Venture Capital Exhibits A Hyper-Pareto Distribution Of Profits: The Top 5% Of VCs Garner 90% Of The Profits

From the University of Chicago's Booth School of Business, Pro-Market, September

What Makes a Venture Capitalist Successful? 

In new research, Blake Jackson and Ilya Strebulaev track the careers of 100,000 people working at venture capital firms in the United States to ask which investors succeed and why. They find that five percent of VCs generate 90 percent of the industry’s profits, that the backgrounds investors bring with them predict who ends up in that group, and that public recognition itself opens the doors to the deals that keep them at the top.

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Much of the United States economy today is made up of companies and innovators that raised their initial financing from venture capitalists (VCs). VC-backed companies account for 41 percent of total U.S. market capitalization and 62 percent of public U.S. companies’ R&D spending. Seven of the top ten largest companies by market capitalization as of December 2025 were primarily backed by VC funds earlier in their lifecycle. 

One important feature of the VC industry is the prominence of individual venture capitalists who make and manage investments on behalf of VC firms. Don Valentine, founder of the VC firm Sequoia, is a well-known early backer of Cisco and Apple. Michael Moritz, also of Sequoia, is widely credited for making early investments in Google and PayPal. Marc Andreessen, of a16z, is famous for highly successful venture investments in Airbnb and Lyft. But their reputations rest on more than a handful of smart bets. Each is known for picking winners repeatedly, across many years and market cycles.

What is, perhaps, most interesting to an observer of the VC industry, or someone seeking to invest in a VC fund, is that existing empirical evidence bears out this reputation. The ability of individual venture capitalists to make successful investments is persistent. For example, the identity of the venture capitalist sitting on the board of a startup is far more important for explaining whether an investment in a startup subsequently succeeds or fails than which VC firm the venture capitalist represented or the year they took a board seat.

However, surprisingly little is known about these individual venture capitalists. Are there persistent differences in the backgrounds of successful venture capitalists? What individual characteristics of venture capitalists, if any, can explain investment outcomes, career paths, and returns? Insofar as these characteristics and experiences are costly to replicate or acquire, to what extent are returns to investing in the VC industry concentrated among a relatively small number of professionals? 

In our new paper, we aim to answer these questions. Such a research agenda has historically been hampered by incomplete, potentially biased, and opaque data. To combat this, we assembled the largest and most comprehensive dataset of individual venture capitalists based in the U.S. to date by tracking their entire careers, deals, and outcomes. We also collected data on their individual characteristics and relevant biographical details based on existing collections of commercial VC data as well as the historical, archived websites of U.S. VC firms. 

To collect our data, we made use of a system of large language models (LLMs) designed to crawl, parse, and scrape these historical websites. We paired this process with large-scale manual collections that helped validate the reliability of our process. All in all, we tracked about 100,000 individual VCs, 37,000 of whom are professional investors. By our estimates, about half of our data points covering the backgrounds and investments of these professionals are not available in standard commercial datasets alone. 

Our new dataset reveals the striking degree to which VC investment success is concentrated among venture capitalists in the U.S. Only 38 percent of the venture capitalists in our sample were ever credited with a successful investment (an investment in a startup that later went public, was acquired for at least five times the amount invested, or achieved a valuation of at least $1 billion). Only about seven percent have made five or more. And no more than three percent of U.S. venture capitalists have ten or more successes to their name. In net profits terms, the top one percent of venture capitalists account for roughly 57 percent of the approximately $1.2 trillion in inflation-adjusted net profits generated across the sample, while the top five percent account for about 90 percent. This distribution is very unlikely to arise from randomly assigning investments to venture capitalists.

As the concentration implies, venture capitalists who previously made successful investments are more likely to succeed again. Deals made by investors with one prior successful investment are two percentage points more likely to have a successful outcome, and those with five prior successes are about seven percentage points more likely to succeed. This is almost a 50 percent jump relative to the average rate of investment success....

....MUCH MORE

Either that or get a time machine. Both H.G. Wells or Back to the Future have interesting possibilities but going completely meta would have the VC fund a time machine.

If interested in the broader realm of who gets the profits see also HBR—From Pareto To Hyper-Pareto: "AI Is Going to Change the 80/20 Rule" and the outro links therefrom:

This type of information advantage is more and more accruing to the biggest and richest of corporations. It is a type of rich-get-richer advantage akin to the flywheel effect:

• Competitive Advantage and Feedback Loops
• How to Think About Companies: "Advantage Flywheels"
• Flywheel Effect: Why Positive Feedback Loops are a Meta-Competitive Advantage
• "Analyzing the deepening divide in learning capabilities between a few corporate giants and the rest of the world." (plus advantage flywheels)
• "America's Biggest Firms' Moat Is Becoming Impregnable" (TSLA; NVDA; GOOG)

And related, now that we see what is happening, what, if anything, should society do about it?

• FHI: Who Gets The Benefits Of Artificial Intelligence?
• "AI Designs Computer Chips for More Powerful AI" (GOOG)
• "Inside big tech’s high-stakes race for quantum supremacy"
• Not into quantum computers? Then you've made the decision to be a peasant, working for those who are.
  And the rich get richer.

• "The concentration of economic power has led to spectacular investment returns"
• "An AI payout? Should companies remunerate society for lost jobs?"
• How Amazon Rebuilt Itself Around Artificial Intelligence
• A Very Smart Look at Income Inequality: The Claremont Institute Book Review of "Winner-Take-All Politics: How Washington Made the Rich Richer—And Turned its Back on the Middle Class"
• "Facebook, Google And Amazon Wield Power Over Us All, And Everyone Should Be Worried" (AMZN; FB; GOOG)
• HBR: Corporations in the Age of Inequality — Inequality isn’t just about individuals — it’s risen between companies, too.
• "Why Do the Biggest Companies Keep Getting Bigger? It’s How They Spend on Tech" 

...Much more important than the direct monetization of big data is the strategic advantage it can bestow over time.

In a winner-take-all economy, as in a horse race, small differences in superiority are rewarded all out of proportion to the actual advantage. A top thoroughbred may only be a couple fifths of a second faster than the field but those two lengths over the course of a season can mean triple the earnings for #1 vs. #2.

