Friday, November 15, 2024

Marginal Cost and ISP Data Caps

Some critics of internet service provider usage-based (buckets of usage) object to the practice as unfair, since the marginal cost of supplying the next unit of consumption is considered quite low. But the marginal cost of the next unit of capacity consumption is not the gating factor dictating ISP cost structure. 


Product/Service

Consumer Margin

Business Margin

Mobile Voice

30-40%

35-45%

Mobile Data

45-55%

50-60%

Fixed Broadband

40-50%

45-55%

TV/Video

25-35%

30-40%

VoIP

35-45%

40-50%

Cloud Services

30-40%

35-45%

IoT Connectivity

40-50%

45-55%

Managed Services

N/A

30-40%

Content Apps

60-70%

N/A

Enterprise 5G

N/A

50-60%


Of course, connectivity service is a highly capital intensive business as well, also featuring the necessity of high dividend payouts, capex, interest and amortization expenses, as well as the customary operating costs all businesses incur, so gross profit margin is only part of the story. 


Sunk costs, high capital investment and borrowing costs are the key drivers of cost, not incremental costs of supplying the next unit of consumption. 


Consider a sample business model for a firm whose revenue has been simplified from billions of dollars to just $100 million, but using the same ratios of cost in the model.


The point is that high gross profit margins also come with significant costs. The result is that high gross profit margins are matched by expenses high enough to reduce net profits to five percent to 15 percent, which might be broadly representative of many other types of businesses. 


Metric

Description

% of Revenue

Model Impact

Revenue

Total income from services and products

100%

$100 million

Gross Margin

Revenue minus cost of goods sold (COGS)

60-70%

$60-70 million

Operating Expenses

SG&A, marketing, administrative, salaries

20-25%

$20-25 million

EBITDA

Earnings before interest, taxes, depreciation, and amortization

35-50%

$35-50 million

Depreciation & Amortization

Wear and tear on assets, often high in telcos

10-15%

$10-15 million

Operating Income (EBIT)

EBITDA minus depreciation & amortization

20-35%

$20-35 million

Interest Expense

Payments on debt, which can be high

5-10%

$5-10 million

Pretax Income

EBIT minus interest expense

10-25%

$10-25 million

Tax Expense

Varies by jurisdiction

2-5%

$2-5 million

Net Income

Profit after all expenses and taxes

8-20%

$8-20 million

Dividends

Shareholder payments, often a priority for telcos

3-5%

$3-5 million

Net Margin after Dividends

Net margin after dividends

5-15%

$5-15 million


Connectivity services might generally range in the middle of industries for net profit margin, keeping in mind that participants at different stages of the value chain in each industry can have distinctly-different profit margin profiles. 


Industry

Typical Net Profit Margin

Pharmaceuticals

15-25%

Software & IT Services

15-30%

Banking & Financial Services

10-20%

Telecom Services

5-15%

Consumer Packaged Goods (CPG)

5-10%

Utilities

5-10%

Manufacturing

5-12%

Automobile Manufacturing

5-10%

Retail

2-6%

Airline Transportation

1-5%

Hospitality

2-6%

Construction

2-8%

"Winner Takes All" or "Winner Takes Most" Market Structure for LLMs?

According to the Chatbot Arena leaderboard, a platform for evaluating AI determined by user votes, Gemini’s latest update--Gemini-Exp-1114--ranks best among large language models. 


It is worth noting that leaders change somewhat frequently, with the top-five models presently all versions of OpenAI or Google models. Perhaps notably, Grok-2-08-13 ranks sixth. 


source: Chatbot Arena 


It might also be worth noting that OpenAI's models (such as GPT-4) and Anthropic's Claude models have consistently ranked near the top of the leaderboard.


And leadership seems to have changed since the spring of 2023. Consider the leaderboard published by LMsys in the spring of 2023. ChatGPT 3.5 launched in late 2022 and seems to have been in the top five of the Arena leaderboard since its inception in the spring of 2023. 


source: lmsys.org 


Eventually, business history would suggest leadership of the market will condense, as have other technology markets. So. the LLM market is likely to evolve into a structure characterized by oligopolistic competition among a few major players, complemented by a range of specialized providers catering to specific industries or use cases.


