Nvidia is preparing for the AI era after GPUs, reportedly hiring ASIC engineers to compete with Broadcom and Marvell.
Nvidia is hiring 1,000 engineers in Taiwan to enhance its ASIC expertise.
Nvidia, known for its leadership in AI and GPU technologies, has decided to venture into the application-specific integrated circuit (ASIC) market to address growing competition and changes in semiconductor design for artificial intelligence. The demand for GPUs has significantly increased, driven by the rise of generative AI and large language models (LLMs). In a statement made in 2024, Nvidia's CEO, Jensen Huang, announced that the company plans to hire 1,000 engineers in Taiwan.
Recently, Nvidia has created a new ASIC department and is seeking talent to integrate into it. While Nvidia's H-series GPUs, optimized for AI learning tasks, have been widely used in training AI models, the AI semiconductor market is transitioning toward inference chips, such as ASICs. This shift is due to the need for chips designed for real-world AI applications, such as large language models and generative AI. Unlike GPUs, ASICs offer greater efficiency in inference tasks and are also useful for cryptocurrency mining.
According to recent studies, the market for AI inference chips is expected to grow from a valuation of $15.8 billion in 2023 to $90.6 billion by 2030. Tech companies like Google have already adopted custom ASIC designs, such as their "Trillium" AI chip, which is set to be released to the public in December 2024.
The trend toward custom AI chips has intensified competition among semiconductor giants, leading companies like Broadcom and Marvell to gain relevance and value in the market through collaborations with cloud service providers to develop specialized chips for data centers. To stay at the forefront, Nvidia's new ASIC department focuses on leveraging local expertise, recruiting talent from leading companies such as MediaTek.
