Last year, a strange was released onto the quiet roads of Monmouth County, New Jersey. The experimental vehicle, developed by researchers at the chip maker Nvidia, didn’t look different from other autonomous cars, but it was unlike anything demonstrated by Google, Tesla, or General Motors, and it showed the rising power of Artificial Intelligence knows many different definitions, but in general it can be defined as a machine completing complex tasks intelligently, meaning that it mirrors human intelligence and evolves with time.. The car didn’t follow a single instruction provided by an engineer or programmer. Instead, it relied entirely on an An algorithm is a fixed set of instructions for a computer. It can be very simple like "as long as the incoming number is smaller than 10, print "Hello World!". It can also be very complicated such as the algorithms behind self-driving cars. that had taught itself to drive by watching a human do it.
What are decisions based on?
Getting a car to drive this way was an impressive feat. But it’s also a bit unsettling, since it isn’t completely clear how the car makes its decisions. Information from the vehicle’s sensors goes straight into a huge network of artificial neurons that process the data and then deliver the commands required to operate the steering wheel, the brakes, and other systems. The result seems to match the responses you’d expect from a human driver. But what if one day it did something unexpected—crashed into a tree, or sat at a green light? As things stand now, it might be difficult to find out why. The system is so complicated that even the engineers who designed it may struggle to isolate the reason for any single action. And you can’t ask it: there is no obvious way to design such a system so that it could always explain why it did what it did.
How much mystery is too much?
The mysterious mind of this vehicle points to a looming issue with artificial intelligence. The car’s underlying technology, known as , has proved very powerful at solving problems in recent years, and it has been widely deployed for tasks like image captioning, In voice recognition an algorithm is able to listen to what a human or machine says and write it down and understand its meaning. Image Recognition describes the process of a machine knowing that you are currently looking at cat pictures. Consequently, video recognition denotes the act of a machine watching a video, and being able to understand what it 'sees'., and language translation. There is now hope that the same techniques will be able to diagnose deadly diseases, make million-dollar trading decisions, and do countless other things to transform whole industries. But this won’t happen—or shouldn’t happen—unless we find ways of making techniques like more understandable to their creators and accountable to their users. Otherwise it will be hard to predict when failures might occur—and it’s inevitable they will. That’s one reason Nvidia’s car is still experimental […]