Frequently asked questions

Get answers to the most commonly asked questions about this product.

The Oxford Dictionary defines AI as “the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.”

AI essentially involves making computers more able to match or exceed human intelligence in its various forms by mimicking the human ability to discover, infer and reason.

Machine learning is a subfield of AI and computer science that has its roots in statistics and mathematical optimization. Machine learning covers techniques in supervised and unsupervised learning for applications in prediction, analytics, and data mining.

Machine learning can be (and often is) used independently of other AI or cognitive technologies. In fact, this is the most prevalent type of “AI” we see today. Many machine learning algorithms and techniques are already in use within various solutions that look for patterns or anomalies in data.

Deep learning is a new set of methods that is changing machine learning in fundamental ways. Deep learning isn't an algorithm, per se, but rather a family of algorithms that implement deep networks with unsupervised learning.

Cognitive computing is a subfield of AI which builds on neural networks and deep learning. It applies knowledge from cognitive science to build systems that simulate human thought processes.

Rather than focusing on a singular set of technologies, cognitive computing covers several disciplines, including machine learning, natural language processing, vision, and human-computer interaction. Of those, Cognitive computing focuses most heavily on natural language processing.

Rather than being explicitly programmed, they learn and reason from their interactions with us and from their experiences with their environment.

Watson is IBM’s AI, Machine Learning and Cognitive computing platform. It provides a wide range of AI technologies to process both structured and unstructured information from a wide range of sources, understand what they mean and add them to its body of knowledge (a.k.a. corpus) for subsequent use.

Predictive analytics extracts information from data using many techniques from data mining, statistics, modeling, machine learning and artificial intelligence to analyze current data to make predictions about unknown future events.

AI has been used to hype a lot of things that have stretched the definition of the term. Some promises of AI have already been realized while others remain in the realm of research. Instead of thinking of AI as a single feature, it is better to envision it as a collection of related technologies.

IBM is now applying AI and cognitive technologies to the cybersecurity space in order to allow organizations to identify threats and respond more quickly. Watson for Cyber Security has ingested over 2 billion documents in the corpus and is adding thousands more every day.

No. The goal of AI is to augment human intelligence – not replace it. There are still significant limits to what cognitive technologies can do, especially in the area of decision making, where humans are able to weigh factors that can’t easily be expressed in algorithmic terms.

You’ve been watching too many sci-fi movies.

Like any technology, it can be misused. We know that the ‘bad guys’ are interested in abusing AI for their own ends, but we’re far ahead of them at the moment. AI is just a tool that can be leveraged for good or malicious work.

Yes. IBM customers using QRadar Advisor with Watson typically see an improvement in their security posture because they are able to complete investigations faster, more thoroughly and more consistently.