Centering on Data

Data has never been more powerful, useful, and revelatory. This is true regardless of the subject matter and includes all types and sources of data, including healthcare data, transaction data, and even human resources data. Human Resource Executive brought this interesting information to our attention in their article, “Your HR data is extremely valuable—how to…

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Gambling on Technology

Since machine learning models are imperfect, people must understand when to believe a model’s predictions in high-stakes situations. MarkTechPost brought this interesting news to our attention in their article, “MIT researchers have developed a new technique that can enable a machine learning model to quantify how confident it is in its predictions.” Robust machine learning…

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Semantic Search in Social Media

Elon Musk is investing in artificial intelligence (AI) and building his own generative AI models. He recently announced they are also working on semantic search for X, formerly Twitter. This news came to us from Social Media Today in their article, “Elon Musk Says Semantic Search Coming Soon to X.” Semantic search in social media…

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Both Sides of Generative AI

There has always been fear surrounding artificial intelligence (AI) and, with the recent advances using natural language processing (NLP) and chatbots, it has increased by quite a bit. There are, however, perpetual advances in science. It’s up to us to find the benefits where we can. Analytics Insight brought this interesting information to our attention…

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Deep Learning is About Training

Deep learning training is the process whereby a deep neural network is taught using a set of data such that it can make predictions for a modeled event. It can involve trial and error, and it can take many tries until the network is able to accurately draw conclusions based on the training data. Constructing training…

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Technology in Marketing

The future of marketing is driven by technology, data, and consumer behavior. There are also strong emphases on delivering personalized, engaging, and socially responsible experiences for customers. What does this mean to day-to-day data management? Business Day brought this interesting information to us in their article, “Technology, data, consumer behaviour driving future of marketing –…

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Mitigating Risks with AI

It is understood that artificial intelligence (AI) models that are built on consumer data must also be built with data privacy in mind. Some users are hesitant of automated systems that collect and use their data, so to remain viable, AI models must incorporate privacy protection into their design. This interesting information came to us…

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Human Error in Technology

Artificial intelligence (AI) has been helping us in various applications such as customer service, securities trading, and healthcare. Now researchers have found that AI can be used to predict natural disasters. AI can forecast the occurrence of several different types of natural disaster, using vast volumes of high-quality data, and is therefore now at the…

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Calming Fear

A lot of fear surrounds artificial intelligence (AI). Some is connected to perceived job security and some is related to technology “doomsday” scenarios. The University of Waterloo researchers have developed a new explainable AI model to reduce bias and enhance trust and accuracy in machine learning-generated decision-making and knowledge organization. This interesting information came to…

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Emerging Technologies and Regulation

The question of whether emerging technology should be regulated is a complex and nuanced one. The answer depends on various factors, including the specific technology in question, its potential benefits and risks, and the broader societal context. This interesting information came to us from Governing in their article, “How Should Government Regulate Emerging Technology?” There…

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