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Mar 13 2024

The Rise of Generative AI in Insurance

The global market for artificial intelligence (AI) in insurance is predicted to reach nearly $80 billion by 2032, according to Precedence Research. This growth is being driven by the increased adoption of AI within insurance companies, enhancing their operational efficiency, risk management, and customer engagement. Despite widespread integration of AI in the industry today, its full […]

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Explainable AI: 5 Open-Source Tools You Should Know

Explainable AI refers to ways of ensuring that the results and outputs of artificial intelligence (AI) can be understood by humans. It contrasts with the concept of the “black box” AI, which produces answers with no explanation or understanding of how it arrived at them. Explainable AI tools are software and systems that provide transparency […]

The Growing Impact of AI on Data Science in 2023

While AI’s ubiquity is becoming increasingly evident through everyday tools like chatbots, smart cameras, and smart content generation, there’s an expansive universe of less recognized but highly potent advancements poised to redefine how data scientists interact with and leverage the burgeoning volume and complexity of datasets. Emerging AI trends such as natural language processing, reinforcement learning, […]

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AI and Privacy: Navigating the Intersection of Technology and Personal Data

The rapid adoption of generative AI in the business world is transforming the way we work and improving our ability to engage with customers, streamline internal processes, and drive cost savings while introducing unprecedented challenges to the protection of individual privacy. As AI technologies continue to evolve and permeate various aspects of our lives, concerns about data […]

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What Is a Feature Store in Machine Learning?

A feature store is a centralized platform for managing and serving the features used in machine learning (ML) models. A feature is an individual measurable property or characteristic of data that is used as input to an ML model. In order to build effective ML models, it is critical to have high-quality, well-engineered features that […]

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