Right now, the world is fixated on Nvidia’s dominant position in the market, but it’s important to delve into this a bit further. Nvidia is clearly the.
Why it matters: Depending on who you ask the market for AI semiconductors is estimated to be somewhere between a few billion and infinity dollars. We are firmly in the realm of high expectations when it comes to the category, and determining more precise market size estimates is crucial for the large group of people making investment decisions in the coming year.
Right now, the world is fixated on Nvidia’s dominant position in the market, but it’s important to delve into this a bit further. Nvidia is clearly the leader in the market for training chips, but that only makes up about 10% to 20% of the demand for AI chips. There is a considerably larger market for inference chips, which interpret trained models and respond to user queries. This segment is much bigger, and no single entity, not even Nvidia, has a lock on this market.
Further, we need to break down the market. Users will require inference processing in both edge and cloud environments. Cloud inference will be contingent on data center demand. The total market for data center semiconductors today stands at approximately $50 billion (not counting memory, which admittedly is a significant exclusion). This inference market is not only large but also quite fragmented.
Editor’s Note:
Guest author Jonathan Goldberg is the founder of D2D Advisory, a multi-functional consulting firm. Jonathan has developed growth strategies and alliances for companies in the mobile, networking, gaming, and software industries.
Nvidia arguably has a large share of this already, likely the largest, given that a substantial amount of AI work is conducted on GPUs. AMD is also targeting this market, but they trail significantly behind Nvidia.
