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Tuesday, October 7, 2025

Uh Oh: Big AI Circular Deals

So now we have a new wrinkle to add to the “potential AI bubble” thesis: circular deals between AI infra suppliers (chips and compute platforms) and models.

It has been 25 years since that “problem” was evident. But that is a long enough time that new investors will not have lived through the aftermath of a market meltdown such circular deals contributed to creating.

Investors during the dot-com era were burned, in part, by vendor financing and circular deals where firms passed funds back and forth to prop up their businesses. One example was capacity supplier A buying X amount of capacity from carrier B, while B purchased the same amount of capacity from A.

Under “normal” circumstances that is just business as usual, since no single capacity supplier has a network that covers 100 percent of the locations its customers might need to reach.

The problem was simply that both A and B were able to show some “revenue” on their books (capacity sales) that were essentially fictitious. The net impact was zero.

Such “circular deals” now are a feature of artificial intelligence investments. Nvidia’s partnership with OpenAI, wherein Nvidia can invest up to $100 billion in the firm over time, is one example.

So are deals such as the deal between OpenAI, Oracle, and Nvidia to support the "Stargate" data center project.

This deal involves OpenAI securing computing power from Oracle, which in turn purchases billions of dollars worth of Nvidia's AI chips, while Nvidia invests directly in OpenAI.



source: Liberty's Highlights

Most recently, OpenAI struck a partnership with Advanced Micro Devices AMD in which OpenAI gets warrants in AMD’s common shares representing potentially 10-percent ownership of AMD, while OpenAI pledges to buy six gigawatts worth of AMD processors.

Nvidia’s partnership and investment with CoreWeave CRWV also is circular. CoreWeave funded some debt using Nvidia’s GPUs as collateral. Nvidia owns shares of CoreWeave. Nvidia also struck a deal to use any of CoreWeave’s excess capacity through 2032.

The AI circular deals issue creates a potential problem: an artificial ecosystem where large AI firms receive investments from major suppliers, who in turn receive massive orders from the AI firm, masking the true source of demand and inflating stock prices accordingly.

That isn’t to say there is an immediate problem, but the risk increases if revenue growth does not match the valuations currently used to support the deals.

Monday, September 29, 2025

AI Might Not Diminish Critical Thinking, But Vested Interests Often Do

One sometimes hear it argued that fewer homes will "get internet" because of changes to Broadband Equity, Access, and Deployment Program rule changes. One also hears arguments that increased use of artificial intelligence will reduce critical thinking skills. 


Sometimes those arguments are highly questionable. There are other reasons why reality, truthfulness or factuality can be challenged, and it has nothing to do with human critical thinking or using AI. Instead, the issue is vested economic interest. 


Advocates for local or state government, for example, have a vested interest in increasing the share of federal resources they can deploy to solve problems. And sometimes they have vested interests in particular ways of solving problems. 


Consider arguments for how to bring better home broadband services to rural areas. For decades, the preference has been for a particular solution, namely optical fiber to the home, with opposition to using other arguably more-affordable and immediately-deployable solutions including satellite service and using mobile networks rather than cabled networks. 


Nobody disagrees that optical fiber to the home is the most “future proof” solution, providing it is economically feasible. The problem is that feasibility often is precisely the issue. 


FTTH Deployment Environment

Typical Homes Passed per Mile

Cost per Mile (All-In)*

Cost per Location (Homes Passed)

Key Cost Drivers

Urban (High Density)

80 – 150+

$50,000 – $100,000

$500 – $1,200

Shorter drops, existing duct/conduit, shared trenching, many users per mile

Suburban (Moderate Density)

30 – 70

$40,000 – $80,000

$1,200 – $2,500

Mix of aerial and buried, moderate trenching cost, fewer homes per mile

Rural (Low Density)

5 – 20

$25,000 – $60,000

$3,000 – $10,000+

Long distances, expensive trenching, new poles/conduit, very few users per mile


Very-rural areas might require investment so high no payback is possible. 


