NVIDIA: Technological Journey for Dominating the Evolving AI Chips

NVIDIA experienced a technological journey for dominating the AI chips in the 21^st century

Artificial Intelligence and machine learning algorithms are reigning in the tech-driven era with their efficiency through smart machines across the world. Recently, AI hardware is the next-generation computer hardware for these machine learning models. Thus, it has created a massive demand for AI chips that are cheaper and faster to drive the growth and revenue of multiple organizations and industries. Meanwhile, an American multinational technology company known as NVIDIA is popular for designing GPUs (Graphics Processing Units) for gaming units as well as a system on AI chips units for advanced mobile computing and the automotive market. The GPUs of NVIDIA tend to dominate the AI chips and this leads to a technological journey for NVIDIA in dominating the evolving AI chips in this tech-driven cut-throat competitive market.

NVIDIA is focused on better performance and better economics. The company has invented numerous AI chips to bring AI to each and every industry and organization with the help of a comprehensive software suite known as NVIDIA AI Enterprise. Multiple reputed tech giants in the world— AWS, Baidu, Google, Microsoft, and many more have started incorporating the GPU in their data center architectures. The company announced the 8^th generation GPU named A100 GPUs that are based on Ampere architecture, DGX A100 that helps 56 applications to run independently, Grace AI chip will boost Artificial Intelligence as well as self-driving vehicles and many more. But to successfully develop and launch these AI chips and GPUs, NVIDIA has had a technological journey since the beginning of the idea of producing AI chips.

Bill Dally, a Chief Scientist at NVIDIA, and Andrew Ng, one of the popular AI influencers, observed in 2010 that a system required thousands of CPUs to power computers and this could be done with a few GPUs. Bill Dally mentioned that GPUs are specialized for more intense workloads and work better than CPUs to boost Artificial Intelligence models. Bill Dally and Bryan Catanzaro, a leader of deep learning research at NVIDIA, proved that 12 GPUs worked faster and efficiently than CPUs. NVIDIA broke a record in 2019 when its sales of GPUs for data centers reached US$6.7 billion to enhance processing speeds of four top Cloud providers— AWS, Google, Alibaba, and Microsoft Azure. But the challenges start rising in the next few years when the other tech giants and start-ups started producing their own AI chips— Google in 2015, Amazon in 2016, Intel in 2019, and so on. NVIDIA wants to dominate the upcoming market of evolving AI chips due to the increase in the data flow, IoT, and more cutting-edge technologies.

When half of the world was not aware of Artificial Intelligence, NVIDIA discovered the unknown industry of AI chips with smarter GPUs. There have been a few controversies related to its GPUs like some claimed that these GPUs were designed only for graphics in games but not for machine learning, market dominance only lasted for a few years due to utmost careful optimization as well as complicated layers of software and there are plenty more AI chips available in the market that are made of the new architecture. NVIDIA is on a competitive verge to show that NVIDIA GPUs run a bit faster than Google's TPU. Thus, the company has upgraded an in-house supercomputer from 36 DGX to 96 DGX for one version of the benchmark.

There is also a concern from the competitors of NVIDIA that the company is taking control of one of the major designers of AI chips known as ARM. It bid US$40 billion for this British AI chip designer but it created controversies from different countries due to political and national security issues. The market size of Artificial Intelligence chips is predicted to hit US$129 billion by 2025. The competition is intense among NVIDIA and other hi-tech companies because these companies are acquiring numerous AI start-ups to enhance the production of AI chips and launch a new architecture. Nonetheless, NVIDIA is gaining high revenue by being at the top for high-end GPUs to attract potential customers in the AI market.

That being said, NVIDIA remains in a better position and tends to dominate the evolving AI chip market for a long time due to its robust and efficient GPUs as an undisputed leader.