Once fiction, now reality

We use it every day: the smartphone. The little helper in your pocket is packed with artificial intelligence. The keyboard recognizes typing  behavior, the phone book recognizes the most important contacts, and  the  voice recognition recognizes our voice. This requires computing power. ZEISS enables the semiconductor industry to produce ever smaller, more powerful and energy-efficient  microchips  – and thus ensures that smartphones, including AI, become ever more intelligent.

Smart housemates have moved into modern households. This does not have to be the thoroughly digitalized smart home. Artificial intelligence is already programmed into smart TVs, for example in the applications of streaming services. Anyone who has a voice bot at home is conversing with artificial intelligence on a daily basis. And most recently, ZEISS technology is also built into the Multifunctional Smart Glass.

Modern factories rely on automation and artificial intelligence. Machines are no longer operated by humans alone. Automation is the keyword: ZEISS develops innovative solutions for quality assurance with which measurement data can be automatically recorded, evaluated and forwarded in real time. With the help of algorithms, the data is analyzed to distinguish between good and bad parts, for example. Welcome to the new industrial age.

Man and machine not only act in unison, they also speak the same language. Thus, algorithms trained on speech can recognize it – and derive actions. A voice bot responds to specific commands. A text tool transcribes spoken words. A voice control executes issued commands. This is how speech recognition is changing the relationship between humans and machines. This is an advantage that ZEISS is already taking advantage of in the user experience of microscopes or in customer service.

When it comes to autonomous driving, people believe the car actually drives itself. In reality, an artificial intelligence controls the vehicle. Among other things, ZEISS sensors measure the distance to the vehicle in front. This generates a large amount of data that needs to be analyzed in real time. Finally, the vehicle must react when the car in front of it brakes hard. Algorithms scan this data to identify which driving behavior is appropriate.