Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Some dogs might be smarter than others. Hungarian researchers at Eötvös Loránd University are gathering evidence on this topic with a "Genius Dog Challenge." The nonprofit research project has been studying canine memory as a means to improve dog and human communication.

As a Principal Automation Architect at Magenic, Paul Grizzaffi is following his passion for providing technology solutions to testing, QE, and QA organizations, including automation assessments, implementations, and through activities benefiting the broader testing community. An accomplished keynote speaker and writer, Paul has spoken at local and national conferences and meetings. In addition to spending time with his twins, Paul enjoys sharing his experiences and learning from other testing professionals; his mostly cogent thoughts can be read on his blog. Jennifer Bonine is a well-known speaker, teacher, and trainer at both national and international conferences. She has keynoted numerous Testing, Agile, and Development conferences.

Loom Systems Ltd. is joining the growing ranks of companies applying artificial intelligence to the task of making sense out of the mass of data that overwhelms security professionals. The company today is announcing an operational analytics platform for real-time detection and resolution that reads log files and looks for anomalies. The Tel Aviv-based company says it does this by mathematically modeling the ways in which humans analyze such data, and then simulating the process via machine learning. It correlates each metric to baseline patterns in order to detect anomalies and predict future trends. The result is what the company claims is a 45 percent reduction in mean-time-to-resolution and a 93 percent reduction in log file clutter.

Loom Systems Ltd. is joining the growing ranks of companies applying artificial intelligence to the task of making sense out of the mass of data that overwhelms security professionals. The company today is announcing an operational analytics platform for real-time detection and resolution that reads log files and looks for anomalies. The Tel Aviv-based company says it does this by mathematically modeling the ways in which humans analyze such data, and then simulating the process via machine learning. It correlates each metric to baseline patterns in order to detect anomalies and predict future trends. The result is what the company claims is a 45 percent reduction in mean-time-to-resolution and a 93 percent reduction in log file clutter.