Amazon SageMaker has introduced a new capability that can help reduce the time it takes for the generative artificial intelligence (AI) models it supports to automatically scale. With this enhancement, the responsiveness of AI applications can be improved when demand becomes volatile. The emergence of foundation models (FMs) and large language models (LLMs) has brought…
This is a joint collaboration post between Salesforce and AWS, in which they discuss how the Salesforce Einstein AI Platform team has utilized Amazon SageMaker to enhance the efficiency and performance of their code generation LLM (Large Language Models) features, known as CodeGen.
Salesforce, a cloud-based software company, offers customer relationship management (CRM) software applications focused…
This post explains how large language models (LLMs) can be fine-tuned to better adapt to specific domains or tasks, using Amazon SageMaker and MLflow. When working with LLMs, customers may have varied requirements such as choosing a suitable pre-trained foundation model (FM) or customizing an existing model for a specific task. Using Amazon SageMaker with…
Amazon Web Services (AWS) has announced the availability of the Cohere Command R fine-tuning model on Amazon SageMaker, making it the newest addition to the SageMaker suite of machine learning capabilities. The Cohere Command R model is a scalable, large language model (LLM) designed to handle enterprise-grade workloads and is optimized for conversational interaction and…
BRIA AI 2.0 is a high-resolution (1024x1024) text-to-image diffusion model. It was trained by BRIA AI on a dataset of licensed images, through a quick and economic process with the assistance of Amazon SageMaker, a platform that offers tools and workflows to build, train, and deploy machine learning models. BRIA AI specializes in generative artificial…
Retrieval Augmented Generation (RAG) enhances the performance of large language models (LLMs) by incorporating extra knowledge from an external data source, which wasn't involved in the original model training. The two main components of RAG include indexing and retrieval.
Despite their merits, pre-trained embeddings models, trained on generic datasets like Wikipedia, often struggle to effectively portray…
Organizations are increasingly investing in artificial intelligence (AI) to help employees complete their tasks more efficiently and innovate their operations. Tapping into this potential, Amazon has developed a comprehensive generative AI stack to help organizations build and scale customized AI applications.
At the top of this stack, Amazon has its AI-powered assistant, Amazon Q. Amazon Q…