Posts in tag

AI Systems


Opening up the “black box” helps remove uncertainties about AI outcomes, providing insight into the modeling process and identifying biases and errors. Artificial intelligence (AI) is being used more frequently in our daily lives, with systems such as Siri and Alexa becoming commonplace in many households. Many households themselves are “smart,” powered by devices that …

New documentation standards in machine learning can enable responsible technology. These risk management strategies highlight how organizations can be compliant while protecting their valuable intellectual property. The growing use of machine learning (ML), within a global drive toward digital acceleration, raises the question, “Who’s minding the store?” We’ve seen many examples of both the power …

Artificial intelligence feeds on data, and data is piling up from increasingly cheap sensors and surging Internet use: videos, images, text; time series data, machine data; structured, unstructured and semi-structured data. And while AI is currently confined to narrow problems in discreet domains, the ambition of machine-learning researchers globally is to write algorithms that can cross …

Can you fool Artificial Intelligence? No? Think again. Three years ago, Apple launched IphoneX with cutting-edge facial recognition technology. This advanced AI technique (Face ID) replaced the old fingerprint recognition technology (Touch ID). The latest technology claimed to be more secure and robust. However, shortly after the launch of Face ID, researchers from Vietnam breached …

Artificial intelligence seems to be making enormous advances. It has become the key technology behind self-driving cars, automatic translation systems, speech and textual analysis, image processing and all kinds of diagnosis and recognition systems. In many cases, AI can surpass the best human performance levels at specific tasks. We are witnessing the emergence of a …

In recent years, entire industries have popped up that rely on the delicate interplay between human workers and automated software. Companies like Facebook work to keep hateful and violent content off their platforms using a combination of automated filtering and human moderators. In the medical field, researchers at MIT and elsewhere have used machine learning to help …