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Showing posts with label Qualcomm. Show all posts
Showing posts with label Qualcomm. Show all posts

Monday, September 28, 2026

The Qualcomm-Amazon deal - and how Qualcomm and Nvidia fit in Robotics development!

 


On September 8, 2026, Qualcomm announced a multi-generation AI data-center partnership with Amazon/AWS. This is considerably more important than a conventional chip-supply agreement because it gives Qualcomm a credible path into the hyperscale AI market alongside its existing Meta relationship. Qualcomm

What Amazon and Qualcomm are doing

There are really three pieces to the agreement.

1. Custom AI silicon for AWS. Qualcomm and Amazon will jointly develop customized chips for AWS's large-scale AI infrastructure, with a particular emphasis on AI inference—running trained AI models rather than training them. Qualcomm's pitch is power efficiency: generating more AI output per watt, which becomes increasingly important as hyperscalers run into power and cooling constraints. Qualcomm

2. Qualcomm gets into AWS's AI networking infrastructure. This may be almost as interesting as the processors. Qualcomm will provide technology for high-speed optical connectivity, including links extending to 1.6 Tbps and future generations, using its SerDes and optical-DSP technology. In other words, Qualcomm isn't merely trying to sell Amazon an AI processor—it wants silicon inside the networking fabric connecting AI servers and racks. Qualcomm Investor Relations

3. Amazon received warrants tied to potentially enormous purchases. Qualcomm issued Amazon warrants for 25 million QCOM shares at $161.26 per share, representing roughly $4 billion if exercised. Importantly, those warrants vest in stages tied to commercial arrangements and Amazon purchases that could reach $60 billion of Qualcomm server chips and related technology. Reuters

That last point requires some care: this does not mean Qualcomm has booked a guaranteed $60 billion order. The structure gives Amazon incentives as purchases scale toward that amount. Qualcomm's own announcement does not disclose firm unit volumes or a detailed deployment schedule. Qualcomm

Why I think this matters so much for Qualcomm

This reinforces our thesis around QCOM: Qualcomm is evolving from

Smartphones to Edge AI → Physical AI → Data-center AI infrastructure.

And Amazon is now a powerful validation point.

Qualcomm unveiled its Dragonfly data-center portfolio this year, covering CPUs, AI accelerators, custom silicon and connectivity. Meta already agreed to use Qualcomm's Dragonfly C1000 CPUs in next-generation servers. Amazon now adds a second hyperscaler relationship, centered on custom inference silicon and connectivity. Data Center Dynamics

The emerging picture looks something like:

Amazon AWS
↓
Qualcomm custom AI silicon
↓
AI inference
↓
Qualcomm SerDes / optical DSP
↓
1.6T+ data-center networking

That is a dramatically larger addressable market than Qualcomm's traditional Snapdragon handset franchise.

The $60-billion number is especially interesting

For perspective, Reuters reports that Qualcomm is targeting $15 billion of annual data-center chip revenue by 2029. The Amazon arrangement gives some credibility to what previously looked like a very ambitious target. Reuters

The warrant structure also creates unusual alignment. If Qualcomm's technology works well and Amazon dramatically increases purchases, Amazon can become a meaningful Qualcomm shareholder.

There is a downside: if all 25 million warrants ultimately vest and are exercised, existing QCOM shareholders face some dilution. But that dilution would occur in connection with very substantial commercial purchases, so investors need to evaluate the dilution against the revenue generated.

Why Amazon wants Qualcomm

AWS already develops its own silicon—Graviton CPUs, Trainium AI accelerators and Inferentia inference chips. So Amazon isn't abandoning custom silicon and simply buying Qualcomm processors.

Rather, Qualcomm brings intellectual property and engineering expertise in areas Amazon increasingly needs: low-power compute (Robotics), custom silicon, high-speed SerDes, optical DSPs, system integration and inference optimization. Data Center Dynamics

This fits an important change occurring in AI. Training giant models made NVIDIA GPUs indispensable. But as hundreds of millions of users and AI agents continuously run those models, inference becomes an enormous workload of its own.

Qualcomm is effectively betting:

AI inference will eventually dwarf AI training in volume, and electricity efficiency will become one of the industry's most important competitive advantages.

That's precisely where Qualcomm's decades of designing high-performance processors under severe power constraints become relevant.

What it means for the QCOM investment thesis

For someone evaluating Qualcomm primarily as a smartphone-chip company, this agreement changes the picture materially. 

The company now has credible exposure to hyperscale AI compute + custom silicon + AI networking + edge AI + automotive + robotics/physical AI.

The principal risk is execution. Amazon has not guaranteed $60 billion of purchases, NVIDIA remains extraordinarily entrenched, and Qualcomm must prove that Dragonfly/custom silicon can move from design wins into large-scale production revenue.

But Amazon joining Meta as a major hyperscaler relationship makes Qualcomm's data-center ambitions substantially harder to dismiss as merely a roadmap.

For our QCOM thesis specifically, I consider the Amazon agreement one of the most important developments we've seen this year. It strengthens the part of the thesis that had previously been the least proven: Qualcomm becoming a serious AI data-center infrastructure supplier, while the edge/robotics opportunity remains intact.

