Posts Tagged ‘Explainable AI’
Revolutionizing Information Science: The Impact of Deep Learning
In the digital age, where vast amounts of data are generated and consumed every second, the field of information science has evolved significantly. One of the most transformative technologies driving this evolution is deep learning. Deep learning is a subset of artificial intelligence (AI) and has proven to be a game-changer in improving the efficiency,…
Read MoreLearning From Machines
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…
Read MorePredictive Analytics and AI
Artificial intelligence (AI) has been helping us in various applications such as customer service, financial transactions, 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…
Read MoreAI and Data Privacy
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…
Read MoreEmbracing Green Technology
2023 is quickly becoming a pivotal year for organizations as technologies emerge and advance and 5G enables innovation and revolutionary models of connectivity. The growth in many areas, including 5G, robotics, green technology, and digital skills and reskilling continues to evolve. This interesting topic came to us from Bizz Buzz in their article, “How these…
Read MoreData Analytics and Generative AI
Generative artificial intelligence (AI) is beginning to materially affect what organizations can do with their data. Tech Target brought this interesting information to us in their article, “Generative AI hype evolving into reality in data, analytics.” Generative models can generate synthetic data that resembles real data, helping to augment a dataset and increase its size.…
Read MoreInterdependency of Data
Artificial intelligence (AI) models that are built on consumer data must also be built with data privacy in mind. It is understandable that some users are hesitant to use automated systems that collect and use their data, so to remain viable, AI models must incorporate privacy protection into their design. This interesting topic came to…
Read MoreValuing the Taxonomy
The International Sustainability Standards Board (ISSB) has issued a proposal reflecting the disclosure requirements under the inaugural global standards IFRS S1 and IFRS S2. The proposed IFRS Sustainability Disclosure Taxonomy is designed to help users better understand how to produce sustainability-related financial information digitally. This important news came to us from Corporate Secretary in their article, “ISSB proposes…
Read MoreEmerging Tech in Healthcare
Deep learning has already shown tremendous potential in improving healthcare in various ways, and there continues to be additional advancements and applications of deep learning in the field of healthcare. This interesting news came to us from EurekAlert! in their article, “Deep learning method developed to understand how chronic pain affects each patient’s body.“ One…
Read MoreThe Gap Between Human and Artificial Intelligence
Artificial intelligence (AI) brings with it the possibility of genuine human-to-machine interaction. When machines become intelligent, they can understand requests, connect data points, and draw conclusions. They can reason, observe, and plan. It’s very common to hear the terms “machine learning” and “AI” thrown around interchangeably, but they are often used in the wrong context.…
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