That is the reason a rational argument can be made that FTTH should not be built “everywhere,” and that feasible solutions must include satellite or mobile network access. The argument that “work from home” is not possible unless FTTH is deployed is almost always false. 


I have “worked from home, full time” on connections including symmetrical gigabit per second broadband and on connections offering less than 100 Mbps downstream and single digits upstream. My work has never been adversely affected. 


To be sure, my work does not routinely involve upgrading large files on a sustained basis. But most of us do not require a home-based server role, do not create long-form 4K video content all day and need to upload those files continually. 


So if it is said that changes to BEAD rules mean “fewer households will get high speed internet,” the statement is misleading or false. Fewer households might get internet access using FTTH, but that does not mean they will not get internet. And whether such access is “high speed” or not depends on the definitions we choose to use. 


Beyond that, “high speed” might not actually provide any user-perceivable advantage beyond a few hundred megabits per second in the downstream direction. Whether it makes any difference in the upstream direction might be a more-relevant issue, but even there, actual users might not find their work from home impeded. 


We sometimes forget that society has any number of pressing problems to be solved, and internet access is just one of those problems. Investments we make in any area have opportunity costs: we cannot spend the money to solve additional problems. 


Any engineering problem involves choices. Any allocation of societal resources likewise requires choices. Those choices have consequences. 


It is a perfectly logical and appropriate issue to suggest that serving more people, right now,  is a value as great as serving them with a particular solution or capability. Likewise, being efficient in the use of public resources also is a value we tend to believe makes sense. Virtually nobody ever advocates “waste, fraud and abuse.” 


But as a practical matter, it might well be a waste of scarce resources to insist on one particular solution for all home broadband requirements, when other workable solutions exist. 


For every public purpose there are corresponding private interests. Critical thinking might be said to aid decision making when scarce resources must be committed. And that critical thinking might include weighing claims that certain approaches mean “fewer homes will get internet,” when the truth is that the claim only means “fewer homes will get internet using FTTH:

  • in areas where other providers already exist

  • where there are locations that might not actually require access (an area might have business users but no home users)

  • there are other reasons why subsidized service will still be available

  • In areas too expensive to serve using FTTH.


In our justified zeal to ensure that critical thinking skills are not diminished by AI, we should not forget that critical thinking skills often are ignored when vested interests interpret reality in ways that serve those interests.


Thursday, July 10, 2025

Agentic AI Should Change Computing Infrastructure: Issue is How Much

Agentic artificial intelligence, eventually featuring teams of autonomous agents working in concert, should have some obvious impact on computing infrastructure. 


Chips will shift further in the direction of custom silicon. There will be more need for low-latency networking; more local or edge processing in addition to remote processing; more parallel and dynamic context to processing; distributed and fault-tolerant processing; more access to distributed databases. 


Specialized hardware (graphics processing units and field programmable gate arrays); more orchestration and more security also will be needed. Think perhaps of swarms of autonomous drones that have to work together, for example. 


In general, we will need “more:” more energy; more chips; more networking; more processing; more interworking and collaboration between autonomous systems. 


So how does that look for a firm such as Lumen Technologies, as a supplier of networking? Perhaps nobody doubts that “more” capacity will be needed, and might be needed in some different locations. 


The issue might be “how much” AI networking requirements actually change market demand, aside from the obvious “more capacity” that is continually needed. 


For starters, Lumen is doubling its intercity fiber mileage; upgrading bandwidth to 100 Gbps and 400 Gbps, using self-provisioning for enterprise customers, with plans to upgrade to 1.2 Tbps to 1.6 Tbps. 


Lumen also is building private networks that connect data centers owned by hyperscalers. But it might be the change in where capacity is needed that will change most. For some time, networking capacity has been driven both by the need to interconnect data centers and the need to make more bandwidth available in the access network so end users are connected with sufficient bandwidth and low-latency services. 