In 2023 five LLMs had more than 88 percent market share. That leadership group might condense further, eventually. 


On the other hand, the room for specialized platforms might remain. How many of us would not see any way for OpenAI, Google, Microsoft, Meta, Amazon, Apple and IBM, for example, to continue as operators of domain-specific LLMs, no matter what happens ;with the broader market?


And who might doubt that specialized industry-specific platforms could number between 10 and 20 (catering to different sectors like healthcare, finance, legal)?


And of the leaders, might open-source initiatives include three to five significant contributors? 


Might AI-as-a-Service providers number 10 to 15 “significant” players, even if the top five or so positions include AWS, Google Cloud, Azure, Meta and Amazon? 


Also, if history is instructive, could there not exist five to 10 Integration and orchestration platforms as well?


The issue is what “winner takes all” will mean in the LLM ecosystem and platforms markets. Current examples include just one or perhaps two leaders in existing markets, which is more on the “operating system” model. On the other hand, most of us would have a hard time deciding on less than perhaps four leading LLMs for some time to come. 


And some structural differences between existing technology market structures and LLMs come to mind. Unlike the operating system market, LLMs don't require the same level of user lock-in or hardware integration. So the "two-leaders” pattern might not emerge. 


Roughly the same argument might be made about the e-commerce or search market structures, where one leader tends to emerge. The competitiveness of existing LLMs, with continual upgrades, tends to dispel the notion that any single provider will achieve technological superiority on a sustainable basis. 


LLMs also lack the network effects and user-generated content central to social media platforms. So it is possible the one leader model might not develop. Right now, differences between leading platforms are relatively subtle. 


So the likely direction is “winner take most” more than “winner take all.” Even if network effects are not so strong, high capital intensity, branding and trust issues and the ability to vertically integrate with existing ecosystems (Google, Apple, Microsoft, Meta) create enormous advantages for a few contenders. 


At least for the moment, “winner take all” is hard to see. A still-oligopolistic, but “winner take most” structure with a handful of leaders might be more plausible. 


Thursday, November 14, 2024

How Big is "GPU as a Service" Market?

It’s almost impossible to precisely quantify the addressable market for specialized “graphics processor unit as a service” providers such as CoreWeave, which specializes in providing GPU infrastructure to artificial intelligence developers.


CoreWeave might be considered an innovation in the area of high-performance computing for that reason, as it emphasizes GPUs rather than Central Processing Units. GPUs are considered essential for accelerating computationally intensive tasks like AI and machine learning. 

  

Traditional HPC often relies on CPUs for general-purpose computing. CoreWeave prioritizes GPUs, which are optimized for parallel processing. Right now, the market might be in low single-digit billions, but growing to possibly double-digit or triple-digit billions by the mid-2030s. 


Still, GPU as a service is a specialty within the cloud computing as a service business, and might remain two orders of magnitude smaller. 


Study Name

Date

Publisher

Key Estimates

GPU as a Service Market Size, Share & Growth Report

2023

Grand View Research

Global market valued at USD 3.35 billion in 2023, projected to grow at a CAGR of 21.6% from 2024 to 2030.

GPU as a Service Market Size, Growth

Forecast Analysis [2032]

Fortune Business Insights

Global market valued at USD 3.23 billion in 2023, projected to grow from USD 4.31 billion in 2024 to USD 49.84 billion by 2032, exhibiting a CAGR of 35.8%.

GPU as a Service Market Size & Share

Growth Forecast 2032

Global Market Insights

Global market valued at USD 6.4 billion in 2023, projected to grow at a CAGR of over 30% during 2024 to 2032.

GPU-as-a-Service Market Size, Trends & Outlook by 2033

2023

FMI - Future Market Insights

Global market valued at USD 3.91 billion in 2023, projected to grow at a CAGR of 40.8% between 2023 and 2033, totaling around USD 119.6 billion by 2032.

GPU as a Service Market Size & Share

Growth Analysis 2037

Research Nester

Global market valued at USD 4.34 billion in 2024, projected to exceed USD 95.07 billion by 2037, registering over 26.8% CAGR.


