Intro to Artificial Intelligence

What is AI?

AI stands for Artificial Intelligence. AI replicates the intelligence of humans or animals, just displayed by a machine. In other words, AI makes computers mimic human intelligence using logic. Why logic? More on that below.

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Why was AI made in the first place?

AI was mainly created due to the growth of the Data Economy. The amount of Data used is growing progressively. The amount of data has come to such a height to the point where humans can’t process all of it. That’s when AI comes in! It does much of the work that humans do, but a lot faster.

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Why does AI matter and when is it used?

AI will be extremely common in the future as it makes tasks easier. Careers in tech and AI are increasingly growing. As the world revolutionizes, AI grows more and more common. One way AI can help is in the business field: It allows the business to make decisions quickly and efficiently. In the future, we would have many more businesses, which will make use of lots more…guess what?...AI! But, why AI over humans? One: AI is much more advanced than the human brain. Two: The precision of AI is practically unbeatable. Three: AI is extremely versatile. It can be used in the medical field, the educational field, scientific fields, etc. There are so many ways AI will be used in the future. Let’s break it down into a few.

(1) AI in the Medical field

AI has many benefits towards the medical field. After learning a little bit about AI, you’d see why. You would think that AI would only be a platform to store medical information and data. You're wrong! AI can help when it comes to making drugs and medicine. It can also help do repetitive or tedious jobs. One application is a Virtual Nurse!

(2) AI can help on the road

America has one of the highest auto accident numbers. According to a blogpost by readwrite.com, “A whopping 95 percent of these accidents are caused by human error, meaning accidents are avoidable.” With the growing AI industry, self-driving cars are being developed. Meaning a decrease in human error and, therefore, a decrease in auto accidents. To add to AI’s help on the road, it helps with traffic conditions too. Smart systems are being spread throughout the world to analyze traffic lights at congested intersections. Avoiding jammed roads leads to a safer and healthier world.

(3) AI in Retail

AI allows us to shop on our couch! Online businesses are growing every second. (Especially on Amazon Prime Day)

(4) AI creates more jobs than it takes away

Many say that AI will replace the world. AI can potentially take away many jobs in the future. But, AI can also create more jobs. Here’s an example: If a company hires people to calculate for them, AI would take over the job. But, the cost to hire people to calculate will drop to near zero, therefore, allowing the company to expand and spend more on jobs!

(5) AI will transform agriculture

The agricultural industry is an industry that we are never going to be leaving behind! With the increase and expansion of the agricultural industry, there seems to be a lot more effort put in just to water the plants everyday. AI can help with that! AI is used in agriculture to plant seeds, spray pesticides, fertilize, harvest, and potentially even water the crops on a daily basis. AI could also help improve the final result. Data on the existing plants are collected by AI machines, and by analyzing the data, it can give you better outcomes.

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How does AI work?

We can program AI to sense, reason, and act logically. Machine learning & Deep Learning are subsets of AI that allow computers to do this. They allow a machine to learn from past data without being explicitly programmed to do so. For humans, learning comes from lots of practice and experience. For computers, learning comes from analyzing large amounts of data.

Machine learning can take place in many types of data. For example, it can take place in videos, images, text, etc. Once it learns to recognize patterns in that data, it learns to make predictions based on the patterns. Let’s take one of these types of data: images. The computer needs to analyze that image in order to recognize patterns. How does a computer do that? Computers do it by using Computer Vision. Computer Vision is the way machines interpret images: First, the computer will look at an image and guess what it is, then, the ‘trainer’ corrects the computer, lastly, the computer stores the correct answer and can use that data to find patterns for other things. In this case, the computer is trying to recognize, not only patterns, but recognize patterns in order to create rules. The Computer sets these rules with Deep Learning. Deep Learning is the second subset of AI that helps create algorithms (or rules) that will help Machine Learning mimic the human brain. For example, if the image was a square, the computer would guess the shape, store the correct answer for the shape, and would establish rules (With Deep Learning) like ‘4 vertices’, ‘4 sides’, etc. This is to identify a square in the future. It’s important to note that the computer will not get it right every time. The computer must go through a lot of trial and error in order to expand its knowledge, and get it right more often.

In order for the computer to develop patterns in the data, create rules, and expand on knowledge, the computer must store the information. Otherwise, the computer would forget what it has already learned! The computer does this via Neurons (not human neurons!), which come together to make Neural Networks. First, let’s talk about what a Neuron is: According to freecodecamp.org neurons are, “nodes through which data and computations flow.” A Neuron has two ends, the Input and Output. The data comes through the Input, that data is processed inside the neuron and comes out as an Output. These Artificial Neurons come together to create a Neural Network. Here’s an example of when a Neural Network can be used: If you give a thumbs up on a video about art, subscribe to a youtuber that does crafts, and give a thumbs down to a picture related to school, your recommended section will include content on arts & crafts but won’t try to include content related to school. Why? There were three Neurons stored (art, craft, school). The input came from the topics that you showed interest in. When you liked a video on art, the neuron’s input used that data, processed it, and gave an output. In this case, one of the outputs in the Neural Network was an art related video in your recommended section.

So, hopefully after reading this you have a little bit of understanding with Artificial Intelligence. Below is a game made by google (web game, no download needed) that gives you a great example of how Machine Learning, Deep Learning, and Neural Networks work together to recognize drawings. Check out the game and hopefully this post sparked some interest to learn more!

Quick, Draw! (Google Game)