Generative Data Intelligence

Tag: data lake

Democratize ML on Salesforce Data Cloud with no-code Amazon SageMaker Canvas | Amazon Web Services

This post is co-authored by Daryl Martis, Director of Product, Salesforce Einstein AI. This is the third post in a series discussing the integration...

Accelerating AI/ML development at BMW Group with Amazon SageMaker Studio | Amazon Web Services

This post is co-written with Marc Neumann, Amor Steinberg and Marinus Krommenhoek from BMW Group. The BMW Group – headquartered in Munich, Germany –...

Your guide to generative AI and ML at AWS re:Invent 2023 | Amazon Web Services

Yes, the AWS re:Invent season is upon us and as always, the place to be is Las Vegas! You marked your calendars, you booked...

Build well-architected IDP solutions with a custom lens – Part 1: Operational excellence | Amazon Web Services

The IDP Well-Architected Lens is intended for all AWS customers who use AWS to run intelligent document processing (IDP) solutions and are searching for...

Principal Financial Group uses AWS Post Call Analytics solution to extract omnichannel customer insights | Amazon Web Services

An established financial services firm with over 140 years in business, Principal is a global investment management leader and serves more than 62 million...

Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD | Amazon Web Services

Building out a machine learning operations (MLOps) platform in the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML) for organizations is...

Huawei Unveils OceanStor A310—A Speedy Storage Solution for AI Model Trainers – Decrypt

Huawei debuted its new artificial intelligence (AI) storage model, the OceanStor A310, at GITEX GLOBAL 2023 last week, marking an attempt to address certain...

Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker | Amazon Web Services

Customers of every size and industry are innovating on AWS by infusing machine learning (ML) into their products and services. Recent developments in generative...

Simplifying the ‘data product’

Through the continuing evolution of the modern data platform, there is an exciting turn towards new architectural patterns and terms. What started with ‘data...

Looking Beyond the Hype Cycle of AI/ML in Cybersecurity

Most security teams can benefit from integrating artificial intelligence (AI) and machine learning (ML) into their daily workflow. These teams are often understaffed and...

Understanding the Differences Between On-Premises and Cloud Cybersecurity

The difference between managing cybersecurity in on-premises and cloud environments is not unlike playing traditional versus three-dimensional chess. While the tactics are similar and...

The Double-Edged Sword of Cyber Espionage

In today's digital age, cybersecurity is a critical concern, especially with the emergence of state-sponsored cyber-espionage actors tied to the Chinese government. Utilizing various civilian...

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