Three stocks of AI ‘enablers’ to consider as Nvidia sets up another surprise

All eyes are on Nvidia Corp. this week — the company will announce its latest quarterly results after the close on Wednesday. It has been dominating the market for graphics processing units (GPUs) being deployed by datacenters for the rollout of artificial intelligence technology.

But during what he expects to be another year dominated by “AI enablers,” Ken Laudan, the portfolio manager of the Buffalo Large Cap Fund BUFEX BUIEX suggests considering three stocks of companies involved in network communications, data storage and power management as additional ways to ride the wave.

The Buffalo Large Cap Fund is rated four stars (out of five) within Morningstar’s “Large Growth” fund category, with a three-year performance ranking in the top 15% among 1,119 funds. Nvidia

NVDA

was the fund’s fifth-largest holding as of Dec. 31, making up 4.6% of the portfolio.

Before looking at Laudan’s three other stock picks, let’s take a look at estimates for Nvidia, updated Monday morning. Sales for the company’s GPUs took off during the middle of last year, so year-over-year comparisons of quarterly numbers are expected to be eyepopping. But analysts working for brokerage firms polled by FactSet expect Nvidia’s sequential growth to slow. Here are estimates for the Wednesday report, with revenue figures in billions.

Estimate for quarter ended 1/29/2024

Quarter ended 10/29/2023

Quarter ended 07/30/2023

Quarter ended 04/30/2023

Quarter ended 01/29/2023

Sales

$20,395

$18,120

$13,507

$7,192

$6,051

Change from year-earlier quarter

237%

206%

101%

-13%

-21%

Change from previous quarter

13%

34%

88%

19%

2%

Earnings per share

$4.59

$3.71

$2.48

$0.82

$0.57

Change from year-earlier quarter

705%

1262%

850%

29%

-52%

Change from previous quarter

24%

50%

202%

44%

110%

Source: FactSet

Nvidia’s quarterly sales are expected to triple from those a year earlier, but to increase “only” 13% from the previous quarter. That would be a slowdown from three previous three quarters’ sequential growth rates.

During an interview with MarketWatch, Laudan said he expected another blowout quarter from Nvidia, with numbers well above the consensus estimates, because “even hyperscalers [among datacenter operators] are buying whatever GPUs they can get.”

Nvidia’s stock has risen 240% over the past year, so it is no surprise to see warnings for investors:

Three more AI stock picks as “enablers” dominate

When Laudan discussed “AI enablers,” he listed well-known names as examples, including Nvidia and Taiwan Semiconductor Manufacturing Co.

TSM

,
as well as the big three cloud services providers — Microsoft Corp.

MSFT

,
Amazon.com Inc.

AMZN

and Alphabet Inc.

GOOGL

.

He said that eventually (maybe in 2025) investors will direct more attention to “AI adapters,” which he described as “software-centric companies that sell a AI large-language model on top of their enterprise or vertical software stock to their clients.” As examples, Laudan cited what he called “the usual suspects,” including Adobe Inc.

ADBE

,
ServiceNow Inc.

NOW

,
Salesforce Inc.

CRM

,
MongoDB Inc.

MDB

and Snowflake Inc.

SNOW

,
adding that “you might even put S&P Global

SPGI

in there.”

But for now, he suggested investors become familiar with three more AI enablers held by the Buffalo Large Cap Fund:

Coherent

Coherent Corp.


COHR

uses optical fibers, made of silicon carbide material, to manufacture various components of devices that need to withstand extreme temperatures. These can include parts used in vehicles and aircraft. But Laudan said he was holding shares of Coherent as a play on the AI build-out.

Coherent has a 60% global market share for optical transceivers, according to Laudan.

“You plug in one of these transceivers in a datacenter into a router or networking switch and it converts the network into optical signals,” he said. He described the transceivers as “a key enabler to improve data transmission among the AI servers” over the next few years.

Laudan estimated that the total addressable market (TAM) for optical transceivers was about $1 billion in 2023, and said Coherent expected the TAM to expand to $6.5 or $7 billion by 2027.

Pure Storage

While most computer users would probably agree that it would be better to rely on flash storage than on hard drives with moving parts, Laudan said ”about 90% of data in the cloud is stored on spinning hard disk drives.”

Pure Storage Inc.

PSTG

brought out its FlashBlade//E product last year — it is a flash storage array designed for commercial use, ”that on a gigabyte basis is the same price has spinning hard drives,” Laudan said. This means the total cost of ownership will be lower than that of spinning hard drives because of flash memory’s greater durability, he said.

“The E product is a 75 terabyte product. They will come out with a 150 this year and a 350 in 2025. So that will drive the price even further down,” he said.

Laudan said datacenters were already deploying the FlashBlade//E, which he described as a “door-opener” to “storage-as-a-service” offered by Pure Storage. This is a consumption-based subscription service which would improve the company’s revenue stream while potentially lowering datacenters’ storage costs even more, he said.

Eaton Electric

Eaton Corp. PLC

ETN

provides power management components for datacenters, aircraft, cars, trucks and machines. These include generators, transformers, switches, cooling systems and battery storage.

With AI requiring so much raw processing power, datacenters will feed a “logarithmic” expansion of demand for electricity, which means a greater need for power management, Laudan said.

He said Eaton was one of the five largest players in the space, and that it was also a major supplier of equipment for electric vehicle charging and for the aerospace industry. He described the company as a “U.S. version” of Schneider Electric SE

SU

,
which is based in France.

Don’t miss: Nvidia is expected to be the best performer in the S&P 500 through 2025, by this measure

Reference

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