Cognitive Computing

Deployment of Cognitive Technologies for Narrow AI

Smriti Srivastava

Today several companies are building AI solutions to solve ultimate business problems or in other words, they are looking at applying very specific subsets of AI to narrow problem areas. According to Forbes, however, certain subsets are pursuing AI technologies in order to create artificial general intelligence (AGI) that can handle any problem, situation, and thought process that a human can. Although AGI is certainly the goal for many in the AI research being done in academic and lab settings, since no one has successfully built an AGI solution, it follows that all current AI solutions are narrow.

It is being believed that perhaps 'cognitive technology' is a better term for narrow AI being applied for only those narrow applications. Companies, instead of building artificial intelligence, are employing cognitive technologies to automate and enable a wide range of problem areas that require some kind of cognition.

Understanding the distinction

Artificial Intelligence and Cognitive Technology are the terms that are often used interchangeably but have a different sense in context to their practical application. Where AI can be considered as a technology that helps machines augmented intelligence, some believe that it will soon outdo humans in accuracy, strength, and agility. On the other hand, cognitive technology advocates claim that the technology can deal with huge volumes of data and repeatable loops of analytics. However, in this approach, humans remain in charge of the decision making process.

According to Intel CEO Brian Krzanich, it is apparent that both AI and cognitive computing are "based on the ability of machines to sense, reason, act and adapt based on learned experience." This implies that they are similar in intent but differ in their tendencies in interacting naturally with humans.

Therefore, it is transparently clear that even if cognitive technologies are indeed a subset of AI technologies but the significant difference between them is that the latter can be applied both towards the goals of AGI as well as narrowly-focused AI applications. As quoted in the article, on the other hand, "using the term cognitive technology instead of AI is an acceptance of the fact that the technology being applied borrows from AI capabilities but doesn't have ambitions of being anything other than technology applied to a narrow, specific task."

Conclusion

However, the landscape of AI is going through a great transformation in terms of marketing hype, venture capital dollars, and government interest – all together are encouraging and propelling its reach to the next level, yet the industry is still quite far away from the end vision of AGI.

Kathleen Walch, Managing Partner & Principal Analyst at AI Focused Research and Advisory firm Cognilytica, said, "perhaps the issue never has been with the term Artificial Intelligence. AI has always been a lofty goal upon which to set the sights of academic research and interest, much like building settlements on Mars or interstellar travel. However, just as the Space Race has resulted in technologies with broad adoption today, so too will the AI Quest result in cognitive technologies with broad adoption, even if we never achieve the goals of AGI."

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