Is Micron the new Nvidia?

Alphabet’s latest breakthrough in generative AI memory efficiency has triggered a sharp sell-off across the memory chip sector, with Micron Technology among the hardest hit. The move challenges the prior expectation that AI memory capacity would remain in supply constraint for years, keeping memory prices elevated.

Alphabet’s TurboQuant cuts AI memory needs

Generative AI models require large memory capacity to access training data and prior conversations as models are trained on increasing volumes of information. Alphabet describes the challenge as a “needle in a haystack.”

Alphabet’s TurboQuant algorithm is designed to reduce the amount of memory needed by generative AI models by six times. The article links the announcement to a broad decline in memory-related stocks, arguing that investors are reacting to the possibility that AI hyperscalers may need substantially less memory than before.

Market reaction spreads to Micron, Sandisk and SK Hynix

Since the paper’s publication on March 24, Micron’s stock is down nearly 20%, aligning with the sell-off seen in its peer, Sandisk. The article also notes that other leading memory providers, including SK Hynix, were affected.

Because the algorithm was open-sourced, the article says competitors can access it, raising fears that AI companies could integrate the approach quickly and reduce memory demand in the near term.

Supply-demand outlook and the Jevons Paradox

The article cautions that the market’s assumption may be too broad. It highlights that memory has been a limiting factor for AI models, and that Micron has been able to fulfill only about half to two-thirds of customer orders. It also points to Micron’s projection that the high-bandwidth memory market—primarily used for AI—would grow from $35 billion to $100 billion from 2025 to 2028.

Even if AI systems become more memory-efficient, the article argues that prices may not fall automatically. It cites the Jevons Paradox: when something becomes cheaper or more efficient, demand can rise because it becomes more accessible. Applied to memory chips, the article suggests demand could increase if AI improves its ability to use memory more effectively, potentially keeping the sector’s pricing and supply dynamics unchanged.

Micron performance and guidance

The article says Micron has faced a bearish market sentiment since its latest earnings reports and that shares are down 30% since then. It also includes Micron’s revenue guidance and recent quarterly figures: revenue is guided to rise to $33.5 billion, up from $23.9 billion in its latest quarter, and $13.6 billion in the quarter before that.

What investors are watching next

The article recommends that investors avoid rushing into Micron immediately while the TurboQuant news is still being digested. It suggests monitoring consumer memory prices—specifically RAM stick prices—to see whether they begin to fall. If prices decline, the article says it could indicate falling product prices for Micron. If prices remain elevated, it would suggest the memory supply constraint is still active and that Jevons Paradox dynamics may be at work.

Bottom line

The article characterizes TurboQuant as a significant development, but argues that AI companies may adapt by using freed-up memory capacity differently, potentially sustaining elevated memory chip demand. It concludes that Micron could still be a smart buy, though timing may depend on whether memory prices start to ease.