The rise of AI chips

What is the News?

The adoption of Artificial Intelligence (AI) chips has risen as chipmakers design different types of AI chips to power AI applications such as natural language processing (NLP), computer vision, robotics, and network security across a wide variety of sectors.

What is Artificial Intelligence (AI)?

What are AI chips?

AI chips are built with specific architecture and have integrated AI acceleration to support deep learning-based applications. Deep learning is commonly known as active neural network (ANN) or deep neural network (DNN).

DNN is a subset of machine learning and comes under the broader umbrella of AI. DNNs combine a series of computer commands or algorithms that stimulate activity and brain structure. Deep learning can make the process of collecting, analysing, and interpreting enormous amounts of data faster and easier.

These chips make it possible to infuse AI into a broad spectrum of applications to help turn data into information and then into knowledge.

Types of AI Chips: a) Application-specific integrated circuits (ASICs), b) Field-programmable gate arrays (FPGAs), c) central processing units (CPUs) and d) GPUs, designed for diverse AI applications.

How AI chips are different from traditional chips?

Traditional chips: These chips contain processor cores and memory, perform computational tasks. AI works on huge volumes of data, hence, these traditional chips are not ideal for AI applications as they would not be able to handle the higher computational necessities of AI workloads.

AI chips: These generally contain processor cores as well as several AI-optimised cores (depending on the scale of the chip). The AI cores are optimised for the demands of heterogeneous AI workloads with low-latency inferencing.

What is the growth of the AI chips industry?

As per a report by Allied Market Research, the rise in the need for smart homes and cities, and the surge in investments in AI start-ups are expected to drive the growth of the global AI chip market. The Worldwide AI chip industry accounted for $8.02 billion in 2020 and is expected to reach $194.9 billion by 2030, growing at a compound annual growth rate (CAGR) of 37.4% from 2021 to 2030.

What are the applications of AI chips?

They are used in a multitude of smart machines and devices. Such as a) delivering the performance of a data centre-class computer to edge devices, b) Supporting in-vehicle computers to run state-of-the-art AI applications more efficiently, c) Powering applications of computational imaging in wearable electronics, drones, and robots, d) Supporting financial services workloads like fraud detection, loan processing, clearing and settlement of trades, anti-money laundering and risk analysis, e) Train massive, unstructured data sets, etc.

Source: The post is based on the article “The rise of AI chips” published in The Hindu on 23rd May 2022.