Modern Implementation
Since the release of iRobot’s first Roomba vacuum cleaner in 2002, artificial intelligence has played a huge role in commercial production. While the Roomba vacuum cleaner can only complete one simple task: cleaning floors, other A.I. systems like speech recognition software, are much more powerful. These systems take the form of personal assistants like Siri, Cortana and Alexa and are available on a large array of personal devices including phones, laptops, TV's and gaming systems. These systems are hands-free and allow users to navigate through their devices without pressing any buttons. They are able to recognize words and voices and complete tasks based on certain commands.
Self-driving vehicles are another type of AI system that is continuing to be developed. Engineers have developed cars that can drive reliably and autonomously, but the task of navigating around heavy traffic is very complicated. The self-driving car needs to be able to react quickly to unexpected behavior such as last-minute braking or lane-switching. It also needs to account for weather changes and roadwork. Although engineers have successfully developed autonomous vehicles, they are not yet widely used because of the aforementioned obstacles.
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Some may say that the most appealing AI systems are lifelike robots such as Sophia (pictured above), the first robot to earn citizenship in any country (Saudi Arabia). Robots like Sophia are able to hold conversations with human beings and even express emotions to an extent. Although at times these robots may not seem human-like, as they hold more and more conversation, they learn more about human interaction and are able to develop more human-like behavior. Other types of AI-powered robots focus less on developing human-like discourse and are instead concerned with imitating human navigation. In this video, Boston Dynamics showcases an example of how their AI uses sensors to recognize obstacles and navigate along a designated route.
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Artificial Intelligence has come a long way since the early 50's, but the more intwined they become with our daily lives, the higher the demand for improvement. Current limitations with products such as self-driving cars demonstrate the ever-present need for continued research in AI technology.