It's been a tough past couple of weeks for Micron Technology and Sandisk shareholders. Both computer memory chipmakers have been outright upended. Blame Google parent Alphabet (GOOG +0.50%)(GOOGL +0.58%), mostly. It introduced a set of algorithms it collectively calls TurboQuant back on March 24, that purport to allow artificial intelligence (AI) computing platforms to handle the same amount of work with just one-sixth the amount of (currently very scarce) physical memory usually needed. The news immediately undermined much of the memory pricing power that's been propping up both of these stocks.
This unveiling, of course, has also worked against several other artificial intelligence infrastructure stocks, many of which were already struggling on concerns that AI in general may not live up to its previously frenzied hype.
Image source: Getty Images.
Not every name in the AI business is going to be hit by Google's revolutionary development, though. Some of them may even benefit simply because AI could become more affordable to more enterprises. Here's a closer look at three of these names.
Qualcomm
Qualcomm's (QCOM +0.99%) time may finally have come.
This is one of those companies that's been on the cusp of AI greatness even before artificial intelligence moved into the mainstream. The latest iterations of its mobile Snapdragon processor are capable of handling AI work. But, so far, the stalwart names in the mobility business -- like Apple and Samsung -- have opted to use their own silicon in their AI-capable mobile devices. Only a handful of laptops purpose-built for on-device AI currently use Snapdragons; interest has been modest. Qualcomm is also working on its own high-efficiency data center processors based on its Snapdragon architecture, although it's trying to break into a business already dominated by Nvidia.
Power-boosted by TurboQuant, though, interest in Qualcomm's proven high-performance mobile processor could soar in a hurry.
NASDAQ: QCOM
Key Data Points
TurboQuant should be capable of working on almost any modern computing hardware. But it may well demonstrate its greatest value on mobile devices, which have inherent memory constraints that don't apply to data centers: namely, size and the cost of memory chips themselves. Large AI models that couldn't effectively operate entirely on a mobile device before now should be able to do so quite well. This is particularly true for single-purpose "edge" computing devices that need to be powerful enough to handle the demands of AI inference, but small enough and cost-effective enough to deploy en masse (think "smart" utility meters, connected cars, or wearables).
The only catch? These processors must still be powerful enough to handle AI workloads autonomously. Qualcomm's Snapdragon fits the bill nicely.
Broadcom
Data center networking specialist Broadcom (AVGO +2.92%) isn't in any serious jeopardy due to Google's TurboQuant. Regardless of how many memory chips you need or don't need to connect every motherboard within a data center, after all, you still need to connect all of these processors into a massive neural network. Indeed, there's an argument to be made that Google's research will not only not hurt demand for data center networking solutions, but may actually enhance it.
Bank of America analyst Wamsi Mohan notes of his recent interview with Sandisk CFO Luis Visoso to discuss the unveiling of Google's new solution, "Mr. Visoso pointed out that [TurboQuant] can improve return on investment of hyperscale capex, and this increased efficiency could, in-turn, cause demand [for AI hardware] to rise." Morgan Stanley's Shawn Kim agrees, explaining in a research note: "Models that need cloud clusters can [now] fit on local hardware, effectively lowering the barrier to deploying AI at scale. More applications become viable, more models remain active and utilization of existing infrastructure improves."
NASDAQ: AVGO
Key Data Points
Obviously, Broadcom isn't the only name in the AI hardware business that stands to benefit from any uptick in total demand driven by lower entry and operating costs. Broadcom is leading the assault on the technology's biggest bottleneck, though (aside from a lack of affordable memory chips). That's not processing power. That's the speed at which all of a data center's computer processors can communicate with one another from different motherboards.
And for what it's worth, Google's flagship Tensor Processing Units (TPUs) are largely designed and manufactured by Broadcom. If would-be AI users specifically want Google's TurboQuant to run on Google hardware, it's ultimately made by Broadcom.
TTM Technologies
Finally, add TTM Technologies (TTMI 4.75%) to your list of stocks that could benefit from Google's AI computing breakthrough.
It's not a household name. In fact, you've probably never even heard of the company. You do, however, likely depend on its products on a regular basis.
See, TTM makes the printed circuit boards -- the flat, (usually) green plates that connect all of the components required to make computers, routers, mobile phone networking equipment, industrial automation controllers, and more. No modern technology would function without circuit boards first bringing all of the technical components together in the right way.
NASDAQ: TTMI
Key Data Points
No, it's not exactly a sexy business, even if it's one that should do well regardless of what's next for the AI industry. All sorts of stuff has some sort of circuit board in it these days, after all, including home appliances, toys, and even smart light bulbs.
And that's an important nuance.
While last year's revenue growth of 19% was impressive, most of 2025's top line of $2.9 billion didn't come from data centers or the networking business; TTM obviously doesn't need the AI industry to continue exploding to do well enough.
Data centers and networking are TTM's fastest-growing businesses, though, which is arguably the chief reason analysts expect similar revenue growth this year as well as next. The thing is, these projections were made before TurboQuant's availability. If Morgan Stanley's Kim and BofA's Mohan are right about TurboQuant creating rather than crimping demand for more artificial intelligence tech, this already solid growth outlook may be underestimating what's actually in store from TTM.
