Machine Intelligence
Machine Intelligence is advanced computing that enables a technology (a machine, device, or algorithm) to interact with its environment intelligently, meaning it can take actions to maximize its chance of successfully achieving its goals. The concept of machine intelligence highlights the intersection of machine learning and artificial intelligence, as well as the broad spectrum of opportunities and approaches in the field.[1]
To understand machine intelligence better, it is good to look at this term within the context of two other terms that are proliferating in today’s tech world – “artificial intelligence” and “machine learning.” Artificial intelligence is composed of systems that allow computers to imitate human cognitive processes or perform tasks that used to be done by humans. Machine learning is defined as systems that enable a computer system to learn from inputs, rather than being directed only by linear programming.
In this context, another way to explain “machine intelligence” is that through a basis of machine learning and artificial intelligence, the machine learns to work proactively. Theoretically, if a machine learns to extract various kinds of data to put together its own processes and arrive at its own conclusions, you could say that that constitutes machine intelligence based on both machine learning and artificial intelligence functionalities.[2]
Machine intelligence is what’s created when machines are programmed with some (but not all) aspects of human intelligence, including learning, problem solving and prioritization. With these (limited) abilities, a machine can tackle a complex set of problems.
Machine intelligence by necessity involves deductive logic. For example, systems exhibiting true machine intelligence come to understand when they’ve made mistakes, watch out for similar data that could lead to a similar mistake the next time, and avoid doing so.
This means that machine intelligence will have a suite of different machine learning methods available to it, as well as a battery of automation techniques, and will smartly prioritize and deploy a sequence of them in the right order, with the right timing to achieve specific business goals. You can think of machine intelligence as a higher evolution of machine learning with prioritization and goals added in - a stepping stone on the path to true AI.[3]
The Reason Behind Machine Intelligence[4]
Machine intelligence is taking place through a basis of machine learning and artificial intelligence. The machines basically learn to work proactively. Practically saying, when a machine learns to extract a variety of data, putting together its own processes and arriving at its own conclusions, you can say that it constitutes machine intelligence on the basis of both machine learning as well as artificial intelligence capabilities.
Programming along with some aspects of human intelligence, that includes learning, problem solving and prioritization, gives rise to machine intelligence. It’s indeed surprising how with these limited abilities, a machine is able to tackle a complex set of problems.
In order to make Machine intelligence work, deductive logic comes into the picture. For instance, systems, practicing true machine intelligence, are able to understand when they’ve made mistakes. Likewise, they watch out for similar data that may lead to the same mistake later, and avoids doing so.
This is how intelligent machines are born. If you make a good one, it will have a variety of diverse machine learning methods available to it. It will also include a variety of automation techniques, and will smartly prioritize and deploy a sequence of them in the right order. This will ensure the right timing to achieve specific business goals. Machine intelligence is, therefore, a higher evolution of machine learning. Along with priorities and goals added in, it is truly a stepping stone on the path to true Artificial Intelligence.