Posts Tagged ‘Explainable AI’
AI on Watch
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…
Read MoreFinding the Data
Enriching metadata with better tags and descriptions makes it easier for anyone to search and find quicker and more easily. Recent advances in IT and artificial intelligence (AI) offer remarkable opportunities for the automatic enrichment of cultural heritage metadata with minimal resources. However, involving humans in this work remains important. This interesting topic came to…
Read MoreHierarchy of Classification
The security concept of classified vs declassified data is somewhat clear, and there is yet a broader type of commerce-oriented data classification for businesses that contributes to the success of data analytics pipelines. Tech Target brought this interesting information to our attention in their article, “Data analytics pipeline best practices: Data classification.” There is a…
Read MoreAI and the Environment
If we’re going to rely on more renewable energy sources, utilities will need better ways of predicting how much energy is needed, in real time and over the long term. There has been much discussion and debate in the scientific community regarding the efficacy and suitability of machine learning techniques to help improve our understanding of local…
Read MoreSustainability and Technology
Everything has an expiration date. We move ahead as a civilization while leaving behind everything that doesn’t evolve, with efficiency sifting out what remains. New technologies, including mobile applications, wireless sensor networks, and online computer/video gaming show great promise for advancing citizen science. This interesting topic came to us from Fast Company in their article,…
Read MoreUnderstanding Machine Learning
Machine learning is a field related to artificial intelligence (AI) that focuses on the development of algorithms and models enabling computers to learn from and make predictions and decisions based on data, without having been explicitly programmed to perform specific tasks. This interesting topic came to us from The Scholarly Kitchen in their article, “The…
Read MoreUnderstanding Deep Learning
Deep learning is a machine learning technique that teaches computers to do what comes naturally to humans: learning by example. Venture Beat brought this information to us in their article, “This is what makes deep learning so powerful.” Deep learning is a key technology behind driverless cars, enabling them to recognize a stop sign or…
Read MoreRelying on Data Management
Data management is critically important in any organization, especially in the context of modern technology and the increasing reliance on data-driven decision-making. Every business relies on data and data management allows businesses to better organize and access the information gathered across a wide range of software solutions. Most modern businesses recognize the value of data and for…
Read MoreData and Public Health
Open data and public health overlap in numerous ways to improve health outcomes, enhance research, and empower communities. By sharing and utilizing open data, public health efforts can become more effective, efficient, and transparent. PLOS brought us this interesting topic in their article, “The beauty of (open) data will save public global health.” Public health…
Read MoreDeveloping New Applications for Deep Learning
Emerging technologies are being used for different things every day. A systematic approach to retraining deep learning artificial intelligence (AI) algorithms to deal with different situations has been developed by climate researchers in the United States, and they discovered fascinating new approaches for creating training algorithms. Physics World brought this interesting information to us in…
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