This Tool Defends AI Models Against Adversarial Attacks

The potential number of applications for machine learning has grown tremendously in the last several years, as AI models become increasingly more powerful. Machine learning is already being used in many areas of daily life, whether that's in recommendation algorithms, self-driving cars, or being used in novel ways in fields like research or finance. Even more promising is how machine learning models might someday revolutionize healthcare, and may even help us grapple with impossibly complex issues like mitigating climate change. But despite the great potential of machine learning models, they are not foolproof and can make mistakes -- sometimes with disastrous consequences. These unintended impacts are all the more concerning when image recognition algorithms are being increasingly used in evaluating people's biometric data.