AI Physical Interfaces Not as Important as Virtual

Microsoft’s dedicated AI key on some keyboards--which opens up access to Microsoft’s Copilot--now is joined by Logitech’s Signature AI mouse, with a button to open up the Logi AI Prompt Builder software and ChatGPT. 

Both might be viewed as equivalent to shortcut keys that simplify access to a chosen AI engine or feature on a device, and likely will be pitched as an easier way for some users to use a specific AI engine, though in principle more-evolved versions by these or other suppliers might offer access to a user’s chosen engine or engines, or offer context-aware AI functions. 

The issue there is the eternal balance between the values of curation (walled gardens that simplify or unify experience, provide greater security and consistency of experience) and the values of openness (flexibility, power, choice at the cost of complexity, risk and security). 

Some might view such interfaces as gimmicks of a sort, and they also represent walled garden approaches to use of generative AI. 

Proponents might argue such buttons or keys provide value by making it easier for users to use one AI engine.  

Instead of navigating menus or opening separate applications, a single click on the AI button brings up Logitech's AI Prompt Builder software, for example. Users can write prompts, customize the desired response tone and complexity, and receive results directly within the Prompt Builder window.

Using the AI button, users also might be able to quickly access ChatGPT's “summarize” function for documents or emails, as well.

AI keys or buttons might be useful for beginners or those unfamiliar with navigating menus, some might argue.

Skeptics might argue this is reminiscent of the early days of the multimedia web, when AOL offered a walled garden internet experience deemed helpful for new users, but was less helpful--or limiting--for users who had some experience. The idea then was to simplify the user experience, and perhaps AI buttons and keys will do that for some new AI users. 

One might envision such keys or buttons launching built-in AI assistants enabling voice commands or  dictation.  In some cases functions might become context aware.

Ideally, users might be able to program the buttons or keys to perform their preferred AI action, such as providing image editing suggestions or content creation prompts.

So AI buttons and keys are an experiment in making AI features more accessible and user-friendly.

In that sense, they resemble voice interfaces for smart speakers, and speech-to-text functions, which aim to make interacting with technology more natural and efficient. But, as with earlier efforts to simplify access, users might quickly outgrow the interfaces, opting instead for the more-flexible and powerful use of menus or other open-ended interfaces. 

Using the AOL analogy, users rather quickly outgrew the walled garden interface and opted instead to rely on open, general-purpose browsers. 

And some innovations simply do not catch on. Smart speakers have failed to become a dominant interface, though voice-to-text functions on smartphones are routinely used. 

It remains to be seen whether walled garden keys and buttons actually provide the intended value, and if so, for how long before users become more AI-proficient and outgrow the interfaces. 

The Graphical User Interface (GUI) and touchscreens, on the other hand, provide classic examples of successful interfaces. And there always are exceptions. The Apple iOS is a walled garden that works. Windows Phone is an example of a failed walled garden. 

In other words, there always is a tension between curation of experience and choice, customization, broad access to features and an open approach. 

Some of us might be so convinced AI keys or buttons will be enduring interfaces. 

Meta Warns Significant AI Profits are "Several Years Away"

Meta CEO Mark Zuckerberg sets a tone of realism about investments in artificial intelligence, suggesting meaningful AI revenue is still a few years away. “Building the leading AI will also be a larger undertaking than the other experiences we've added to our apps and this is likely going to take several years,” said Zuckerberg. 

Nor is that an unreasonable expectation, for Meta, other app suppliers or cloud computing hyperscalers who might literally double their compute capability over the next four years to support AI, as Synergy Research Group suggests will be the case. 

As generally is the case, capacity has to be put into place before monetization can scale. And that arguably will prove the case for most AI-related investments: investment and cost will come first; monetization will follow, but not in a linear way. 

"Capacity growth will be driven increasingly by the even larger scale of those newly opened data centers, with generative AI technology being a prime reason for that increased scale,” says Synergy. 

Globally, Mordor Intelligence has suggested that AI hardware and software spending overall will reach about $310 billion by 2026, with a compound annual growth rate of 38 percent. Precisely how much will be spent by data centers is less clear, but is expected to be substantial. 

Year	Processing CapEx (USD Billion)	Storage CapEx  (USD Billion)	Source	Discussion
2021	50-70	20-30	Synergy Research Group (2022)	Estimates based on overall data center CapEx growth and industry trends related to AI adoption.
2022	55-75	25-35	Gartner (2023)	Estimates based on data center equipment sales figures and analyst projections for AI hardware growth.
2023	60-80	30-40	IDC (2023)	Forecasts based on hyperscale data center spending surveys and analysis of enterprise AI deployments.
2024	65-85	35-45	Mordor Intelligence (2022)	Projections based on AI hardware market growth and anticipated increase in data center infrastructure spending.
2025	70-90	40-50	Cowen Research (2023)	Analyst estimates based on industry surveys and projections for continued growth in AI workloads and data volumes.

