No AI "Killer App?" It is to be Expected

It's too early to contemplate an artificial intelligence "killer app." Indeed, some will be tempted to argue there will be lots of killer use cases, and less likely an identifiable killer app.

Indeed, that is characteristic of "general-purpose technologies" that affect whole economies.

GPTs are technologies that have the potential to transform multiple sectors and industries, such as the steam engine, electricity, and the internet. By definition, such technologies affect the entire economy.

Given the broad applicability and versatility of GPTs, it's unlikely that a single killer app would be the primary driver of adoption. Instead, GPTs often enable a wide range of innovative use cases across various industries.

The Internet: enabled e-commerce, online education, remote work, social media, and has affected the entire economy, virtually every industry to some extent and life in general.

Other compuing technologies which are not GPTs, also by definition, have some “killer app” or “killer use case” that drove mass adoption. The spreadsheet drove business adoption of personal computers, for financial modeling. Graphic design software (and desktop publishing) arguably propelled adoption of the Macintosh.

Word processing arguably drove widespread adoption of PCs by non-financial personnel. The web browser and World Wide Web’s multimedia capabilities spurred mass adoption of all sorts of visual, auditory and interactive applications (aided by broadband, which made visual content possible). 

Computing “in your pocket or purse” drove smartphone adoption beyond business users whose killer app was mobile email access. 

Year	Platform	Killer App	Description
1979	Apple II	VisiCalc	Spreadsheet software that revolutionized personal finance and business analysis.
1983	IBM PC	Lotus 1-2-3	Powerful spreadsheet software that further popularized the PC.
1985	Macintosh	MacPaint and MacDraw	Graphic design software that showcased the intuitive user interface of the Mac.
1987	IBM PC	Microsoft Word for Windows	Word processor that became the industry standard for document creation.
1990	Various	World Wide Web	The interconnected network of web pages that transformed information access.
1995	Windows 95	Microsoft Internet Explorer	Web browser that popularized the internet for the masses.
1998	iPod	iTunes	Digital music player and media store that revolutionized the music industry.
2007	iPhone	App Store	Marketplace for mobile apps that transformed the smartphone industry.
2009	Various	Google Chrome	Web browser that focused on speed and simplicity.
2010	iPad	Various apps	Tablet computer that popularized e-books, gaming, and productivity apps.
2016	Various	Pokémon Go	Augmented reality game that brought the world outside into the digital realm.
2020	Various	Zoom	Video conferencing software that became essential during the COVID-19 pandemic.

If AI emerges as a GPT, it is unlikely to have a single killer app or use case. GPTs just are different. 

ISP Marginal Cost Does Not Drive Consumer Prices

As the U.S. Federal Communications Commission opens an inquiry into ISP data caps, some are going to argue that such data caps are unnecessary or a form of consumer price gouging, as the marginal cost of supplying the next unit of consumption is rather low. 

Though perhaps compelling, the marginal cost of supplying the next unit of consumption is not the best way of evaluating the reasonableness of such policies.  

If U.S. ISPs were able to meet customer data demand during the COVID-19 pandemic without apparent quality issues, it suggests several things about their capacity planning and network infrastructure, and much less about the reasonableness of marginal cost pricing.

In fact, the ability to survive the unexpected Covid data demand was the result of deliberate overprovisioning by ISPs; some amount of scalability (the ability to increase supply rapidly); use of architectural tools such as content delivery networks and traffic management and prior investments in capacity as well. 

Looking at U.S. internet service providers and their investment in fixed network access and transport capacity between 2000 and 2020 (when Covid hit), one sees an increasing amount of investment, with magnitudes growing steadily since 2004, and doubling be tween 2000 and 2016.

Year	Investment (Billion $)
2000	21.5
2001	24.8
2002	20.6
2003	19.4
2004	21.7
2005	23.1
2006	24.5
2007	26.2
2008	27.8
2009	25.3
2010	28.6
2011	30.9
2012	33.2
2013	35.5
2014	37.8
2015	40.1
2016	42.4
2017	44.7
2018	47
2019	49.3
2020	51.6

At the retail level, that has translated into typical speed increases from 500 kbps in 2000 up to 1,000 Mbps in 2020, when the Covid pandemic hit. Transport capacity obviously increased as well to support retail end user requirements. Compared to 2000, retail end user capacity grew by four orders of magnitude by 2020. 