In commerce the results can be even more dramatic because rather than the 60%/20%/10% purse structure of the racetrack the winning vendor will often get 100% of a customer's business.....

Also 2024's:

The Hyper-Pareto Distribution Of Profits Is Happening Right Now (plus an anniversary)

It's not some cutesy management* fad or pop insight like "Business secrets of Genghis Khan."

To the rich go the profits and internalizing that fact makes the rest of this portfolio construction/fund management/investing stuff easier to conceptualize and execute.

And AI is accelerating the already extant dynamic....

And 2025's:

"The 'new normal' of growth stock dominance"
What our five years of blather regarding advantage flywheels is all about.*

Something like half of the Russell 2000 small caps are unprofitable. Own them at your own risk. 

Hyper-Pareto: "75% of gains, 80% of profits, 90% of capex—AI’s grip on the S&P is total and Morgan Stanley’s top analyst is ‘very concerned’"

This isn't news, the article is six months old, but I pulled it out of the link-vault not because of the scary warning but because the point it illustrates, the concentration of profits in the largest companies is key to understanding the economic and investment landscape. 

(plus, as the kids say, it validates our priors) 

From Fortune, October 7, 2025:  

A top Wall Street analyst has sounded an alarm over the U.S. equity bull market, warning that its remarkable run is built on a precariously narrow foundation: a surge in spending on, and optimistic assumptions about, infrastructure for artificial intelligence (AI). This spending has fueled a boom in the shares of most of the so-called Magnificent 7 and a few dozen related businesses, which have now come to account for roughly 75% of the S&P 500’s returns since the rally of the last few years began. 

The commentary on September 29 by Morgan Stanley Wealth Management’s chief investment officer, Lisa Shalett, frames the current market boom as a “one-note narrative” almost entirely dependent on massive capital expenditures in generative AI, raising questions about its durability as economic and competitive risks start to mount. Shalett’s critique came squarely in the middle of some people in the AI field — and many financial commentators around Wall Street —fretting at market exuberance and beginning to talk openly about a bubble.

In an interview with Fortune, Shalett said she was “very concerned” about this theme in markets, saying her office had broadened from a belief that the market would only bid up seven or 10 stocks to roughly 40. “At the end of the day … this is not going to be pretty” if and when the generative AI capital expenditure story falters, she said. 

Shalett said she’s worried about a “Cisco moment” like when the dotcom bubble burst in 2000, referring to the company that was briefly the most valuable company in the world before an 80% stock plunge. When asked how close we are to such a moment, Shalett said probably not in the next nine months, but very possibly in the next 24. When you look at the actual spending and the amount of capital coming into the space, “we’re a lot closer to the seventh inning than the first or second inning,” she said.

‘Starting to do what all ultimate bad actors do’

Shalett’s comments centered on several recent multibillion-dollar deals to scale up data-center infrastructure. As notable substacker and former Atlantic writer Derek Thompson recently noted in a post titled “This is how the AI bubble will pop,” so much money is being spent to support AI’s energy-consumption needs that it’s the equivalent of a new Apollo space mission every 10 months. (Tech companies are spending roughly $400 billion this year alone on data-center infrastructure, while the Apollo program allocated about $300 billion in today’s dollars to get to the moon from the 1960s to the ’70s.)

What’s more than a little concerning to Shalett is that one company alone, Nvidia—the most valuable company in the history of the world, with an over $4.5 trillion market cap—is at the center of a significant number of these deals. In September alone, Nvidia invested $100 billion in OpenAI in a massive deal, just days after pledging $5 billion to Intel (the Intel agreement was tied to chips, not data-center infrastructure, per se).

Fortune‘s Jeremy Kahn reported in late September on significant concerns about “circular” financing, or Nvidia’s cash essentially being recycled throughout the AI industry. Shalett sees this as a major concern and a major sign that the business cycle is headed toward some kind of endgame. “The guy at the epicenter, Nvidia, is basically starting to do what all ultimate bad actors do in the final inning, which is extending financing, they’re buying their investors.”

Shalett expanded on her concerns by saying that companies around Nvidia “are starting to become interwoven.” She noted that OpenAI is partially owned by Microsoft, but now Nvidia has also made an investment in the startup, while Oracle and AMD each have their own purchasing agreements with OpenAI. But OpenAI also has a data-center deal with tech giant Oracle, with the “bad news,” Shalett notes, that this deal is “totally debt-financed.” OpenAI also struck a deal in October with chip-maker AMD that allows OpenAI to buy up to 10% of AMD. “Essentially, Nvidia’s main competitor is going to be partially owned by OpenAI, which is partially owned by Nvidia. So, Nvidia can ‘own’ a piece of its largest competitor. It is totally circular and increases systemic risk.”

When reached for comment, a spokesperson for Nvidia said, “We do not require any of the companies we invest in to use Nvidia technology.”

Nvidia CEO Jensen Huang discussed the OpenAI investment in an appearance on the Bg2 podcast with Brad Gerstner and Clark Tang on September 25, calling it an “opportunity to invest” and part of a partnership geared toward helping OpenAI build their own AI infrastructure. When asked about the allegation of circular financing in general and the Cisco precedent in particular, Huang talked about how OpenAI will fund the deal, arguing that it will have to be funded by OpenAI’s future revenues, or “offtake,” which he pointed out are “growing exponentially,” and by its future capital, whether it’s raised by a sale of equity or debt. That will depend on investors’ confidence in OpenAI, he said, and beyond that, it’s “their company, it’s not my business. And of course, we have to stay very close to them to make sure that we build in support of their continued growth.”....

....MUCH MORE 

And our priors? From a bit before the Fortune piece was published, July 9, 2025. 

"The 'new normal' of growth stock dominance"
What our five years of blather regarding advantage flywheels is all about.* 

*****

*"Big techs’ AI empire"

The Big Get Bigger: "The trade war uncovers new economies of scale"

This is a corollary of the basic framework for understanding businesses and investing that we've been pitching for the last six or seven years.

If interested see:

Why Do the Biggest Companies Keep Getting Bigger? It’s How They Spend on Tech" 

...Much more important than the direct monetization of big data is the strategic advantage it can bestow over time.