The Edge Edge!

Qualcomm has an “edge at the edge” because much of the next wave of AI will move out of giant data centres and into physical devices—robots, humanoids, vehicles, drones, industrial machines, PCs and smartphones—where AI must operate locally, instantly and with limited battery power.

This is precisely where Qualcomm has spent decades building expertise: highly power-efficient processors that combine CPU, GPU, NPU/AI acceleration, connectivity, cameras, sensors and real-time processing in compact systems. 

While NVIDIA dominates centralized AI training, Qualcomm's particular opportunity is AI inference at the physical edge, where sending every decision back to the cloud is too slow, expensive or unreliable.

 If Physical AI develops as expected, Qualcomm's competitive advantage could therefore be its ability to put a powerful, energy-efficient “AI brain” directly inside millions of intelligent machines—an “edge at the edge.”

Robotics:

Qualcomm now has several concrete relationships with robotics manufacturers, including humanoid companies. The most significant are Figure and NEURA Robotics, and Qualcomm says its processors are already powering robots from other OEMs including Booster and VinMotion. Qualcomm

The relationships break down like this:

Robotics companyQualcomm relationshipSignificance
Figure AICollaborating to define the next generation of compute architecture for Figure's humanoidsVery important
NEURA RoboticsLong-term strategic collaboration; Dragonwing processors + NEURA humanoids/robotsVery important
Booster RoboticsDragonwing processors already powering humanoid platformsCommercial ecosystem
VinMotionDragonwing processors powering humanoid platformsCommercial ecosystem
KUKA RoboticsDiscussions/collaboration around next-generation robotics solutionsIndustrial robotics opportunity
Advantech / AutoCoreAMR and industrial robotics developmentIndustrial Physical AI
PickNik RoboticsQualcomm agreed this month to acquire it; owns/stewards MoveIt robotics softwareStrategically important

Qualcomm describes the Dragonwing IQ10 as essentially the "brain of the robot"—a processor designed specifically for advanced AMRs and full-sized humanoids. It integrates CPU, NPU/AI acceleration, vision, sensor processing, connectivity and real-time control. Qualcomm

1. Figure is the one I watch most closely

Figure AI and Qualcomm announced in January that they are collaborating on the next generation of compute architecture as Figure scales its humanoid platforms. 

Figure CEO Brett Adcock specifically highlighted Qualcomm's combination of compute performance and energy efficiency as a building block for scaling Figure's humanoids. Qualcomm

This is particularly interesting because Figure is trying to manufacture humanoids at very large scale.

The relationship suggests Qualcomm wants to occupy a position analogous to:

NVIDIA → AI servers

Qualcomm → autonomous robots / Physical AI

It is far too early to say Qualcomm will achieve that position, but that is clearly the strategic direction.

2. NEURA Robotics is an even broader agreement

NEURA Robotics and Qualcomm announced a long-term strategic collaboration in March 2026.

This goes considerably beyond supplying a processor.

They're developing what the companies call a "Brain + Nervous System" reference architecture for robots. Qualcomm supplies Dragonwing compute, AI acceleration, connectivity and software; NEURA contributes the robot hardware and embodied-AI stack. The architecture is intended for robotic arms, AMRs, service robots and humanoids. Qualcomm

That is exactly the type of relationship I'd want to see if the thesis is that Qualcomm becomes a major picks-and-shovels supplier to Physical AI.

3. Qualcomm silicon is already inside humanoid platforms

Qualcomm says its Dragonwing industrial processors already power humanoid robots from Booster Robotics and VinMotion, among other robotics manufacturers. Its newer IQ10 reference-design program also includes NEURA, Booster and VinMotion as early-access ecosystem partners. Qualcomm

So this isn't entirely a 2028–2030 story. There is hardware being developed and deployed now.

4. And Qualcomm just made another very interesting move

Only five days ago—September 23—Qualcomm announced an agreement to acquire PickNik.

PickNik is the longtime steward of MoveIt, one of the most widely used open-source software frameworks for robotic motion planning and manipulation.

Qualcomm intends to integrate MoveIt much more tightly with Dragonwing. That potentially gives Qualcomm both:

Robot hardware compute: Dragonwing
+
Robot software/motion layer:
MoveIt
+
AI inference:
Qualcomm NPU
+
Connectivity:
Wi-Fi/5G/6G
+
Real-time control:
Dragonwing robotics architecture**

That's strategically much more interesting than merely selling chips. Qualcomm

But there are some conspicuous absences

I don't find evidence of announced Qualcomm compute agreements with Tesla Optimus, Boston Dynamics or Apptronik.

For example, Apptronik's disclosed AI relationship is with Google DeepMind; its latest Apollo 2 announcement describes fleets collecting real-world data to develop humanoid AI models in partnership with DeepMind. Apptronik

And I would not assume Tesla is a future Qualcomm customer. Tesla has strong incentives to develop its own Optimus compute architecture.