Year	Capacity (Mbps)
2000	0.5
2002	1.5
2004	3
2006	6
2008	10
2010	15
2012	25
2014	50
2016	100
2018	250
2020	1000

But that arguably misses the larger point: internet access service costs are not contingent on marginal costs, but include sunk and fixed costs, which are, by definition, independent of marginal costs. 

Retail pricing based strictly on marginal cost can be dangerous for firms, especially in industries with high fixed or sunk costs, such as telecommunications service providers, utilities or manufacturing firms.

The reason is that marginal cost pricing is not designed to recover fixed and sunk costs that are necessary to create and deliver the service. 

Sunk costs refer to irreversible expenditures already made, such as infrastructure investments. Fixed costs are recurring expenses that don't change with output volume (maintenance, administration, and system upgrades).

Marginal cost pricing only covers the cost of producing one additional unit of service (delivering one more megabyte of data or manufacturing one more product), but it does not account for fixed or sunk costs. 

Over time, if a firm prices its products or services at or near marginal cost, it won’t generate enough revenue to cover its infrastructure investments, leading to financial losses and unsustainable operations.

Marginal cost pricing, especially in industries with high infrastructure investment, often results in razor-thin margins. Firms need to generate profits beyond just covering marginal costs to reinvest in growth, innovation, and future infrastructure improvements. 

In other words, ISPs cannot price at marginal cost, as they will go out of business, as such pricing leaves no funds for innovation, maintenance, network upgrades and geographic expansion to underserved or unserved areas, for example. 

Marginal cost pricing can spark price wars and lead customers to devalue the product or service, on the assumption that such a low-cost product must be a commodity rather than a high-value offering. Again, marginal cost pricing only covers the incremental cost of producing the next unit, not the full cost of the platform supplying the product. 

Gigabit Services are Right on Schedule According to Edholm's Law and Nielsen's Law

U.S. home broadband customers buying gigabit tiers of service grew 35 percent year over year in the third quarter of 2022, according to Openvault. At the moment, more than 15 percent of U.S. home broadband accounts use gigabit connections. 

Also, more than half of home broadband accounts buy service in the 200 Mbps to 400 Mbps range. That group grew 100 percent year over year. 

A little more than a year ago about half of households were buying service in the 100 Mbps to 200 Mbps range, showing that Nielsen’s Law and Edholm’s Law of bandwidth supply continue to operate. 

source: Openvault 

Edholm’s Law states that internet access bandwidth at the top end increases at about the same rate as Moore’s Law suggests computing power will increase. Nielsen's Law essentially is the same as Edholm’s Law, predicting an increase in the headline speed of about 50 percent per year. 

Nielsen's Law, like Edholm’s Law, suggests a headline speed of 10 Gbps will be commercially available by about 2025, so the commercial offering of 2-Gbps and 5-Gbps is right on the path to 10 Gbps. 

source: NCTA  

Headline speeds in the 100-Gbps range should be commercial sometime around 2030. 

How fast will the headline speed be in most countries by 2050? Terabits per second is the logical conclusion. Though the average or typical consumer does not buy the “fastest possible” tier of service, the steady growth of headline tier speed since the time of dial-up access is quite linear. 

Gigabit tier subscribers hit an inflection point last year. The rule of thumb is that any successful and widely-bought consumer technology enters its mass adoption phase when about 10 percent of homes are users. For U.S. gigabit adoption, that happened in 2021. 

Some might attribute the Covid pandemic and work from home as driving the change, but adoption rates would have taken off in 2021 in any case, as predicted by the 10-percent-of-homes adoption theory. 

It also is easy to predict that 2 Gbps to 4 Gbps is the next evolution, as speeds at the top end continue to increase by 50 percent a year. Ny 2025 we should start seeing the first 10-Gbps services deployed at scale.