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While there are definitely a few narrow AI solutions that attempt to fix wider intelligence problems, the vast majority of narrow AI solutions do not seek to accomplish something larger than the particular problem applied to technology.
FREMONT, CA: There is definitely a subset of people pursuing AI technologies with the goal of solving the ultimate problem: developing artificial general intelligence (AGI) that can deal with any problem, situation, and method of thinking that a person can do. AGI is definitely the aim for many in AI research to be carried out in academic and laboratory environments, as it is at the heart of addressing the basic question of whether knowledge is something that only biological organisms can have. But most of those who speak about AI on the market today are not talking about AGI or discussing these main intelligence issues. Rather, they are looking at applying unique AI subsets to restricted problem areas. This is the classic Broad/Narrow (Strong/Weak) AI debate.
As no one has successfully developed an AGI solution, it follows that all existing AI solutions are narrow. While there are definitely a few narrow AI solutions that attempt to fix wider intelligence problems, the vast majority of narrow AI solutions do not seek to accomplish something larger than the particular problem applied to technology. What we mean to say here is that we are not doing narrow AI for the sake of solving a general AI problem, but rather narrow AI for the sake of narrow AI. It won't get any wider for those particular organizations. In fact, it should be said that many corporations do not really care about AGI, and the purpose of AI for these organizations is not AGI.
What are cognitive technologies?
Perhaps a better term for narrow-minded AI to be used exclusively for these narrow applications is cognitive technology. Instead of trying to develop artificial intelligence, businesses are using cognitive technology to automate and allow a wide range of problem areas that require some kind of cognition. Generally, these facets of perception can be grouped into three types of "P" borrowed from the Autonomous Vehicle Industry:
Perceive – Understand the world around you and the feedback from the sensors.
Forecast – Understand trends to predict what happens next and learn from various iterations to boost the overall performance of the system.
Plan – Use what has been learned and perceived to make decisions and plan the next steps.