AITech

Artificial intelligence

Introduction

Artificial intelligence is a branch of computer science that aims to build machines capable of performing tasks normally requiring human intelligence. This includes learning, planning and problem solving.

Artificial Intelligence has been a major topic in science fiction and popular culture, and its presence is felt in many areas of daily life.

Your smartphone is an artificial intelligence device.

Your smartphone, your car and even your fridge are all artificial intelligence devices. They’re all part of the internet of things, a collection of internet-connected devices that work together to make life easier.

The idea behind AI is simple: Create a computer program that mimics the brain functions of humans as closely as possible, using logic and reasoning to solve problems and make decisions.

In other words, an artificial intelligence device can use software instead of hardware to solve problems in much the same way we do – with data processing and analysis.

While this sounds like it could be great for business owners who want to stay on top of their competition or keep up with customer demand in real time, there are some drawbacks too (more details below).

Face recognition, speech synthesis and object recognition are some of its most stable findings, but it has no idea what’s going on in your mind and can’t tell the difference between reality and fantasy.

It’s important to understand that artificial intelligence is not a human being, a human mind, or a human brain. It’s not even anything close to those things. It can have some very specific tasks it performs well (like facial recognition or speech synthesis), but it has no idea what’s going on in your mind and can’t tell the difference between reality and fantasy.

Face Recognition Technology

AI Trends – Artificial Intelligence Trends

AI is a very broad topic, and it’s best to look at AI from a more general perspective.

Artificial Intelligence is not:

  • A single technology, even though many AI technologies share some common elements (e.g., machine learning algorithms)
  • An industry; many different industries can use AI in their products and services — finance, healthcare, manufacturing and so on
  • An application; there are many potential applications of artificial intelligence ranging from chatbots to self-driving cars
  • A business or product — although some businesses may be focused on an area that leverages AI for its success (e.g., an insurance company that uses neural networks for better risk assessments)
  • A job — there are jobs that involve artificial intelligence but also those that don’t directly use it (e.g., truck drivers will become more efficient with self-driving trucks over time but they won’t have “AI” stamped on their name badges just yet)

The same goes for your microwave oven, computer and many other devices.

The same goes for your microwave oven, computer and many other devices. “Your refrigerator has a digital light bulb that was designed to replace the incandescent light bulb,” says Anantha Chandrakasan, director of the MIT Microsystems Technology Laboratories (MTL) and head of MIT’s Department of Electrical Engineering and Computer Science. “But it’s more than 100 times more efficient than an incandescent bulb.”

In many cases, this efficiency comes from using sensors: They tell the device when to turn on or off based on whether or not there’s food inside—or liquid levels in a water bottle. The result is that it uses less energy when you’re not actively using it—but turns itself back on immediately when you need it again.

AI is also a marketing term for a computer program that mimics the brain functions of a human being.

AI is also a marketing term for a computer program that mimics the brain functions of a human being. An AI program has the ability to learn and think independently, much like the brain does, but it uses algorithms and rules instead of neurons and synapses.

Unsupervised learning, shown to be present in the brains of children and perhaps others who don’t have normal brains, is what makes AI software so powerful.

Unsupervised learning is a type of machine learning, where the system learns by itself. This is different from supervised learning, where you have to provide a lot of examples for the system to understand what it needs to do.

Unsupervised learning is also known as self-organizing learning. In unsupervised learning, data is fed into the network and it learns how to recognize patterns in the data without being told what those patterns are or what labels should be assigned to them.

For example, if you were going for a ride on an autonomous car and suddenly saw an animal run across your path, you would expect that the car would automatically recognize it as something that requires avoiding or slowing down for (e.g., deer).

You wouldn’t need to tell it this—it’s just part of its training with thousands upon thousands of examples over time using deep neural networks (DNNs).

Google DeepMind beat a world champion at Go just by knowing what’s in the board.

AI is not a single technology, but rather a collection of technologies. AI term is not just one type of software or hardware, but rather encompasses many different tools and processes including machine learning, deep learning and neural networks.

Artificial Intelligence is not just an invention or discovery that we made once upon a time; it’s something we’ve been doing since the beginning of human history.

We’ve used our collective intellect to solve problems from as far back as we can remember—and probably even earlier than that!

Conclusion

I hope this article has helped you understand the basics of AI and its potential. You might have also learned about some of the most common applications of AI, such as speech synthesis, face recognition and object recognition.

If you want to learn more about artificial intelligence or how it can help your business, then visit our website at AI.

For More topics:
The 10 Tech Trends that will transform our world
5G is Going to Transform Mobile Application Development
4 ideas about AI that even ‘experts’ get wrong

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