In a winner-take-all economy, as in a horse race, small differences in superiority are rewarded all out of proportion to the actual advantage. A top thoroughbred may only be a couple fifths of a second faster than the field but those two lengths over the course of a season can mean triple the earnings for #1 vs. #2.

In commerce the results can be even more dramatic because rather than the 60%/20%/10% purse structure of the racetrack the winning vendor will often get 100% of a customer's business.....

Competitive Advantage and Feedback Loops

How to Think About Companies: 'Advantage Flywheels'
A very handy conceptual framework first posted after the start of the U.S. lockdowns, April 2020. Schools were closed so it seemed natural to link to a superb mini-MBA module.
Eat your heat out HBR....

****  

....As artificial intelligence comes more and more to the fore, the advantages accruing to those companies that can afford to make use of their data and custom train the machines will act as advantage flywheels that shift the distribution of profits from the normal Pareto: 80% of the loot goes to the top 20% of businesses to perhaps as much as 95% of all the profits going to the top 5% of businesses.

I didn't really mean the "eat your heart out HBR" line.

Here's the Harvard Business Review on this very point:
HBR—From Pareto To Hyper-Pareto: "AI Is Going to Change the 80/20 Rule"

Flywheel Effect: Why Positive Feedback Loops are a Meta-Competitive Advantage

"Analyzing the deepening divide in learning capabilities between a few corporate giants and the rest of the world." (plus advantage flywheels)

"America's Biggest Firms' Moat Is Becoming Impregnable" (TSLA; NVDA; GOOG)
The announcement at the end of August that Tesla was going live with their supercomputer — Elon Got Himself A Supercomputer: "Tesla's $300 Million AI Cluster Is Going Live Today" (TSLA)—reminded me of this piece at ZeroHedge, last month. We'll be back with more on Morgan Stanley's Tesla note later today but for now the TL;dr is "To the victor go the spoils" or "The rich get richer" or "Those who can afford a supercomputer will get closer to discovering the profitability (if any) of AI than those who can't afford a supercomputer."

In Nvidia's World, If You (and your company) Don't Have Money You Will Not Be Able To Compete (NVDA)

The advantage flywheels keep spinning and reinforcing each other to the point that the Pareto distribution of profits - 20% of companies reap 80% of the profits - is becoming Super-Pareto where 5% of the companies reap 95% of the profits and is approaching Hyper-Pareto at maybe 2% of companies reaping 98% of profits.

It all comes down to having the resources to keep up. 

I watched Mr. Huang give the keynote and it's all a bit much to digest before firing out comments that would make any sense at all so here are some of today's headlines to give a taste of what the intro paragraph is based on.

These are Nvidia's press releases via GlobeNewswire....

"Elon Musk says any company that isn’t spending $10 billion on AI this year like Tesla won’t be able to compete" (TSLA)

This.

This is such an important concept to grasp. It's the advantage flywheels, the rich get richer, winner-take-all reality of business in 2024....

The Hyper-Pareto Distribution Of Profits Is Happening Right Now (plus an anniversary)

It's not some cutesy management* fad or pop insight like "Business secrets of Genghis Khan."

To the rich go the profits and internalizing that fact makes the rest of this portfolio construction/fund management/investing stuff easier to conceptualize and execute.

And AI is accelerating the already extant dynamic....

*****

*Although people had been observing and discussing "rich get richer" and "winner-take-all" dynamics for over a century, one of our favorite pointers toward the current situation did come out of a business school. We've been hammering on this for so long that I start to bore myself. Here's a recapitulation from last year, linking to an article that was published seven years ago today:

HBR—From Pareto To Hyper-Pareto: "AI Is Going to Change the 80/20 Rule"

A prescient article from the Harvard Business Review, February 28, 2017:....

*****

Just to reiterate, every incremental advantage that a company can afford does not affect income production in isolation. They accrete in sometimes unforeseeable combinations:

AI: Tesla Installing Second Dojo Supercomputer In New York Gigafactory (TSLA; NVDA)

AI: "Inside Tesla’s Innovative And Homegrown 'Dojo' AI Supercomputer" (TSLA)

It really is a big deal that a company can afford to spend over a billion dollars to build their own supercomputer and it really is a big deal that the same company has all the training data from the billions of miles of real-world driving and it really is a great example of the concept of advantage flywheels and hyper-pareto distribution of rewards, i.e. the rich get richer.

Whether it is going to open-up the $10 trillion addressable market and add the $500 billion of market cap that Morgan Stanley foresees is still an open question....

....As artificial intelligence comes more and more to the fore, the advantages accruing to those companies that can afford to make use of their data and custom train the machines will act as advantage flywheels that shift the distribution of profits from the normal Pareto: 80% of the loot goes to the top 20% of businesses to perhaps as much as 95% of all the profits going to the top 5% of businesses.

I didn't really mean the "eat your heart out HBR" line.

Here's the Harvard Business Review on this very point:
HBR—From Pareto To Hyper-Pareto: "AI Is Going to Change the 80/20 Rule"

And many more. If interested use the 'search blog' box, upper left.

Amazon to invest up to another $25 billion in Anthropic; Anthropic To Purchase $100 billion Of Amazon Web Services; Prime Membership To...

It gets complicated.

From CNBC, April 20:

• Amazon has agreed to invest up to $25 billion in Anthropic, on top of the $8 billion that it has poured into the artificial intelligence startup in recent years.
• As part of the announcement, Anthropic said it’s committed to spending more than $100 billion on Amazon Web Services technologies over the next 10 years.
• Amazon said in February that it expects to shell out roughly $200 billion this year on capital expenditures, with most of that money going toward AI infrastructure. 

Amazon has agreed to invest up to $25 billion in Anthropic, on top of the $8 billion that it has poured into the artificial intelligence startup in recent years, as part of an expanded agreement to build out AI infrastructure.

In the announcement on Monday, Anthropic said it’s committed to spending more than $100 billion on Amazon Web Services technologies over the next 10 years, including current and future generations of Trainium, Amazon’s custom AI chips. Anthropic said it’s secured up to 5 gigawatts of capacity for training and deploying its Claude AI models.

