Artificial Intelligence, Our New Future

Arqish Minhas
11 min readMay 29, 2021

September 4, 1927, a child was born in Boston Massachusetts. The boy was exceptionally intelligent and graduated high school 2 years early going into California Institute of Technology in 1944. The boy self-studied college math in his teens that were used in CalTech so when he got in, he skipped the first 2 years of math. He was suspended from CalTech for not attending the required Phys-Ed courses. He then served in the US Army and was readmitted, receiving a B.S. in mathematics in 1948. By 1951, he had graduated from CalTech and had a Ph.D. in Projection operators and partial differential equations from Princeton University.

In 1979 the man wrote an article called “Ascribing Mental Qualities to Machines”. In it he wrote, “Machines as simple as thermostats can be said to have beliefs, and having beliefs seems to be a characteristic of most machines capable of problem-solving performance.” In 1980 the philosopher John Searle responded with his famous Chinese Room argument, disagreeing with him and taking the stance that machines cannot have beliefs simply because they are not conscious. Others argue that machines lack “understanding” or “intentionality” (a term commonly used in the philosophy of mind). A vast amount of literature has been written in support of one side or the other.” This man’s name was John McCarthy. And he created the birth of Artificial Intelligence.

John McCarthy

Revolution. That is what AI is causing. Firstly, AI itself is not a physical machine or a particular line of code. It is just Intelligence. You can go on the internet right now and find the literal meaning to it, so I won’t get into that. Yes AI can be described as something that makes machines smart, but can you truly define it? Defining AI is like trying to define the intelligence a human has. They are both complicated. People think that AI is a computer that can perform everyday human tasks or help humans do things, but AI is way bigger than that. AI can learn by itself.

Humans are undoubtedly more capable and possibly smarter than AI, however, humans haven't reached their full brain capacity and AI learns a lot quicker than humans. There are many aspects of AI that all collaborate to create one powerful Intelligence. One aspect of it is Machine Learning. What this does is it gets data and uses trial and error to do a task by itself using an AI algorithm and learn by finding patterns in the data. Using Machine Learning, AI can not only teach itself, but it can learn really fast. If you had to calculate it, it can travel at the speed of light which is 1,079,252,848,800 meters an hour. In the future, it will be able to learn faster than that!

As I mentioned before, there are different aspects of AI and each one plays a role in building AI as a whole. The different sections are Cognitive Computing, Machine Learning, Natural Language Processing, Computer Vision, Deep Learning, Speech Recognition, and Neural Networks. Here is a brief description of each of them.

Cognitive Computing: Cognitive Computing has been derived from Cognitive Learning. Cognitive Computing tries to replicate the thought processes of a human in a computer's way. Using Machine Learning algorithms that use pattern recognition, data mining, and natural language processing, Cognitive Computing can replicate the way a human mind works. p.s looking back at this, you can see that Cognitive Computing uses multiple other aspects of AI to fully function as well. This is a perfect example of how AI is branched out and they all use each other to work best.

Machine Learning: As I mentioned above, it uses data or trial and error to do a task by itself using an algorithm and learn by finding patterns in the data. Machine Learning is one of the more used and well-known aspects of AI as it helps AI learn. Machine Learning has had several applications to our world in the past, present, and future more as it becomes more common and more explored. Machine Learning and AI also have the capacity to be used outside of this world.

Natural Language Processing: Natural Language Processing is another subsection of AI that allows computers to be able to understand, interpret, and manipulate human language. This is pretty awesome! It can allow the computer to recognize emotion in a human’s voice at a more heightened level of use.

Computer Vision: Computer Vision is another subsection of AI that can allow computers to see just like humans! It can understand and interpret images, videos, and live feeds! Computer Vision is way better than the human eye. Unlike humans, Computer Vision can retain everything it sees! Humans also don’t know what something is if we haven’t ever seen it, the Computer Vision can compare images to the web and instantly know what it is, and after a while, using Machine Learning, it won’t need to search up anything as it has that memory stored forever. These give computers a really big advantage in knowing things at the speed of light.

Computer Vision also applies to many different places and aspects like; malls, stores, Autonomous Vehicles, medical diagnostics, monitoring the health of agriculture and farm animals, it can also be very useful to find very dangerous people. Using Computer Vision, a certain picture of a dangerous person can be into an algorithm that will use AI, Computer Vision to identify people in large crowds or just monitor places to hopefully find them.

Deep Learning: Deep Learning is a function that copies exactly how the human brain works when it is making a decision. It mimics how we process data or piece together patterns. Deep Learning is capable of learning from data that is unstructured or unlabeled while it is unsupervised. This means humans need no contact or presence to allow them to learn particular things. Other words for Deep Learning are Deep Neural Learning or Deep Neural Network.

Speech Recognition: Firstly, Speech Recognition is not the same thing as Natural Language Processing. NLP is when a computer can understand multiple varieties of speech from humans like different accents. Speech Recognition is when a computer can differentiate how your voice sounds compared to how your voice sounds and can tell who it is. It can be used to identify people for security reasons.

Neural Networks: People commonly think that neural networks are severely complicated, but actually, it is one of the easiest things to understand. A Neural Network is just an algorithm that is designed to sort of mimic the way our brain sends information across our body. Think of a Neural Network as a way to find an output with input but it has different layers in the middle to help it come up with that output. Another name for it is Artificial Neural Network (ANN). A Neural Network model looks something like this.

Neural Networks always go from input to output (right to left) you can also have many more inputs and multiple outputs too, this model is a very easy-to-understand way of how neural networks operate.

