Artificial Intelligence (AI) Chips

Artificial Intelligence (AI) Chips

This article covers ‘Daily Current Affairs’ and the topic details of “AI Chips” .This topic is relevant in the “Science & Technology” section of the UPSC CSE exam.


Why in the News?

In a stunning display of tech prowess, Kerala’s Digital University has unleashed the Kairali AI Chip, propelling India onto the global edge AI stage. This silicon marvel isn’t just a chip; it’s a paradigm shift, ushering in an era of intelligent machines operating closer to the data’s origin. 


About Kairali AI Chip

  • Kairali embraces the burgeoning world of edge AI, where computations occur directly on devices where data arises.
  •  It can help smartphones in  translating the languages on the fly, analyzing complex images instantly, or making personalized recommendations without sending the data anywhere.
  • This decentralized intelligence, powered by Kairali, promises faster processing, lower latency, and enhanced data privacy – a perfect recipe for revolutionizing countless applications.


Some potential uses-

  • Agriculture: The chip revolutionizes precision farming, providing real-time monitoring of crop health, soil conditions, and environmental factors, optimizing resource usage for enhanced crop yields.


  • Aerospace: The chip elevates Unmanned Aerial Vehicles (UAVs) and satellites by offering advanced processing power for navigation, data collection, and real-time decision-making with minimal power consumption. It also enhances the capabilities of drones for applications such as delivery services and environmental monitoring.


  • Mobile Phones: Enhancing the efficiency of smartphones, the chip enables advanced features like real-time language translation, improved image processing, and AI-driven personal assistants.


  • Security and Surveillance: The chip facilitates faster and efficient facial recognition algorithms, threat detection, and real-time analytics through its edge computing capabilities.


  • Automobile: Serving as a game-changer for autonomous vehicles, the chip provides essential computing power for real-time processing of sensory information, ensuring safe and efficient autonomous driving.


About AI chips

  • AI chips, often called artificial intelligence chips, are specialised processors that improve the efficiency of Artificial Intelligence (AI) tasks. These chips play an important role in speeding up the computation-intensive tasks that machine learning and deep learning algorithms require.
  •  Unlike traditional Central Processing Units (CPUs), which are general-purpose, AI chips are optimised for specialised tasks, resulting in quicker and more energy efficient processing.
  • One famous type of AI chip is the Graphics Processing Unit (GPU), which was originally meant to render visuals in video games but has since been repurposed for parallel processing tasks required by AI. 
  • Furthermore, Field-Programmable Gate Arrays (FPGAs) and Application Specific Integrated Circuits (ASICs) are gaining popularity because they can give even better efficiency by tailoring hardware to specific AI workloads.


How AI chips work

  • It is a collection of computer programmes or algorithms which stimulate activity and brain structure.
  • Deep Neural Networks (DNNs) go through a training phase in which they gain new skills based on previous data.
  • DNNs can then infer by using the skills learnt during deep learning training to make predictions on previously unknown data.
  • Deep learning may accelerate and simplify the collection, analysis, and interpretation of massive volumes of data.
  • Chips like these, with their hardware designs, compatible packaging, memory, storage, and connectivity solutions, enable AI to be incorporated into a wide range of applications, transforming data into information and subsequently knowledge.


Benefits of AI (Artificial Intelligence) chip-

  • Enhanced Performance: AI chips are intended to address the special needs of artificial intelligence applications, resulting in much quicker processing rates and higher performance than standard processors. This acceleration is especially important for the complicated computations used in machine learning and deep learning techniques.


  • Energy Efficiency: AI processors are optimised for parallel processing, which allows AI workloads to be executed more efficiently. This not only speeds up processes, but also lowers energy usage, making AI systems more sustainable and cost-effective in the long term.


  • Specialised Features: Unlike universal processors, AI chips are designed for specific AI applications. This specialisation allows them to excel at tasks like picture recognition, natural language processing, and data analysis, resulting in more accurate and efficient outcomes.


  • Scalability: AI chips help to scale AI systems. Their architecture enables smooth integration with a variety of devices, ranging from edge devices such as smartphones and IoT devices to data centres, offering scalability to meet the expanding demands of AI applications.


  • Optimised Hardware Layout: Manufacturers are always optimising the design of AI chips to increase efficiency and effectiveness. This optimisation takes into account size, weight, and power consumption to ensure that AI-powered devices can be used in a variety of applications and situations.


  • Real-time Processing: AI chips allow for real-time data processing, which is vital in applications such as autonomous vehicles, where split-second decision-making is required for safety. This skill is especially useful in cases that require quick responses, such as cybersecurity and surveillance.

Download Yojna daily current affairs eng med 31st Jan 2024


Prelims practice question

Q1) Consider the following statements:

1) AI chips in autonomous vehicles can be used to enhance safety features

2) AI chips in edge devices reduce the latency by processing AI tasks locally

3) General-purpose computing  is a key feature of AI chips

How many of the above statements are true?

a) One

b) Two

c) Three

d) None




Mains practice question


Q1) Considering the environmental impact of technology, how can the design and manufacturing of AI chips be optimized to minimize their carbon footprint? 

Q2) As AI chips become increasingly integrated into everyday devices, how do you foresee the ethical implications and privacy concerns associated with the widespread use of AI in various aspects of our lives, and what measures should be taken to address these issues?

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