Previous columns in this series introduced the problem of data protection in machine learning (ML), emphasizing the real challenge that operational query data pose. That is, when you use an ML system, ...

Artificial intelligence is transforming how the U.S. military prepares for war, replacing routine drills with adaptive, ...

Machine learning is often key to success for today’s institutions that rely heavily on data. But often, data science teams can have a difficult time convincing their organizations of the breadth and ...

Gengo, a leader in expert, high-scale crowdsourced translation services, is taking aim at the growing need for high-quality multilingual data to train tomorrow’s advanced AI (artificial intelligence) ...

Quality data is at the heart of the success of enterprise artificial intelligence (AI). And accordingly, it remains the main source of challenges for companies that want to apply machine learning (ML) ...

The eight-month program combines deep technical training with applied learning on sustainable AI practices. Participants are trained not only to build advanced models but also to consider the resource ...

eWeek content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More Machine learning (ML) uses advanced mathematical models ...

From machine learning to image recognition, Forbes Research has uncovered how different industries and regions are embracing ...

When people hear “artificial intelligence,” many envision “big data.” There’s a reason for that: some of the most prominent AI breakthroughs in the past decade have relied on enormous data sets. Image ...

As machine learning becomes more pervasive in the data center and the cloud there will be a need to share and aggregate information and knowledge but without exposing or moving the underlying data.