Covering Disruptive Technology Powering Business in The Digital Age

Written by: Martin Dale Bolima, Tech Journalist, AOPG.

There is no doubt about it: 2023 was the year of Artificial Intelligence (AI).

It was also the year of NVIDIA, the world’s leading manufacturer of Graphics Processing Units (GPU).

And AI and NVIDIA appear poised to grow more in 2024—possibly beyond.

Recently released reports show NVIDIA grew its revenue from USD $26.97 billion in 2022 to USD $60.92 billion in 2023, marking an unheard-of 126% increase. As a result, its net income rose from USD $10.02 billion in 2022 to USD $29.76 billion in 2023.

NVIDIA’s fourth-quarter performance alone, which concluded on the 28th of January, is the kind companies can only wish for, as the company’s profits for 2023’s final three months rose from USD $1.4 billion in Q4 of 2022 to USD $12.3 billion.  That is a whopping 769% increase from the year before and punctuated a particularly robust fiscal year for the chipmaker extraordinaire.

AI’s Wins Are NVIDIA’s Gains

Much of this meteoric rise comes down to the world’s fascination with AI, particularly its entry into the mainstream through generative AI. In short, the use of AI has grown considerably, and this has led to an increase in demand for NVIDIA’s GPUs.

“Accelerated computing and generative AI have hit the tipping point,” said NVIDIA Founder and CEO Jensen Huang in a statement. “Demand is surging worldwide across companies, industries and nations.”

That demand, if the numbers are any indication, is sky-high, to say the least. And rightfully so.

NVIDIA’s GPUs are technically suited for AI’s immense computing needs because they can perform technical calculations faster than traditional CPUs, while also being more energy-efficient and cost-effective. Remember, AI at its core is just a series of blazing-fast mathematical calculations, with GPUs enabling these high-speed computations with its numerous cores, which act like tiny, supercharged calculators.

This is the reason NVIDIA GPUs work the best for AI training and inference, as well as for other applications that require accelerated computing.

“GPUs are the dominant computing platform for accelerating machine learning workloads, and most (if not all) of the biggest models over the last five years have been trained on GPUs … [they have] thereby centrally contributed to the recent progress in AI,” research institute Epoch explained in a report on GPU price and performance.

At the Top and Staying There for the Time Being

Little wonder then that more than 40,000 enterprises worldwide are using NVIDIA GPUs for their AI and accelerated computing needs regardless of industry and purpose. The reason for this is actually quite simple: At the moment, NVIDIA is arguably the best in the world when it comes to making GPUs.

NVIDIA is also unmatched in terms of productivity, accounting for approximately 70% of AI semiconductor sales and leaving competitors like Intel in the proverbial dust. Now, competition is on the way, with Meta, Amazon, and a handful of others, starting to make their own chips. However, it does not appear any company is positioned to topple NVIDIA at the top of the AI space—or even eat away at its humongous share of the pie.

Then again, the law of averages dictates that what comes up must come down, and AI could very well follow that trajectory. But, from all indications, it seems it won’t be happening any time soon.

Forrester, for instance, predicts generative AI will have more vital enterprise use cases moving forward, while Progress expects “more enterprises [will] make AI an integral part of their digital experiences”—even as “those who are unable to do so risk falling behind the competition.” HubSpot and Qlik are expecting bigger, brighter things from AI as well, with the former forecasting more businesses will make the AI leap this 2024 and the latter finding out that excitement for generative AI remains high.

In short, AI will continue to thrive for the foreseeable future, and this success extends to NVIDIA as well.

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