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A companion to the Modernization Monday series written for a technical audience, this Deep Dive covers two GPU sizing examples.

Following Part 1 of our GPU conversation, we discuss the four numbers covering the decision of which GPU to use for which model: memory, precision, interconnectivity, and power.

Do you need an AI Factory, or do you need some GPU-capable servers for a few workloads? How do you accurately measure the ROI? We discuss how answers to these and other questions will have a direct impact on tokenomics.

Successful AI adoption depends less on the technology itself and more on coordinated governance through a cross-functional group that aligns AI initiatives with business goals, establishes principles and policies, manages use case intake, and more.

Understanding artificial intelligence necessitates a foundational understanding of its economy and structure. This blog discusses everything from the billable unit of AI to the components of the AI Factory.

Cryptographically relevant quantum computers (CRQC) still may be 5-10 years away, but the time to prepare for them is now.

Discover how retailers are using AI, RFID, loyalty apps, smart security, and connected technologies to reduce customer friction, improve operations, and unlock valuable business insights.

Modernization Monday is a content series designed to clue you in on what it takes to actually modernize your infrastructure for AI.

Discover how ePlus is using agentic AI to handle enterprise operations at machine speed.

In Part 2 of our discussion on Change Management in the Age of AI, we continue the discussion around AI features included within healthcare software updates and how that impacts risk management strategies.

ePlus has helped organizations across manufacturing, distribution, technology, healthcare, and the public sector move from AI curiosity to AI maturity in production. Through these experiences, we’ve noticed something more useful than any single project outcome: the questions themselves have gotten more ambitious, and more complex.

Healthcare IT teams have had an established routine around software updates. While this methodology has worked for years, the inclusion of AI features within software releases is changing how updates are reviewed, tested, and implemented.