Knowing the difference between a platform powered by and one powered by computing is the key to deciding which is the best for your business. IBM’s Watson computing platform might be going through a defining time right now, and part of that seems to do with a small-but-complex question: What is the difference between Artificial Intelligence knows many different definitions, but in general it can be defined as a machine completing complex tasks intelligently, meaning that it mirrors human intelligence and evolves with time. () and computing?
It’s an important question for any company and any system that’s working within this sector, as our assumptions about these two terms define how we respond to the emerging and existing products that claim to do one or the other. If you don’t know the difference between a platform powered by and one powered by computing, and what the implications of those differences, how can you decide which is the best for your business or your application? First, some brief definitions of these two types of machine thinking.
Artificial intelligence: making computers do intelligent things
Artificial intelligence agents decide which actions are the most appropriate to take, and when they should be taken. These agents most often take the form of machine An algorithm is a fixed set of instructions for a computer. It can be very simple like "as long as the incoming number is smaller than 10, print "Hello World!". It can also be very complicated such as the algorithms behind self-driving cars., Neural Networks are simplified abstract models of the human brain. Usually they have different layers and many nodes. Each layer receives input on which it carries out simple computations, and passes on the result to the next layer, by the final layer the answer to whatever problem will be produced. , statistical analysis and more. You feed the information — oftentimes, over a long period of time so that it can “learn” the variables it should pay attention to and the desired outcomes — and it spits out a solution.
computing: solving problems with humanlike thinking
computing is often described as simply marketing jargon, so crafting a working definition is important, although it’s more fluid right now, and there isn’t one consensus that industry experts have settled on. Still, the foundation is that computing systems try to simulate human thought processes.
Aren’t computing and the same thing?
They’re close, but there are some fundamental differences. First, artificial intelligence does not try to mimic human thought processes. Instead, a good system is the simply the best possible algorithms for solving a given problem — in the case of an autonomous car, avoiding collisions and staying on course. It’s not trying to process the same data in the same way as the human brain — that’s a far more complex and more fault-prone system. And, an autonomous car isn’t just making suggestions to the human driver. It’s the one doing the driving. And second, computing does not make decisions for humans, but rather supplements our own decision-making. In medicine, a true would instead be making all the decisions about how to treat a patient, essentially cutting the doctor out of the equation. The reason computing is important is because there’s genuine evidence that machine can supplement human medical diagnoses, but no one would argue that should handle all our medical decisions right now. […]