OpenAI’s founder, Sam Altman, attended Intel’s inaugural IFS Direct Connect conference on February 20th, where he engaged in a conversation with Intel CEO Pat Gelsinger. This appearance comes shortly after The Wall Street Journal reported Altman’s intention to raise $7 trillion to build his own chip factory, showcasing his ambitions in the semiconductor industry.
The industry has generally expressed skepticism towards Altman’s decision to establish his own chip factory. Semiconductor architect Jim Keller, a legend in the field, even stated that he could achieve the same goal with less than $1 trillion, suggesting that Altman’s approach is unnecessary.
Considering the magnitude of the investment, Altman’s funding requirement is astronomical. The global GDP is approximately $105 trillion annually, and $7 trillion accounts for about 6% of that total. This amount is greater than the combined market capitalization of tech giants like Apple. Additionally, Altman faces a significant gap between his AI background and the semiconductor industry. These factors contribute to the lack of confidence from external observers in Altman’s groundbreaking move.
Why does OpenAI want to venture into chip manufacturing? Will they be left behind if they don’t?
Cheng Shijia, co-founder and CEO of Aikala, pointed out that Altman’s goal is to address his biggest disadvantage, which is cost.
After ChatGPT gained worldwide popularity by the end of 2022, large corporations began actively developing AI language models and related applications. Cloud giants such as Microsoft, Amazon, and Google led the way, and by 2023, most major companies had already launched their own language models. This means that ChatGPT is no longer the only player in the field, and “Altman has realized that these large companies are catching up, and the competition is different from a year ago,” said Cheng Shijia.
If we project into the future when AI productivity tools are more developed, smaller-scale OpenAI will not be able to maintain its leading position solely through AI models like ChatGPT. It will also face difficulties in competing with cloud manufacturers due to the inability to order chips in large quantities and lower costs. Cheng Shijia described this as “Altman’s biggest nightmare.”
He further explained that large cloud providers not only have dedicated teams designing their own AI chips but have also invested in infrastructure such as large-scale data centers. This advantage enables them to lower the cost of computing power, which is essentially chip prices. On the other hand, OpenAI lacks these conditions. “This is why Altman is in a hurry because he knows that the ultimate victory lies in infrastructure.”
Will Altman’s endeavor be successful? Three points analyze why it is viewed skeptically by the outside world.
Altman’s determination to compete with cloud giants may be great, but achieving his goal will not be easy. Rumors suggest that he has approached Taiwan Semiconductor Manufacturing Company (TSMC), Intel, and Samsung for potential collaborations. However, Cheng Shijia believes there are three key factors to consider.
Firstly, the AI landscape is evolving rapidly, and there can be significant differences in technological advancements within a span of one year. “Altman needs to take into account that hardware will continue to progress, and AI software architecture will also change. This is a risk,” he said. Currently, there is still plenty of room for optimization in AI chips. In such a situation, investing heavily in chip manufacturing may lead to irreversible consequences and increase the difficulty of fundraising.
Moreover, Moore’s Law, which describes the doubling of transistors on an integrated circuit every two years, is still ongoing. Although prices may be higher than in the past, there is still a chance for costs to decrease. “It is difficult to say whether investors will be willing to foot the bill at this time,” Cheng Shijia said.
Secondly, Cheng Shijia pointed out that semiconductors have become strategic resources for various countries. When considering building chip factories, geopolitical issues must be taken into account. “TSMC is the result of Taiwanese efforts. Whether it can be replicated in the United States is still uncertain.” Even if Altman successfully raises $7 trillion, questions regarding the location and timing of the factory will remain to be discussed, given the complex political factors involved.
Thirdly, it is rumored that NVIDIA CEO Jensen Huang is preparing to establish an application-specific integrated circuit (ASIC) department. This essentially sends a message to AI giants: “Don’t make your own chips.” Guo Dajing, General Manager of Zhonghua Development and Innovation Accelerator, believes that the semiconductor industry is highly specialized, and building an in-house IC design team is not the most suitable choice. Cheng Shijia also believes that based on the available information, the feasibility of Altman’s plan appears to be very low.
Editor: Lin Meixin