“Anthropic’s commitment to run its large language models on AWS Trainium for the next decade reflects the progress we’ve made together on custom silicon, as we continue delivering the technology and infrastructure our customers need to build with generative AI,” Amazon CEO Andy Jassy said in a statement.

Amazon’s investment includes $5 billion into Anthropic now, with up to $20 billion in the future tied to “certain commercial milestones,” according to a release. The initial investment is at Anthropic’s latest valuation of $380 billion.

Anthropic said in the release that it will bring nearly 1 gigawatt total of Trainium2 and Trainium3 capacity online by the end of the year.

With all of the major hyperscalers competing to build out AI capacity as quickly as possible, Amazon said in February that it expects to shell out roughly $200 billion this year on capital expenditures, mostly on AI infrastructure.

Amazon’s investment lands just two months after the e-commerce giant agreed to invest up to $50 billion in OpenAI, Anthropic’s chief rival. The two AI companies have been racing to convince investors of their strengthening positions ahead of potential IPOs that could land as soon as this year. OpenAI executives have been criticizing Anthropic in recent months for making a “strategic misstep to not acquire enough compute.”...

....MUCH MORE 

We're going to have to update the Advantage Flywheels schematic:

 

In the meantime here are a few posts that tried to explain what was coming. 

July 2018 - Why Do the Biggest Companies Keep Getting Bigger? It’s How They Spend on Tech"   

May 2025 - "Big techs’ AI empire"  

 

...As artificial intelligence comes more and more to the fore, the advantages accruing to those companies that can afford to make use of their data and custom train the machines will act as advantage flywheels that shift the distribution of profits from the normal Pareto: 80% of the loot goes to the top 20% of businesses to perhaps as much as 95% of all the profits going to the top 5% of businesses. 

Okay, more than a few:

"The 'new normal' of growth stock dominance"   

The Big Get Bigger: "The trade war uncovers new economies of scale" 

"The economic divide between big and small companies is growing"

Competitive Advantage and Feedback Loops

Flywheel Effect: Why Positive Feedback Loops are a Meta-Competitive Advantage

"Analyzing the deepening divide in learning capabilities between a few corporate giants and the rest of the world." (plus advantage flywheels)

"America's Biggest Firms' Moat Is Becoming Impregnable" (TSLA; NVDA; GOOG)
The announcement at the end of August that Tesla was going live with their supercomputer — Elon Got Himself A Supercomputer: "Tesla's $300 Million AI Cluster Is Going Live Today" (TSLA)—reminded me of this piece at ZeroHedge, last month. We'll be back with more on Morgan Stanley's Tesla note later today but for now the TL;dr is "To the victor go the spoils" or "The rich get richer" or "Those who can afford a supercomputer will get closer to discovering the profitability (if any) of AI than those who can't afford a supercomputer."

In Nvidia's World, If You (and your company) Don't Have Money You Will Not Be Able To Compete (NVDA)

The advantage flywheels keep spinning and reinforcing each other to the point that the Pareto distribution of profits - 20% of companies reap 80% of the profits - is becoming Super-Pareto where 5% of the companies reap 95% of the profits and is approaching Hyper-Pareto at maybe 2% of companies reaping 98% of profits.

It all comes down to having the resources to keep up. 

I watched Mr. Huang give the keynote and it's all a bit much to digest before firing out comments that would make any sense at all so here are some of today's headlines to give a taste of what the intro paragraph is based on.

These are Nvidia's press releases via GlobeNewswire....

"Elon Musk says any company that isn’t spending $10 billion on AI this year like Tesla won’t be able to compete" (TSLA)

This.

This is such an important concept to grasp. It's the advantage flywheels, the rich get richer, winner-take-all reality of business in 2024....

  "Jensen Huang’s extraordinary interview" (NVDA)

And many more, we are playing for keeps.

The Hyper-Pareto Distribution Of Profits Is Happening Right Now (plus an anniversary)
It's not some cutesy management* fad or pop insight like "Business secrets of Genghis Khan."

To the rich go the profits and internalizing that fact makes the rest of this portfolio construction/fund management/investing stuff easier to conceptualize and execute.

And AI is accelerating the already extant dynamic....

Just to reiterate, every incremental advantage that a company can afford does not affect income production in isolation. They accrete in sometimes unforeseeable combinations.

That's it, business, companies and investing in the 21st century. Learn it, love it, live it.

Or not, your call.

"What S&P Earnings Would Be Without The Magnificent Seven"

The core component in our thesis for investing in the 2020's. Because of  advantage flywheels the companies that can afford to invest in technology will receive a greater and greater (hyper-Pareto) share of any available profits.*

From Investor's Business Daily, January 27:

With four Magnificent Seven companies reporting earnings this week, the group continues to dominate the S&P 500 earnings growth.

As a group, the Magnificent Seven are expected to report earnings growth of 20.3% for the fourth quarter. That dwarfs the 4.1% increase in year-over-year EPS growth of the rest of the S&P 500 index, FactSet Senior Earnings Analyst John Butters said in a report.

Q4 earnings for the entire S&P 500 are expected to grow 8.2%. The top five contributors to the increase include Magnificent Seven members Nvidia (NVDA), Alphabet (GOOGL) and Microsoft (MSFT).

Outside the Magnificent Seven, Micron Technology (MU) is another major contributor to S&P's quarterly earnings. Analysts' consensus profit estimate is $8.20 a share, an increase of 494%, per FactSet. Boeing (BA) is another top 5 contributor, even though the company is expected to post a loss of 44 cents a share — much smaller than its year-ago loss of $5.90.

While profit growth has slowed for most of the Magnificent Seven, their massive scale keeps those companies at the top of the S&P earnings pyramid.

Mag 7 Tower Over S&P 500 
About 80% of the expected S&P 500 earnings growth in the fourth quarter rests on the technology sector alone, LPL Research said in a report. That excludes Alphabet and Meta Platforms (META) (both in the Communications Services sector) and Amazon.com (AMZN) (in Consumer Discretionary).

Excluding automaker and AI company Tesla (TSLA), the six biggest technology and tech-oriented companies are expected to drive over 60% of S&P 500 earnings growth for the quarter by growing earnings an average of 19% each.

