AI and Data Accuracy
In the world of artificial intelligence (AI), data is the key ingredient that fuels machine learning models. But getting the right data isn’t always easy. Enter synthetic data— reshaping how AI is developed and deployed. This important topic came to us from InfoWorld in their article, “Breaking through AI data bottlenecks.“ Synthetic data is artificially…
Read MoreSecurity and AI Challenges
Artificial intelligence (AI) is transforming industries, boosting efficiency and driving innovation. However, adopting AI comes with a critical challenge: data security. Businesses must ensure they harness the power of AI without compromising sensitive information. This interesting topic came to us from Built In in their article, “How to Adopt AI Solutions While Safeguarding Data Privacy.”…
Read MoreAI-Empowered Search vs. Traditional Search: Why Taxonomy Still Reigns Supreme
In the ever-evolving digital landscape, the way we find information is undergoing a seismic shift. Traditional keyword-based search engines have long served as the backbone of content discovery, powering everything from intranets to e-commerce platforms. But now, artificial intelligence (AI)-empowered search is changing the game—promising smarter, faster and more intuitive results. Yet amid all the…
Read MoreInnovation Needs Governance
In this data-driven world, the governance of data is no longer just a back-office concern; it has become a front-line priority. Generative artificial intelligence (generative AI), with its ability to analyze, create and interpret vast amounts of information, is reshaping the rules of data governance, introducing smarter, faster and more adaptive ways to ensure data…
Read MoreAI in Cybersecurity: Friend, Foe, and Everything In Between
Let’s face it—artificial intelligence (AI) is changing the game in just about every area of life and cybersecurity is no exception. But here’s the catch: AI isn’t just helping the good guys. It’s also arming cybercriminals with faster, smarter and more adaptive tools to breach systems, exploit vulnerabilities and disrupt operations at scale. This important…
Read MoreWhen Data Becomes Useless
In the digital age, data is often hailed as the new oil—an invaluable resource that fuels innovation, insights and strategic growth. But unlike oil, raw data isn’t inherently useful. Without context, structure or meaning, data is just noise—an overwhelming flood of bits and bytes that can bog down systems and obscure rather than illuminate truth.…
Read MoreCombating Decision Fatigue with AI and Explainability
In today’s high-stakes financial landscape, the role of the CFO has evolved far beyond traditional accounting and budget oversight. CFOs are now central to enterprise strategy—tasked with navigating uncertainty, managing risk, driving operational efficiency and translating complex data into actionable insight. The pressure is relentless, and the volume of decisions required daily can quickly become…
Read MoreFrom Data Overload to Discovery
The life sciences field is no stranger to data. In fact, it’s drowning in it. From clinical trials and genomics to wearables and remote patient monitoring, the volume of information being generated is massive—and growing by the second. But having more data isn’t the challenge. The real question is: What are you doing with it?…
Read MoreThe Fallout of Failing Data Integrity
In today’s data-driven economy, information is currency. From personalized marketing strategies to mission-critical business decisions, organizations across every industry rely on data to operate, innovate and grow. But when data integrity isn’t prioritized, that currency becomes counterfeit—unreliable, misleading and sometimes downright dangerous. This interesting and important subject came to us from Financial Times in their…
Read MoreWhen Do You Need a Taxonomy vs. an Ontology? Insights from Marjorie Hlava on Transforming Knowledge Management
In the evolving landscape of knowledge management—especially in the age of artificial intelligence (AI)—organizations are under increasing pressure to structure, retrieve and leverage their data more effectively. But a common question arises: Do you need a taxonomy, an ontology, or both? In a recent KMWorld article, Marjorie Hlava, Chief Science Officer of Access Innovations and…
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