Artificial intelligence (AI) has advanced by leaps and bounds and continues to do so. Even though machine learning is part of the same emerging technology family, it is starting to hit the wall of its abilities. But never fear, a new technology is waiting in the wings.
Machine learning systems can learn by themselves from preset data. The next step in AI evolution towards human-level intelligence is machine reasoning, or the ability to apply prior knowledge to new situations.
We want to make machines “think” like us and endow them with the reasoning ability that, unfortunately, we don’t quite understand ourselves.
Sports provide a ready example of expounding what machine reasoning is really all about. When humans see soccer players on a field kicking a ball about, they can, with very little difficulty, ascertain that these individuals are soccer players. Today’s AI can also make this determination. However, humans can also see a person in a soccer outfit riding a bike down the street, and they would still be able to infer that the person is a soccer player. Unfortunately, today’s AIs probably wouldn’t be able to make this connection.
There are many benefits to to achieving this reasoning ability that humans are unable to accomplish on their own. One example is the use of a deep learning network to assist in medical diagnoses that was further solidified with the development of a neural network that can outperform qualified dermatologists in detecting skin cancer.
These are big and important reasons. We want a machine reasoning AI that knows what the problem is and then solves it.
Machine learning systems can learn on their own, but only by recognizing patterns in large data sets and making decisions based on similar situations. Machine learning is dependent on large amounts of data to be able to predict outcomes.
Reasoning machines, on the other hand, train on and learn from available data, like machine learning systems, but tackle new problems with a deductive and inductive reasoning approach. This is one of the declarative differences between the two technologies.
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.