Category: Artificial Intelligence

In this post, we illustrate the importance of generative AI in the collaboration between Tealium and the AWS Generative AI Innovation Center (GenAIIC) team by automating the following: 1/ Evaluating the retriever and the generated answer of a RAG system based on the Ragas Repository powered by Amazon Bedrock, 2/ Generating improved instructions for each question-and-answer pair using an automatic prompt engineering technique based on the Auto-Instruct Repository. An instruction refers to a general direction or command given to the model to guide generation of a response. These instructions were generated using Anthropic’s Claude on Amazon Bedrock, and 4/ Providing a UI for a human-based feedback mechanism that complements an evaluation system powered by Amazon Bedrock.

In this post, we illustrate how EBSCOlearning partnered with AWS Generative AI Innovation Center (GenAIIC) to use the power of generative AI in revolutionizing their learning assessment process. We explore the challenges faced in traditional question-answer (QA) generation and the innovative AI-driven solution developed to address them.

Today, we are excited to announce that Pixtral 12B (pixtral-12b-2409), a state-of-the-art vision language model (VLM) from Mistral AI that excels in both text-only and multimodal tasks, is available for customers through Amazon SageMaker JumpStart. You can try this model with SageMaker JumpStart, a machine learning (ML) hub that provides access to algorithms and models that can be deployed with one click for running inference. In this post, we walk through how to discover, deploy, and use the Pixtral 12B model for a variety of real-world vision use cases.

In Parts 1 and 2 of this series, we explored ways to use the power of multimodal FMs such as Amazon Titan Multimodal Embeddings, Amazon Titan Text Embeddings, and Anthropic’s Claude 3 Sonnet. In this post, we compared the approaches from an accuracy and pricing perspective.

Amazon Q Business is a generative AI-powered assistant that enhances employee productivity by solving problems, generating content, and providing insights across enterprise data sources. Beyond searching indexed third-party services, employees need access to dynamic, near real-time data such as stock prices, vacation balances, and location tracking, which is made possible through Amazon Q Business plugins. […]

With access to a wide range of generative AI foundation models (FM) and the ability to build and train their own machine learning (ML) models in Amazon SageMaker, users want a seamless and secure way to experiment with and select the models that deliver the most value for their business. In the initial stages of an ML […]

Today, we are excited to announce that Mistral-NeMo-Base-2407 and Mistral-NeMo-Instruct-2407 large language models from Mistral AI that excel at text generation, are available for customers through Amazon SageMaker JumpStart. In this post, we walk through how to discover, deploy and use the Mistral-NeMo-Instruct-2407 and Mistral-NeMo-Base-2407 models for a variety of real-world use cases.

With trust as a cornerstone of AI adoption, we are excited to announce at AWS re:Invent 2024 new responsible AI tools, capabilities, and resources that enhance the safety, security, and transparency of our AI services and models and help support customers’ own responsible AI journeys.

In this post, we show how to build a RAG application on Amazon SageMaker JumpStart using Facebook AI Similarity Search (FAISS).

In this post, we demonstrate how you can use Amazon SageMaker HyperPod training plans, to bring down your training cluster procurement wait time. We guide you through a step-by-step implementation on how you can use the (AWS CLI) or the AWS Management Console to find, review, and create optimal training plans for your specific compute and timeline needs. We further guide you through using the training plan to submit SageMaker training jobs or create SageMaker HyperPod clusters.