Digital White Papers

Knowledge Management: One Size Does Not Fit All

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57 WWW.ILTANET.ORG | ILTA WHITE PAPER KNOWLEDGE MANAGEMENT Machine-Learning Algorithms Are Still Kind of Stupid Quantum Computing and AI As published in MIT's December 2015 "Technology Review" by Tom Simonite, Google hired John Martinis, a physicist from the University of California, Santa Barbara, to help Hartmut Neven, leader of Google's Quantum Artificial Intelligence Lab, advance quantum computing and AI. As Neven notes, "People talk about whether we can make creative machines. The most creative systems we can build will be quantum AI systems." A quantum AI system would theoretically take only minutes to make calculations that would take today's supercomputers millions of years to make. The impact this would have on the AI space is mind-boggling. The effect on knowledge sharing in this scenario is enormous, both in the consumer world and in focusing on efficiencies and client behavioral adaption in professional seings. Before this advancement has time to be realized, Moore's law could get in the way. Moore's Law A simplified version of Moore's law is that processor speeds or overall processing power for computers will double every two years. Many of the companies the legal industry partners with, and looks to for innovation, are built within a model of continuous improvement with a standard target of 18 months for new innovation realization. Some predict that Moore's law will plateau by the year 2020 due to the finite space available on silicon. If true, will quantum developments render that point in time moot? As John Markoff of the "New York Times" observes, the Semiconductor Industry Associations of the U.S., Europe, Japan, South Korea and Taiwan will make one final report based on a chip technology forecasting system called the International Technology Roadmap for Semiconductors. Nearly every big chip maker, including Intel, IBM and Samsung, belongs to the organization (although, in the last report, Intel said it is not participating). To replace what the semiconductor industry has done for nearly 25 years, a professional organization called the Institute of Electrical and Electronics Engineers announced it will create a new forecasting system, the International Roadmap for Devices and Systems, to track a wider range of computer technologies. Some consider our computing power in the cloud already too vast; we are still learning to harness and program what we currently have. If a relative plateau occurs, that period will be spent harmonizing algorithms and AI within the canvas we have laid out. A New Perspective Applying AI and big data in our businesses requires a new a way of thinking and a new perspective. In my book, "The Sherlock Syndrome," I describe Sir Arthur Conan Doyle's character in modern terms. Imagine a character who could form fantastically detailed observations from his surroundings then come to deductions by cross-referencing an intricate internal analysis of the wealth of information we have at our fingertips. We are heading right for this through AI in behavioral tracking and adaptation. The data from our phones, smart watches, smart thermostats and networks of computers that underpin Google, Facebook and Twier are both searchable and tailor-made to our interests through learned behavior integration. A quantum AI system would theoretically take only minutes to make calculations that would take today's supercomputers millions of years to make.

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