Artificial Intelligence (AI) is a word that needs no more introduction. There are so many concepts evolved around AI… Like neural networks, computer vision, NLP, etc., among them there is one particular word which has became very popular recently is Algorithm.
When it comes to algorithms most people presume that algorithm means using AI. But there is a whole lot difference between these two.
In this article let’s learn about the AI algorithm and what is the difference between a regular algorithm and an AI algorithm.
Here is the concept:
Algorithm:
An algorithm is a set of instructions that gets executed during performing a task by a computer. In other words, Algorithms are the step by step process that a programmer uses to instruct computers what to do next.
The goal of an algorithm is to solve a specific problem, which is instructed to them as a sequence of steps.
Consider this Example:
Imagine you have to find out how many times the word “Blue” was repeated by sorting through a million files. Even if it takes you one second per file, you have to work for 11 days straight without any intervals. But if you assign this same task to the computer using an algorithm, it will compute by using its processing power and accomplish the task in a few seconds.
Few cases where algorithms are used:
- YouTube’s algorithm knows what kind of ads should show to you.’
- Amazons algorithm knows what products you like.
AI algorithm:
ML is a set of algorithms that enable computers to learn from previous outcomes and get an update with the information without human intervention. It is simply fed with a large amount of structured data in order to complete a task without being programmed how to do so.
Based on the data acquired, AI will build assumptions and come up with possible new outcomes by considering many factors into account which helps them to make better decisions than humans.
Consider this Example:
Self-driving cars are one of the best examples of this. AI is mostly used in self-driving cars where the sensors detect instances of a pedestrian crossing, signal lights, oncoming vehicle, lane detection, and surface conditions and maps using sensors like blind-spot monitoring, LIDAR, and ultrasonic all the data will be added to the AI machine to analyze and make the smarter driving decisions.
That’s what algorithms can do for humans (though it’s a single example)
So, what makes the difference?
Traditional algorithm:
The traditional Algorithm takes some input and some logic in the form of code and gives you an output. This output depends upon the steps (codes) described in the algorithm.
Machine Learning (AI) algorithm:
ML algorithm takes an input and also an output and develops a logic using predictive mode and when it receives a new input based on that logic it will give you new output. That logic generated by ML is what makes this different from the traditional algorithm.
Here is an abstract:
ML/AI algorithm learns from the data and come up with unique solutions while traditional algorithm runs on a predefined set of guidelines to make the solution.