Agentic AI does not necessarily change that situation. Data center interconnection will drive developments in the network backbone. And AI used by edge devices will continue to rely on “on the device” local processing. But requirements for more edge processing in addition to “on the device” will likely mean more regional data center computing and therefore more bandwidth of a regional nature. 


Whether peer-to-peer requirements lead to more meshy architectures remains to be seen. But to some extent agentic AI simply continues other trends such as needs for more symmetrical bandwidth in the access network. As upstream bandwidth became more important as users started routinely uploading images and video, so agentic AI will additionally create more need for bidirectional capacity as local processors and actions combine with web services, software as a service platforms and application programming interfaces.


Barring a big change, such as Lumen somehow divesting its entire local telecom business, to become a latter-day Level 3 Communications capacity supplier, AI-driven requirements might be more incremental than disruptive.


As a financial matter, a Lumen that is a pure-play capacity provider might have 70 percent of present revenue, but a higher valuation. Some believe that could result in a Lumen valuation that is up to double what the firm presently commands, assuming "flawless execution" and probably also hinging on how the debt burden gets distributed.

Sunday, April 6, 2025

Fast Food Restaurants Might be Among the Few Firms Able to Measure AI Revenue Upside

Move over, “digital transformation.” Now we have "AI transformation," which  refers to the integration of artificial intelligence into business processes to improve efficiency, decision-making, and innovation.


As a practical matter, AI transformation is likely to be hard to measure and might not happen “rapidly,” as whole business processes might have to be redesigned. On the other hand, it might be easier to illustrate how “AI transformation” can affect some processes in a measurable way. 


McDonald's wanted to improve its drive-thru experience, boost sales through personalized recommendations, and optimize restaurant operations.


CompanyAI ImplementationResults/ImpactYear
McDonald'sDynamic Yield acquisition1-2% increase in average check size in test locations2019-2020
StarbucksDeep Brew3% increase in same-store sales2020-2021
KFCFace-scanning kiosks (China) recognize cusotmers, suggest ordersUp to 27% increased average transaction average transaction size for repeat customers2019
Domino'sDOM AI ordering assistant20% higher conversion rates with personalization2021
ChipotleChippy AI system15% increase in add-on items2022
Sonic Drive-InAI-powered digital menu5.9% increase in promoted-item sales2021
Wendy'sAI-powered drive through6% increase in average check size2022-2023
Burger KingGuest Track AI1.5-3% increase in average check size2021
Taco BellDigital kiosks with AI20% higher average order value2022
Dunkin' Mobile appuses AI7.4% increase in app order value2022-2023
Pizza HutHot Spots3.5% increase in add-on items2021
Panera BreadAI-powered loyalty program8% increase in frequency2022
WingstopDigital platform with AI13.5% higher average transaction2023
Shake ShackAI-powered kiosks18% higher average check2022

McDonald's in 2019 began using Dynamic Yield, an AI-powered personalization platform owned by Mastercard. McDonalds then used it to change digital drive-through menus based on weather, time of day, popular items, and current restaurant traffic.


On a hot day, the menu might prioritize cold drinks; during the morning rush, breakfast combos might be featured. 


In the kitchen, McDonald’s added AI models and sensors (to monitor equipment health)  predict demand for food items, optimize kitchen prep times, reduce waste and limit equipment downtime


The firm also adopted AI-driven forecasting, to  help improve inventory management, reduce food shortages and overstocking.


Other fast food restaurants are doing likewise. Still, “transformation” is more a goal and a process, rather than an easily-quantifiable outcome. 


Saturday, April 5, 2025

Embodied AI (Robots) Likely Key to Some Onshoring of U.S. Manufacturing

It is hard to avoid the conclusion that artificial intelligence, in the the form of embodied robots, will be an important part of the business case if manufacturing facilities return to the United States as part of restoring policies and firm responses, jobs will indeed be created, but not at the scale of the pre-offshoring era, it is reasonable to predict. 

