Associate Technical Marketing Manager
Diego Alvarez Ponce
Diego Álvarez is a Technical Marketing Manager at Red Hat, specialized in Edge and Artificial Intelligence. For the past two years he has worked helping to drive the adoption of edge and its surroundings. He also has a strong interest in artificial intelligence and its possibilities within the edge.
Diego Alvarez Ponce's contributions
Article
Assessing AI for OpenShift operations: Advanced configurations
Learn how OpenShift Lightspeed performed when asked handle complex OpenShift scenarios, such as application security and advanced configurations.
Article
OpenShift Lightspeed: Assessing AI for OpenShift operations
Explore OpenShift Lightspeed through a certification-like exercise, pitting the AI assistant against real-world OpenShift certification questions.
Article
Optimize model serving at the edge with RawDeployment mode
Deploy AI at the edge with Red Hat OpenShift AI. Learn to set up OpenShift AI, configure storage, train models, and serve using KServe's RawDeployment.
Article
How to use pipelines for AI/ML automation at the edge
Learn how to use pipelines in OpenShift AI to automate the full AI/ML lifecycle on a single-node OpenShift instance.
Article
Deploy computer vision applications at the edge with MicroShift
Learn how to deploy a trained AI model onto MicroShift, Red Hat’s lightweight Kubernetes distribution optimized for edge computing.
Article
Model training in Red Hat OpenShift AI
Learn how to configure Red Hat OpenShift AI to train a YOLO model using an already provided animal dataset.
Article
Prepare and label custom datasets with Label Studio
Accurately labeled data is crucial for training AI models. Learn how to prepare and label a custom dataset using Label Studio in this tutorial.
Article
Red Hat OpenShift AI installation and setup
Learn how to install the Red Hat OpenShift AI operator and its components in this tutorial, then configure the storage setup and GPU enablement.
Assessing AI for OpenShift operations: Advanced configurations
Learn how OpenShift Lightspeed performed when asked handle complex OpenShift scenarios, such as application security and advanced configurations.
OpenShift Lightspeed: Assessing AI for OpenShift operations
Explore OpenShift Lightspeed through a certification-like exercise, pitting the AI assistant against real-world OpenShift certification questions.
Optimize model serving at the edge with RawDeployment mode
Deploy AI at the edge with Red Hat OpenShift AI. Learn to set up OpenShift AI, configure storage, train models, and serve using KServe's RawDeployment.
How to use pipelines for AI/ML automation at the edge
Learn how to use pipelines in OpenShift AI to automate the full AI/ML lifecycle on a single-node OpenShift instance.
Deploy computer vision applications at the edge with MicroShift
Learn how to deploy a trained AI model onto MicroShift, Red Hat’s lightweight Kubernetes distribution optimized for edge computing.
Model training in Red Hat OpenShift AI
Learn how to configure Red Hat OpenShift AI to train a YOLO model using an already provided animal dataset.
Prepare and label custom datasets with Label Studio
Accurately labeled data is crucial for training AI models. Learn how to prepare and label a custom dataset using Label Studio in this tutorial.
Red Hat OpenShift AI installation and setup
Learn how to install the Red Hat OpenShift AI operator and its components in this tutorial, then configure the storage setup and GPU enablement.
