Data Science Central

We’re watching a new divide form in enterprise technology, and it has nothing to do with who used AI first. The real split is between companies that built strong data foundations, modern processing layers and governed pipelines… and those still trying to make AI run on brittle, legacy architecture. This isn’t a tooling problem. It’s a readiness problem. Cloud egress costs, GPU shortages, semantic modeling gaps, weak cybersecurity pipelines — all of it is creating a world where AI success comes down to one thing: Are you structurally prepared? In this week’s DSC Newsletter, we look at why AI initiatives are stalling, why agentic systems expose bad architecture instantly and why the cost of inaction is quietly becoming the most expensive line item in IT.

AI and data systems are evolving within measurable limits that define how innovation advances. This edition examines how compute capacity, semantic clarity and workforce capability shape modern intelligence. The focus shifts from expansion to efficiency, showing how resilient design and coordinated governance create sustainable progress across data-driven organizations.

AI and data systems are entering a stress era where autonomy, scale, and oversight collide. This issue examines how that pressure shapes everything from governance and platform design to human capability. The systems we build reveal their true nature only when pushed to their limits.

A Simple Regression Problem

How to Get AI to Deliver Superior ROI, Faster - https://lnkd.in/gMyRgrUP Reducing total cost of ownership (TCO) is a topic familiar to all enterprise executives and stakeholders. Here, I discuss optimization strategies in the context of AI adoption. Whether you build in-house solutions, or purchase products from AI vendors. The focus is on LLM products, featuring new trends in Enterprise AI to boost ROI. Besides the technological aspects, I also discuss the human aspects. Read full article, with link to live presentation on the topic and PowerPoint document, at https://lnkd.in/gMyRgrUP

AI and analytics promise insight, but trust is what makes them usable. Learn how validation, governance and standards are shaping more reliable systems.

Is your company's decision cycle keeping up with the speed of events? Hidden platform debt may be the silent force holding you back, eroding both performance and trust. Learn how to retire that debt by strengthening your data foundations and operating with real-time analytics and AI.

This week's newsletter explains how to make AI useful at scale, whether you're sizing an on-premises cluster or planning simulation-driven decisions.

How the New Breed of LLMs is Replacing OpenAI and the Likes

Spectacular Connection Between LLMs, Quantum Systems, and Number Theory