AI is one of those buzzwords that almost everyone uses, but few really understand. A quick google throws up a list of news items that range from How are Businesses harnessing the power of AI? to When will the machines take over? It seems like a pretty big jump from ‘useful data tool’ to ‘dystopian nightmare’, but it comes down to the broad definition of AI as we currently know it.
Artificial Intelligence is effectively an umbrella term that covers a spectrum of machine intelligence. At one end, we have machines like Deep Blue. At the other, we have Roy Batty and HAL 9000. Obviously, when businesses wax lyrical about ‘embracing AI’ they’re not talking about creating a psychopathic super-computer to sift through their data – but we have moved past basic machines and onto technology that can act and react more independently, largely thanks to the huge amount of data we now have at our disposal.
The different types of AI can be roughly split into four sections:
Type 1: Reactive Machines
This is your basic artificial intelligence – a purely reactive machine that is limited to specific tasks. Deep Blue, the IBM computer that beat chess master Garry Kasparov in the nineties, sits in this class of AI, as does Google’s AlphaGo. They might be brilliant at the task at hand, using the data they have been given to react accordingly, but they have no concept of anything else. They are also incapable of making memories, which means that they can’t learn from their experiences.
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