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Silicon driven AI/ ML revolution
Silicon driven AI/ ML revolution

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Data and some of the insights are from leader sessions in SemiconIndia 2022

AI is fast revolutionizing our world as we know it, making it faster and efficient. Over the past few decades, innovation in silicon manufacturing has been largely confined to shrinking transistors to include more of them in integrated circuits. However, over the last few years, this innovation has significantly changed due to the advent of AI, which has encouraged innovators to think differently and reinvent the basic chip design and build a new type of semiconductor chip, built for AI, powering the next generation of computing.

Over the next several years, growth in the semiconductor industry is expected to grow substantially. In fact, aided with artificial intelligence (AI), the growth is expected to be 5 times more than the non-AI related semiconductor growth, with the global AI related semiconductor market growing from USD 32 bn in 2020 to USD 65 bn in 2025.

AI market dynamics is changing, and intelligence is moving towards edge and one can derive its effects on the chipset revenues as well. While assessing the deep learning chipset revenue, ‘Inference’ revenue is expected to grow almost 10X the revenue from ‘Training’ by 2025. While assessing the deep learning chipset revenues from a power consumption point of view, it is expected that ‘sub 5W’ segment is expected to witness maximum growth, more than 2X the growth of high (>50W) and medium (5-50W) power domains by 2025. In terms of market sector, ‘Edge’ is expected to grow more than 2.5X than the ‘Enterprise’ revenue by 2025.

Many organisations are performing all sorts of complex AI and ML applications. For this, from a pure semiconductor consumption perspective, mobile, high-performance computing (HPC) are most important. Therefore, the next generation of semiconductor chips will have to be smart chips to incorporate efficiency and specialization. Chip architecture will be designed to optimize for the software running on it and run more efficiently.

As companies look to manufacture these chips, they must ensure that the new technologies will have more options for processing stacks that can evolve and change as the demands of ML and AI models evolve and change. This will enable the companies to stay competitive and not stagnate that can occur when software is limited by hardware.

The next generation of chips will shape the field of Artificial Intelligence in the coming years. Effective collaborations between peers, academia and industry, govt and industry associations etc. will lead to creation of that hardware which will power the upcoming era of AI.


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Vandhna Babu
Principal Analyst - Research

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