What are the 5 tribes of artificial intelligence? How do they relate to one another? How is each one disparate from one another? For the average user in cyberspace we’ve heard all the hype, but do we really know what AI is? Its time we break it down and provide the cyber-fuel we need for a little understanding.
Join us in our Wisdom Series where we explore all the latest in disruptive tech for the common user formulated with easily digestible, straightforward chunks. We begin with Meet AI, a user-focused graphic series built on understanding the basics in the field. As AI may very well be the most disruptive technology in the course of human history, it is where we begin.
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Understanding AI Means Breaking Down the Human Approaches to AI
Humanity’s approach to creating machine learning and artificial intelligence comes from a variety of academic fields from statistics to neuroscience. Each provides the opportunity to build on intelligence from a unique human viewpoint. This includes a root origin, or academic field from which the theories are derived, and a problem-solving approach linked to that root origin, that which the approach relies on for its machine learning models, the reliance if you will.
In the graphic above, we illustrate the five human tribes of an intellectual approach regarding how intelligence can be related to machines. As Formtek notes, the discussion is based on the work of Pedro Domingo, the five tribes are recognized to be symbolists, connectionists, evolutionists, bayesians, and analogizers. For Pedro’s work specifically, please refer to this link.
In Artificial Intelligence for dummies, the ultimate goal of these five tribes is to blend the rigor of human intelligence, as personified in these five tribes, bringing together all the strategies and technologies of each, to form one approach (#CommissionsEarned). For a broader discussion on each of the five frameworks see this dummies link.
Synopsizing from dummies‘ Artificial Intelligence again, one singular, master algorithm known as the singularity that can learn anything and problem solve as a human being can is the ultimate goal. Despite this, as we so often find ourselves in this human experience called life, the more we learn the more we realize we don’t know. The same is true here and even bringing together the five tribes may not be enough to truly replicate human intelligence at this point in time.
So in the end, we humans have created a number of ways to understand intelligence. More specifically, we have created five tribes of thought regarding how we might enable machine learning toward true general intelligence. The five, as presented here, are the foremost in academic thought, and each present a problem solving means to be used in artificial intelligence that have been tested and argued over for decades, even centuries.
So now we have our homework, to think about, reflect on, and consider the possibilities for these five approaches? What are their limitations? What are their possibilities? How might a union among all five be achieved? Share with a comment below and get the conversation going!