AI In Robotics

Often, when people see a robot or anything that looks like a robot, they think it has AI in it. That is a misconception, there is a huge difference between AI and Robotics. People get confused by this because they might see in a cool YouTube video or a company ad from Microsoft, a Robot advertised as having AI, this is true, and those companies do have AI robots but that doesn’t mean every robot has AI, that is where normal coding comes in play where someone can make a robot and program it to do certain things like a walk back and forth. I’ll get more into that later on.

So, where do Robotics and AI meet? Why are these companies making it such a big deal that their robots have AI compared to coding? And what is the difference between AI and coding?

These are some common questions that people have when they either hear, see, or talk about AI. Firstly, when companies make their robots and can enable them with AI, it has a couple of implications of why it’s better. AI firstly allows the robot to be smarter compared to just coding and most of the robots out there are programmed with only coding. In coding, anything that you haven’t put in the programming, the robot can’t do. For example, if the robot is programmed to walk forward and back, but not to turn left or right, it can’t until you program it to do so.

AI on the other hand only starts with a lot of data and gets trained to detect and learn how to do things. AI can do things it never was taught, by learning over a period of time. It makes predictions after a long time of being exposed to different situations and if its predictions are wrong (which they mostly are in the beginning) it remembers them and knows never to do it again. It categorizes the right and wrong ways and stores all these possibilities to learn from them. It’s one of the reasons that they can become so much smarter than a human. When we see or experience something dangerous or if we got it wrong, we can’t remember it forever, this is where we can keep making the same mistakes again. While an AI can make another mistake, it won’t be the same one. And since AI can operate at the speed of light, it takes barely any time for them to use trial and error to see what makes them right or wrong.

How AI Is Super Powering Robots

When the first Robot was invented in 1954, it created a spark of revolution, thinking that the machine will be able to help do human work without assistance was crazy. It was only a dream for even the richest. Today, we see robots doing a lot of our work. From our robot vacuums to even Elon Musk using them to build Teslas in the factory. (see picture below)

However, today, our technology has gotten better from 1954 and has advanced and so our dreams have changed. Today, anything with AI is the buzzword. When you combine a robot, with it having the ability to learn, it causes that insane change and revolution. A really good example is Boston Dynamics. They are a company that has made different robots that you might have heard of or seen in a video before. All of them are equipped with AI. Here is one of their robots doing a backflip 🤯

Atlas, a 6ft Boston Dynamic Robot doing a backflip!

Ethics In AI

One of the biggest concerns people have is privacy and that AI will make it unsafe for them. This is one of the reasons that AI isn’t being too populated or lawfully excepted in everyday life… yet. I think there will definitely be a future in which we could see AI helping us out every day like the technology we use today in a couple of decades.

While I agree that AI can be used to hack better, people also need to understand that it still happens on a huge scale, whenever you give your phone apps permissions to everything, you allow it to take all of your data, and in some cases, when people don’t read the policies, let's take WhatsApp as an example, recently, everyone had to accept this update to use WhatsApp

Normally, people just Agree without reading anything, which even I do. These companies give you so much to read that if you click it, it is a maze to find what they are taking from you and you end up just giving up finding and press Agree. What can you do right? If you don’t agree, you can’t even use it.

This particular update had the following things in the privacy policy.

What WhatsApp Collects From You: WhatsApp collects a lot of data on your phone. This includes your phone’s make and model, its operating system, battery status, time zone, signal strength, GPS location, and IP address. It also keeps track of how you use WhatsApp, followed by Group details, Profile pictures, and About Info. Moreover, the giant also stores information about payments

What WhatsApp Shares To Facebook: Almost everything collected by WhatsApp is now shared with Facebook and other Facebook companies. It also includes what you share on WhatsApp. The data can be used to bring you more personalized recommendations, ads, offers, and content on Facebook, Instagram, and others.

What WhatsApp Shares To Businesses: If you interact with a business account on WhatsApp, Facebook might share your data with several people at the business. Your data may also be shared with other third-party services working with that business.

Crazy right? All of this information is not only taken, but they sell it and make billions from it. It is something we can’t eliminate while having a phone. In the end, AI is another amazing way to help us advance more and for us to be able to do more things faster with the assistance of these robots. People often have concern that AI will destroy humans, while that is not possible at this time, AI is being used as a weapon by many international hackers, criminals, and governments to spy and gather information about you because today, data is money. But good for us, AI is being used for much good too! AI is also helping billions of people with things we don’t see like correctly predicting drought season to save crops in places like Africa, also predicting the best time to harvest crops to save food from going bad.

I’d like to end with a quote that lifts a little bit of weight off your shoulders,

“Robots are not going to replace humans, they are going to make their jobs much more humane. Difficult, demeaning, demanding, dangerous, dull — these are the jobs robots will be taking.

Sabine Hauert, Co-founder of Robohub

So while we are living in a world where AI is becoming better and more “dangerous”, It is also being used to solve many important problems and the best part is the number of people we help and save from it.

TL;DR: AI is not a code, but an algorithm that allows it to learn from data and trial and error. AI can be used for many different things both good and bad and can help billions of people. Think about how we humans learn and then picture that in a computer, but the computer can learn at the speed of light. That is AI in a nutshell :)

Article Written By Arqish Minhas

Consider Checking Out My LinkedIn, Medium, TKS Profile, And Instagram!

Image Credits:

https://corporatefinanceinstitute.com/resources/knowledge/other/artificial-intelligence-ai/

https://otexts.com/fpp2/nnetar.html

https://media.wired.com/photos/59327c7752d99d6b984dee6e/master/w_2560%2Cc_limit/john-mccarthy.png

https://www.bloomberg.com/news/features/2018-06-08/tesla-model-3-photos-of-elon-musk-s-factory-in-fremont

--

--