Artificial intelligence, or AI, is a branch of computer science that aims to mimic human intelligence in order to make intelligent systems. In essence, this means that computers will be able to think like humans, but instead of using logic, they’ll use logic to solve problems.

This does mean that the end goal is to create systems that are more accurate than their human counterparts, and by extension smarter than humans. Although there are many arguments about whether this is possible or not there have been some successes over time:

IBM Watson supercomputer — The most famous AI system is the one created by IBM’s Deep Blue AI team in 1997.

Google-AlphaZero — It’s actually become clear that even though AlphaZero was “good enough” for certain games like chess (it beat grandmasters from both North America and Europe), it also can’t seem to beat humans at Go. So why isn’t it good enough for humans? The answer is that humans have evolved over years into something better than before.

One key reason was that it was developed as an educational game and thus didn’t require much data. Other key reasons for its success were it was fun to play because players would know exactly what moves they would need and how to win the board. Because of its simplicity, and the speed of learning it has been used more than its competition.

Google Translate — A machine translation engine for Google and other websites that were created to translate language into English by matching words to phrases in that language. By understanding these words, the engine figures out what phrases are similar to them, so it can find them easily.

There are other interesting points in this about how it uses natural language processing instead of just keywords, it does something no one else had ever done, plus it gives people the power to change their lives with languages that could be difficult to understand without special education. Also in the past, Google found itself in legal trouble when people began making comments on translations made by Google and other sites.

These translations then caused controversy when it was discovered that these translations weren’t always accurate, and Google had been accused of defrauding people. While Google has been doing very well with artificial intelligence, it still can’t match our creativity, drive, or ability to solve complex problems.

DeepMind — If you haven’t heard this name before, it’s because DeepMind is a non-profit organization that is working towards creating Artificial General Intelligence(AGI). Their project consists of teaching robots to perform tasks that are usually required for the development of AGI — things including reasoning, learning, learning to understand, planning, problem-solving, communication, image recognition, speech recognition, natural language generation, robots that drive cars, help doctors write papers, etc.

Now, this might be all cool technology, but unfortunately, we don’t yet have any machines that can take on the jobs that once existed. We still haven’t seen any examples of robots that can be trained to do highly analytical jobs or jobs requiring physical labor such as maintenance, cleaning, gardening, landscaping, etc. As mentioned earlier, Google Translate is only meant to represent the input language and not produce output translations.

Meaning that with the current technology, there is no way to make decisions in your own home or office if you want to see where something comes from. If this happens, it will drastically increase the demand for skilled workers, and decrease the supply of skilled workers that can now only come through those positions which require the highest level of competency.

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Every week I prepare an article based on the topic of my choice. My articles range from industry news, product reviews, tutorials, guides, research, and anything that I think will benefit others.

If you follow me you will know my content focuses on personal development, self-improvement, health, productivity, creative writing, leadership, motivation, business growth, family and relationships, and personal growth as a whole. Today I am going to share my thoughts and opinions about artificial intelligence and what I believe is achievable if we are willing to put forth the effort.

Artificial Intelligence Isn’t Just About Robots

Artificial Intelligence is becoming increasingly popular all around the world, and in fact, is often looked into with curiosity. Unfortunately, however, despite all the hype and potential, there’s still a lot that needs to happen first. First of all, let’s get clear on the definition of artificial intelligence.

According to Merriam-Webster: “Artificial intelligence is a field of study that proposes the creation of computer programs that can perform tasks normally requiring human intelligence, often including visual perception, auditory perception, and many others. These programs are designed to simulate the human capabilities of problem-solving, decision-making, and logical reasoning.”

So far we have defined artificial intelligence, for example, the idea to build an artificially intelligent car can be considered artificial intelligence. But as time goes on, we begin to realize that there are several different types of AI. Some of these types of AI are called weak artificial intelligence.

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When talking about weak artificial intelligence is hard in the sense that some of these programs aren’t capable of carrying out the same level of analysis and comprehension that human beings are capable of doing, especially when it comes to complex functions. Although this type of AI is generally easier to teach, once taught the program has to apply a limited amount of knowledge and reasoning to complete simple tasks. Although this type of artificial intelligence is easier to teach, the downside is it often doesn’t do as well as strong artificial intelligence.

The second type of artificial intelligence refers to Strong Artificial Intelligence. Strong artificial intelligence is a form of artificial intelligence created specifically to accomplish specific tasks, such as playing video games and driving cars. Many times while researching these terms it seems that strong artificial intelligence is difficult or impossible in reality to create.

However, these are not the only types of artificial intelligence, there may also be more specific forms of artificial intelligence that are harder to create. For example, Weak Artificial Intelligence is just as easy to create, whereas Strong Artificial Intelligence is easier to create when compared to Weak Automation Intelligence.

With all the artificial intelligence out there, it’s unclear as to what type is best. Personally, I believe that Strong Automation Intelligence is the ideal type to go forward with future automation. In order for Strong Automation Intelligence to be fully implemented and utilized in the real world, researchers must work together to create Strong Automation Intelligence and define ways to make it beneficial in the workplace, and society as a whole.

Research is underway in place to develop stronger artificial intelligence.

What Can Be Taught To An AI System

As mentioned above, there are two major types of artificial intelligence — Strong Automation Intelligence and Weak Automation Intelligence. Both types help in making Intelligent Systems and helping to reduce costs across industries. Here are some ideas that I would love to see in the industry which would allow us to be productive and help improve efficiency:

Artificial Neural Networks

Artificial Neural Network is an emerging area in the technology world that allows computers to learn the same cognitive abilities as humans. In most cases, humans make decisions on their own. You see this happening quite often in work environments.

Instead of thinking in linear circles because you always have to know what someone is telling you so you know that in a given situation, you should go to a particular action, and then do a different action according to the plan you’ve already determined in your mind already. And again in almost every situation, you may choose to do one thing and it may seem like something is missing in a process or something needs to be changed. That’s what happens in Artificial neurons.

It sounds extremely basic, but it really isn’t. Basically what it does is give the network a bunch of parameters that determine exactly what the inputs are, then determines what the outputs are, and then decide whether or not it should do anything at all with whatever the inputs were.

Think about a scenario that includes having two options, a process that takes three hours, and will take four hours to complete, but the third option would be shorter and faster. Then the fourth option might only take ten minutes, this can happen with either a longer period of time for each option or some kind of mathematical deduction. And so on.

Imagine how many variables you have in these two scenarios, one is definitely going to look like a waste of time (that we would simply be skipping) and another would look like an incredible resource that we would be spending our extra time on anyways (that we didn’t even have the option to spend on). So instead of waiting for something to come to us, it seems like it’s all for nothing — just wait.

But what would be great is that it would allow the user to set some parameters that are related to the inputs for example: if the person trying to decide whether or not to do something is having shortness of breath or an asthma attack, they need to know, and get ready for that possibility. From there, you can have the entire process set up and just go through and start deciding. So far, there’s not much of a market for this type of technology, but it would be fantastic if it ever did become apparent that Artificial neurons could be a profitable solution.

Deep Learning

Deep Learning is a newer type of artificial intelligence that learns much more quickly than previous types of artificial intelligence. Deep learning uses neural networks that are inspired by biological brain networks, and the idea is that these neural networks have multiple hidden layers