Over 10 billion Internet of Things (IoT) devices already surround us in our everyday lives. Its extraordinary growth will be further accelerated by the rollout of 5G—Business Insider believes that there will be more than 64 billion IoT devices worldwide by 2025.
Alongside the growth of the IoT, artificial intelligence (AI) has emerged as the next technology phenomenon. Jim Goodnight, often cited as the “godfather of AI” (thanks to his work on a technology to improve crop yield 45 years ago), recently described AI in an interview with Forbes as a “game changer for society,” with the potential to revolutionize our relationship with technology.
Naturally, it was only a matter of time until these technologies come together to form the “artificial intelligence of things,” or “AIoT.” While the IoT connects “dumb” devices to the internet, artificial intelligence gives them a “brain.” Together, they’re capable of changing the world as we know it.
Why we need AIoT
You might question why the world needs AIoT given the huge take up of cloud computing. Can’t we just connect devices to the cloud, like we do with the IoT, and let the cloud do all of the analysis and decision-making? What’s the point of making the devices themselves intelligent?
The simple answer is that the cloud’s compute capabilities simply can’t scale proportionately with the sheer number of connected devices that the world is going to see in the next few years. Moreover, networks that transport data back and forth between devices and the cloud are bandwidth-limited. Even the most modern communications networks won’t be able to support the explosion of data created by devices. This will inevitably cause unacceptable delays in any decision made in the cloud.
Applications such as autonomous cars, where safety is paramount, simply can’t afford to be restricted by unreliable connectivity, high latency, and low bandwidth when they need to make almost instantaneous decisions based on the changing environment around them.
If, for example, someone steps out into the road in front of a car at speed, there simply isn’t enough time for the sensors on the car to detect the hazard, send the data to the cloud (if indeed there is a connection), and wait for the cloud to tell the car to stop. The perception, reasoning, and action must be done within the car itself to save time.
But beside autonomous vehicles, what other applications could AIoT unlock?