Artificial intelligence involves getting computers to perform tasks that historically only humans can accomplish – voice recognition, language interpretation, visual perception and fact-based decision making – as well as skill- and labor-intensive activities.
But AI also accomplishes tasks people could never do. That’s where another type of intelligence comes in – the one that involves gathering and interpreting information to drive decisions. Computers are very good at this type of intelligence. So good, in fact, that machine learning (ML) algorithms can be trained to pick up patterns and anomalies that elude the human senses.
Where a human might make an educated guess about something or apply “business intuition” to it, a machine learning (ML) algorithm provides an actual likelihood and a percentage, making a data-driven prediction that a person could not provide.
For a human to read 45 million documents and extract the key terms, it would take several lifetimes. For AI or ML, it takes a few minutes. This is why ML and AI have been woven into the fabric of cybersecurity intelligence-gathering and defense.
Getting AI engines to deliver real-world benefits from gathering and interpreting intelligence requires lots and lots of data. Organizations need to implement advanced systems such as the Cloudera Data Platform, often in conjunction with other tools, to manage and automate the entire data lifecycle, from data creation and ingestion to organization to decision-making.
