OpenAI Explores Making AI Chips, Evaluates Acquisition Target Amid Shortage
OpenAI, the renowned artificial intelligence (AI) company responsible for creating ChatGPT, is currently exploring the possibility of developing its own AI chips. It has even gone as far as evaluating a potential acquisition target to tackle the shortage of advanced processors required for running its applications. Recent internal discussions indicate that OpenAI has been actively seeking solutions to address the scarcity of expensive AI chips.
The options being considered by OpenAI include building its own AI chip, collaborating more closely with chipmakers like Nvidia, and diversifying its supply chain beyond Nvidia. While the company has yet to make a final decision, CEO Sam Altman has made increasing their AI chip inventory a top priority. Altman has expressed concerns regarding the scarcity of graphics processing units (GPUs), which are primarily supplied by Nvidia, a company that controls over 80% of the global market for AI chips.
OpenAI’s efforts to acquire more chips are driven by two main concerns: the shortage of advanced processors necessary to power its software and the exorbitant costs associated with running the required hardware. To date, OpenAI has relied on Microsoft’s supercomputer, which incorporates 10,000 Nvidia GPUs, for the development of its generative AI technologies. However, the operational expenses of running ChatGPT have become increasingly burdensome. An analysis conducted by Bernstein analyst Stacy Rasgon reveals that each query on ChatGPT costs approximately 4 cents. If ChatGPT queries were to reach a tenth of the scale of Google search, it would require an initial investment of about $48.1 billion worth of GPUs and an additional $16 billion worth of chips annually to sustain its operations.
If OpenAI proceeds with the development of custom AI chips, it would join a select group of tech giants such as Google and Amazon who have taken control over chip design, recognizing the critical role these chips play in their businesses. However, building custom chips necessitates a significant strategic initiative and would entail substantial investments amounting to hundreds of millions of dollars annually. Success is not guaranteed, even with the allocation of adequate resources.
Alternatively, OpenAI is considering the possibility of acquiring a chip company to expedite the process of developing its own chip, much like Amazon’s acquisition of Annapurna Labs in 2015. One source familiar with OpenAI’s plans revealed that the company has conducted due diligence on a potential acquisition target, although the identity of this company remains undisclosed.
Regardless of whether OpenAI pursues the development of custom chips or engages in an acquisition, such endeavors typically span several years. During this transitional period, OpenAI would still rely on commercial providers like Nvidia and Advanced Micro Devices to meet its chip requirements. It is worth noting that other tech companies that have ventured into building their own processors have encountered challenges. Meta, for instance, faced issues with its custom chip development, resulting in the abandonment of some AI chips. The organization is now working on a new chip designed for various AI tasks.
OpenAI’s primary backer, Microsoft, also reportedly has plans to develop a custom AI chip, which OpenAI is currently testing. These plans could potentially indicate a further separation between the two companies.
The demand for specialized AI chips has soared since the launch of ChatGPT. These AI accelerators are essential for training and operating the latest generative AI technology. However, only a few chipmakers, like Nvidia, produce viable AI chips, thereby dominating the market.
In conclusion, OpenAI’s exploration of creating its own AI chips and evaluating potential acquisition targets reflects its determination to address the current shortage of advanced processors. While the company has yet to make a final decision, the development of custom chips or an acquisition represents a significant strategic initiative that could reshape OpenAI’s future. Despite the challenges associated with such endeavors, they offer the potential to enhance operational efficiency and reduce costs.