Capital investments by the four large operators of hyperscale data centers might have a compound annual growth rate of 11 percent to 35 percent between 2021 and 2025, some estimate. 

Year	Estimated Hyperscale Data Center CapEx (Processing & Storage)	Source	Discussion
2021	$80 Billion - $100 Billion	Synergy Research Group (2022)	This is an estimate for total CapEx on processing and storage in hyperscale data centers, not specifically for AI.
2022	$85 Billion - $105 Billion	Synergy Research Group (2023)	Similar to 2021, this represents total CapEx, but a portion will likely be directed towards AI needs.
2023	$90 Billion - $115 Billion	Gartner (2023)	Gartner predicts a 6.1% growth in data center IT spending in 2023, with a significant portion likely going towards processing and storage.
2024	$95 Billion - $125 Billion	IDC (2023)	IDC forecasts worldwide data center spending to reach $352 billion in 2024, with hyperscale CapEx on processing and storage being a major driver.
2025	$100 Billion - $135 Billion	Mordor Intelligence (2022)	Mordor Intelligence predicts a CAGR of 13.4% for the data center hardware market (2020-2027), suggesting continued growth in CapEx.

Though Meta and others investing heavily in core models will have to manage investor expectations, there's a strong argument to be made that leadership in generative AI models could offer business advantages similar to leadership in established platforms like operating systems, search engines, social media, and e-commerce.

Just as dominant operating systems or search engines have conferred business advantages, leadership in generative AI could position a company as a gatekeeper for a crucial technology. Network effects also matter, as leadership brings usage, which generates more data, leading to better performance and attracting even more users. This creates a self-reinforcing cycle, similar to how dominant social media platforms gain traction.

Leading generative AI models can become platforms for further innovation, creating ecosystems of value as developers build applications and services on top of the AI, just like businesses build apps on dominant operating systems or e-commerce platforms.

Whatever the Eventual Impact, Telecom Execs Say They are Investing in AI

With the caveat that early reported interests, tests, trials and investments in new technology such as artificial intelligence--especially those deemed important--will overstate the degree of actual deployment, telecommunications professionals say they are investing in machine learning, deep learning, generative AI, high-performance computing and digital twins or metaverse at rates that might surprise some observers, according to a survey sponsored by Nvidia. 

source: Nvidia 

Of course, technology investment is pursued in order to obtain some business advantage. According to surveyed professionals, those desired outcomes include better customer experience, productivity enhancements, better network operations cost savings and revenue growth. 

Many respondents report non-zero changes (as would be expected). In terms of inputs, the report says “43 percent of respondents reported an investment of over $1 million in AI.” About seven percent of respondents claimed AI investments in excess of $50 million. 

source: Nvidia 

None of that should come as a surprise, given the attention executives now place on reassuring stakeholders that they are “doing something” about AI. In 2023, AI was mentioned in 394 earnings calls, representing nearly 80 percent of all Fortune 500 companies, according to Stanford University’s Human-Centered AI institute.

Fixed Wireless Platforms Make Sense for Rural Markets--Including the U.S.

It might seem obvious that fixed wireless access--though important in many countries where fixed network infrastructure is hard to create and sustain--would also be important in markets such as the United States. 

But fixed wireless grew by about 6.6 percent from the fourth quarter of 2022 to the fourth quarter of 2023, significantly led by  “healthy growth rates in the United States, especially by T-Mobile and Verizon,” say researchers at Point Topic.

source: Point Topic 

“We expect this trend to persist due to demand for connectivity in remote and underserved areas where wired broadband infrastructure is difficult to deploy, and due to some consumers cord-cutting their broadband access services,” Point Topic says. 

What bears repeating is the largely-rural or non-populated character of most of the United States. Most people live on just six percent of the U.S. land surface, according to the USDA. 

And about 94 percent of the land surface is unsettled or lightly populated, including mountains, rangeland, cropland and forests, according to the U.S. Department of Agriculture. 

The result is that fixed networks are expensive across most of the land surface, which is rural, sparsely populated or largely unpopulated. So fixed wireless makes lots of sense.  

Disintermediation Does Not Always Help OEMs

“Disintermediation,” the removal of “middle man” or “distribution” stages in a value chain, has been a major outcome of the internet, leading to flatter distribution chains with a new emphasis on “direct to customer” strategies. 

