Are we alone in the universe? Scientists may have just moved us closer to answering this question. The team – led by researchers from the University of Toronto – has streamlined the search for extraterrestrial life by using a new algorithm to organize the data from their telescopes into categories, in order to distinguish between real signals and interference. This has allowed them to quickly sort through the information and find patterns, through an artificial intelligence process known as machine learning. They discovered eight extraterrestrial signals that seem to have the hallmarks of technology.

Artificial intelligence (AI) is making inroads in the healthcare industry in various ways. From improving medical diagnoses to finding new cures for diseases, AI is revolutionizing the way healthcare professionals approach their work. One exciting example of AI in healthcare is its application to electrocardiograms (ECGs), which are used to monitor and diagnose heart health. Researchers in northern Alberta, Canada, are utilizing AI to glean more information from ECGs and improve patient care and the healthcare system as a whole. ECGs are a standard test in hospitals, used to check the rhythm and electrical activity of the heart.

An AI-based home screening test to detect oral and throat cancers from saliva samples is now available in the United States with the hope of transforming oral and throat cancer detection. Based on a technology approved by the US Food and Drug Administration (FDA) as a "breakthrough device," the saliva test can detect early symptoms of oral and throat cancer with more than 90 percent accuracy. Due to a lack of effective diagnostic tools, these cancers often go undiagnosed until they have reached an advanced stage, resulting in low survival rates. In a previous study, Maria Soledad Sosa from the Icahn School of Medicine at Mount Sinai and Julio A. Aguirre-Ghiso, now at Albert Einstein College of Medicine, discovered that the ability of cancer cells to remain dormant is controlled by a protein called NR2F1. This receptor protein can enter the cell nucleus and turn numerous genes on or off to activate a program that prevents the cancer cells from proliferating.

Artificial intelligence presents a major challenge to conventional computing architecture. In standard models, memory storage and computing take place in different parts of the machine, and data must move from its area of storage to a CPU or GPU for processing. The problem with this design is that movement takes time. You can have the most powerful processing unit on the market, but its performance will be limited as it idles waiting for data, a problem known as the "memory wall" or "bottleneck." When computing outperforms memory transfer, latency is unavoidable.