"That pace of growth from this group, which may end up north of 25% when all the results are in, will probably more than double the earnings growth rate that the 'S&P 493' will be able to deliver," LPL said in its report.

Growth outside of the top tech-oriented companies has improved slightly in recent quarters. The 493 S&P companies outside the Magnificent Seven grew earnings 11.8% in the third quarter. But the major AI companies may continue to deliver superior growth for at least the next few quarters, researchers added.

Magnificent Seven Earnings This Week 
Four of the Magnificent 7 companies are reporting earnings this week: Tesla, Microsoft and Meta report after the close on Wednesday. Apple (AAPL) delivers results on Thursday. Apple, Meta and Microsoft earnings are seen rising 11%, 2% and 21% respectively. Tesla's EPS is estimated to fall 38%....

....MORE, including a dozen related stories.
*"The 'new normal' of growth stock dominance"

What our five years of blather regarding advantage flywheels is all about...

Many back-links. 

"The economic divide between big and small companies is growing"

But you knew that.* 

From the Wall Street Journal via MSN, December 25: 

It has been a good year for most of America’s biggest companies, with surging profits and enthusiasm for artificial intelligence propelling stocks to record highs. But for many small businesses, it has been just the opposite.

At small businesses, which are unable to withstand economic headwinds as easily as their larger counterparts, years of high inflation, increasingly cautious consumers and tariffs are weighing on earnings and prompting cutbacks. Over the past six months, private firms with fewer than 50 workers have steadily shed jobs, according to payroll processor ADP, cutting 120,000 in November alone. Midsize and, especially, large firms have continued to add jobs.

Cumulative change in employment since Dec. 2024, by firm size

Typically, in early December, Almost Famous Popcorn would have been staffing up for the holiday rush, when the gourmet popcorn company does 60% of its sales.

“In a normal year we’d hire 10 to 15, and this year we’re closer to four or five,” said Sydney Rieckhoff, chief executive of the Cedar Rapids, Iowa-based company. “We’re definitely seeing more thoughtful spending,” she said, with companies placing smaller orders for client and staff gifts.

It has been a good year for most of America’s biggest companies, with surging profits and enthusiasm for artificial intelligence propelling stocks to record highs. But for many small businesses, it has been just the opposite.

At small businesses, which are unable to withstand economic headwinds as easily as their larger counterparts, years of high inflation, increasingly cautious consumers and tariffs are weighing on earnings and prompting cutbacks. Over the past six months, private firms with fewer than 50 workers have steadily shed jobs, according to payroll processor ADP, cutting 120,000 in November alone. Midsize and, especially, large firms have continued to add jobs.

Cumulative change in employment since Dec. 2024, by firm size

Typically, in early December, Almost Famous Popcorn would have been staffing up for the holiday rush, when the gourmet popcorn company does 60% of its sales.

“In a normal year we’d hire 10 to 15, and this year we’re closer to four or five,” said Sydney Rieckhoff, chief executive of the Cedar Rapids, Iowa-based company. “We’re definitely seeing more thoughtful spending,” she said, with companies placing smaller orders for client and staff gifts.

The growing divide between the fortunes of small and large businesses mirrors the divide that has emerged over the past year between low-income Americans and their high-income counterparts. That split among categories of consumers is exacerbating, according to the Federal Reserve’s latest compilation of economic anecdotes from around the country, known as the beige book. “Overall consumer spending declined further, while higher-end retail spending remained resilient,” it said.

The growing divides are also related: Workers at small businesses tend to earn less than those at large companies. And the increases in stock-market wealth stemming from the rally in shares of large, public companies accrue mostly to the rich.

“We’re seeing two different economic realities on both the consumer and the business landscape,” said Bank of America Institute economist Taylor Bowley.

Giant, well-capitalized businesses such as Amazon.com and Nvidia generally have had a very good year. Net income for the large, publicly traded companies in the S&P 500 was up 12.9% from a year earlier in the third quarter, according to LSEG..... 

....MUCH MORE
* This dynamic has been one of our guiding principles for investing in the 2020's. 

April 2023 - HBR—From Pareto To Hyper-Pareto: "AI Is Going to Change the 80/20 Rule"

This type of information advantage is more and more accruing to the biggest and richest of corporations. It is a type of rich-get-richer advantage akin to the flywheel effect.

And related, now that we see what is happening, what, if anything, should society do about it?

• FHI: Who Gets The Benefits Of Artificial Intelligence?
• "AI Designs Computer Chips for More Powerful AI" (GOOG)
• "Inside big tech’s high-stakes race for quantum supremacy"
• Not into quantum computers? Then you've made the decision to be a peasant, working for those who are.
  And the rich get richer.

• "The concentration of economic power has led to spectacular investment returns"
• "An AI payout? Should companies remunerate society for lost jobs?"
• How Amazon Rebuilt Itself Around Artificial Intelligence
• A Very Smart Look at Income Inequality: The Claremont Institute Book Review of "Winner-Take-All Politics: How Washington Made the Rich Richer—And Turned its Back on the Middle Class"
• "Facebook, Google And Amazon Wield Power Over Us All, And Everyone Should Be Worried" (AMZN; FB; GOOG)
• HBR: Corporations in the Age of Inequality — Inequality isn’t just about individuals — it’s risen between companies, too.
• "Why Do the Biggest Companies Keep Getting Bigger? It’s How They Spend on Tech" 

...Much more important than the direct monetization of big data is the strategic advantage it can bestow over time.

In a winner-take-all economy, as in a horse race, small differences in superiority are rewarded all out of proportion to the actual advantage. A top thoroughbred may only be a couple fifths of a second faster than the field but those two lengths over the course of a season can mean triple the earnings for #1 vs. #2.

In commerce the results can be even more dramatic because rather than the 60%/20%/10% purse structure of the racetrack the winning vendor will often get 100% of a customer's business.....

February 2024 - The Hyper-Pareto Distribution Of Profits Is Happening Right Now (plus an anniversary)

It's not some cutesy management* fad or pop insight like "Business secrets of Genghis Khan."

To the rich go the profits and internalizing that fact makes the rest of this portfolio construction/fund management/investing stuff easier to conceptualize and execute.