As a rule, that should reduce costs for goods and services suppliers.  Perhaps oddly, that has not been true for parts of the video content industry. You might expect “direct to consumer” video streaming services to provide competition and a substitute product for linear video subscriptions. 

So cable TV and telco linear video subscription businesses arguably are damaged by direct-to-consumer video streaming services, as they are distributors or “middle men” in the value chain.

But it remains unclear whether most direct-to-consumer video streaming services actually benefit so much from the flatter value chains and disintermediation. 

For starters, content owners have traditionally earned affiliate fees from their distribution partners. Disney, for example, has earned about 17 percent of total revenue from affiliate fee payments. Warner Brothers Discovery and Paramount have tended to earn about 21 percent of their total revenues from affiliate fee payments, while NBC (Comcast NBCUniversal has earned about 22 percent.

Revenue Source	Linear Model	Streaming Model	Change in Marketing Cost
Subscription Revenue	High (Bundled with other services)	Variable (Can be higher or lower depending on platform strategy)	Potentially Higher (Need to directly compete for subscribers)
Advertising Revenue	Low (Limited ad inventory)	Variable (Can be a significant source of revenue)	Potentially Higher (Need to build audience and ad platform)
Affiliate Fees	High (Revenue from cable/satellite providers)	Low (Little to no role in streaming model)	Not Applicable

Ironically, cutting out a major part of the distribution chain also has reduced revenue for content owners. 

Nor is it so clear that “direct to consumer” has actually reduced marketing and other distribution costs. Selling direct means building a fulfillment process including retail billing and lots more marketing. 

The point is that disintermediation is "supposed"to reduce costs for supplers of goods and services (original equipment manufacturers). In the case of video content owners, going "direct to consumer" has yet to do so, consistently, if at all.

Cloud Computing Value Might Hinge on Where You Use It

“A stunning 95 percent of European companies in our recent survey say they’re capturing value from cloud, and more than one in three say they intend to have more than half of their workloads on cloud,” say McKinsey consultants Bernardo Betley, associate partner; Hana Dib, associate partner; Bjørnar Jensen,  senior partner and Bernhard Mühlreiter, partner. That’s the good news. 

The bad news? “The vast majority of the value companies have captured, for example, remains in isolated pockets and at subscale,” the consultants also say. 

Some of that might be caused by the way European companies (the subjects of the study) have implemented cloud computing. 

“The focus of their cloud efforts, for example, has been disproportionately on improvements to IT, which generate lower rates of value than improvements to business operations,” McKinsey says. 

Somewhat oddly, “most companies (71 percent) measure it (benefits) in IT operational improvements, 66 percent in IT cost savings, and 63 percent in number of applications on cloud,” McKinsey says. “Only about one in three European companies, however, monitors non-IT outcomes, such as cost savings outside IT (37 percent) or new revenue generation (32 percent).”

That might seem odd for many observers, since those outcomes (cost savings or revenue enhancement) might seem the obvious way to measure outcomes. “Our research and experience are clear that about two-thirds of the potential value of cloud comes from revenue uplift and cost savings in business operations,” McKinsey says. 

Study Title/Author	Methodology	Findings
"The Business Value of Cloud Computing" by McKinsey & Company (Report) / 2019	Surveyed over 1,500 executives globally	Found that companies with a clear cloud strategy focused on business outcomes achieved 3x the return on investment (ROI) compared to those with a technology-centric approach.
"Cloud ROI: Why Businesses Need a Strategic Approach" by Forrester Research (Report) / 2021	Analyzed data from cloud adoption projects	Concluded that companies with a well-defined cloud strategy focused on business goals like agility and innovation saw a 20% increase in revenue growth compared to those with a tactical, workload-centric approach.
"Unlocking the Economic Advantage of Cloud Computing" by Accenture (Report) / 2022	Examined the impact of cloud on various industries	Identified that companies using cloud to drive innovation and customer experience saw a 15% increase in customer satisfaction and a 10% improvement in operational efficiency.
"Cloud Adoption and Firm Performance: A Meta-Analysis" by Florian Schreibert et al. (Journal Article) /2020	Analyzed 42 prior academic studies on cloud adoption	Concluded that while workload shifts can lead to some performance improvements, the most significant benefits are seen when cloud adoption focuses on strategic goals like cost reduction, efficiency, and innovation.
"The Cloud Dividend: How Businesses Benefit from Cloud Computing" by Accenture (Report) /2022	Analyzed financial data from over 10,000 companies	Identified a strong correlation between effective cloud adoption strategies focused on business outcomes and improved financial performance.

“Compared to U.S. companies, about five times more European companies are still pursuing an IT-led cloud migration, with significant emphasis on lifting and shifting existing workloads,” the consultants say.