Data Layers and Semantic Layers: Where AI Finds Meaning

Artificial intelligence (AI) depends on data, but having access to enormous amounts of data does not automatically mean an AI system understands what that data means. That distinction helps explain the relationship between two important components of modern AI applications: the data layer and the semantic layer. DATAVERSITY brought this topic to our attention in…

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Deep Learning: How AI Is Expanding the Reach of Machine Intelligence

Artificial intelligence (AI) is often discussed as though it is a single technology. In reality, AI is an umbrella encompassing many approaches designed to enable computers to perform tasks that traditionally required human intelligence. Machine learning sits beneath that umbrella, and deep learning is a specialized and increasingly powerful branch of machine learning. Understanding the…

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When Meaning Meets Machines: AI, Semantics and Knowledge Graphs

Semantics and knowledge graphs have been quietly doing important work for years. Semantics helps systems understand that words, concepts and context are related. Knowledge graphs turn those relationships into structured networks of people, places, products, ideas and facts. This interesting topic came to us from Bio-IT World in their article, “Trends from the Trenches: Why…

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AI Agents Need Data Governance and Data Governance Needs to Keep Up

Artificial intelligence (AI) agents are changing how organizations interact with data. Unlike traditional AI tools that primarily analyze information or generate responses, agents can take action: retrieving data, making decisions, initiating workflows and interacting with other systems with limited human intervention. This topic came to us from CIO in their article, “Why AI agents will…

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Digital Literacy in a Rapidly Changing Technology Landscape

Digital literacy has evolved far beyond knowing how to use a computer, navigate a website or send an email. In today’s technology environment, it means understanding how digital systems influence the information we consume, the decisions we make and the ways we work. This topic came to us from Nature in their article, “How digital…

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Protecting the Past: Historians Are Calling for AI Governance

Artificial intelligence (AI) is giving historians powerful new ways to explore the past. AI can analyze enormous collections of documents, identify patterns across archives, transcribe handwritten materials, translate texts and uncover connections that might otherwise take researchers years to find. The Guardian brought us this important topic in their article, “Historians advocate binding AI rules,…

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How AI Is Changing the Role of Taxonomists

Artificial intelligence (AI) is changing how organizations create, manage and use information and taxonomists are right in the middle of that transformation. While AI can automate portions of classification, tagging and metadata generation, it has not eliminated the need for taxonomy expertise. Instead, it is shifting the taxonomist’s role from primarily building and maintaining controlled…

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AI’s Growing Role in the Future of Healthcare

Artificial intelligence (AI) is rapidly changing healthcare, offering new ways to detect disease earlier, improve diagnostic testing, personalize treatment and accelerate research into some of medicine’s most challenging conditions. This important information came to us from Texas A&M University in their article, “A new AI model could aid earlier Alzheimer’s diagnosis.” One of AI’s greatest…

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The Promise and Fear of Artificial Superintelligence

Artificial intelligence (AI) is already changing how we work, search, analyze data and make decisions. But artificial superintelligence (ASI) represents something very different. ASI is the theoretical point at which an AI system surpasses human intelligence across virtually every field. Not just calculation or data processing, but reasoning, creativity, strategy, scientific discovery and problem-solving. MIT…

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Predictive Analytics in the Age of AI: Smarter Predictions, New Risks

Predictive analytics has always been about using what we know to make an educated guess about what comes next. By analyzing historical data, patterns and trends, organizations can forecast customer behavior, anticipate market shifts, identify risks and make better-informed decisions. This subject came to us from International Business Magazine in their article, “Predictive AI Analytics:…

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