Trends: Harvest without End
An army of algorithms is being developed. Built on expert knowledge and capable of learning from experience, these systems are pointing out anomalies in radiology exams, providing decision support in a range of fields, and optimizing split-second decision making in high-speed industrial processes. As such systems harvest knowledge, there will be no limit to what we will learn from them
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Health Care: Digital Decision Support
Medical diagnostic procedures are overwhelming physicians with data. In response, doctors are turning to computer programs that help them assess and interpret results. Newly-developed software is now providing fast, accurate decision support
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Automated Meaning Extraction: Computers Get the Picture
How can a computer learn to interpret images, catalogue them, find them in databases, and recognize similarities? That’s what researchers want to find out in the Medico project—a part of the German Theseus program
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Safety and Security: Advent of an Invisible Army
Digital assistants are substantially increasing safety and efficiency in pipelines, wind parks, cement plants, and tunnels
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Facts & Forecasts: Electronic Safety and Security Systems on the March
Safety technology should warn people of dangers or prevent hazards from occurring in the first place. Here, the trend is clearly toward electronic, digital safety solutions
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Financial Sector: Tracking Transactions
Siemens Financial Services utilizes IT solutions it developed itself for in-house banking processes and the assessment of credit and stock market risks. These systems keep finance specialists up to date on all financial movements
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Networks: Optimizing Energy and Water Management
Reliable, environmentally-friendly power supply networks rely on computers and high-performance information technology and control systems—as do water networks in major cities. An optimal solution for these applications is provided by Siemens’ Spectrum Power CC network monitoring and control system
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Interview: Toward Computers that Can Analyze the Content of Text
Interview with Dr. Tom M. Mitchell, Head of the Machine Learning Department at Carnegie Mellon University. His research interests are generally in machine learning, artificial intelligence, and cognitive neuroscience
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In Brief
Developments, contacts, links, literature
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