New technologies are always a bit hazy for a few reasons. While most of the topics are still in development, the language used to describe them isn’t always accurate.

Things can get mislabeled in discussions of emerging techs. It’s also common for terms to be used interchangeably, even when there is a distinction between them. One example of this is the debate concerning cognitive computing vs. artificial intelligence.

To those who have little understanding of these concepts, they both may seem to represent the same thing. They both involve the concept of electronic devices and systems learning, and having the ability to make choices. Though there is plenty of overlap, there are some factors that set the two apart.

The difference between the two lies not only in their design, but the way humans tie into the concept of smart machines.

The Definition and Applications of Artificial Intelligence

Artificial intelligence is a broad term, covering many different algorithms, systems, and technologies designed for the same purpose.

AI is a term that refers to a characteristic of a machine to reason and weigh options based on certain parameters. AI involves helping machines recognize patterns in data, and allowing them to analyze trends to make predictions and choices accordingly.

AI has many applications, ranging from analyzing records and picking out important pieces of information to helping autonomous drones operate safely with no human at the controls. The possibilities are vast for AI, and the same can be said of other concepts in the same category of smart technology.

Understanding the Concept Behind Cognitive Computing

cognitive computing vs. artificial intelligenceCognitive computing may seem like a complex idea, and the technical specifics behind it will certainly validate this belief. However, the basic concept behind cognitive computing can be compared to the function of the human brain.

Designed to mimic cognitive activity in humans, cognitive computing deals with understanding through experience. Cognition has always been a vital characteristic of humans, and it, is now being mimicked by computers.

The result of teaching a computer to think and understand in the same way as a human, is that the machine becomes much more valuable to humans. It becomes much more like a partner rather than a tool in practice.

Why the Confusion Between the Two?

The concept of AI and smart machines is one that has existed for decades. However, the technology is developing at a faster rate than ever before. With so many umbrella terms, broad concepts, and mysterious technologies being discussed, it is easy for some confusion to develop.

The misunderstandings about these techs stems from a lack of understanding about the real question. While both concepts involve smart machines, one is more results based, while the other focuses more heavily on the process.

It’s the same idea as finding an answer vs. showing the process, to some degree. While both of these concepts can be useful in many applications, their impact on the progress of machine learning serves two different purposes.

Results vs. Process: Understanding the Distinction

The name cognitive computing provides an easy way of remembering the overall purpose of this concept. Cognition, which involves learning from perception and making decisions accordingly, can augment and improve the human thought-process. Technology already augments human ability in many other areas, so the roots of cognitive computing have been around for generations.

Artificial intelligence also has a name that makes its function somewhat easy to remember. While Ai is largely an umbrella term that is used to describe a wide variety of technologies, it’s about teaching machines how to solve problems that require intelligence.

Teaching machines to solve problems and mimicking brain activity with a machine are two very different things. They both have the ability to help machines perform more intricate and diverse functions, but the distinction between the two deals with the role of humans in the process.

How Humans Factor Into the Machine-Learning Movement

cognitive computing vs. artificial intelligence
One of the things that has delayed machine learning has been the public’s perception about how this technology will impact the world. Debates like cognitive computing vs. artificial intelligence now deal with practices rather than simply just theories, and the pace has caused some people to feel concerned.

These concerns are justified. Such a promising new technology could have unexpected side effects, and some of technology’s greatest minds have already voiced their concerns about how unchecked AI could pose a serious threat.

The biggest fears involve machines replacing humans, and to some degree this has already happened. But in a situation where AI and cognitive computing would be used in the same application, what would be the difference?

If a business owner implemented these solutions to help clean up the company’s finances, the difference would be noticeable. While both would solve the problem if they were programmed properly (the problem in this case being refining accounts) they would do it in different ways.

The AI system could make a choice based on its own analysis. The cognitive computing system would be more likely to serve as an assistant of sorts throughout the process, mimicking the owner’s thought process, sharing the load, and sometimes even developing new solutions through quicker calculations.

Cognitive Computing vs. Artificial Intelligence: Debate Continues 

Cognitive computing vs. artificial intelligence is a debate that will likely gain more attention in the future. With big steps being made in the progression of both technologies, confusion may continue about them before they become better understood.

Both concepts are important to the phenomenon that is taking place, which in this case involves making technology smarter. Whether it’s using algorithms and values to help machines make choices or it’s analyzing the way a machine thinks, smart technology as a whole will likely make some massive progress in the coming decades.

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