AI and Unstructured Data: Finding Meaning in the Mess
Organizations have never lacked data. The bigger problem has been figuring out what to do with all of it, especially the information that doesn’t fit neatly into rows and columns. This interesting and important topic came to us from CDO Magazine in their article, “Why AI Changes Unstructured Data: Data X-Ray’s Kyle DuPont on Metadata…
Read MoreBetter Data, Better Intelligence
Artificial intelligence (AI) may get the headlines, but its effectiveness still depends on something far less glamorous: data. That is where FAIR data becomes increasingly important. This interesting topic came to us from Nature in their article, “Advancing FAIR data towards comparable, organized, predictive AI-ready data for community validation.” FAIR stands for Findable, Accessible, Interoperable…
Read MoreHow Emerging Technology Is Reshaping Cloud Computing
Cloud computing has been one of the defining technologies of the digital era, giving organizations access to computing power, storage and applications without requiring them to build and maintain everything themselves. Now artificial intelligence (AI) is changing that equation again. AI is not simply another workload moving to the cloud. It is influencing how cloud…
Read MoreGarbage In, Garbage Out: Why Are We Still Having This Conversation?
Artificial intelligence (AI) may be advancing at breakneck speed, but one stubborn truth hasn’t changed: AI is only as good as the data behind it. RT Insights brought this topic to us in their article, “Why AI Systems Are Only as Good as the Data Being Fed into Them“. This is not new news. “Garbage…
Read MoreFrom Information to Action: Turning Data into Better Decisions
Organizations today have access to more data than ever before. Customer behavior, operational performance, financial trends, market activity and employee insights can all be measured and analyzed. But having data and making good decisions with it are two very different things. This interesting topic came to us from IDB in their article, “How Can Governments…
Read MorePeer Review in the Age of AI: Is It Time for an Upgrade?
For generations, peer review has been a cornerstone of scholarly publishing. Before research enters the academic record, experts evaluate its methodology, evidence, originality and conclusions. The system is imperfect, but its purpose remains essential: protecting the credibility and integrity of scholarship. The Scholarly Kitchen brought this interesting topic to our attention in their article,”Guest Post…
Read MoreData 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…
Read MoreDeep 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…
Read MoreWhen 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…
Read MoreAI 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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