Subject: AI in Environmental Protection
This article explores the utilization of deep learning to make predictions on when and how much damage a flood may cause. The study explains the usage of "rapid and accurate flood risk prediction" (RAPFLO), which uses a "hierarchical deep neural network (HDNN)." This tool would be able to predict floods at a much cheaper rate and utilize less energy than a regular Machine learning program.
Read Annotated Article View on Google DriveSubject: Machine Learning in Environmental Monitoring
This research explores the utilization of a machine learning program for predicting air quality in Indian cities. The paper reviews multiple books on the topic and runs their own study to explain how important it is to know how polluted the air has become. Air quality models are beneficial for allowing a city to create more green spaces and initiate programs to clean cities.
Read Annotated ArticleSubject: Sustainable AI Development
This article explores how artificial intelligence can be designed in a way that reduces energy consumption and supports sustainability. The authors propose "green AI" approaches that optimize algorithms and reduce the data needed for training without compromising performance. They note that some AI models require enough energy to "power around 121 homes for a year."
Subject: AI Applications in Climate Solutions
This article provides a detailed look at how AI could help address climate change, while also stressing the ethical and practical challenges. The authors explain that AI can assist in "classification, prediction, and decision-making," making it a potentially powerful tool for identifying solutions to environmental problems.
Subject: Ethical AI Development
This journal gives an informational analysis of the ethical issues seen with using AI. It references how algorithms can accomplish tasks at high speeds, but AI is doing more than it is asked to—it can scan information and figure out private information about users, resulting in a need for caution in what we allow AI to do.
Subject: AI Applications in Healthcare
This article reveals key information on how AI can be broken down into Machine Learning, Artificial Neural Networks (ANN), and Deep Learning. It explains how machine learning is trained on data and utilizes an ANN to differentiate between different characteristics in the data, with applications in the medical field.