NER and LLMs on SageMaker.
Accelerate pre-training of Mistral’s Mathstral model with highly resilient clusters on Amazon SageMaker HyperPod
In this post, we present to you an in-depth guide to starting a continual pre-training job using PyTorch Fully Sharded Data Parallel (FSDP) for Mistral AI’s Mathstral model with SageMaker HyperPod.
How Skyflow creates technical content in days using Amazon Bedrock
This guest post is co-written with Manny Silva, Head of Documentation at Skyflow, Inc. Startups move quickly, and engineering is often prioritized over documentation. Unfortunately, this prioritization leads to release cycles that don’t match, where features release but documentation lags behind. This leads to increased support calls and unhappy customers. Skyflow is a data privacy […]
Establishing an AI/ML center of excellence
The rapid advancements in artificial intelligence and machine learning (AI/ML) have made these technologies a transformative force across industries. According to a McKinsey study, across the financial services industry (FSI), generative AI is projected to deliver over $400 billion (5%) of industry revenue in productivity benefits. As maintained by Gartner, more than 80% of enterprises […]
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 […]
Overcoming common contact center challenges with generative AI and Amazon SageMaker Canvas
Great customer experience provides a competitive edge and helps create brand differentiation. As per the Forrester report, The State Of Customer Obsession, 2022, being customer-first can make a sizable impact on an organization’s balance sheet, as organizations embracing this methodology are surpassing their peers in revenue growth. Despite contact centers being under constant pressure to […]
Simplify access to internal information using Retrieval Augmented Generation and LangChain Agents
This post takes you through the most common challenges that customers face when searching internal documents, and gives you concrete guidance on how AWS services can be used to create a generative AI conversational bot that makes internal information more useful. Unstructured data accounts for 80% of all the data found within organizations, consisting of […]
Build a secure enterprise application with Generative AI and RAG using Amazon SageMaker JumpStart
In this post, we build a secure enterprise application using AWS Amplify that invokes an Amazon SageMaker JumpStart foundation model, Amazon SageMaker endpoints, and Amazon OpenSearch Service to explain how to create text-to-text or text-to-image and Retrieval Augmented Generation (RAG). You can use this post as a reference to build secure enterprise applications in the Generative AI domain using AWS services.