Digest #2019.09.30 – Making the Most of Machine Learning

Understanding Fairness in Machine Learning – This article is a great reminder and defense for the statement, “the data speaks for itself.” Biases in training models affect the results of analyses. It is essential to understand how our models make decisions to tackle this bias by adding more balanced training data. Knowledge of biases in our training models also help in adjusting our training loss function or adjusting prediction thresholds to account for the type of fairness we want to work towards.  

Ways in which AI and ML are improving endpoint security – Take a look at the predicted billions of dollars that will be pouring in to improve cybersecurity. “Cloud platforms are enabling AI and machine learning-based endpoint security control applications to be more adaptive to the proliferating types of endpoints and corresponding threats.” The article sheds interesting light on how AI and ML can revolutionize the field of cybersecurity and improve endpoint security.

AI gears up for data analysis – The article explores how the use of Machine Learning and AI can help scientific research with the potential to improve data analyses speeds and accuracy of results dramatically. Machine learning can change scientific experiments, improve results, and significantly reduce production failures in different industries. “By looking at the long-term patterns [in the signals], you can actually spot imminent failures. One example could be a gradual increase in motor operating temperature, which may indicate that an actuation unit is on its way to overheating.” While investing in AI and ML and gathering data is resource-consuming, the returns and rewards prove to be well worth it.