What is AI or Artificial Intelligence

What you see here is a full Artificial Intelligence course. In section 1-3, I’ll be covering all the domains and the concepts involved under the umbrella of artificial intelligence, and I will also be showing you a couple of use cases and practical implementations by using Python.

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Agenda to clear up myths

There’s a lot to cover in this session and let me quickly run you through today’s agenda. So we’re gonna begin the session by understanding the history of artificial intelligence and how it came into existence. We’ll follow this by looking at why we’re talking about artificial intelligence now, why has it gotten so famous right now.

Part 1 – AI

Then we’ll look at what exactly is artificial intelligence. We’ll discuss the applications of artificial intelligence, after which we’ll discuss the basics of AI wherein we’ll understand the different types of artificial intelligence. We’ll follow this by understanding the different programming languages that can be used to study AI. And we’ll understand why we’re gonna choose Python. All right, I’ll introduce you to Python.

Machine learning

And then we’ll move on and discuss machine learning. Here we’ll discuss the different types of machine learning, the different algorithms involved in machine learning, which include classification algorithms, regression algorithms, clustering, and association algorithms.

To make you understand machine learning better, we’ll run a couple of demos wherein we’ll see how machine learning algorithms are used to solve real-world problems. After that, we’ll discuss the limitations of machine learning and why deep learning is needed.

Deep learning concept – what is it

I’ll introduce you to the deep learning concept, what are neurons, perceptrons, multiple layer perceptrons, and so on. We’ll discuss the different types of neural networks, and we’ll also look at what exactly backpropagation is.

Apart from this, we’ll be running a demo to understand deep learning in more depth. And finally, we’ll move onto the next module, which is natural language processing. On the natural language processing, we’ll try to understand what is text mining, the difference between text mining in NLP, what are the different terminologies in NLP, and we’ll end the session by looking at the practical implementation of NLP using Python.

Python

There’s a lot to cover in today’s session. So let’s move ahead and take a look at our first topic, which is the history of artificial intelligence. So, guys, the concept of artificial intelligence goes back to the classical ages. Under Greek mythology, the concept of machines and mechanical men were well thought of.

Talos

So, an example of this is Talos. I don’t know how many of you have heard of this. Talos was a giant animated bronze warrior who was programmed to guard the island of Crete. Now these are just ideas. Nobody knows if this was actually implemented, but machine learning and AI were thought of long ago. Let’s get back to the 19th century. Now 1950 was speculated to be one of the most important years for the introduction of artificial intelligence.

In 1950, Alan Turing published a paper in which he speculated about the possibility of creating machines that think. So he created what is known as the Turing test. This test is basically used to determine whether or not a computer can think intelligently like a human being. He noted that thinking is difficult to define and devised his famous Turing test.

Turin test

So, basically, if a machine can carry out a conversation that was indistinguishable from a conversation with a human being, it was reasonable to say that the machine is thinking, meaning that the machine will pass the Turing test. Now, unfortunately, up to this date, we haven’t found a machine that has fully cleared the Turing test.

So, the Turing test was actually the first serious proposal in the philosophy of artificial intelligence. Followed by this was the era of 1951. This was also known as the game AI. In 1951, by using the
Ferranti Mark 1 machine of the University of Manchester, a computer scientist known as Christopher Strachey wrote a checkers program. And at the same time,a program was written for chess as well.

Now, these programs were later improved and redone ,but this was the first attempt at creating programs that could play chess or that would compete with humans in playing chess. This is followed by the year 1956. This is probably the most important year in the invention of AI.

1956 Dortsmouth

Because in 1956, for the first time, artificial intelligence was coined by John McCarthy at the Dartmouth Conference in 1956. Coming to the year 1959, the first AI laboratory was established. This period marked the research era for AI.

So the first AI lab where research was performed is the MIT lab, which is still running till date. In 1960, the first robot was introduced to the General Motors assembly line. In 1961, the first chatbot was invented. Now we have Siri; we have Alexa.

1961 a long way from home

But in 1961, there was a chatbot known as Eliza, which was introduced. This is followed by the famous IBM Deep Blue. In 1997, the news broke down that IBM’s Deep Blue beats the world champion, Garry Kasparov, in the game of chess. Here we see the kind of the first accomplishment of AI.

2005 Grand challenge

It was able to beat the world champion at chess. In 2005, when the DARPA Grand Challenge was held, a robotic car named Stanley, which was built by Stanford’s racing team, won the DARPA Grand Challenge. That was another big accomplish of AI. In 2011, IBM’s question answering system, Watson, defeated the two greatest Jeopardy champions, Brad Rutter and Ken Jennings. So, guys, this was how AI evolved.

It started off as a hypothetical situation. Right now, it’s the most important technology in today’s world. If you look around everywhere, everything around us is run through AI deep learning or machine learning. So since the emergence of AI in the 1950s, we have actually seen an exponential growth and its potential.

AI = includes machine learning, deep learning, etc.

So AI covers domains such as machine learning, deep learning, neural networks, natural language processing, knowledge-based, expert systems, and more. It is also made its way into computer vision and image processing.

Over 50 years of AI

Now the question here is if AI has been here for over half a century, why has it suddenly gain so much importance? Why are we talking about artificial intelligence now? Let me tell you the main reasons for the demand for AI. The first reason is what we have more computation power now. Artificial intelligence requires a lot of computing power.

