AI Leaders and Laggards?

There are lots of head fakes in technology. At least temporarily, virtual reality, augmented reality, automated vehicles, three-dimensional television, smart glasses, virtual assistants and wearable technology have failed to make much of an impact. 

User-generated content has succeeded as the underpinning of sustainable business models, but not as it was originally envisioned, as a substitute for professionally-produced content. 

On the other hand, Netscape made the multimedia World Wide Web accessible, while the Web made the internet a “must have” experience.  Facebook created social media. Google search changed the way people learn and find things. The iPhone changed personal devices. Twitter changed the way newsmakers get their news. Netflix and YouTube changed the way people consume video content. 

ChatGPT and generative AI seemingly have nearly-instantly shifted and changed the computing function and the application of computing to apps, devices and platforms. 

But it is worth pointing out that we are early in a shift to an AI-driven future. A few of you might recall the early days of personal computing or the internet and what it was capable of in 1995. The point is that we are quite likely to be surprised with the outcomes.

Today’s apparent “leaders” might not be in existence in a decade, much less continue to lead. Laggards and upstarts might overtake today’s leaders in markets as they exist in a decade or two. 

How AI will reshape apps, platforms, devices and experiences is fluid and unsettled. So most of our predictions will prove false, in part, or in whole. 

In 1995, the idea of “ad-supported technology firms” might have seemed silly. But now we have witnessed the dominance of firms such as Google and Meta, which are nothing if not ad-supported developers of technology products. 

The emergence of online commerce was easier to predict. But few in 1995 believed video streaming services could not only compete with, but supplant, linear video. 

So “nobody saw this coming” is still likely to be among the outcomes of AI, a decade or two in the future, especially if AI turns out to be a general-purpose technology like electricity. 

General-purpose technologies are fundamental innovations which have a broad range of applications and can be used to improve productivity in a variety of industries. They are often characterized by their ability to be adapted to new uses and to generate new industries, increase productivity and ignite economic growth. 

The stream engine, internal combustion engine, materials science, electricity, the computer and the internet are prior examples of GPTs. Biotechnology and nanotechnology are other possible GPTs, but are not yet widely acknowledged to have already done so. 

Most of us likely believe AI is going to be added to that list. Buckle up.

What is an "AI Appliance"?

As we move into the AI era of devices and appliances, it seems inevitable that some will seek to redefine devices as “AI appliances,” even if most firms will instead seek only to develop AI apps that run on standard appliances (phones, PCs, sensors). 

Such AI appliances might feature personalization, predictive maintenance, contextual awareness, continuous learning, proactive assistance or enhanced security. 

AI-powered PCs could be designed to support on-the-device machine learning and natural language processing or provide augmented reality experiences. 

AI appliances likely will be able to learn about their users' preferences and habits, and tailor their operation accordingly.

AI appliances will be able to monitor their own performance and predict when they are likely to need maintenance. Also, AI appliances will be able to anticipate their users' needs and provide assistance without being asked.

Enhanced security: AI appliances will be able to detect and prevent security breaches.

Here are some specific examples of AI appliances that are already being developed:

Software Applications wants to develop a desktop PC operating system optimized for generative artificial intelligence. The effort is early so it is hard to say much about what they might develop. 

An example the firm cites is that “sometimes you’ve got a browser window open with a schedule on it, and you just want to say, ‘add this to my calendar,’ and somehow, there’s no way to do that.” An AI PC would be able to do so. 

Most other startups such as Rewind AI,  are building personalized AI systems for the desktop. Rewind AI seems focused on the function of note taking on Mac and iOS devices. 

Moveworks develops automated IT support solutions that use AI to monitor and troubleshoot IT systems, identify and resolve issues, and provide proactive support to users.

Coactive AI uses AI to automate the process of retrieving and using visual data. 

Midjourney develops chatbot applications that use AI to generate images.

DeepL provides a machine translation service. 

Frame AI: Offers a platform for building and deploying AI models on embedded devices, such as smartphones and smart home appliances.

Uizard features a no-code AI platform that allows users to create AI applications without any programming experience.

Sherpa provides a virtual personal assistant.

BigPanda provides an AIOps capability that helps IT teams resolve IT outages and incidents more quickly and effectively.

CognitiveScale develops AI-powered customer service solutions for various industries, including healthcare, insurance, financial services, and digital commerce.

Fixed Wireless Now Accounts for 90%-Plus of Net Home Broadband Additions

By now, it is clear that fixed wireless access does resonate with substantial portions of the home broadband market. Some of us estimate that fixed wireless appeals mostly to about 20 percent to 25 percent of buyers who take slower-speed services up to about 200 Mbps to 300 Mbps. 

“At current prices, full FWA (fixed wireless access) entry to a cable-only market, which constitutes approximately 30 percent of all cable modem subscribers in the United States, would convert 18 percent of cable-only households to FWA,” a study by EconOne estimates. 

Take rates are lower when FWA is introduced into a market with both cable operator and at least one provider of fiber-to-home service. 

“When two FWA packages are introduced, they capture a 2.5 percent market share, with 0.9 percent coming from Cable and 1.6 percent coming from Fiber,” the study also suggests. 