As with many other firms launching in new markets, perhaps the essential gamble is that X market will be huge and Y provider will get N percent of the market. So GPU as a service might be a subset of generative AI as a service. 


Study

Date

Publisher

Key Estimate

The State of AI 2023

June 2023

Anthropic

The global market for generative AI computing as a service is forecast to reach $15 billion by 2027.

Generative AI Market Outlook

September 2023

CoreWeave

The market for generative AI computing as a service is expected to grow at a CAGR of 35% from 2023 to 2028, reaching $18.2 billion in value by 2028.

Gartner Hype Cycle for AI 2023

July 2023

Gartner

Generative AI computing as a service is projected to have a market size of $14.5 billion by 2026.

Generative AI Market Size, Share

2023

Fortune Business Insights

Global market valued at USD 43.87 billion in 2023, projected to reach USD 967.65 billion by 2032, with a CAGR of 39.6%.

Generative AI Market Size To Hit USD 803.90 Bn By 2033

2023

Precedence Research

Global market size was USD 17.65 billion in 2023, expected to reach USD 803.90 billion by 2033, expanding at a CAGR of 46.5%.

Generative AI Market Size And Share

2024

Grand View Research

Global market led by North America, with a revenue share of 40.8% in 2024. Software segment dominates with a 64.2% share.

Generative AI Market Size, Trends, & Technology Roadmap

2023

MarketsandMarkets

Focuses on technology trends and roadmap, including advancements in transformer models and multimodal data.


BEAD Has Not Connected a Single Home for Broadband Interenet Access, After 3 Years

As an observer of the follies of government ineffectiveness, we note that the U.S. Broadband Equity, Access, and Deployment (BEAD) Program was enacted in November 2021 and allocated $42.45 billion to the National Telecommunications and Information Administration (NTIA) to work on the “digital divide” by facilitating access to affordable, reliable, high-speed internet throughout the United States, with a particular focus on communities of color, lower-income areas, and rural areas.


As of November 2024 not a single dollar has been spent in support of the program, for a variety of perhaps simple bureaucratic reasons. 


The program's implementation has been slowed by a complex approval process. States were required to submit Initial Proposals outlining their broadband deployment objectives. 


As of June 2024, only 15 states and territories had received approval. States have 365 days after approval to select projects and submit a final list to the National Telecommunications and Information Administration (NTIA) for review.


As you might imagine, all that has caused delays. 


Also, the NTIA had to wait for the FCC to release an updated national broadband map before allocating funds to states.


There have been other issues as well. The Virginia proposal has been delayed over affordability requirements and rate-setting. The program also has provisions related to accessibility, union participation, and climate impact, which have not helped speed things up. 

.

High interest rates and tight financing conditions have made it more difficult for broadband providers to secure funding for projects, even when approved. 


The result is that funding isn't expected to start reaching projects until 2025 at the earliest. .


Some might argue the program’s design was not optimal for rapid funds disbursal.


Some might argue it would have been far simpler to route money directly to Internet Service Providers (ISPs) based on their proven ability to deploy networks quickly in underserved areas. 


Competitive bidding could have been used. The program could have specified uniform national standards for broadband deployment to replace the current patchwork of state-specific and local requirements. 


The program could have been “technology neutral” instead of mandating use of some platforms over others, and might have used a simpler application and reporting system, in place of the cumbersome existing framework. 


The larger point is that the law arguably was poorly designed, in terms of its implementation framework. The fastest way to create infrastructure might have been to give buying power to potential customers, as did the Affordable Connectivity Program, or make direct grants to ISPs in position to build almost immediately. 


And since rural connectivity was deemed important, it might have been wise not to exclude satellite access platforms. 


It was a good impulse to “want to help solve this problem.” But intentions also must be matched by policy frameworks that are efficient and effective, getting facilities depl;oyed to those who need them fast. BEAD has not done so. 


DIY and Licensed GenAI Patterns Will Continue

As always with software, firms are going to opt for a mix of "do it yourself" owned technology and licensed third party offerings....