Remove Accountability Remove Big data Remove Conference
article thumbnail

Build a self-service digital assistant using Amazon Lex and Knowledge Bases for Amazon Bedrock

AWS Machine Learning

Prerequisites To implement this solution, you need the following: An AWS account with privileges to create AWS Identity and Access Management (IAM) roles and policies. For Data source name , Amazon Bedrock prepopulates the auto-generated data source name; however, you can change it to your requirements.

article thumbnail

Federated learning on AWS using FedML, Amazon EKS, and Amazon SageMaker

AWS Machine Learning

Healthcare organizations must navigate strict compliance regulations, such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States, while implementing FL solutions. FedML Octopus is the industrial-grade platform of cross-silo FL for cross-organization and cross-account training.

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

Designing generative AI workloads for resilience

AWS Machine Learning

Ingesting from these sources is different from the typical data sources like log data in an Amazon Simple Storage Service (Amazon S3) bucket or structured data from a relational database. In the low-latency case, you need to account for the time it takes to generate the embedding vectors.

article thumbnail

From The Field: Oracle CX Conference 2016 Report

Natalie Petouhof

Tweet What we saw at the conference was a full suite for customer experience. With suites there is the opportunity to know your customers better, via shared data, shared knowledge across lines of business for personalized and relevant offers, products and services. Troy Carter, Atomic Factory, Keynote at Oracle CX Conference.

Banking 40
article thumbnail

How to Bring Agile Innovation to Customer Success

Totango

An agile approach brings the full power of big data analytics to bear on customer success. This provides transparency and accountability and empowers a data-driven approach to customer success. 7 Steps to Bring Agile Innovation to Customer Success. Define How to Measure Success.

article thumbnail

Generate financial industry-specific insights using generative AI and in-context fine-tuning

AWS Machine Learning

As we can see the data retrieval is more accurate. Additionally, the generated analysis has considered all of the volatility information in the dataset (1-year, 3-year, and 5-year) and accounted for present or missing data for volatility. In entered the Big Data space in 2013 and continues to explore that area.

article thumbnail

Securing MLflow in AWS: Fine-grained access control with AWS native services

AWS Machine Learning

How to use MLflow as a centralized repository in a multi-account setup. Prerequisites Before deploying the solution, make sure you have access to an AWS account with admin permissions. Multi-account considerations Data science workflows have to pass multiple stages as they progress from experimentation to production.

APIs 83