Artificial intelligence has been a far-flung goal of computing since the conception of the computer, but we may be getting closer than ever with new cognitive computing models.
Cognitive computing comes from a mashup of cognitive science — the study of the human brain and how it functions — and computer science, and the results will have far-reaching impacts on our private lives, healthcare, business, and more.
What is cognitive computing?
The goal of cognitive computing is to simulate human thought processes in a computerized model. Using self-learning algorithms that use data mining, pattern recognition and natural language processing, the computer can mimic the way the human brain works.
While computers have been faster at calculations and processing than humans for decades, they haven’t been able to accomplish tasks that humans take for granted as simple, like understanding natural language, or recognizing unique objects in an image.
Some people say that cognitive computing represents the third era of computing: we went from computers that could tabulate sums (1900s) to programmable systems (1950s), and now to cognitive systems.
These cognitive systems, most notably IBM IBM -1.28%’s Watson, rely on deep learning algorithms and neural networks to process information by comparing it to a teaching set of data. The more data the system is exposed to, the more it learns, and the more accurate it becomes over time, and the neural network is a complex “tree” of decisions the computer can make to arrive at an answer.
What can cognitive computing do?
For example, according to this TED Talk video from IBM, Watson could eventually be applied in a healthcare setting to help collate the span of knowledge around a condition, including patient history, journal articles, best practices, diagnostic tools, etc., analyze that vast quantity of information, and provide a recommendation.
The doctor is then able to look at evidence-based treatment options based on a large number of factors including the individual patient’s presentation and history, to hopefully make better treatment decisions.
In other words, the goal (at this point) is not to replace the doctor, but expand the doctor’s capabilities by processing the humongous amount of data available that no human could reasonably process and retain, and provide a summary and potential application.
This sort of process could be done for any field in which large quantities of complex data need to be processed and analyzed to solve problems, including finance, law, and education.
These systems will also be applied in other areas of business including consumer behavior analysis, personal shopping bots, customer support bots, travel agents, tutors, security, and diagnostics. Hilton Hotels recently debuted the first concierge robot, Connie, which can answer questions about the hotel, local attractions, and restaurants posed to it in natural language.
The personal digital assistants we have on our phones and computers now (Siri and Google GOOGL -2.32% among others) are not true cognitive systems; they have a pre-programmed set of responses and can only respond to a preset number of requests. But the time is coming in the near future when we will be able to address our phones, our computers, our cars, or our smart houses and get a real, thoughtful response rather than a pre-programmed one.
As computers become more able to think like human beings, they will also expand our capabilities and knowledge. Just as the heroes of science fiction movies rely on their computers to make accurate predictions, gather data, and draw conclusions, so we will move into an era when computers can augment human knowledge and ingenuity in entirely new ways.
Feel free to contact E-SPIN for the various technology solution that can facilitate your cognitive computing infrastructure availability and security monitoring.
