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This article discusses what an AI strategy means, the different types of AI strategies that you should know about, and how as a leader you can get started with an AI strategy. What Is An AI strategy? An AI strategy may seem like a complicated business-speak, but it’s simply a vision or high-level plan for integrating AI into the organization, such that it aligns with your broader business and automation goals. This high-level plan can be a: Product-level AI strategy (I often call this AI product strategy) Business-unit-level AI strategy Organizational-level AI strategy AI startup strategy The granularity of the plan…

In 1905, Albert Einstein published a paper on the photoelectric effect — a deceptively simple observation that light could eject electrons from metals. This work, which later won him the Nobel Prize, didn’t just explain an oddity in physics. It shattered classical mechanics, birthing quantum theory and reshaping our understanding of reality.But here’s a provocative question: Could an AI, trained on 19th-century data, have made the same leap?The answer isn’t just about physics. It’s about whether machines can replicate — or surpass — the spark of human genius. Let’s dissect this.1. The Photoelectric Effect: A Perfect Storm of Genius

Learning Objectives By the end of this article, you will: Automate advanced vSphere tasks involving NSX and Aria Operations. Use PowerCLI to manage NSX logical switches, firewall rules, and Aria Operations alerts. Integrate Python for orchestration, scheduling, and reporting of complex workflows. Visualize complex automation with an diagram. My Personal Repository on GitHub VMware Repository on GitHub Prerequisites Completed Articles 1–7. PowerCLI modules for NSX and Aria Operations installed (see below). vCenter, NSX-T Manager, and Aria Operations access with automation privileges. 1. PowerCLI and NSX-T Integration PowerCLI supports NSX-T for advanced network automation. You can create logical switches, manage firewall…

AI ethics is about releasing and implementing AI responsibly, paying attention to several considerations, from data etiquette to tool development risks, as discussed in a previous article. In this article, we’ll explore some of the ethical issues that arise with AI systems, particularly machine learning systems, when we overlook the ethical considerations of AI, often unintentionally. The 5 Common AI Ethical Issues 1. Bias propagation Although there’s a strong belief that algorithms are less biased than humans, AI systems are known to propagate our conscious and unconscious biases.  For example, there are known recruiting tools that algorithmically “learned” to dismiss…

OpenAI, Sam Altman, Elon Musk, xAI, Anthropic, Gemini, Google, Apple… all these companies are racing to build AGI by 2025, and once achieved, it will be replicated by dozens of others within weeks. The idea of creating a compressed knowledge base of humanity, extracting information, and iterating on outputs to optimize results is no longer revolutionary. Thousands of engineers worldwide can replicate what OpenAI has accomplished because it primarily involves scaling up Transformers — a model developed by Google, which itself was just an advancement of prior AI research.Press enter or click to view image in full sizeBut what comes…

Learning Objectives By the end of this article, you will: Use PowerCLI and Python to send data to and receive data from external REST APIs. Automate notifications and ticket creation with VMware scripting. Build workflows that bridge VMware and IT service management tools. Visualize multi-tool integration with an diagram. My Personal Repository on GitHub VMware Repository on GitHub Prerequisites Completed Articles 1–8. PowerCLI, Python, and access to the external tool/API (e.g., ServiceNow, Slack, Jira). Network permissions for API access (outbound HTTP/S). 1. Why Integrate PowerCLI with External APIs? Many organizations automate IT workflows by connecting VMware scripts to ticketing, chat,…

One of the problems business leaders face in communicating with their technical counterparts is trying to describe their AI problem. To simplify some of the communication, here are some common AI problem types. Try to map AI opportunities at hand to these common problem types. Note that the problem types often overlap—but that’s ok. The key is to identify problem types that most closely match the task at hand when communicating with your AI and data science experts. Common AI Problem Types 1. Classification A classification problem is about assigning one or more categories to a document, product, person, or…