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Ontology: The Invisible Architecture Powering Findability in the Age of AI
In information science, ontology is one of those terms that sounds intimidating but quietly does some of the most important work behind the scenes. At its core, an ontology is a structured framework that defines the relationships between concepts within a domain. It goes beyond simple lists of terms or categories by mapping how ideas…
Read MoreAccess Innovations, Inc. to Exhibit at SSP’s 48th Annual Meeting
Access Innovations, Inc. is proud to support the Society for Scholarly Publishing’s (SSP) 48th Annual Meeting, taking place May 27–29, 2026, at the Gaylord Pacific Resort & Convention Center in Chula Vista, California. As one of the premier gatherings for the scholarly communications community, the SSP Annual Meeting brings together publishers, librarians, researchers, technologists and…
Read MoreGarbage In, Genius Out? Not Without Data Governance
Generative artificial intelligence (GenAI) is having a moment. It writes, summarizes, predicts, designs and occasionally makes you question your own job security before your coffee kicks in. But beneath all the flash and promise is something far less glamorous and far more important: data governance. Because no matter how sophisticated your AI tools are, they…
Read MoreAccessInn.ai Launches: API-Driven Ontological Services for Multi-Disciplinary Large Language Model Development
Access Innovations, Inc. is proud to announce the launch of AccessInn.ai, a next–generation platform providing API–accessible ontological services designed to empower developers, data scientists, and AI architects in building, managing, and scaling language model programs across public, private, and enterprise environments. Using agnostic, fungible APIs, the ontologies tag content at the level of content submitted, from full documents…
Read MoreBig Data and AI: A Partnership with Power and Pressure
Big data and artificial intelligence (AI) are often discussed together because each strengthens the other in ways that drive real value. Big data provides the volume, variety and velocity of information that AI systems need to learn, adapt and improve. AI, in turn, turns that raw data into something useful by identifying patterns, making predictions…
Read MoreConnected Intelligence: How Graph Databases Power Taxonomies and Explainable AI
Graph database technology is quietly reshaping how we organize and understand complex information. Unlike traditional databases that store data in rigid tables, graph databases focus on relationships. They map how things connect, not just what they are. That shift turns out to be incredibly powerful when dealing with messy, real-world data where context matters as…
Read MoreWhere AI Meets the Cloud and Things Get Interesting
Artificial intelligence (AI) and cloud computing used to feel like two separate conversations. Now they are basically inseparable. The cloud gives AI room to stretch out and do its thing, and AI turns the cloud into something a lot smarter than just a place to park data. One of the biggest shifts is how easy…
Read MoreRetrieval Augmented Generation and the Role of Taxonomies in AI
Retrieval Augmented Generation (RAG), is becoming an important approach in the development of reliable artificial intelligence (AI) systems. While large language models are powerful tools for generating natural language responses, they are often limited by the information contained in their training data. RAG improves this process by connecting language models with external knowledge sources so…
Read MoreWhen Innovation Outpaces Human Bandwidth in Academic Publishing
Artificial intelligence (AI) has quickly moved from an emerging technology to an unavoidable presence across nearly every industry. In academic publishing, AI now touches everything from manuscript screening and peer review assistance to metadata generation, discoverability tools and predictive analytics. While these advancements promise efficiency and innovation, they have also produced an increasingly common side…
Read MoreWhy Meaning Must Come Before Machines
Artificial intelligence (AI) is often described as understanding language, content or knowledge, but this description can be misleading. AI does not interpret meaning in the way humans do. It does not comprehend intent, nuance or context as lived experience. Instead, AI operates by identifying patterns and relationships within structured data. What it recognizes is not…
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