Michael P Tuszynski

The shift toward AI workloads has fundamentally changed how we approach cloud infrastructure design. Traditional architectures, optimized for web applications and microservices, often fall short when handling the unique demands of AI training and inference. Drawing from my experience architecting large-scale AI infrastructure, this article explores the technical considerations and

A deep dive into the data engineering, automation, and machine learning powering next-generation marketing measurement platforms—covering scalable data workflows, experiment automation, and the technical challenges of building a true system of record for marketing analytics.

In today's rapidly evolving AI landscape, organizations are increasingly faced with the challenge of building robust, scalable infrastructure to support their machine learning initiatives. While cloud-managed ML services offer convenience, many enterprises require more control, flexibility, and cost optimization than these services can provide. This is where Kubernetes

In the ever-evolving cloud landscape, event-driven serverless architectures have emerged as a powerful paradigm for building scalable, resilient, and cost-effective systems. By combining the operational simplicity of serverless computing with the flexibility of event-driven design, organizations can create systems that respond dynamically to changes, scale automatically, and minimize infrastructure costs.

After years in technology consulting, I've learned that technical expertise is only half the equation. The other half? The art of maintaining professional relationships and protecting all parties through proper documentation and clear boundaries. Let me share what I've learned along the way. Picture this: You&

In the world of DevOps, automating infrastructure deployment securely is crucial. This blog post will guide you through setting up GitHub Actions to automatically deploy your Terraform configurations to AWS using OpenID Connect (OIDC) for enhanced security. Prerequisites * A GitHub repository with your Terraform configuration * An AWS account * Basic knowledge

In today's digital-first environment, businesses and organizations can leverage intelligent document processing (IDP) to effectively manage and utilize the massive influx of data embedded in various document formats. Machine learning (ML), a pivotal branch of artificial intelligence, is revolutionizing IDP by offering sophisticated solutions for extracting, analyzing, and

Two terms often surface in Artificial Intelligence: Fine-Tuning and Retrieval-Augmented Generation (RAG). Both play pivotal roles in enhancing the capabilities of AI models, yet they serve distinct purposes and follow different methodologies. This blog post will explore both concepts, delving into their mechanics, applications, and how they compare. We'

In DevOps and continuous integration/continuous deployment (CI/CD) pipelines, optimizing containers' build and deployment processes is crucial for efficiency and resource management.