Difference between Normal Processor and AI Processor


In IT and computing field, the processor is one of the most essential components of a computing system. Processors are being upgraded every day. Read this article to find out more about normal processors and AI (Artificial Intelligence) processors and how they are different from each other.

The fundamental difference between a normal processor and an AI processor is that a normal processor is a general-purpose processor used to perform general computing tasks, while AI processors are special purpose processors used to perform specialized AI and Machine Learning tasks.

What is a Normal Processor?

A Normal Processor, also called a Regular Processor, is a general-purpose processor designed to perform a variety of computing functions like word processing, spreadsheet, web browsing, multimedia editing, and more.

It is also called Central Processing Unit (CPU) of a computer system. Normal processor is a small sized chip which has electronic circuits for data processing on a single silicon chip. A normal processor is primarily design to process data based on instructions provided to it. A processor used in a typical desktop or laptop computer is a normal or regular processor.

What is an AI Processor?

An AI Processor is a special-purpose processing unit used in computer system employed for artificial intelligence and machine learning tasks. AI processors are optimized to process data based on user’s instructions as well as self-learning/machine learning approach.

Therefore, AI processors are mainly used to perform specialized tasks like complex mathematical problems, matrix calculations, vector operations, and more. AI Processors are capable of performing operations much faster than normal processors. Common examples of AI processors include GPU (Graphics Processing Unit), FPGA (Field-Programmable Gate Array), etc.

Difference between AI Processor and Normal Processor

The following table highlights all the significant differences between normal processor and AI processor −

Normal Processor

AI Processor

Normal processor, also called Central Processing Unit, is a general-purpose processing device used in desktops, laptops, smartphones, etc. to process data according to instruction given to it.

AI processors are artificially trained processors that are used in special applications to make computing systems smarter.

Normal processors are lower than AI processors.

AI processors execute instructions at a faster speed.

Normal processors are more versatile, as they can perform a wide range of functions.

AI processors are specialized processors as they are designed for specific tasks.

Normal processors are less expensive.

AI processors are more expensive than normal processors.

Normal processors have generalized instruction sets to perform different operations.

AI processors have specialized instruction sets to perform special operations in the field of artificial intelligence and machine learning.

Normal processors use ICs for instruction-based computation.

AI processors use modern computing technologies like artificial intelligence, machine learning, deep learning, etc. for complex computation applications.

Normal processors are relatively less efficient.

AI processors are more efficient than normal processors.

Normal processors are marked average in terms of performance.

AI processors are high-performance processors.

Normal processors are also called processors, CPUs, or regular processors.

AI processors are also called NPUs, i.e. Neuromorphic Processing Units.

Normal processors are used by all users.

AI processors are mainly used by users that involve AI and ML development related tasks.

Conclusion

The most significant difference that you should note here is that a normal processor is one that can perform arithmetic and logical operations based on the instruction provided from the user, while an AI processor is one that is artificially trained to perform tasks and use machine learning (ML) and deep learning (DL) like advanced technologies to perform complex tasks.

Updated on: 26-Jul-2023

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