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Berlin to go, english edition, 01/2019

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The Krausenhöfe

The Krausenhöfe (Krausen Courtyards) are home to Amazon’s Berlin development center YOU ALSO HAVE A TEAM AT YOUR BERLIN OFFICES WORKING ON MACHINE TRANSLA­ TIONS. WHAT EXACTLY IS GOING ON THERE? A team of speech scientists has developed a system that makes it possible to translate product descriptions into many different languages automatically. This means that sellers on Amazon’s “Marketplace” e-commerce platform can have their product descriptions automatically translated into the many different languages in Europe, thus offering them access to markets beyond their countries of origin. This generates new sales opportunities for companies and even greater choice for customers. It enables small and medium-sized companies to enter international markets with marginal or no additional effort. Machine translation also makes it possible for them to test the demand for certain products in foreign markets at no great expense. This translation service is a development that emerged from the Berlin machine learning team in cooperation with several Amazon teams in Europe and the United States. Each year, hundreds of millions of product pages on Amazon’s Marketplace are translated with the service. ENERGY-EFFICIENT ALGORITHMS ARE ANO­ THER FUTURE-RELEVANT ISSUE. HOW ARE YOU TARGETING IT? These days, we already have self-learning software that can defeat human beings at complex board games such as Chess and Go. But these algorithms still require one hundred or a thousand times more energy than humans do. I run marathons, so I’m well aware of the need to ration my energy, because I know it’s going to run out at some point, probably at a very unfavorable moment. But these days, academic research into AI is not concentrating on the energy-efficiency of algorithms. However, the more industry applies such demand forecasts, the more important this aspect becomes as the costs of computer processing capacities are going to play an increasingly important role in the future. Today, we human beings are still the most energy-efficient form of intelligence. It will be a while before computer processors become as efficient as the human brain. The largest challenge facing AI today is no longer the idea of becoming as precise as human beings with regard to perception and prediction; instead, the challenge is to be able to use as little energy as human beings in the process. OVER 700 EMPLOYEES WORK AT AMAZON’S BERLIN DEVELOPMENT CENTER. AN IMPORT­ ANT GLOBAL AMAZON MACHINE LEARNING TEAM ALSO WORKS FROM OFFICES IN THE GERMAN CAPITAL. WHAT MAKES BERLIN SUCH A GOOD PLACE TO DO BUSINESS? Berlin has three key advantages: first, leading global scientists work at Berlin universities in the fields of machine learning and robotics. Second, the city has an incredibly vibrant startup scene that continues to attract leading minds from all over the world. And, finally, Berlin is truly international. I really like it and I see over and over again that my Amazon colleagues from all over the world like to work here. IN WHAT WAYS DO YOU BENEFIT FROM YOUR PROXIMITY TO BERLIN UNIVERSITIES SUCH AS THE TU? We cooperate with many research institutions, including several universities and institutes such as the Max Planck Society. For example, we joined with TU Berlin to create a model for post-docs in which they work four days with us and one day at the TU’s Database Systems and Information Management Group under Prof. Volker Markl. The Amazon Scholar program offers a different model by allowing scientists to take a semester off to work on projects for Amazon. Our CEO Jeff Bezos is already setting a great example by working four days at Amazon and one day at the space company Blue Origin. So the model is obviously quite good. Read the entire interview with Dr. Ralf Herbrich on where you’ll also find additional articles and reports on the subject of artificial intelligence in Berlin. Photos: © Amazon, Montage RAZ 12

TITLE WELCOME TO REALITY! From science fiction to everyday technology Text: Anja Jönsson Question: What makes it possible for Siri, Alexa or Google Assistant to answer questions and solve tasks? Answer: artificial intelligence (AI). Anyone who spends time in the digital world interacts with it. And AI is a hot topic today. Most magazines, newspapers and science programs have covered the subject in recent months. AI is indeed fascinating, but it’s also something many people are afraid of. Although artificial intelligence is not necessarily anything new, it is most definitely experiencing a renaissance today, many decades after its first mention. People have been exploring AI since the beginning of electronic computing. In the 1950s, one of the most influential theoreticians in the early phase of computer development, British computer scientist Alan Turing, posed the question as to whether machines were capable of thought. Since then, the scientific field of AI has experienced a number of ups and downs. In the 1990s, scientists concentrated more on using AI for real-life problems. A milestone in AI research occurred when IBM’s “Deep Blue” computer beat world champion Garri Kasparov at chess in 1997. On a side note, an average chess app on any smartphone these days would be able to beat “Deep Blue,” which shows just how far the technology has come in the meantime. But what is actually behind the recent waves of progress and popularity in AI? The development is being driven in part by massive amounts of data (global data volume grows at a rate of 50% per year); on the other hand, the rapidly growing computing power and capacity of computers along with significantly improved algorithms and approaches to machine learning are also playing an key role. Scientists have been exploring the subject of AI for decades, but that doesn’t mean there is any clear or universally accepted definition of it. American mathematician Marvin Minsky is considered an AI pioneer, having co-founded the brand-new scientific discipline in 1956 with the words: “Artificial Intelligence is the science of making machines do things that would require intelligence if done by men.” Minsky argued that the things a human brain accomplishes were not supernatural, and therefore that it must be possible to teach these things to machines. “There is no universal definition of artificial intelligence,” notes Claudia Pohlink, head of artificial intelligence and machine learning at Deutsche Telekom’s Innovation Laboratories in Berlin. “We define AI as follows: The goal of research into artificial intelligence is to enable intelligent behavior in machines with the help of science. In that process, one of our key priorities is to point out that AI is designed to support people in their everyday lives, not replace them. AI is a very complex concept, and when they talk about AI, many people are actually talking about machine learning, which 13

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