And AI is accelerating the already extant dynamic....

Just to reiterate, every incremental advantage that a company can afford does not affect income production in isolation. They accrete in sometimes unforeseeable combinations:

How to Think About Companies: "Advantage Flywheels"

A very handy conceptual framework first posted after the start of the U.S. lockdowns, April 2020. Schools were closed so it seemed natural to link to a superb mini-MBA module.  

Eat your heat out HBR....

 *****

As artificial intelligence comes more and more to the fore, the advantages accruing to those companies that can afford to make use of their data and custom train the machines will act as advantage flywheels that shift the distribution of profits from the normal Pareto: 80% of the loot goes to the top 20% of businesses to perhaps as much as 95% of all the profits going to the top 5% of businesses.

I didn't really mean the "eat your heart out HBR" line.

Here's the Harvard Business Review on this very point:
HBR—From Pareto To Hyper-Pareto: "AI Is Going to Change the 80/20 Rule"

July 2025 - "The 'new normal' of growth stock dominance"

What our five years of blather regarding advantage flywheels is all about.....

***** 

"Analyzing the deepening divide in learning capabilities between a few corporate giants and the rest of the world." (plus advantage flywheels)

"America's Biggest Firms' Moat Is Becoming Impregnable" (TSLA; NVDA; GOOG)
The announcement at the end of August that Tesla was going live with their supercomputer — Elon Got Himself A Supercomputer: "Tesla's $300 Million AI Cluster Is Going Live Today" (TSLA)—reminded me of this piece at ZeroHedge, last month. We'll be back with more on Morgan Stanley's Tesla note later today but for now the TL;dr is "To the victor go the spoils" or "The rich get richer" or "Those who can afford a supercomputer will get closer to discovering the profitability (if any) of AI than those who can't afford a supercomputer."

In Nvidia's World, If You (and your company) Don't Have Money You Will Not Be Able To Compete (NVDA)

The advantage flywheels keep spinning and reinforcing each other to the point that the Pareto distribution of profits - 20% of companies reap 80% of the profits - is becoming Super-Pareto where 5% of the companies reap 95% of the profits and is approaching Hyper-Pareto at maybe 2% of companies reaping 98% of profits.

It all comes down to having the resources to keep up. 

I watched Mr. Huang give the keynote and it's all a bit much to digest before firing out comments that would make any sense at all so here are some of today's headlines to give a taste of what the intro paragraph is based on.

These are Nvidia's press releases via GlobeNewswire....

"Elon Musk says any company that isn’t spending $10 billion on AI this year like Tesla won’t be able to compete" (TSLA)

This.

This is such an important concept to grasp. It's the advantage flywheels, the rich get richer, winner-take-all reality of business in 2024....

And many, many more. 

Again: 

• Competitive Advantage and Feedback Loops
• How to Think About Companies: "Advantage Flywheels"
• Flywheel Effect: Why Positive Feedback Loops are a Meta-Competitive Advantage
• "Analyzing the deepening divide in learning capabilities between a few corporate giants and the rest of the world." (plus advantage flywheels)
• "America's Biggest Firms' Moat Is Becoming Impregnable" (TSLA; NVDA; GOOG)

"The Godmother of AI Didn’t Expect It to Be This Massive"

From Bloomberg, November 21:

Stanford scientist Fei-Fei Li talks about teaching machines to see as humans do, the US-China AI arms race, and what worries her about a more automated future. 

AI is now so present in our lives that the story of how it came to be so is receding — that is, if we ever absorbed it properly. It’s a tale of scientists laboring for years in the hope of one day making machines intelligent, and breaking down the components of human intelligence in order to get there.

Stanford University professor Fei-Fei Li was at the forefront of that quest, which is why she has been called the “godmother of AI.” In 2006 she released her academic work on a visual database containing millions of images, and the idea of training computers to “see” as humans do sparked a wave of AI development.

Behind this breakthrough is a woman with an unusual background, one that plays a role in how she sees the world. Li arrived in the US at age 15 when her parents emigrated from China. She spoke little English and had to adjust academically, socially and financially to a new environment; after her parents set up a small dry-cleaning business to make ends meet, she ran it through her college years.

When Li came into Bloomberg headquarters in London, we talked about her personal and professional history, and I found in her a deep sensitivity. Excited about the potential of technology she’s helped create, she also emphasizes human agency — you’ll find her message to parents towards the end. 

This conversation has been edited for length and clarity. You can listen to an extended version in the latest episode of The Mishal Husain Show podcast. 

May I start with this remarkable period for your industry? It’s been three years since ChatGPT was released to the public. Since then there have been new vehicles, new apps and huge amounts of investment. How does this moment feel to you?

AI is not new to me. I’ve been in this field for 25 years. I’ve lived and breathed it every day since the beginning of my career. Yet this moment is still daunting and almost surreal to me, in terms of its massive, profound impact.

This is a civilizational technology. I’m part of the group of scientists that made this happen and I did not expect it to be this massive. 1

¹ Li spoke to us while in London to receive the 2025 Queen Elizabeth Prize for Engineering, alongside Nvidia CEO Jensen Huang and five others. Li has previously written and spoken about what she’s called “the AI winter” of the early 21st century, when those working in the field were getting no attention.

When was the moment it changed? Is it because of the pace of developments or because the world has woken up and therefore turned the spotlight on people like you?

I think it’s intertwined, right? But for me to define this as a civilizational technology is not about the spotlight. It’s not even about how powerful it is. It is about how many people it impacts.

Everyone’s life, work, wellbeing, future, will somehow be touched by AI.

AI Investment Surge
Capital spending on AI-related activities exceeds half of all investment...

*** 

In bad ways as well as good?

Well, technology is a double-edged sword, right? Since the dawn of human civilization, we have created tools we call technologies, and these tools are meant, in general, for doing good things. Along the way we might intentionally use them in the wrong way, or they might have unintended consequences.

In bad ways as well as good?

Well, technology is a double-edged sword, right? Since the dawn of human civilization, we have created tools we call technologies, and these tools are meant, in general, for doing good things. Along the way we might intentionally use them in the wrong way, or they might have unintended consequences.

