Here are the five ways that machine learning systems can be protected from potential attacks: 1. Securing soft assets: Generally, not much weightage is given to protecting soft assets like ...

Applications for machine learning. The field of machine learning is very active right now, with many common applications in business, academia, and industry. Here are a few representative examples: ...

Benefits of and Best Practices for Protecting Artificial Intelligence and Machine Learning Inventions as Trade Secrets Marguerite McConihe , Meena Seralathan Mintz - Intellectual Property Viewpoints ...

Machine-learning algorithms use statistics to find patterns in massive* amounts of data. And data, here, encompasses a lot of things—numbers, words, images, clicks, what have you.

“Successful machine learning is only as good as the data available, which is why it needs new, updated data to provide the most accurate outputs or predictions for any given need,” said ...

As machine learning and AI became more advanced, CrowdStrike leveraged these tools to build alert systems based on events. “One of the things that CrowdStrike pioneered was attack indicators ...

To a large extent, supervised ML is for domains where automated machine learning does not perform well enough. Scientists add supervision to bring the performance up to an acceptable level.

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

Machine learning has enabled AI to get around one of its biggest obstacles, the so-called Polanyi’s paradox. Explicit knowledge is formal, codified, and can be readily explained to people and ...

Machine learning is the process by which computer programs grow from experience. This isn’t science fiction, where robots advance until they take over the world. When we talk about machine ...