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Artificial Intuition or “Computational Gut Feeling”. Who Got it First?

Numerous articles have been appearing about Artificial Intuition being the newset form of AI, actually fourth generation AI. One such article, describes Artificial Intuition as:

What is Artificial Intuition?

The fourth generation of AI is ‘artificial intuition,’ which enables computers to identify threats and opportunities without being told what to look for, just as human intuition allows us to make decisions without specifically being instructed on how to do so.  It’s similar to a seasoned detective who can enter a crime scene and know right away that something doesn’t seem right, or an experienced investor who can spot a coming trend before anybody else. The concept of artificial intuition is one that, just five years ago, was considered impossible.  But now companies like Google, Amazon and IBM are working to develop solutions, and a few companies have already managed to operationalize it. “

A similar article, says the following:

“What is Artificial Intuition?

Artificial Intuition allows systems to detect threats, problems, as well as opportunities without knowing what exactly they are looking for or being told what to look for, just as human intuition allows them to make certain decisions without being taught how to do so.

Based on the analysis of information and data, Artificial Intuition can sense that something is not working as it should, or it can detect a problem before it happens, or it can detect an opportunity that may be good for the company. For example, it can sense that a new cyber-attack will happen, even if all transactions appear to be “innocent”. To achieve all this, Artificial Intuition draws its knowledge from a variety of domains and technologies, such as computational neuroscience, linguistics, data science, computer engineering, Machine Learning, Deep Learning, Cognitive Analytics, RPA and bots.

These algorithms mimic the most powerful part of the human brain, that of common sense, instinct and intuition. This ability is similar to human intuition in that it can quickly assess the totality of a situation, including the most subtle, and often overlooked, indicators of a specific activity.”

Surely Google, IBM and Amazon are looking into it. However, just to get things straight, and for the sake of honest reporting and journalism, both articles failed to mention Ontonix. Ontonix launched OntoNet™, the first Artificial Intuition tool in 2005. Since then, the tool has evolved and been used in hundreds of projects and applications, mainly in early anomaly detection, i.e. identifying imminent anomalies and malfunctions before they materialize in a way visible to conventional methods. There even is a specific chip that does Artificial Intuition in real time.

If you want to learn as to how Artificial Intuition finds things it has never seen, how it detects threats without being told what to look for, try our blog. There are hundreds of articles, examples of applications and ideas from diverse fields and disciplines.

Today, OntoNet™ is established technology, not a concept, not an idea, not a working prototype. Read more here.

Established originally in 2005 in the USA, Ontonix is a technology company headquartered in Como, Italy. The unusual technology and solutions developed by Ontonix focus on countering what most threatens safety, advanced products, critical infrastructures, or IT network security - the rapid growth of complexity. In 2007 the company received recognition by being selected as Gartner's Cool Vendor. What makes Ontonix different from all those companies and research centers who claim to manage complexity is that we have a complexity metric. This means that we MEASURE complexity. We detect anomalies in complex defense systems without using Machine Learning for one very good reason: our clients don’t have the luxury of multiple examples of failures necessary to teach software to recognize them. We identify anomalies without having seen them before. Sometimes, you must get it right the first and only time!

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