Complex deep learning models are deployed

Recently, many advances have been made, and complex deep learning models are deployed. Also one of the greatest technology that made this possible are GPUs. Since we have more computational power now, it is possible for us to implement AI in our daily aspects. Second most important reason is that we have a lot of data at present.

Data is generated at an unprecedented pace

We’re generating data at an immeasurable pace. We are generating data through social media through IoT devices. Every possible way, there’s a lot of data. So we need to find a method or a solution that can help us process this much data, and help us derive useful insight so that we can grow business with the help of data.

Neural Networks

Alright, so, that process is basically artificial intelligence. So, in order to have a useful AI agent to make smart decisions like telling which item to recommend next when you shop online, or how to classify an object from an image. AI are trained on large data sets, and big data enables us to do this more efficiently. Next reason is now we have better algorithms.
Right now we have very effective algorithms which are based on the
idea of neural networks. Neural networks is nothing but the concept behind deep learning.

Better Algorithms – everybody talks about it, and who uses it ?

Since we have better algorithms which can do better computations and quicker computations with more accuracy, the demand for AI has increased. Another reason is that universities, governments, startup, and tech giants are all investing in AI. Okay, so companies like Google, Amazon, Facebook, Microsoft, all of these companies have heavily invested in artificial intelligence because they believe that AI is the future.

So AI is rapidly growing both as a field of study and also as an economy. So, actually, this is the right time for you to understand what is AI and how it works. So let’s move on and understand what exactly artificial intelligence is. The term artificial intelligence was first coined in the year 1956 by John McCarthy at the Dartmouth Conference.

1956 is the birth year of AI

It was the birth of AI in the 1956. Now, how did he define artificial intelligence? John McCarthy defined AI as the science and engineering of making intelligent machines. In other words, artificial intelligence is the theory and development of computer systems able to perform task that normally require human intelligence, such as visual perception, speech recognition, decision making, and translation between languages.

So guys, in a sense, AI is a technique of getting machines to work and behave like humans. In the rest past, artificial intelligence has been able to accomplish this by creating machines and robots that have been used in wide range of fields, including healthcare, robotics, marketing,business analytics, and many more. With this in mind, let’s discuss a couple of real world application of AI, so that you understand how important artificial intelligence is in today’s world. Now, one of the most famous applications of artificial intelligence is the Google predictive search engine.

GOOGLE makes recommendations = AI

When you begin typing a search term and Google makes recommendations for you to choose from, that is artificial intelligence in action. So predictive searches are based on data that Google collects about you, such as your browser history, your location,your age, and other personal details. So by using artificial intelligence, Google attempts to guess what you might be trying to find. Now behind this, there’s a lot of natural language processing, deep learning, and machine learning involved. We’ll be discussing all of those concepts deeper soon.

MORGAN CHASE

It’s not very simple to create a search engine, but the logic behind Google search engine is artificial intelligence. Moving on, in the finance sector, JP Morgan Chase’s Contract Intelligence Platform uses machine learning, artificial intelligence,and image recognition software to analyze legal documents. Now let me tell you that manually reviewing around 12,000 agreements took over 36,000 hours. That’s a lot of time. But as soon as this task was replaced by AI machine, it was able to do this in a matter of seconds. So that’s the difference between artificial intelligence and manual or human work. Even though AI cannot think and reason like humans but their computational power is very strong compared to humans, because the machine learning algorithm, deep learning concepts, and natural language processing, AI has reach a stage wherein it can compute the most complex of complex problems in a matter of seconds.

HEALTHCARE

Coming to healthcare, IBM is one of the pioneers that has developed AI software, specifically for medicine. Let me tell you that more than 230 healthcare organizations use IBM AI technology, which is basically IBM Watson. In 2016, IBM Watson technology was able to cross reference 20 million oncology records quickly and correctly diagnose a rare leukemia condition in a patient. So, it basically went through 20 million records, which it probably did in a matter of second or minutes, max to max. And then it correctly diagnosed a patient with a rare leukemia. Knowing that machines are now used in medical fields as well, it shows how important AI has become. It has reached every domains of our lives. Let me give you another example. The Google’s AI Eye Doctor is another initiative, which is taken by Google, where they’re working with an Indian eye care chain to develop artificial intelligence system which can examine retinal scans and identify a condition called diabetic retinopathy which can cause blindness. Now in social media platforms like Facebook, artificial intelligence is used for face verification wherein you make use of machine learning and deep learning concept in order to detect facial features and tag your friends.

Facebook auto-tagging = AI

All the auto-tagging feature that you see in Facebook, behind that there’s machine learning,deep learning, neural networks. There’s only AI behind it.

So we’re actually unaware that we use AI very regularly in our life. All the social media platforms like Instagram, Facebook, Twitter, they heavily rely on artificial intelligence. Another such example is Twitter’s AI which is being used to identify any sort of hate speech and terrorist languages in tweets. So again, it makes use of machine learning, deep learning, natural language processing in order to filter out any offensive or any reporting content. Now recently, the company discovered around 300,000 terroristic link accounts and 95% of these were found by non-human artificially intelligent machines.

VIRTUAL ASSISTANTS

END OF PART 1

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