Why this strengthens the QCOM thesis we've been discussing

This is where our interest in Qualcomm as a Physical AI investment becomes increasingly relevant. Qualcomm is building an actual robotics ecosystem rather than simply claiming that Snapdragon-type processors could someday be used in robots. Qualcomm

And the timing is interesting because Qualcomm's Dragonwing IQ10 can deliver up to 700 TOPS, while supporting as many as 20 cameras plus lidar/radar and real-time control—all designed around relatively power-efficient edge computation. Qualcomm

That potentially puts Qualcomm into three enormous AI markets simultaneously:

Amazon/Meta → Data-center AI

PCs/phones/automotive → Edge AI

Figure/NEURA/Booster/VinMotion → Physical AI & humanoids

That third category was considerably more speculative when we first discussed the "sleeping dragon" QCOM thesis. As of September 2026, it is becoming much more tangible.

Thursday, August 6, 2026

Is this a good time to buy or add to Qualcomm stock? I believe it is "on the EDGE" so to speak!


 I think Qualcomm (NASDAQ: QCOM) is one of the more attractive large-cap AI semiconductor investments at current prices, particularly for an investor with a 2–5 year horizon. Whether it is a "great" buy this week depends on whether you're willing to tolerate near-term volatility after earnings.

Here are the reasons I've been adding shares.

1. The market is still valuing Qualcomm too much like a smartphone company

For years, Qualcomm's fortunes rose and fell with Android handset sales.

That is no longer the whole story.

Today, Qualcomm has meaningful growth businesses in:

  • Automotive
  • AI PCs
  • Industrial IoT
  • Edge AI
  • Data-center inference
  • Networking

Those businesses continue to become a larger percentage of revenue even while handset demand fluctuates. Automotive and AI PC adoption remain important long-term growth drivers.


2. Edge AI may become larger than many investors appreciate

One theme we've discussed several times is that AI won't live exclusively in data centers.

Billions of devices will perform inference locally:

  • laptops
  • robots
  • industrial equipment
  • drones
  • automobiles
  • XR headsets
  • smartphones

This is Qualcomm's specialty.

Unlike Nvidia, whose strength is training enormous AI models, Qualcomm has spent decades designing extremely power-efficient processors.

As AI moves onto devices, Qualcomm's technology becomes increasingly valuable.


3. Snapdragon X is becoming a legitimate Windows competitor

Microsoft's AI PC initiative is only beginning.

Qualcomm's Snapdragon X processors have proven that ARM Windows laptops can offer

  • exceptional battery life
  • strong AI acceleration
  • competitive CPU performance

Adoption won't happen overnight, but if Windows-on-ARM succeeds over the next several years, Qualcomm could become a much larger PC chip supplier than investors currently expect.


4. Automotive is becoming a very large business

My favorite part of the story.

Every modern vehicle is becoming

  • a rolling computer
  • AI platform
  • communications platform
  • autonomous sensing platform

Qualcomm supplies:

  • Digital Cockpit
  • ADAS
  • connectivity
  • infotainment
  • AI processing

Automotive revenue has been one of the company's fastest-growing segments 

and provides diversification away from smartphones.


5. AI infrastructure isn't only GPUs

Most investors think

Nvidia = AI

But AI requires an enormous ecosystem.

Qualcomm participates in:

  • edge inference
  • industrial AI
  • networking
  • enterprise AI
  • automotive AI
  • AI PCs

If inference increasingly shifts from centralized clouds to devices at the edge, 

Qualcomm is well positioned.


6. Recent earnings weren't as bad as the headline suggested

The latest quarter showed:

  • revenue slightly ahead of expectations
  • continued strength in automotive
  • continued expansion in AI PCs

The weakness came primarily from the smartphone business, which remains cyclical. That has weighed on investor sentiment despite progress in newer businesses.


7. Valuation

Compared with many AI leaders:

  • Nvidia
  • AMD
  • Broadcom

Qualcomm generally trades at a lower earnings multiple.

That means investors are paying less for future growth.

If Qualcomm successfully proves it is an AI platform company—not just a handset chip company—the valuation multiple could expand.

That can create two sources of return:

  • earnings growth
  • multiple expansion

Risks

The biggest risks are:

  • prolonged weakness in global smartphone demand
  • slower-than-expected AI PC adoption
  • increasing competition from MediaTek and Apple silicon
  • geopolitical exposure related to China

None of these are trivial, but I don't think they negate the longer-term thesis.


My view

If I were ranking the major AI semiconductor investments today for risk-adjusted upside over the next 2–3 years, my list would look something like:

  1. Nvidia
  2. Qualcomm
  3. Micron
  4. AMD
  5. Broadcom

That ranking reflects my view that Qualcomm still offers a favorable combination of diversified AI exposure, improving end markets, and a valuation that is less demanding than several peers.

Given our investment approach—seeking companies that supply the infrastructure behind AI, robotics, autonomous systems, and edge computing—I think Qualcomm continues to fit well with those themes.

My approach, accumulate gradually rather than make one large purchase. Semiconductor stocks remain volatile after earnings and macro headlines, so scaling in over several buys can reduce timing risk while still increasing exposure to what I believe is a strong long-term opportunity.