NVIDIA’s role in Industrial Digital Transformation

NVIDIA has seen explosive growth over the past three years, becoming one of the most talked about players on the global tech scene. It’s important to understand their past, present, and future, especially in terms of how their technology impacts the manufacturing and logistics sectors.

GPU vs. Traditional CPU

NVIDIA’s GPU chip designs are the heart of their business.

In the past, GPUs (Graphic Processing Units) were mainly used for advanced video games. Advanced video games required strong computing power to create interactive visuals. Traditional CPUs (Computer Processing Units) were not robust enough for the task because CPUs do computations serially. GPUs do computations in parallel, exponentially increasing their computing power.

A few years ago, NVIDIA expanded its GPU use cases beyond video gaming. NVIDIA now has 150 SDKS (Software Development Kits) that work directly on their GPUs with specific applications for different industries and utilizations. This expansion is what has fueled the AI boom.

GPU and AI

Because of GPUs’ parallel processing power, coupled with NVIDIA’s proprietary CUDA (Computer Unified Device Architecture) system, NVIDIA GPUs are built to perform machine learning, GenAI (generative AI), and edge computing.

Chances are, if a business is claiming to have AI capabilities, they are using NVIDIA GPUs.

Industrial Manufacturing and Logistics

Many manufacturing and logistics companies are utilizing machine learning, GenAI, and edge computing as part of their digital transformation.

For example, a company may want to implement a computer vision program in their maintenance yard. It’s not possible to transfer all the data to the cloud, have it computed in the cloud, and then have it transferred back to the yard in a realistic fashion. So, the company would run one or two NVIDIA GPUs onsite to do the computing locally.

This example of edge computing is only one example of how manufacturing and logistics companies might use NVIDIA’s GPUs.

NVIDIA’s Valuation and Future

There are concerns that this is a bubble—that companies have gobbled up NVIDIA GPUs with the hopes of creating enormous new value through AI, and that those hopes might not be widely realized.

Another concern is the geopolitical tensions affecting NVIDIA’s GPU manufacturing. TSMC is the company that physically makes the NVIDIA GPU chips. It’s a Taiwanese company that often finds itself in the crosshairs of US and China politics.

These concerns highlight the need for smart, tailored uses of AI by companies. NVIDIA GPUs should always be used in well-designed systems that add real value.