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AI Governance in Action: Practical Insights from a Data-Driven Enterprise

As AI adoption skyrockets, how can organizations harness its power responsibly? AI promises enhanced decision-making and customer interactions, but it comes with ethical, compliance, and infrastructure risks. Consequently, AI governance is crucial to address these risks.  In response, many businesses turn to their established data governance (DG), aiming to leverage existing controls and procedures. However, AI introduces […]

Large Language Models 101

Large language models (LLMs), built on the transformer architecture of deep learning, are designed to process very high volumes of textual data at a high speed. LLMs also have the power to generate new text and interact with human language innovatively. Training on different types of data, including articles, books, periodicals, and websites, LLMs develop […]

Generative AI vs. Traditional AI

Traditional AI, also known as “classical AI,” is known for being rule-based and dependent on stringent programming for its intended output. These techniques revolve around the manipulation of symbols and logical reasoning to perform tasks.  Key methodologies include rule-based systems, where knowledge is encoded in the form of “if-then” statements, enabling machines to make decisions […]

Choosing a Data Quality Tool: What, Why, How

Data-driven organizations are in a race to collect the information that modern analytics techniques rely on to generate insights and guide business decisions. The ever-growing flow of data into business systems challenges companies to devise new techniques for ensuring the quality of the data as its quantity skyrockets. Data quality tool vendors are rising to […]