Artificial Intelligence in PhotoShop
Another way that AI could be impacting our everyday lives soon is by automatically editing your photo at the moment it is taken. The technology would be able to enhance select portions of a picture (no more picture-wide effects or corrections necessary) in less than 20 milliseconds. The blistering speed means users may be able to view the corrected image before they even snap the picture.
When this technology emerges in its fully developed form, it could revolutionize the photography industry and relegate applications like Photoshop to an industry professional-specific tool overnight.
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How Do Self-Driving Cars Work?
Tesla's autopilot system has by far been the highlight of self-driving tech, and it has been in the spotlight since the beginning. Tesla has the first-mover advantage, having reinvented how an automobile company is structured and functions. In the last year, Tesla's autopilot system has clocked over 2 billion miles of use.
That's a significant amount of miles, with very few accidents, compared to human drivers.
With the technology still advancing, perhaps still in its infancy, what is self-driving technology, and how do cars equipped with it work?
What are self-driving cars?
The terms self-driving and autonomous are used fairly interchangeably, and they essentially are. Autonomous is more general, whereas self-driving only relates to vehicles. In the case of cars though, those technicalities don't matter.
Self-driving cars rely on hardware and software to drive down the road without user input. The hardware collects the data; the software organizes and compiles it. On the software side, the input data will normally be processed through machine learning algorithms or complex lines of code that have been trained in real-world scenarios. It's this machine learning technology that is at the center of self-driving technology.
As more and more data is processed through autonomous self-driving algorithms, they only get better and better—smarter and smarter. Machine learning algorithms can essentially teach themselves how to function, assuming they've been given the right constraints and goals.
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