AI hardware has been highlighted in Chris Miller’s book Chip War which discusses advanced chip manufacturing. Semiconductor industry is the most precise and complex industry. In early days, there was vertical integration. These days, we have fabless chipmaking and foundries.

These days we also have Nvidia’s GPUs, Google’s TPUs and emerging neural processing units — NPUs. These are all advanced accelerators. It is an evolution from 7nm to 5nm to 3nm fabrication. While giving more compute power, it manages power consumption and heat dissipation.

GPUs are good at parallel processing and are good for training LLMs. TPUs are application-specific integrated circuits (ASICs). They are good for low precision computations. NPUs are a type of ASICs designed for accelerating neural network computations for specific tasks in mobile and edge-computing.

India is entering into semiconductor space. There is continuous advancement in semiconductor technology. The demand for AI hardware is soaring — from accelerator for training to inference chips.THere is a demand for specific chips — power management, telecom, digital signal processing, cryptography and so on. There are advances in ASICs. At the same time, material science and quantum computing do help in these endeavors. There could be combinations of GPUs and NPUs on a single chip. There are AI-optimized field-programming gateways.

There are neuromorphic chips that mimic CNS and ANS. These could be used in robotics and complex sensor networks.

India has a talent pool of STEM graduates. They could be leveraged to maintain our competitive edge in AI space. The government is planning to have conducive infrastructure — a cluster of 25000 GPUs. AI hardware is a promising field.