Introduction:
Man: Alexa! Play “Sunflower, by Post Malone”
Alexa: Starts playing!!
Man: Alexa! Stop
Alexa: Stops playing!!
Seems fascinating! Isn’t it? Who could have imagined all this back in the early ’90s that human-machine interaction will turn into a reality? But here you are in the 21st-century witnessing it by yourselves. Currently, big tech giants like Google, Facebook, Apple, Microsoft are all working to make machines intelligent, smarter, and capable enough to learn new things. Google’s self-driving car is one of the instances, which shows how machines are getting smarter.
But AI is not only limited to this; online marketing is also reaping the benefits of AI.
With the introduction of AI in online marketing, marketers are now able to understand better what their target audience wants.
Moreover, with the presence of Apple’s Siri, Amazon’s Alexa, and Google Assistant in the market, the use of terms like AI and ML has frequently increased, and quite often, they are used interchangeably.
So, if you are one of those who see no difference between AI and ML, or who often get confused between these terms, then this article is for you. But before diving into the differences straight away, first, let’s just define what AI and ML are.
Artificial Intelligence Explained:
Before diving into the technical definition, ask yourself what comes to your mind when you see the term Artificial Intelligence? Some of the Avenger fans will relate AI to Tony Stark’s “J.A.R.V.I.S” or some of you may relate it to the robots shown in the movie Terminator. The way these sci-fi movies have represented AI is what we call as STRONG AI.
Technically, it is a theoretical computer system that has a mind just like humans do and can create a better version of itself. Contrary to this, WEAK AI or NARROW AI acts intelligently, but it’s not. An AI capable of predicting the weather will not be able to challenge you in chess, this shows that weak AI is a bit more task-specific, whereas a strong AI is more generalized.
Machine Learning Explained:
Have you ever wondered how a newborn child can speak a language without taking any help from a tutor? If not, then you should, because of the way he does that, it will help you in a better understanding of what machine learning is.
Now for a moment, go back to your childhood and try to recall how you learned to speak, you’ll get your answer. You’ll see that it was not any tutor who helped you, but it was your brain, who was constantly collecting the words you use to hear from your surroundings, and these words are known as data set in terms of machine learning.
Therefore, with time and experience, you learned to speak a language proficiently, and you still are getting better and better at it. And this is what machine learning aims for. I.e., creating software capable enough to improve their performance from their experience for specific tasks.
Machine Learning (ML) vs Artificial Intelligence (AI)
Till now, it is clear that AI is more generalized, which aims to create machines that can stimulate the human mind and it’s intelligence whereas, under this big umbrella of AI, ML is a subset of it.
The other major differences between AI and ML are as follows:-
Goals
AI aims to create a human-like machine that can perform any task that a human can do but in a better and efficient manner, whereas ML aims to create a software to perform specific tasks accurately and can learn from its prior experiences.
Adaptability to New Situations
AI focuses on how efficiently and successfully a machine can adapt itself to new situations whereas, ML focuses on how efficiently and accurately a software can perform a specific task, it will not be able to perform a task if it is out of its domain.
Decision Making
AI can make decisions on its own no matter what the situation is whereas ML can only learn new things from the data that has been fed to it. E.g. In online marketing, AI can help in deciding the effectiveness of a particular content depending upon the targeted customers.
Closeness to the Human Mind
AI is closer to how a human mind works as it has the decision-making skills, and tries to successfully adapt to new situations as well whereas in ML the only trait that is similar to the human mind is the capability to learn new things for its data set.
Artificial Intelligence Types
Artificial Intelligence is of two types:
● Strong AI
● Weak or Narrow AI
Machine Learning Types
Whereas Machine Learning can be categorized into three types:
● Supervised Learning
● Unsupervised Learning
● Reinforcement Learning
ML vs AI Real Life Examples
Artificial Intelligence Examples:
● Chess grandmaster Gary Kasparov was beaten by IBMs Deep Blue AI in 1996. Deep Blue is an example of narrow AI.
● Sophia by Hanson Robotics is a big step towards strong AI.
Machine Learning Examples:
● Lee Sedol was beaten by Google DeepMind’s Alpha go in 2016 at GO. It was trained on a large data set of expert moves.
● Speech recognition, facial recognition all comes under ML.
Conclusion
From the above-stated differences, it is clear that though ML and AI are related to each other but are not at all the same. In other words, we can state that AI is a superset of ML or ML is a subset of AI.
Moreover, from driverless cars to the use of AI chatbots to answer customer queries in online marketing, AI and ML are continuously evolving to make this world a smarter place to live.
COMMENTS