Reading medieval literature, it's hard not to be impressed with how much the characters get done--as when we read about King Harold doing battle in one of the Sagas of the Icelanders, written in about 1230. The first sentence bristles with purposeful action: "King Harold proclaimed a general levy, and gathered a fleet, summoning his forces far and wide through the land." By the end of the third paragraph, the king has launched his fleet against a rebel army, fought numerous battles involving "much slaughter in either host," bound up the wounds of his men, dispensed rewards to the loyal, and "was supreme over all Norway." What the saga doesn't tell us is how Harold felt about any of this, whether his drive to conquer was fueled by a tyrannical father's barely concealed contempt, or whether his legacy ultimately surpassed or fell short of his deepest hopes.
The overarching term "artificial intelligence (AI)" is a hub with many spokes. One of the most exciting of these from a business perspective is machine learning. As I explained in my first blog in the series, at its most basic, machine learning involves'teaching' a computer to learn and change when given a vast amount of data. The computer is not necessarily explicitly programmed for these changes, but instead learns to spot patterns and make connections. Therefore, the machine learns (get it?)
In the 1990s, there was a popular book called Re-engineering the Corporation. Looking back now, Re-engineering certainly has had a mixed success – but it did have an impact over the last two decades. ERP deployments led by SAP and others were a direct result of the Business Process re-engineering phenomenon.
The SETI Institute of Mountain View is inviting all citizen data scientists and technologists to join us as collaborators in our mission to find intelligent radio signals from beyond our solar system. We are issuing a worldwide, public code challenge and accompanying hackathon in San Francisco for the purpose of expanding our radio-telescope signal classification tools using the latest developments available in machine- and deep-learning.