You said the word powerful. The power of this technology is in the hands of a very small number of companies, most of them American. How does that sit with you?

You are right. The major tech companies — through their products — are impacting our society the most. I would personally like to see this technology being much more democratized.

No matter who builds, or holds, the profound impact of this technology: Do it in a responsible way.

I also believe every individual should feel they have the agency to impact this technology.

You are a tech CEO as well as an academic. Your very young company, little more than a year old, is reportedly already worth a billion dollars.

Yes! [Laughs]

I am co-founder and CEO of World Labs. We are building the next frontier of AI — spatial intelligence — which people don’t hear too much about today because we’re all about large language models. I believe spatial intelligence is as critical [as] — and complementary to — language intelligence. 2

² World Labs raised more than $200 million ahead of its launch in 2024. In a TED Talk she delivered that year, Li said: “If we want to advance AI beyond its current capabilities, we want more than AI that can see and talk. We want AI that can do.”

I know that your first academic love was physics.

Yes.

What was it in the life or work of the physicists you most admired that made you think beyond that particular field?

I grew up in a small, or less well known, city in China. And I come from a small family. So you could say life was small, in a sense. My childhood was fairly simple and isolated. I was the only child. 3

³ Li grew up in Chengdu in China’s Sichuan Province; her mother was a teacher and her father worked in the computer department of a chemicals factory. In her book The Worlds I See: Curiosity, Exploration and Discovery at the Dawn of AI, she linked her professional path to her early years: “Research triggered the same feeling I got as a child exploring the mountains surrounding Chengdu with my father, when we’d spot a butterfly we’d never seen before, or happen upon a new variety of stick insect.”

Physics is almost the opposite — it’s vast, it’s audacious. The imagination is unbounded. You look up in the sky, you can ponder the beginning of the universe. You look at a snowflake, you can zoom into the molecular structure of matter. You think about time, magnetic fields, nuclear.

It takes my imagination to places that you can never be in this world. What fascinates me to this day about physics is to not be afraid of asking the boldest, [most] audacious questions about our physical world, our universe [and] where we come from.

But your own audacious question, I think, was What is intelligence?

Yes. Each physicist I admire, I look at their audacious question, right from [Isaac] Newton to [James Clerk] Maxwell to [Erwin] Schrödinger to Einstein — my favorite physicist.

I wanted to find my own audacious question. Somewhere in the middle of college, my audacious question shifted from physical matters to intelligence. What is it? How does it come about? And most fascinatingly, How do we build intelligent machines? That became my quest, my north star.

And that’s a quantum leap because, from machines that were doing calculations and computations, you’re talking about machines that learn, that are constantly learning.

I like [that] you use the physics pun, the quantum leap.

Around us right now, there are multiple objects. We know what they are. The ability that humans have to recognize objects is foundational. My PhD dissertation was to build machine algorithms to recognize as many objects as possible.

What I found really interesting about your background is that you were reading very widely. And your ultimate breakthrough was possible when you started thinking about what psychologists and linguists were saying that was related to your field.

That’s the beauty of doing science at the forefront. It’s new, no one knows how to do it.

It’s pretty natural to look at the human brain and human mind and try to understand, or be inspired by, what humans can do. One of the inspirations in my early days of trying to unlock this visual intelligence problem was to look at how our visual semantic space is structured. There are so many tens and thousands, millions, of objects in the world. How are they organized? Are they organized by alphabet, or by size or colors? 4

⁴ While doing her PhD at Caltech, Li became convinced that larger datasets would be crucial to AI progress. Later, she was influenced by neuroscientist and psychologist Irving Biederman’s paper on human image understanding, which estimated that the average person recognizes around 30,000 different kinds of objects....

....MUCH MORE 

Earlier on Professor Li:
"Fei-Fei Li’s Startup Allows You to Walk in the 3D World of Edward Hopper Paintings"

The godmother of AI.

From Observer, December 4:

The new startup is working to develop A.I. models with so-called "spatial intelligence."

The startup is turning images of famous artworks like Edward Hopper’s Nighthawks into 3D worlds. 

Scott Olson/Getty Images

World Labs, a startup co-founded by Stanford A.I. pioneer Fei-Fei Li earlier this year that quickly grabbed the attention of high-profile investors, has remained relatively quiet on its products—until now. The startup yesterday (Dec. 3) provided a glimpse of one of its early projects, which takes the form of virtual 3D scenes generated from a 2D image. “This will change how we make movies, games, simulators and other digital manifestations of our physical worlds,” said World Labs in a blog post accompanied by interactive examples of its 3D worlds. The preview shines a light on Li’s larger efforts to develop A.I. models that have “spatial intelligence” and can understand and interact with the real world....

....MUCH MORE

 Ha, that's nothin'. Iowahawk (David Burge) has been inserting himself into Nighthawks for years.

Previously on the good Professor:

November 2016 - Google, Facebook, and Microsoft Are Remaking Themselves Around Artificial Intelligence (GOOG; FB; MSFT)

Fei-Fei Li is a big deal in the world of AI....

May 2024 - "‘Godmother of A.I.’ Fei-Fei Li On Why You Shouldn’t Trust Any A.I. Company"
It's not the technology that should be feared it is the people using the technology.

In March 2016 this seemed noteworthy:
The Hottest PhD Market In the World
From The .Plan: A Quasi-Blog:

Fei-Fei Li, a Stanford University professor who is an expert in computer vision, said one of her Ph.D. candidates had an offer for a job paying more than $1 million a year, and that was only one of four from big and small companies.

--John Markoff and Steve Lohr, NYT, on the brains arms race in artificial intelligence

And in May 2024 this did:
Former Google CEO Schmidt On The Ever-Increasing Tempo Of AI

Gardels: One thing that worries Fei-Fei Li of the Stanford Institute on Human-Centered AI is the asymmetry of research funding between the Microsofts and Googles of the world and even the top universities. As you point out, there are hundreds of billions invested in compute power to climb up the capability ladder in the private sector, but scarce resources for safe development at research institutes, no less the public sector....

....Eventually, in both the U.S. and China, I suspect there will be a small number of extremely powerful computers with the capability for autonomous invention that will exceed what we want to give either to our own citizens without permission or to our competitors.  They will be housed in an army base, powered by some nuclear power source and surrounded by barbed wire and machine guns..... 

