Spiking demand for AI chips could lead to global revenue of US$53bn this year
However, there are certain individuals aiming to have a share of the success, and a growing number of enterprises such as AMD are striving to establish a position and gradually diminish Nvidia's prevailing position. (Photo credit: MANDEL NGAN / AFP)
In a recent post, we discussed Nvidia Corp and its significant contribution to the current AI chip market. It is evident that AI heavily relies on substantial computational capabilities, resulting in a surge in demand for semiconductors, particularly with the emergence of ChatGPT and other generative AI services. This increased demand for AI chips presents a favorable situation for Nvidia as there is now a greater need for their specialized chips.
Nvidia has been utilizing its AI chips, also called graphics processing units (GPUs), to train AI models such as ChatGPT and generate query results. These top-notch GPUs are currently facing a significant shortage due to the overwhelming demand, despite the fact that shortages in other chip categories are starting to improve.
However, there are those who desire a share of the market, and a growing number of companies like AMD are striving to establish a position and gradually reduce Nvidia's control. In fact, numerous startups have at different times asserted their superiority over specific Nvidia products when it comes to certain tasks, such as the training of extensive language models that enable chatbots like ChatGPT and other generative AI systems to generate text and images resembling human-like quality.
However, researchers in artificial intelligence as well as the emerging companies that are transforming their research into marketable products, predominantly favor Nvidia's technology. As a result, the AI chips market is currently the most thriving segment within the technology industry. The demand is so high that Gartner has predicted a lucrative revenue potential of $53.4 billion for the semiconductor industry solely from the sale of AI workload processors.
According to the most recent prediction made by Gartner, there has been a notable rise of 20.9% compared to the previous year. "The advancements in generative AI and the growing utilization of various AI-driven applications in data centers, edge infrastructure, and endpoint devices necessitate the implementation of top-notch graphics processing units (GPUs) and enhanced semiconductor devices," affirmed Alan Priestley, Gartner's VP Analyst.
According to predictions, the revenue generated from AI chips is expected to more than increase twofold by the year 2027.
Priestley stated that this is propelling the creation and implementation of AI chips. The AI chips industry is so promising that Gartner even forecasts a continuous and significant growth in revenue, with a projected increase of 25.6% to reach US$67.1 billion in 2024. Gartner highlighted that by 2027, the revenue from AI chips is expected to surpass the market size in 2023 and reach a staggering US$119.4 billion.
What Drives AI Chip Market?
It is bound to happen that numerous industries and IT entities will integrate AI GPUs into their systems as AI-driven tasks in the business realm advance. In the market for consumer electronics, analysts from Gartner predict that the worth of AI-capable application processors employed in devices will reach $1.2 billion by the conclusion of 2023, a significant increase from $558 million in 2022.
According to Gartner, there is an anticipation of high profits in the industry throughout the current year as well as the following one.
In addition, there will be a rising demand for streamlined and improved designs to assist in the affordable implementation of AI-related tasks, leading to a surge in the usage of specially crafted AI processors. This trend is particularly evident in Gartner's recent study, in which 45% of the surveyed executive leaders, out of a sample size of over 2,500, expressed that the widespread attention received by ChatGPT has compelled them to amplify their investments in AI.
According to Priestley, numerous companies will opt for custom AI chips instead of the prevailing discrete GPUs, which are commonly used in a variety of AI tasks, particularly those involving generative AI methods.
The artificial intelligence community absolutely adores NVIDIA's GPUs.
The rise of Generative AI is causing a surge in the need for powerful computing systems for both creating and implementing the technology. This has resulted in vendors who supply high-performance GPU-driven systems and networking equipment experiencing substantial short-term advantages. Looking towards the future, as hyperscalers seek more efficient and affordable methods of deploying these applications, Gartner predicts a rise in the utilization of specially designed AI chips.
Just a friendly reminder, the upcoming section is a blog post written by Dashveenjit Kaur, whose Twitter handle is @DashveenjitK.
Dashveen contributes to Tech Wire Asia and TechHQ, offering insightful analysis on the dynamic realm of technology within the business landscape. Prior to this, she covered the energetic political scene and stock market in Malaysia firsthand.
