Remove APIs Remove Big data Remove Data
article thumbnail

Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning

The solution integrates large language models (LLMs) with your organization’s data and provides an intelligent chat assistant that understands conversation context and provides relevant, interactive responses directly within the Google Chat interface. The following figure illustrates the high-level design of the solution.

APIs 122
article thumbnail

Reducing hallucinations in LLM agents with a verified semantic cache using Amazon Bedrock Knowledge Bases

AWS Machine Learning

While these models are trained on vast amounts of generic data, they often lack the organization-specific context and up-to-date information needed for accurate responses in business settings. The function checks the semantic cache (Amazon Bedrock Knowledge Bases) using the Retrieve API. which is received by the Invoke Agent function.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

How Formula 1® uses generative AI to accelerate race-day issue resolution

AWS Machine Learning

During these live events, F1 IT engineers must triage critical issues across its services, such as network degradation to one of its APIs. This impacts downstream services that consume data from the API, including products such as F1 TV, which offer live and on-demand coverage of every race as well as real-time telemetry.

APIs 69
article thumbnail

Secure Amazon SageMaker Studio presigned URLs Part 2: Private API with JWT authentication

AWS Machine Learning

In this post, we will continue to build on top of the previous solution to demonstrate how to build a private API Gateway via Amazon API Gateway as a proxy interface to generate and access Amazon SageMaker presigned URLs. The user invokes createStudioPresignedUrl API on API Gateway along with a token in the header.

APIs 97
article thumbnail

Generating value from enterprise data: Best practices for Text2SQL and generative AI

AWS Machine Learning

One such area that is evolving is using natural language processing (NLP) to unlock new opportunities for accessing data through intuitive SQL queries. Instead of dealing with complex technical code, business users and data analysts can ask questions related to data and insights in plain language.

article thumbnail

Schedule Amazon SageMaker notebook jobs and manage multi-step notebook workflows using APIs

AWS Machine Learning

Amazon SageMaker Studio provides a fully managed solution for data scientists to interactively build, train, and deploy machine learning (ML) models. Amazon SageMaker notebook jobs allow data scientists to run their notebooks on demand or on a schedule with a few clicks in SageMaker Studio.

APIs 109
article thumbnail

Access Snowflake data using OAuth-based authentication in Amazon SageMaker Data Wrangler

AWS Machine Learning

In this post, we show how to configure a new OAuth-based authentication feature for using Snowflake in Amazon SageMaker Data Wrangler. Snowflake is a cloud data platform that provides data solutions for data warehousing to data science. For more information about prerequisites, see Get Started with Data Wrangler.

APIs 96