As the topic says lets us see the difference between artificial intelligence and machine learning, we need to understand first each separately. Let`s start with artificial intelligence.

Artificial intelligence term itself says that it is a kind of intelligence coming from artificial intelligence. So the question arises what intelligence is? Well of human beings intelligence is a capacity to understand and derive complex things much easily. Which is used by humans in day to day life? For example, an experienced driver can handle a complex accidental or bad weather situation very easily. Due to his capacity to understand the situation and react accordingly in minimum time like a fraction of a second which can save lives. Imagine a young teenage driver instead of that driver in the same situation. Well, he will get tense, and there you go. If you are doing analysis or research on such project, you can hire freelancer online who know AI as it is difficult to get such skilled employees for short term.

So when a machine takes decisions like an experienced human being in similarly tough situations are taken by a machine it is called artificial intelligence.

The machine learning is an ability to learn without being explicitly programmed. Sound complex? Let us make it easy. You can say that machine learning is a part of artificial intelligence because it works on similar patterns of artificial intelligence. But, instead of taking a decision it learns from it and enhances your user experience. Example your mobile phone will add those apps to your favorite apps which you use frequently. Or you can have seen those contacts you use frequently are added to speed dials automatically to save your time and efforts. In a single sentence, I can say that in the text to speech software where you say “hello world how are you?”

Now let’s take a look in detail at artificial intelligence. In computer science, the simplest meaning of artificial intelligence depends on external agents, such as a thermometer, photodiode, hygroscopic sensors. Using data collected from all these sources in real time is analyzed through small processors and in minimum time the decision about the action taken. For example, you might have seen some traffic camera traps which are triggered when a vehicle pass in front of with high speed beyond the speed limit only then it triggers the camera and photograph of the number plate get captured. Now let`s imagine that this process is through machine learning. Each vehicle monitoring is through this process when one crosses the speed limit, it takes a photograph and saves it, or sends it to a computer from where the manual process takes it over.

Now if a criminal is on the run and his license plate number is with all such camera traps. In this case, only one artificial intelligent system can tell accurately that this vehicle has passed through this point by identifying the number on the license plate. It will also alert the police immediately. That’s the main difference between artificial intelligence and machine learning.

History of artificial intelligence:

It all started long back in 1940 but soon due to funding issues it was put on hold many times. From 1951 scientist stared writing programs for games like chess and checker in which it is possible to defeat humans using computers. Finally in the 21st century after successful application of machine learning artificial intelligence came back in the boom.

On the other side in 1950 pioneering research on machine learning was conducted by the use of the simple algorithm. Later it also suffered from a funding crisis. In 1980 rediscovery of backpropagation gave it boost. 1990 was the turning year for machine learning as the focus shifts to data driven approach instead of knowledge driven approach. Now programs were created which analyzed lager amount of data and draw a conclusion or learn from the result. These things became very popular as it saved huge efforts and boring work for humans. From the year 2000 deep learning was feasible and neural network spread widely with commercial use. After 2010, machine learning became integral to many software services and became even more popular.

Now artificial intelligence in used in many places. Like optical character recognition, handwriting recognition, speech recognition, face recognition, artificial creativity, image processing, virtual reality, diagnosis, game theory, strategic planning, computer game bot, game artificial intelligence, natural language processing, translation, chatterbots, nonlinear control, and robotics. You can say artificial intelligence is the back bone of automation.

Machine learning also has large applications like adaptive websites, bioinformatics, classifying DNA sequences, detecting internet and credit card fraud, marketing, medical diagnosis, economics, online advertisement, recommender systems, synthetic pattern recognition, software engineering and search engine. You can find freelancers in this area as it is developing fast.

Artificial intelligence gives advantages of taking a quick decision in the absence of any experts. The place can be your room while playing chess or a war zone where every second is important. A medical emergency room at midnight while the doctor takes some time to come or extreme weather condition rescue mission. Kindergarten class or bomb diffusing zone. Hot desert zone or lonely gravity free space. Even an expert have physical limits, human needs to fulfill. But thanks to artificial intelligence we can do things from a safe distance much accurately. Automation done at various places proved that after a certain time even humans start producing errs in the work they are doing since a long time. Now automation assures us that the lengthy, boring work gets controlled easily.

The accuracy of Data:

As machine learning is giving results by analyzing large data, we can assure that it is correct and useful and time required is very less. Imagine the data and number crunching work for a flight simulation or space craft launching. We cannot do all the lengthy work quickly; we cannot put more men on it or need to verify if by some more men for assurance. But machine learning will get through it easily. Results produce early, and we can also get the multiprocessed results. Much more easy to understand. Now big experiments are going smoothly through machine learning and giving many simple results.

Summary: Both technologies are doing extremely well, but on a serious note let`s talk about disadvantages of these developing technologies. Human supervision is always necessary while using it. Yes, tragedies happened due to the failure of these systems are also big and takes the time to recover. Biggest disadvantage it`s taking human jobs. And we are yet to strike a fine balance in between technology and humans.

 

Kitty Gupta
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