In a strategic move to lessen its dependence on Nvidia, OpenAI is advancing plans to develop its inaugural in-house artificial intelligence (AI) chip, Reuters is reporting.
The company aims to finalize the chip’s design within the next few months and subsequently send it for fabrication to Taiwan Semiconductor Manufacturing Co. (TSMC), utilizing TSMC’s advanced 3-nanometer process technology.
Leading this initiative is Richard Ho, a former Google engineer who played a pivotal role in developing custom AI chips at Alphabet. Since joining OpenAI over a year ago, Ho has expanded his team to approximately 40 members, collaborating closely with Broadcom in the chip’s design phase.
The initial version of this chip is expected to focus primarily on running AI models and will be integrated into OpenAI’s infrastructure on a limited scale. Future iterations are planned to offer enhanced capabilities, reflecting OpenAI’s commitment to advancing its hardware alongside its software innovations.
Currently, Nvidia dominates the AI chip market with an estimated 80% share. However, rising costs and a reliance on a single supplier have prompted companies like OpenAI to explore alternative solutions. By creating its own AI chip, OpenAI aims to strengthen its negotiating position with existing suppliers and reduce potential bottlenecks in its supply chain.
The journey from design to a functional chip, however, is complex and costly. A typical tape-out can cost tens of millions of dollars and requires approximately six months to produce a finished chip. There is also no guarantee that the silicon will function correctly on the first attempt.
In addition to its hardware endeavors, OpenAI is actively expanding its global partnerships. The company recently announced a collaboration with South Korea’s chat app operator Kakao to develop AI products, marking its second significant alliance in Asia within a week.
OpenAI’s CEO, Sam Altman, has also engaged in discussions with leaders from Samsung, SoftBank, and Arm Holdings, exploring opportunities to enhance AI infrastructure and services.
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