Watson vs Newton

AI is not about learning to play games that have predefined moves, pieces and spaces. Simply put, AI is not Machine Learning. Why has Watson struggled to help assist cancer research, or transform the financial markets? Primarily, Watson relies heavily on machine learning. Unfortunately we never have enough transactions to learn from, the real world operates in real-time, and machine learning cannot make a cognitive leap outside its base knowledge, or detect new type of catalyst events that will produce new outcomes.

An innovative AI solution named Newton, has been developed by Qikspace, a Seattle based startup. Newton recognizes that AI and its disparate sources of information need to push the boundaries and determine when was a fundamental understanding is no longer applicable, what is the true contextual relevance of a data point and what is contextual nature of the interaction. An example of machine learning is to do a search for a book on Amazon or Google, you will get that book and where to buy it, but the user would typically want other relevant suggestions. Relevant suggestions are not this person also bought a pencil, relevant suggestions are like going to the physical library and finding the same book. What do you see when you find that book? An array of books that are similar, extending out on each side in an infinite contextual spectrum. What should an Amazon or Google search enable? The ability to see that spectrum in different dimensions, the physical library is constrained by only being able to display the information in one way, our electronic searches have still not reached the initial sophistication of the physical library. Why not? Because of the application of machine learning vs true AI.

Humans need simplified explanations that are converted to our 4 dimensional concept of the world. Scientists and engineers recognize that many of our current scientific theories are over simplifications of the real world and only provide approximations of the results. AI needs to look beyond the established theories and seek better simplifications of the real world. Newton has made great strides in creating this new framework that will enhance the understanding of our world and the interactions that are part of it. Newton makes sense of all the external data, interactions, assumptions and needed responses; even when they are from other legacy systems. Newton has been part of the Qikspace development since 2012, and has been part of the founders 20+ yrs of research and deployment of these theories.

The author is the founder of Qikspace a Seattle based startup. To learn more about how Qikspace is deploying Newton visit www.qikspace.com