What is AI?

We take for granted how our brains effortlessly calculate the world around us, every second of every day, AI is the concept that a computer can do the same. The term “artificial intelligence” wasn’t coined till 1956, at a conference at Dartmouth College, but AI has become a big hit thanks to the data age and tech improvement.

It refers that engineers attempted to make machines think as human beings but only in mechanical and symbolic ways, by doing so, AI is capable of solving problems and learning complicated methods that human minds are not. For example, the famous competition between Korean Go master Lee Se-dol and Google’s artificial intelligence program AIphaGo in 2016.

The history of AI

• The 1950s-1970s: Neural Networks

In the 1950s, early AI research focused on problem-solving and symbolic approaches. The US Department of Defense found it interested and began training computers to emulate fundamental human reasoning. In the 1970s, the Defense Advanced Research Studies Agency undertook street mapping projects, and in 2013, they created an intelligent personal assistant that was long before Siri, Alexa.

• The 1980s-2010s: Machine Learning

Artificial intelligence is much like a machine or a computer that given human-like properties. While AI is the broad science of mimicking human abilities, machine learning is a specific subset of AI that trains a machine how to learn.

Machine learning models look for patterns in data and try to draw conclusions as you or I would. They’re not explicitly programmed by people, you can actually give them examples and they’re going to learn what to do from those examples. That’s a huge difference because it’s much easier for us humans to give examples than it is for us to write code.

Once the algorithm gets really good at drawing the right conclusion, it applies that knowledge to new sets of data. Therefore, a life cycle achieved: ask the question, collect the data, train the algorithm, try it out, collect the feedback, use the feedback to make the algorithm better than AI has increased accuracy and performance.

If you look at the google car, it has lasers on the top which are telling it where it is in terms of the surrounding area. It has radar in the front, which is informing the car of the speed and motion of all the cars around it. And it uses all of that data to figure out not only how to drive the car but also to figure out and predict what potential drives around the car are going to do. That’s almost a gigabyte a second of data that the car is processing.

• The Present: Deep Learning

Deep learning is one of the foundations of AI. It has improved the ability to classify, recognize, detect and describe. For example, deep learning is used to classify images, recognize speech, detect objects and describe contents. Person assistant systems such as Siri and Cortana are powered by deep learning partly.

Other than that, human-to-machine interfaces have evolved greatly as well. The mouse and the keyboard are being replaced with gesture, swipe, touch, and natural language, ushering in a renewed interest in AI and deep learning.

How AI is Being Applied

• AI at home

Apart from its application in home security systems, such as interfacial cameras, AI is utilized to control smart devices with the voice control feature of AI-enabled units, such as Alexa, Siri, and Google Assistant. Netvue has been working with Amazon Alexa to provide a better experience for your smart home lifestyle.

• Banking

Artificial intelligence enhances the speed, precision, and effectiveness of human efforts. In financial institutions, AI techniques can be used to identify which transactions are likely to be fraudulent, adopt fast and accurate credit scoring, as well as automate manually intense data management tasks.

• Health care

AI applications can provide personalized medicine and X-ray readings. Personal health care assistants can act as life coaches, reminding you to take pills, exercise, or eat healthier.

• Retail

AI provides virtual shopping capabilities that offer personalized recommendations and discuss purchase options with consumers. Stock management and site layout technologies will also be improved with AI.

• Game industry

It refers to responsive and adaptive video game experiences. These AI-powered interactive experiences are usually generated via non-player characters that act intelligently or creatively as if controlled by a human game player.