Artificial intelligence and machine learning have been the key buzzwords for this decade, A lot of surveys conducted and analytics proof to say that Artificial intelligence and machine learning related jobs will be the top contenders for the next decade as well.
We’re going to compare Artificial intelligence And machine learning, we’ll start by checking out a quick introduction to Artificial intelligence and where Artificial intelligence is used.
And after this, we can check out what machine learning is how it is related to Artificial intelligence.
Introduction to Artificial intelligence
It is a theory and the development of computer system basically helping it to perform tasks, which actually require some sort of human intelligence, you might wonder what sort of tasks actually require human intelligence?
1. Image recognition
Well, the first thing Artificial intelligence is very good at doing is image recognition. Because image recognition is a very useful when it comes to social media, or even a couple of traffic cameras, when it comes to violations.
2. Speech recognition
You can have various safety and security locks, which are just answered to one person’s voice, then you have voice assistants who pop up for this particular speech, and much, much more.
3. Decision making
As you might know, it, you know, will require some sort of cognition, it’ll require some sort of human intelligence, but then the Artificial intelligence of these days are trying to achieve very good level of cognition to pretty much level up with humans.
A language translation, image translation, or whatever it is, it would require some sort of intelligence here as well. But then the machines have got good enough such that they can do it without having any human interference there as well.
So where are we with the Artificial intelligence of today, when it has been so suddenly integrated into our lives? We don’t even notice it is there anymore?
Well, why do we say this? Well, the first thing that pops into my head is because think about all the advertisements you get recommended by google when you go on to an E-commerce site.
Think about every time you say, hey Siri, or Hey Google, hey Cortana, whatever it is, and you have a voice assistant already there to answer for all your needs.
So this is where we are with Artificial intelligence today, we have self driving cars, and so much more than you might have heard of this particular term, which is Artificial intelligence is the best Carrier part of this decade.
And yes, this decade, it’s 2021 and 10 years from now, it has been proven by various trends and surveys that Artificial intelligence will be the best career path.
So every time you open up your Google Assistant, talk to Cortana, Alexa ,Siri and much, much more.
I mean, there are many other chat bots out there. Make sure to know that there is natural language processing that there is Artificial intelligence working there.
And the next most important application of Artificial intelligence is when it comes to finance.
If you’re a stock trader, then again, people might know that stock trading will require huge amounts of experience a lot of skill.
You should know, Artificial intelligence working for you machine learning models working for you, which can give you a better insight, a better look at what the future would look like.
There is a lot of people around the world who are actually making use of a good couple of models for their trading ,
I mean, you can do a lot of pattern recognition of how your stock is performing, you can perform prediction activities and much, much more.
The most important thing that happened in the year 2021 was the use of Artificial intelligence to track breast cancer prematurely and about 53% of the time,
you know, the chances are that the Artificial intelligence model actually are diagnosed the people right, and this was one year before they would actually get an official diagnosis So this is something amazing.
8. Data generation and data storage
So we’re gonna find all the data in the world, this is what big data solution does, actually. So you know, we find all the data in the world, then we pretty much store it for further processing. And the processing part is where Artificial intelligence comes in,
you can use a lot of machine learning techniques, there are concepts even more deeper, such as you know, deep learning, in fact, where we can perform very good amount of data processing in a very rapid way very efficient way where the data can be transformed from the raw, unruly entity, it has to very good information.
And this information later again, with the help of Artificial intelligence is converted into actionable insight, you can get very good visualizations out of it, predict trends, perform data analytics, and much, much more.
Introduction of machine learning
Well, machine learning is a very simple application of Artificial intelligence. Or you could say machine learning is one of the ways to achieve Artificial intelligence.
So again, this basically provides our machines the way that they can automatically learn automatically improve and go about without actually being programmed every step of the way.
So machine learning today is pretty much a lot of mathematics, statistics and algorithms,But then the future goal of machine learning is, again to achieve Artificial intelligence.
1. Google Brain
Here are some of the key moments in the life of machine learning in today’s world, in 2012, people at Google came up with Google brain.
And this sort of established the open source world of machine learning to the world. And people started realizing Google brain is an amazing product to which they can dwelve into algorithms, they can work with machine learning.
2. DeepFace by facebook
After Google brain, came DeepFace the faces by the people at Facebook, and this was basically their deep learning solution for face recognition.
So the amazing face recognition face detection algorithms, we see when we tag friends on Facebook, where Facebook automatically tags people for us. That’s deep bass working for you.
