For a long time, storage chips have been a standardized commodity whose market is cyclical. First comes a growth in demand from segments like consumer electronics, then comes a ramp-up of manufacturing capacity by all fabs, next is oversupply once all producers pour huge amounts of interchangeable products onto the market, and then the inevitable bust happens as all manufacturers lower prices to get rid of the excess inventory that has flooded the market.
The AI boom is rapidly changing the picture. For a while, AI hyperscalers have been content to use the standardized storage chips while building out their infrastructure, such as data centers. However, the limitations of these standardized products have come to the fore as the needs of the different AI segments become increasingly complex and specialized.
For example, firms that focus on training large models in the cloud require storage chips with extreme capacity and bandwidth, while edge AI applications require storage chips that meet rigorous temperature tolerance parameters and volume capacity. For storage chips intended to be used in PCs with high AI capabilities, the need is for chips that will strike a balance between power consumption and performance metrics.
The demand scenarios above clearly show that all-purpose or general-use storage chips cannot meet the specific needs of each AI segment, and changes need to be made, fast, so that memory storage chips are customized to address specific markets.
For storage chip makers like Micron, SK Hynix, Samsung, Intel and many others, this reality opens opportunities while also presenting challenges.
The opportunity comes in the form of developing storage chips that meet the stringent needs of each AI segment. The company that can do that will enjoy a near monopoly in the way Nvidia has dominated the global market for GPUs. Companies that manage to produce products tailored for different AI use cases have the chance to be the market leaders and reap the rewards that come with the exploding demand for specialized storage chips.
However, tapping those opportunities isn’t just going to be a matter of flipping a switch during production. New manufacturing architectures have to be developed from scratch so that the storage chips produced are customized to the specific needs of a segment or even a customer.
For decades, storage chips have been standardized and all manufacturers first produced products, then looked for customers to buy them. That will not cut it in the new era of customization. Manufacturers may find themselves involving customers right from the product design stage in order to make exactly what a client needs.
That introduces a risk of making a product that only has one or a few customers. When that market segment bites the dust in the rapidly transforming AI landscape, storage chip makers could find themselves in the unenviable position of having products they can’t sell since the target buyers no longer have a need for them or are out of the market.
The opportunities are massive, but they aren’t without significant hurdles to overcome. Perhaps storage chip makers can look to other firms in the semiconductor industry, such as Taiwan Semiconductor Manufacturing Company Ltd. (NYSE: TSMC), to learn lessons on how to find success in such a complex industry.
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