Discerning narrow and general AI in cognitive applications

Are we close to having robots that can represent (and possibly replace) our intelligence? The answer is yes and no according to an article in the Washington Post.

One reason we don’t have full artificial intelligence (AI) is because the field is made up of many components, with some more advanced than others. As an example, while speech-to-text is well established at this point, we’re still at the embryonic stages of computers obtaining real meaning from video. The field of AI is not moving at uniform pace.

We are also more advanced at having AI be applied to set tasks (such as a chat bot that can book an Uber) rather than the overall bots that try and replace all functions of humanity. Development of these task-based bots equate more to the division of labor we see in business, especially in areas of low-skilled work where we humans perform very similar tasks within a bounded range, and it is these areas where advances in AI have so far had the biggest business impact.

So when thinking about design of cognitive solutions, it’s important to distinguish between applications that are task-based and rely on narrow AI compared to the more challenging general AI applications.

 

 


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