Artificial Intelligence (AI) Transactions: Thoughts and a Few Tips
Abstract
Predictive algorithms and computers independently generating output are not new. Some of us remember Deep Blue beating Gary Kasparov. Well, that was in 1997, and there are many antecedents to smart computing, however crude by today’s standards. After many years of anticipation, or trepidation for those spooked by 2001: A Space Odyssey, the AI train has left the station – doubtless without a conductor. AI controls your car, selects your favorite songs, second guesses your doctor’s diagnosis, assesses your insurance claims, detects fraud on your credit card account, or, soon, may underwrite your loan applications or select stock trades. Now that companies can harness the increasing computational power, almost-limitless cloud systems to process Big Data, and the ubiquity of Internet of Things (IoT), AI has matured towards large scale implementation and AI-based R&D and deployments are spiking. PwC reported from Tractica, a market research firm, that estimates of AI-generated revenues of $644 million in 2016 will grow to $15 billion by 2022 , while Gartner predicts that by 2020, 80% of CIOs will be piloting AI programs through a combination of buy, build, and outsourced efforts.
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