Five significant differences between general and narrow Artificial Intelligence (AI) that you should know

For a human being it has always been difficult to put oneself in the shoes of another, now imagine how complicated this is for the teams of data scientists that are working in developing artificial intelligence (AI). Machines analyze the world in different ways and transmit that information in code making this is a complex process to understand and achieve.

Most people associate AI with intelligent robots, however, the applications of AI are much more broad than this specific use case. The types of AI that are used today doesn’t necessarily require a physical robots. For example, the AI application on Facebook and Google search engine that allows them to predict what the user is looking for and prefill the search results.

Artificial intelligence is divided into two types, the artificial general intelligence (AGI) and the artificial narrow intelligence (ANI). In the following table I will highlight some characteristics of AGI and ANI so clear understanding of the two is drawn.

Artificial Intelligence can be defined as any kind of thinking power exhibited by non-living things “aka” machines. That definition is perhaps the simplest definition that can be found. When we study AGI and ANI, there is a high probability of getting confused with the terms and definitions.

Learning and reasoning, planning, adaptability, vision, voice recognition, automation and mobility are qualities that represent the ANI. The AGI in technical terms is still not feasible, which tries to expose this version of the AI is that the machines can come to have the same reasoning of a person. Nowadays, even a human mind with basic reasoning would surpass supercomputer because there is still no way to program a machine so that it can make decisions based on complex algorithms.

Still the future of Ai is uncertain in many ways, but there are significant advancements that are impacting the world in different areas. Are you ready to start implementing AI in your company and solve complex problems that humans are not able to?