Again, only those with massive amounts of cash will be able to maximize the benefits of AI.

See advantage flywheels and hyper-Pareto distribution of profits if interested.

And possibly most important:

March 18 - In Nvidia's World, If You (and your company) Don't Have Money You Will Not Be Able To Compete (NVDA)

So:
"'AI godmother' Fei-Fei Li raises $230 million to launch AI startup"

 

"China Decade of Dominance in EV Batteries" (CATL; BYD; TSLA)

You don't hear much about cobalt any more do you? 

From EETimes, August 25:

Not accidental but the result of a “very smart” long-term strategy, over ten years, to prioritize LFP batteries. 

For over a decade, China has meticulously orchestrated a strategic ascent in the global electric vehicle (EV) batteries market, culminating in a dominance that now presents a formidable challenge to Western manufacturers. 

From government-backed gigafactories to proprietary technology in crucial materials, China has established what one industry expert describes as “almost a moat” around its battery production, leaving Europe and the United States scrambling to catch up.

In an exclusive interview with EE Times, Doron Myersdorf, CEO of the battery technology company StoreDot, offers a stark assessment of the geopolitical and technological landscape. He attributes China’s current position to a “very smart” long-term strategy, initiated over ten years ago, to prioritize Lithium Iron Phosphate (LFP) batteries. 

This foresight capitalized on China’s abundant iron resources and its early development of intellectual property (IP) in producing the composite for liquid fermions.

LFP power play and China’s strategic advantage
China’s calculated shift from Nickel Manganese Cobalt (NMC) to LFP production was not merely a material preference; it was a blueprint for global control. Myersdorf notes that it was “there was a deliberate long-term strategy, conceived a decade ago, to leverage existing supply chains, intellectual property, and operational gigafactories. This foresight has resulted in a global dominance in LFP production today.”

This strategic leverage is evident in the struggles of companies like Northvolt, Europe’s once-heralded battery hope, which, despite significant efforts, was unable to achieve the economies of scale or yield competitive advantages, partly due to its reliance on Chinese equipment and expertise. 

Beyond raw material control, China has innovated within LFP chemistry, significantly improving efficiency. By enabling the use of larger LFP cells—a design not feasible with NMC due to safety concerns—Chinese manufacturers developed concepts like BYD’s blade battery and the “cell to pack,” “cell to chassis,” and “cell to body” designs.

These innovations eliminate modules and their associated overhead, a design inherent to NMC. Myersdorf explains that this combination of factors has effectively created “almost a monopoly on LFP” for China, establishing “like a moat for China in dominance of batteries for at least the next 10 years.”

While NMC still offers better performance for high-end vehicles, providing superior range and fast charging—a segment where StoreDot leverages NMC and silicon to deliver technologies like the Polestar 5, capable of charging in 10 minutes, LFP remains the dominant choice for A, B, and C-segment cars, as well as commercial vehicles, primarily due to cost, with supply almost exclusively coming from China.

Another critical component, graphite for anodes, also sees China holding a significant market share, “controlling over 90% percent of the graphite in the market.”....

....MUCH MORE 

Previously on iron batteries:

Deep Dive: Iron Batteries Crushed The Demand For Cobalt, Reduced The Demand For Nickel

Watch Out Elon, Here Come The Iron Batteries (TSLA)

Tesla's Pivotal Move In Battery Chemistry (TSLA)

"What Tesla’s bet on iron-based batteries means for manufacturers" (TSLA)

 "Tesla will only use iron-based batteries for standard model EVs" (TSLA)

 Batteries: Lithium-Iron may be Competitive With Lithium-Cobalt

Platts' "Commodity Tracker: 5 charts to watch this week"

Batteries: ...The Race to Build Europe’s First Lithium-Iron-Phosphate Battery Gigafactory
Lithium-Iron, it's all anyone is talking about....

"Tesla in talks with China's EVE for low-cost battery supply deal -sources" TSLA)
Well I guess Tony Stark Elon Musk is now officially Iron Man. 

One more from 2018—apparently a great year for Iron Age types while I kept writing Bronze Age on my checks. ("Dad, what's a check?"):

Twenty Month Payback for Tesla 100-MW Utility Scale Battery Storage System
Elon (and Panasonic) may have just found another multi-billion dollar business.
Going forward the chemistry probably won't be Lithium ion, maybe molten-salt or iron based, but the fact TSLA can now pitch this kind of payback probably heralds the beginnings of lithium rush 3.0, or at least the promotion thereof....

And on fast charging:

Seven years ago - "DOE to fund $15M for fast electric vehicle charging research":
The fast-charging ability is going to be crucial for mass acceptance of electric vehicles if they are to be anything more than commuter-type transportation that can recharge overnight at home.

 

Watch Out Elon: Sweden's Polestar Extreme Fast Charging EV Prototype Can Add 100 Miles Of Range In Five Minutes

"China's top EV battery maker announced a breakthrough, but top boffin isn't convinced"

 
Watch Out Elon: "Wireless EV Charging Hits Key Benchmark"

Chinese EV battery maker CATL unveils LFP battery with 1,000 km range

It's not just the 620 mile range. The battery can handle extremely fast charging. From Electrek, also April 25:

CATL unveils world’s first LFP battery with 4C ultra-fast charging for 370-mi in 10 mins

"....that can add 370 miles (600 km) range in 10 minutes..."

And the flywheels? From the time CATL introduced the predecessor to the new battery, July 11, 2023:

"CATL announces new battery with 400 kilometer range on 10 minute charge"
Have I ever mentioned the "Flywheel Effect?"
*****
I think we're witnessing the Flywheel Effect in action at, not just China's but the world's largest battery producer.
Incremental advantages lead to overwhelming business success. I don't know if there are 16,000 researchers in the entire rest of the battery biz. If that's the case, how can they catch up to CATL? 

Amazing what being able to hire 16,000 researchers can lead to,

And just for grins and giggles, from Reuters, April 29, 2024:

CATL boss visits Elon Musk's Beijing hotel on Tesla CEO's surprise trip