Cognitive Solutions and Search Engines: Understanding the Differences

Often, I am asked the question, “what is the difference between web search engines and cognitive solutions?” Clients understand that web search engines and cognitive solutions are both simple and easy to use, but they also realize the complexity behind each.  In short, cognitive solutions give you an answer to your question, and search engines give you a list of links where you may find the answer to your question. However, they serve different purposes.

Cognitive solutions are typically bounded by a particular domain of knowledge

For example, the domain might be a list of regulations and procedures. The cognitive solution is trained to use machine learning techniques in order to give precise, customizable answers to questions. Part of this ability comes from its natural language processing of the question and potential responses.

Search engines are not bounded by a domain of knowledge. They can span a very broad range of types of questions and answers. While they do not have the precision of a cognitive solution, they are able to respond to questions across much broader set of information. Cognitive solutions tend to be narrow and deep while a search engine is broad and shallower in its ability to answer questions. Search engines are a powerful tool, but they fall short for many large enterprises, and organizations that handle and face complex matter in various business domains.

An example of how IBM uses cognitive solutions is at Memorial Sloan-Kettering Cancer Center in New York. IBM is providing meaningful work, and our clients are witnessing the impact and effectiveness of IBM’s cognitive solutions. IBM Watson is helping Memorial Sloan-Kettering Cancer Center fight cancer with evidence-based diagnosis and treatment suggestions. Assisting non-specialized or general doctors and their teams, IBM Watson helps counsel teams with evidence-based information from the patients’ records. Watson uses a set of transformational technologies which leverage natural language, hypothesis generation and evidence-based learning. Combined with massively parallel probabilistic processing techniques, Watson has helped doctors and their teams to think, act and operate in new ways.


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