Today, bigness means the retailer's machine learning efforts benefit from data generated by people who shop at Walmart every week and activities around the tens of millions of items on its website. "Scarcity of data is what makes artificial intelligence really hard," Mr. King told Ms. Castellanos. "If you have volumes of data like we do, you can really apply it much quicker across the board," he said. Mr. King shared his take on several technologies, some not quite ready for prime time. Overseas traders charged with hacking SEC's public filings site.

It is likely self-evident to many that the security industry's most overused buzzword of the year is "machine learning." Yet, despite the ubiquity of the term and its presence in company marketing literature, most people – including those working for many of the vendors using the term – don't actually know what it means. Scanning through industry sites and product descriptions, machine learning is often positioned as either a "new" tool or a "new" method – something that can provide additional capabilities or features. For many classes of threat detection, machine learning is positioned as "signatureless" detection by those that don't yet know the basic principles of the math or science behind it. The best way to understand what machine learning is and what it truly brings to the security industry is to compare it to a technology advance that kick-started two centuries ago – the steel age.