by MARTIN U. MULLER, MARCEL ROSENBACH, and THOMAS SCHULZ
SOURCE/DPA/Google
Forget Big Brother. Companies and countries are discovering that algorithms programmed to scour vast quantities of data can be much more powerful. They can predict your next purchase, forecast car thefts and maybe even help cure cancer. But there is a down side.
On balmy spring evenings, Hamburg’s Köhlbrand Bridge offers an idyllic postcard view of the city’s harbor. The Elbe River shimmers in the reddish glow of sunset, forklifts, cranes and trucks seem to move in slow motion, and occasionally a container ship glides by. But from the standpoint of Sebastian Saxe, the area is primarily an equation with many variables. For the past four-and-a-half years, the 57-year-old mathematician has been working on his trickiest computing task yet at the behest of the company that manages the Hamburg port.
The port covers an area of 7,200 hectares (about 28 square miles). Roughly 200 trains a day traverse its 300-kilometer (186-mile) network of rails and its 130 bridges to transport goods that have arrived by ship. Saxe, as chief information officer of the Hamburg Port Authority (HPA), faces the enormous task of optimizing this logistical nightmare.
The amount of land is finite, and further expansion is not possible. Nevertheless, the Hamburg Senate has announced its goal of almost tripling container transshipment volumes in the city by 2025. This will only work if Saxe and his 60-member IT team manage to optimally exploit another resource: data. He certainly has plenty of it.
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