Automation, particularly robots using artificial intelligence, likely will handle much of the repetitive, labor-intensive work. 


Study/Source

Estimated Job Creation

Role of Automation

Key Insights

Forbes (2025)

Hyundai's $20 billion investment expected to create 1,500 jobs in Louisiana

Automation is a major factor in reducing traditional manufacturing jobs.

Manufacturing production is high, but job creation is modest due to automation replacing manual labor.

Davron (2024)

Reshoring creates advanced manufacturing jobs requiring higher skills and wages

Advanced manufacturing relies heavily on technology, reducing reliance on manual labor.

Reshoring fosters innovation but requires a skilled workforce trained for automated processes.

Business Insider (2024)

Reshoring could add $10 trillion to the economy over the next decade

High-tech sectors benefit most, integrating automation for efficiency.

Automation is central to reshoring efforts, enhancing productivity but limiting traditional job growth.

Christian Science Monitor (2025)

AI-driven factories may add slightly more jobs than they destroy

Factories integrate AI and robotics to increase efficiency and resilience.

Human roles shift toward managing robots and AI rather than performing manual tasks.

Shoplogix (2023)

Robotics create new roles like technicians and engineers but displace manual labor jobs

Robots perform repetitive tasks faster and more accurately than humans.

Upskilling is essential as traditional roles are replaced by tech-focused positions.

LinkedIn (2025)

Manufacturing output increased 15% since 2020, employment rose only 3%

Automation reduces factory jobs while creating opportunities in high-tech roles.

Reshoring with automation boosts productivity but limits job creation in traditional sectors.



Where an existing garment factory presently operating in Southeast Asia employs X workers, a repatriated operation in the United States might require perhaps 10 percent to 20 percent of those workers. Recall that the reason such facilities moved from U.S. domestic locations to off shore is precisely lower labor rates. 


Assuming higher U.S. wage rates, the only way the economics would work is if far fewer workers were required. 


Study/Analysis

Source

Key Findings on Job Increases

Automation Consideration

Date

Reshoring Initiative Report

Reshoring Initiative

Estimated 1.6 million jobs reshored from 2010-2022, with potential for more if trends continue.

Notes automation reduces job counts; 2022 data shows 364,000 jobs added, but robotics limits scale vs. past.

2022

Oxford Economics:  How Robots Change the World

Oxford Economics

Robots could displace 20 million global manufacturing jobs by 2030, but reshoring may add some back.

Predicts automation will cap U.S. job gains; historical 1.6 jobs lost per robot suggests fewer net gains.

2019

MIT: Robots and Jobs

Acemoglu and Restrepo (NBER)

Between 1990-2007, 1 robot per 1,000 workers reduced employment by 6 workers locally.

Automation in reshored facilities could mean 50-70% fewer jobs than offshored totals due to robot density.

2017

Ball State University:  Manufacturing Study

Center for Business and Economic Research

U.S. lost 5.8 million manufacturing jobs (1980-2016), mostly to productivity automation, not trade.

Suggests reshoring creates high-skill jobs (e.g., technicians), but far fewer than original low-skill positions.

2017

McKinsey Global Institute: Future of Work

McKinsey

Automation could displace 16-20 million U.S. jobs by 2030, but reshoring may offset some losses.

Highlights that returning facilities will lean on robots/AI, creating 10-20% of original job numbers.

2017

ITIF: Robotics and Production

Information Technology and Innovation Foundation

Robotics boosts productivity, potentially adding manufacturing jobs in developed nations.

Job growth tied to engineers/tech roles; traditional labor replaced by robots, reducing total job count.

2019

Brookings: Automation and Jobs

Brookings Institution

Automation offsets job losses from trade, but reshoring impact limited by tech adoption.

Estimates 100-150 jobs per large reshored factory, vs. 500-1,000 historically, due to automated processes.

2015, 2022


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