Jelani Harper

Jelani Harper is an editorial consultant servicing the information technology market. He specializes in data-driven applications focused on semantic technologies, data governance, and analytics.

A Brief Overview of the Strengths and Weaknesses of Artificial Intelligence

Artificial Intelligence is not a technology, but a composite of different technologies and approaches, with the propensity to produce strikingly human-like actions from information technology systems. The three dominant forms of AI involve logic-based systems (machine reasoning), statistical approaches (machine learning), and Large Language Models (LLMs). Granted, LLMs are a manifestation of advanced machine learning, …

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Can Artificial Intelligence Fully Automate Data Integration?

Depending on whom one asks, Artificial Intelligence’s utility for time-honored data management problems involving data integration and data architecture has been highly exaggerated. In this article, we will review Artificial Intelligence in data integration. According to Gartner’s definition of a data fabric (which unites enterprise data regardless of location to make them singularly accessible), AI …

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Points of Consideration Before Implementing ChatGPT

ChatGPT can readily traverse the vast amounts of information on the internet to answer almost any ad-hoc question users pose. That it does so via natural language, in close to real-time, is indicative of the immense advancements of Generative Artificial Intelligence—and of Natural Language Generation, in particular. ChatGPT’s practical utility spans most tasks associated with …

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The Door to Tomorrow: Predictive and Prescriptive Data Security Governance

Data security and access governance has become one of the cardinal points of commonality for all organizations. The need to ascertain where one’s sensitive data is, administer the proper controls to protect it, and demonstrate doing so with timely auditing is pivotal to survival in today’s hyper-regulatory compliant business conditions. But just as data governance …

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The One-Shot Learning Phenomenon

Machine learning detractors frequently cite three limitations of this statistical expression of Artificial Intelligence. These alleged drawbacks include: Comprehension: For natural language technology applications and others, naysayers claim machine learning algorithms don’t actually understand the underlying language they parse—certainly not the way that systems predicated on AI’s knowledge base do. Applicability: Another frequent criticism of …

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Two of a Kind: Real-Time Analytics and Machine Learning

The assessment of data systems as they actually are, as opposed to what they were previously or are predicted to be, is arguably the paragon of contemporary analytics. Coupling this capability with machine learning enables organizations to not just make the right business decisions, but to capitalize on them in real-time. Achieving this ideal requires …

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The Extensibility of Knowledge Graphs for Natural Language Understanding

The universal applicability of enterprise knowledge—across use cases, domains, and languages—is widely understood. It’s foundational to the history of Artificial Intelligence. And, it’s likely the main reason adoption rates for knowledge graphs have steadily inclined of late, making them one of the most utilitarian forms of AI available today. True knowledge graphs are extensible and …

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The Taxonomic Underpinnings of Cognitive Computing

Although it’s making a resurgence of sorts with the concepts of neuro-symbolic AI and what Gartner has termed composite AI, machine reasoning has traditionally been overlooked in recent years. Rules, axioms, inferences, and logic-based systems are integral aspects of cognitive computing, particularly as it underlies machine intelligence. Taxonomies are the substrate of nearly each of …

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The Crux of Artificial Intelligence’s Enterprise Utility: Timely Analytics

The assortment of use cases Artificial Intelligence supports for enterprise users is constantly burgeoning. Applications of neural networks, symbolic reasoning, and prescriptive analytics are appearing in everything from internal systems for data management to customer-facing ones that generate revenues. These cognitive computing techniques are instrumental for increasing the speed and scale at which organizations accomplish …

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