Posts by Melody Smith
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…
Read MoreAI’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…
Read MoreThe 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…
Read MorePredictive 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:…
Read MoreBeyond Adoption: What AI Maturity Really Means
Implementing artificial intelligence (AI) and being mature in your use of AI are two very different things. This interesting topic came to us from Concentrix in their blog post “The Analytics Catalyst – A Practical Framework for Data & AI Maturity.” AI maturity describes how effectively an organization moves from experimenting with AI to integrating…
Read MoreAI Isn’t the Data Problem. It’s the Spotlight.
Artificial intelligence (AI) may be dominating technology conversations, but underneath the excitement, urgency and evolving tools lies a very familiar challenge: data. AI did not create the data problem. It simply made it much harder to ignore. For years, organizations have struggled with fragmented information, inconsistent terminology, disconnected systems, weak metadata and poor governance. Those…
Read MoreWhen the Data Has to Hold Up in Court
Artificial intelligence (AI) is rapidly changing the legal profession. From contract review and e-discovery to legal research, case analysis, document drafting — the list goes on and on – AI can process enormous amounts of information far faster than a human team. This pertinent topic came to us from Wolters Kluwer in their article, “Would…
Read MoreAI Is Changing Data Protection. Is Your Organization Ready?
Artificial intelligence (AI) has changed how organizations collect, analyze, use and protect data, and the pace of change isn’t slowing down. Tech Target brought this topic to us in their article, “How AI is changing data protection.“ AI systems can process enormous volumes of information at remarkable speed, uncovering patterns and connections that traditional technologies…
Read MoreRAG Doesn’t Replace Publishers, It Makes Their Authority More Valuable
As artificial intelligence (AI) reshapes how people search for and consume information, publishers may understandably wonder where they fit into a world of AI-generated answers. Retrieval-Augmented Generation, or RAG, offers a reassuring answer: publishers are not becoming obsolete. In well-designed systems, their authority becomes even more important. This interesting and important topic came to our…
Read MoreWhen AI Learns the Wrong Lessons
Data bias is one of the most significant challenges facing organizations that rely on artificial intelligence (AI) and machine learning. AI systems learn from the data they are given, which means that when the data contains historical biases, gaps or imbalances, those problems can become embedded in the technology’s results. This interesting and important article…
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