Read Kathleen Walch’s article in Forbes about weak vs. strong AI.
Artificial intelligence has a broad range of ways in which it can be applied — from chatbots to predictive analytics, from recognition systems to autonomous vehicles, and many other patterns. However, there is also the big overarching goal of AI: to make a machine intelligent enough that it can handle any general cognitive task in any setting, just like our own human brains. The general AI ecosystem classifies these AI efforts into two major buckets: weak (narrow) AI that is focused on one particular problem or task domain, and strong (general) AI that focuses on building intelligence that can handle any task or problem in any domain. From the perspectives of researchers, the more an AI system approaches the abilities of a human, with all the intelligence, emotion, and broad applicability of knowledge of humans, the “stronger” that AI is. On the other hand the more narrow in scope, specific to a particular application the AI system is, the weaker it is in comparison. But do these terms mean anything? And does it matter whether we have strong or weak AI systems?
Read the full story here.