3. Google DeepMind
DeepMind mind is another huge, amazingly well put out project by the people at Google where they developed complex machines, which could play very good games against humans and win against them as well
AlphaGo was another project of Google DeepMind, basically, where there was a machine learning model put into place and one of the most sophisticated models because it could beat the world champion the multiple times world champion at this game called go,
which is considered to be the toughest board game ever made, And then this machine could beat that particular person. And in fact, the person who actually lost to the machine decided to retire,
because he believed that he was not the best in the world anymore, because there was a machine beating mattered.
Comparison Between Artificial Intelligence And Machine Learning
The first thing has to be definition, we’ve already looked at this. So let’s quickly glance over it again.
Well, basically, in the world of Artificial intelligence, the intelligence part of it is actually defined, when we talk about, you know, the machines gaining knowledge and you know,
The ability to actually learn something and pretty much apply what it has learned this particular store knowledge, that is where the word intelligence comes.
Machine learning basically involves the process very similar to Artificial intelligence where it’s acquiring information, but then it’s doing it in a very different way.
There’s something called repeated learning, you know, where it actually learns on one particular concept again, and again, again, to master it, and then understand what the concept actually is.
AI is concerned about, you know, increasing chances of success in actually mimicking human intelligence, So it at a couple of stages, Artificial intelligence is not concerned with how accurate it is.
There is a different story when you come to machine learning, because when it comes to machine learning, machine learning strives to increase the accuracy, And you know,
it would actually sideline the amount of success that it sees because achieving accuracy in the mathematical model in terms of machine learning is actually a very good priority. And it is actually built for what it’s supposed to do. And it does it very well.
When we talk about the goal of AI it is to again, as I’ve already told you to simulate natural intelligence to prove to humans that machines can be as good as humans, And this is done by solving complex problems
Primary goal of machine learning is to actually learn from the data that actually sees understand what the data is, then perform certain tasks using the data, you know, since it does it repetitively,
it understands it better and better every time it does it, and this increases the performance of that particular machine.
Artificial intelligence put in very simple terms is basically that it has decision making on steroids, because to a computer what feels like a very complex convoluted entity,
it is actually a very simple dump machine, which has been coded by the human kind, right, so Artificial super intelligence claims to you know, it has ever been founded.
Or if a machine chooses to, you know, start coding another machine, the decision making skills of an Artificial intelligence entity will be equal to that of human intelligence, or better than that as well.
Machine learning basically allows a system or a computer to you know, learn things from the data it sees, does it repetitively as you already know it.
Artificial intelligence again, you know, leads to developing system which basically will mimic human activities in certain circumstances.
But then at this point of time, it can mimic everything apart from emotions and much more. In fact, it can detect emotions, that is how good it is. But for it to mimic human level emotion is impossible at this point of time.
But then let’s not say it’s impossible in the future as well, because we do not know what the future holds.
Machine learning involves this entire procedure where you will be creating algorithms which learn on their own. And here’s the best part about the comparison, machine learning will help achieve Artificial intelligence at the end of the day.
- Sixth point
The average salary of an Artificial intelligence developer and the machine learning engineer and AI developer gets somewhere over 120,000 USD per year.
And then an average salary of a machine learning engineer is over $100,000 per year as well.
Well, this number is an average number for an associate to a junior or middle intermediate level programmer,
but do know that there are companies out there in the world which which will actually pay three times, four times right now throughout the world.
So they don’t mind where you are, they don’t mind what amount they’re paying out if you’re actually good with the skills and you have the right certification when it comes to especially Artificial intelligence, machine learning and concepts of data science guys,
Final thoughts about comparison
Artificial intelligence will lead to intelligence at the end of the day, or, you know, some sort of wisdom. But if you’re talking about machine learning, again, it’s all about acquiring knowledge.
So to summarize the entire thing, guys, Artificial intelligence will actually use all of the experience to acquire knowledge to acquire skills to learn it and understand how it has to apply all that knowledge.
And machine learning will basically you know, use all the experience that has from learning again and again and again, to basically you know, look for some pattern understand what’s going on there to amplify the amount of knowledge it has gained to see where you know,
it’s like picking a needle in a haystack. So machine learning is where, you know, it’s the process of picking the needle in the haystack when we’re talking about Artificial intelligence,
it finds the fastest way it finds the most important way where a human is not required to pick out that needle from the haystack guys.
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