Category: Amazon SageMaker Canvas

Fine-tuning large language models (LLMs) creates tailored customer experiences that align with a brand’s unique voice. Amazon SageMaker Canvas and Amazon SageMaker JumpStart democratize this process, offering no-code solutions and pre-trained models that enable businesses to fine-tune LLMs without deep technical expertise, helping organizations move faster with fewer technical resources. SageMaker Canvas provides an intuitive […]

Imagine harnessing the power of advanced language models to understand and respond to your customers’ inquiries. Amazon Bedrock, a fully managed service providing access to such models, makes this possible. Fine-tuning large language models (LLMs) on domain-specific data supercharges tasks like answering product questions or generating relevant content. In this post, we show how Amazon […]

Amazon SageMaker Studio is a web-based, integrated development environment (IDE) for machine learning (ML) that lets you build, train, debug, deploy, and monitor your ML models. SageMaker Studio provides all the tools you need to take your models from data preparation to experimentation to production while boosting your productivity. Amazon SageMaker Canvas is a powerful […]

Amazon SageMaker Canvas allows you to use machine learning (ML) to generate predictions without having to write any code. It does so by covering the end-to-end ML workflow: whether you’re looking for powerful data preparation and AutoML, managed endpoint deployment, simplified MLOps capabilities, or the ability to configure foundation models for generative AI, SageMaker Canvas […]

With the use of cloud computing, big data and machine learning (ML) tools like Amazon Athena or Amazon SageMaker have become available and useable by anyone without much effort in creation and maintenance. Industrial companies increasingly look at data analytics and data-driven decision-making to increase resource efficiency across their entire portfolio, from operations to performing […]

Launched in 2021, Amazon SageMaker Canvas is a visual, point-and-click service for building and deploying machine learning (ML) models without the need to write any code. Ready-to-use Foundation Models (FMs) available in SageMaker Canvas enable customers to use generative AI for tasks such as content generation and summarization. We are thrilled to announce the latest […]

Data is the foundation to capturing the maximum value from AI technology and solving business problems quickly. To unlock the potential of generative AI technologies, however, there’s a key prerequisite: your data needs to be appropriately prepared. In this post, we describe how use generative AI to update and scale your data pipeline using Amazon […]

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 […]

This is a guest post co-written with Babu Srinivasan from MongoDB. As industries evolve in today’s fast-paced business landscape, the inability to have real-time forecasts poses significant challenges for industries heavily reliant on accurate and timely insights. The absence of real-time forecasts in various industries presents pressing business challenges that can significantly impact decision-making and […]

We are excited to announce the launch of Amazon DocumentDB (with MongoDB compatibility) integration with Amazon SageMaker Canvas, allowing Amazon DocumentDB customers to build and use generative AI and machine learning (ML) solutions without writing code. Amazon DocumentDB is a fully managed native JSON document database that makes it straightforward and cost-effective to operate critical […]