Presented by Beyond Limits
Conventional, data-crunching artificial intelligence, which is the foundation of deep learning, isn’t enough on its own; the human-like reasoning of symbolic artificial intelligence is fascinating, but on its own, it isn’t enough either.
The unique hybrid combination of the two — numeric data analytics techniques that include statistical analysis, modeling, and machine learning, plus the explainability (and transparency) of symbolic artificial intelligence — is now termed “cognitive AI.”
It’s an extraordinary breakthrough to have the ability to implement a human-like ability to perceive, understand, correlate, learn, teach, reason, and solve problems faster than existing AI solutions.
Key technology components were at the core of the wildly successful NASA Mars Rover’s mission. Alone and 150 million miles from Earth, the rover was able to successfully adapt to conditions without direct instruction. After a dust storm, it taught itself to rotate its solar panels and shake off accumulated dust blocking essential solar ray absorption. Then it taught itself to correlate sensory evidence with mission objectives to build the first practical weather model of another planet.
Here on earth, cognitive AI combines the best of numerical/statistical approaches with the best of symbolic/logical techniques to solve problems that conventional machine learning, neural nets and deep learning cannot do alone.
Get the whole story: Learn more about the Mars mission, the development of cognitive reasoning engines, and how the merging of numeric and symbolic approaches delivers a true cognitive artificial intelligence solution that supports human decision-making.
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Author: VB Staff
Source: Venturebeat
