Author: Eduardo Monich Fronza

As organizations look to scale AI across their operations addressing issues of trust, transparency, and compliance is essential. While AI models offer significant opportunities, managing them effectively requires addressing challenges such as bias, fairness, security, and model efficiency. Additionally, key regulations like the EU AI Act, U.S. AI Bill of Rights, Singapore AI Governance Framework, […]

IBM has open-sourced its Granite Code Models, which are now available in Amazon SageMaker JumpStart, and can also be deployed in Amazon Bedrock using Custom Model Import. These models provide developers and data scientists with generative AI capabilities for code generation. IBM Granite AI foundation models are designed to be cost-efficient and enterprise-ready. These models […]

Amazon Web Services customers who are looking to deploy and use IBM Cloud Pak for Data (CP4D) on the AWS Cloud, can use Red Hat OpenShift Service on AWS (ROSA). ROSA is a fully managed service, jointly supported by AWS and Red Hat. It is managed by Red Hat Site Reliability Engineers and provides a […]

In today’s interconnected world, customers need seamless integration between their mission-critical applications, systems, and services. IBM Cloud Pak for Integration (CP4I) when combined with Amazon Web Services (AWS) services, can help address these integration challenges. In this blog, you will learn how to use CP4I, deployed on Red Hat OpenShift Service on AWS (ROSA), to […]

Customers in regulated industries often need to avoid using external software registries and long-term credentials to comply with regulatory requirements. When deploying Red Hat OpenShift Container Platform (OCP) on Amazon Web Services (AWS), these same customers can use restricted Amazon Virtual Private Cloud (Amazon VPC) networks and the AWS Secure Token Service (AWS STS). AWS […]

Customers across different industries are looking for ways to use all of their data to enhance their planning and decision-making processes. They seek solutions to integrate data from various sources, aiming to build innovative AI solutions, gain a 360-degree view of their operations, and uncover new insights to differentiate their businesses. IBM Planning Analytics (PA) is […]

In the rapidly evolving landscape of artificial intelligence and machine learning (AI/ML), governance has emerged as a critical imperative. As organizations increasingly rely on AI to drive business decisions and automate processes, ensuring enforcement of policies and standard practices has become a top priority. Amazon Web Services (AWS) and IBM have joined forces to provide […]

Customers across most industries run critical applications like bulk data processing, industry and consumer statistics, enterprise resource planning, and large-scale transaction processing on mainframe architectures such as IBM Z. Much of this data is created and stored using Db2 for z/OS. At the same time, these customers are also performing their modernized data operations on […]

Customers who are interested optimizing workload performance and costs while achieving sustainability objectives can now leverage IBM Turbonomic on AWS. IBM Turbonomic is an AI-driven Application Resource Management (ARM) solution that helps organizations improve the performance and cost of their IT infrastructure on AWS and hybrid cloud environments. This containerized, microservices ARM application is offered […]

Data quality is essential for successful artificial intelligence (AI) workloads. For this reason, customers want to move beyond basic database management tasks such as backups and upgrades, to building modern data architectures. They seek to implement efficient strategies to unify data, removing duplication and implement governance to ensure secure data access. These challenges aren’t new […]