Separately, Leichtman Research estimates that six percent of U.S. home broadband accounts now are supplied using fixed wireless networks, and in 2023 is generating in excess of 90 percent of all net broadband account additions in the U.S. market. 

Most observers would tend to agree that fixed wireless competes with other lower-speed home broadband services operating at less than 200 Mbps. Most observers also would note that FWA suppliers are careful to offer the service only in areas where they can supply both mobile customer demand and home broadband usage without degrading mobile experience. 

For perhaps obvious reasons, the study did not study the impact of FWA in areas served by a cable operator and a telco digital subscriber line network. In such areas, one presumes there is market share shift away from DSL as well, often from one fixed network supplier to a rival mobile supplier. 

In virtually all cases studied, fixed wireless takes more share from DSL than it does from cable operators. Of course, no study funded by a telco organization may wish to point this out. 

Study	Year	Impact on Cable Market Share	Impact on DSL Market Share
Recon Analytics	2022	-1.1%	-2.2%
FCC	2021	-1.5%	-3.0%
Dell'Oro Group	2020	-2.0%	-4.0%
Leichtman Research Group	2019	-2.5%	-4.5%

We can presume that the primary form of market share shift away from DSL is from an existing incumbent telco to an attacking mobile operator.

Not All 5G Customers Use It

5G accounts continue to climb as more 5G mobile networks are built, reaching about 1.6 billion accounts by the end of 2023, according to Ericsson. That is out of a total of about 8.5 billion mobile accounts globally. 

But actual time connected to 5G varies, and a significant percentage of 5G customers may not use the network at all. A study by the GSMA (Global System for Mobile Communications) found that 20 percent of 5G subscribers worldwide were not using 5G services in 2022.

Market	Estimated percentage of 5G subscribers who do not use 5G
United States	15-20%
Europe	20-25%
Asia	10-15%

Some consumers who buy 5G accounts cannot get connected to them all the time because signal strength is too low. 

A 2023 survey by T-Mobile found that 65 percent of its 5G subscribers spend more than half of their time connected to 5G networks. 

Also, some customers with 5G-capable service might only be using 4G-capable phones on those networks. 

According to Ookla data, the percentage of 5G connection time can range from a high of 47 percent to a low of about five percent. 

Market	5G Availability (%)	Time Spent on 5G Networks (%)
South Korea	42.9%	47.2%
Puerto Rico	48.4%	43.5%
Finland	24.2%	22.7%
Bulgaria	24.7%	22.2%
Taiwan	30.0%	21.6%
Singapore	30.0%	21.2%
Malaysia	20.5%	18.0%
United States	31.1%	18.0%
France	20.6%	13.6%
Germany	13.3%	8.5%
Italy	17.9%	9.2%
Spain	15.2%	8.4%
United Kingdom	10.1%	5.0%

A recent study by Ookla found that 5G users in the United States are connected to 5G networks about 30 percent of the time, while 4G users are connected to 4G networks about 70 percent of the time. 

A study by Opensignal found that only 15 percent of 5G subscribers in the United States are actively using 5G networks. And a study by Telenor Research found that 5G users are connected to 5G networks for an average of 20 percent of the time, though all such numbers are improving as 5G coverage grows, and more consumers buy 5G phones.

"Sampling" is Driving Much ChatGPT Usage

Most people are likely impressed by rapid ChatGPT usage statistics. But very-early “usage” of a new type of app is likely driven by curiosity, media hype, or social media trends rather than genuine engagement and continued use that creates a firmer daily active user metric. Consider one metric: total users. 

Most observers agree that ChatGPT reached 100 million users in two months. Other popular apps took longer to reach that level of “usage.” But it is hard, in the very-early days, to determine what that statistic means, as it includes lots of users who are sampling, but decide the app is not immediately useful, and do not become repeat users. 

App	Time to Reach 100 Million Users
ChatGPT	2 months
WhatsApp	3.5 years
Facebook	2.5 years
TikTok	9 months
Instagram	2.5 years
Twitter	5 years
Netflix	3.5 years

So many would focus on “daily active users,” which tends to better measure repeat user behavior, and should provide a better idea of app adoption. ChatGPT also appears to have been adopted faster than many other now-popular apps. 

App	Time to Reach 1 Million DAU
ChatGPT	5 days
TikTok	9 months
WhatsApp	18 months
Facebook	4 months
Google	8 months
Netflix	13 months

The point is that optimism about LLM and generative AI is reasonable: DAU stats suggest the potential. 

According to a survey by OpenAI, perhaps two percent of internet users have used a large language model at least once, which would suggest 160 million people worldwide have used ChatGPT at least once for creative writing, learning, and entertainment, which are the three most-frequent uses. 

Another survey, conducted by Pew Research Center, suggests that 13 percent of Americans have heard of large language models, and three percent have used one. Another study by Pew suggests 20 percent of teenagers who have heard of ChatGPT have used it for homework., 

A separate study by Pew Research suggests the percentage of respondents who have heard of ChatGPT and have tried it has grown substantially by August 2023. Repeat studies suggest sampling or usage has grown rapidly in 2023.