Never Waste A Good [Venture] Crisis

A reminder for new readers. That Was The Week collects the best writing on critical issues in tech, startups, and venture capital. I select the articles because they are of interest. The selections often include things I disagree with. The articles are only snippets. Click on the headline to go to the original. I express my point of view in the editorial and the weekly video below.

This Week’s Video and Podcast:

Content of the week from : @CoatsDavid, @lessin, @fintechjunkie, @ericnewcomer, @jordsnel, @scottehartley, @tomerdean, @jason, @DavidSacks, @friedberg, @chamath, @packym, @drewharwell, @TaylorLorenz, @pmarca, @elonmusk, @x, @HollyEmblem, @ashleynbelanger, @WhiteHouse, @Fauza4IR, @aidanfitzryan, @adhutchinson, @SharonWrobel1, @restofworld, @anothercohen



Essays of the Week

Venture Capital — We’re Still Not Normal – @CoatsDavid

Seed investing can’t turn back on – @lessin

The Broken Venture Value Chain – @fintechjunkie

Here Are The Venture Capital Firms That Are Investing Much Less – @ericnewcomer

Indexing Venture and Other Fool’s Errands – @jordsnel

Manager Selection in Venture Capital – @scotthartley

The meeting that showed me the truth about VCs – @tomerdean

All-In Podcast on the venture business – @jason, @chamath, @DavidSacks, @Friedberg

In Defense of Strategy – @packym

The creator economy was already exploding. Then Hollywood went on strike. – @drewharwell, @TaylorLorenz

Video of the Week:

Marc Andreessen on Why Elon is Special – @pmarca

AI of the Week

A Case for Heuristics: Why Simple Solutions Often Win in Data Science – @HollyEmblem

OpenAI, Google will watermark AI-generated content to hinder deepfakes, misinfo – @ashleynbelanger

Fact Sheet: Biden-⁠Harris Administration Secures Voluntary Commitments from Leading Artificial Intelligence Companies to Manage the Risks Posed by AI – @WhiteHouse

News Of the Week

Sam Altman’s biometrics-based cryptocurrency Worldcoin is now live – @Fauza4IR

How Sam Altman’s Worldcoin Engineered Its Token Launch – @aidanfitzryan

Elon Musk Says the Twitter Brand Will be Retired, Renamed ‘X’, Very Soon – @adhutchinson

Almost 70% of Israeli startups act to shift funds, relocate due to judicial shakeup – @SharonWrobel1

Startup of the Week:

Cafe Cyberia – @restofworld

Tweet of the Week:

Not the X Designer – @anothercohen


So, I could write about X (see this week’s news) or Worldcoin. I’m in favor of both.

But this week saw a torrent of excellent writing about venture capital, particularly about the seed stage. It gave rise to this week’s title – Never Waste a Good [Venture] Crisis – loosely modeled on Winston Churchill’s famous utterance. These writers are being forced by circumstance to question everything, and that is a wonderfully creative time.

This week’s Essay of the Week was hotly contested, but I place Correlation Ventures David Coats’ essay “We’re Still Not Normal” in first place.

Sam Lessin’s essay about the end of seed investing, @fintechjunkie’s X thread on the broken value chain in venture capital, and Packym’s essay on strategy are all excellent. There are eight venture-related pieces, all substantial, thoughtful, and challenging.

We’re Still Not Normal is a clever title that points to the fact that almost all returns from venture capital come from successful outliers – what is called the ‘power-law.’

U.S. venture continues to be a hits-driven business. Overall industry returns, and most fund returns, are driven by the relatively small percent of outcomes that are the winners.

From the point of view of Sam Lessin, even this truth is now going to be called into question. He focuses on the “factory” model of seed-stage investing:

About 15 months ago I wrote a post on how seed investing was pretty clearly going to be in an 18 month timeout … that the capital ‘factory’ line would be shutdown until the inventory of dramatically over-marked late-stage private deals got worked through / washed out / expired on the line.

This is basically how the world has looked for the last almost year-and-a-half

Now, 15 months later, he doubles down on that point of view:

The thing I think seed investors need to come to terms with at this point, is that this isn’t an 18 month timeout, it is likely much much longer — and perhaps what even the death of systematic / thematic seed investing as we knew it between 2010-ish and 2022-ish…

Really, it was the Snap-Allbirds-Robinhood-Lyft-Box-Dropbox-Buzzfeed-Zoom-Oscar-BlueApron etc. Etc at deca-billion outcomes that made all the math work for seed … and it turns out that those companies just relatively aren’t work that much (some less than capital invested!)

But will clubby seed investing on a capital pipeline through series A to Z firms to public exist in the future — I actually think no… will the YC playbook of how to start a company and finance it work any more? IMHO certainly not — I think the whole factory is going to need to be shut-down and reconstituted.

“The whole factory is going to have to be shut down” is a strong statement, but it is driven by the belief that I wrote about last week – later-stage capital, and public markets, are not going to pull early-stage bets into giant-sized rapid outcomes. The entire value chain is broken. If the big checks are gone, then the growth is gone.

@fintechjunkie has a long X thread spelling out the details. After outlining the “old normal” in VC, he says:

Making matters worse, valuations were much higher during this period which brings into question how many 3X+ funds there will be in the 2017-2021 vintages. And we’re already seeing markdowns and write-offs that highlight the issue.

His point is that 2017-21 investments will not produce the expected returns, so LPs will be unable to allocate to the next vintages.

Many underperforming VCs will have to reduce their fund sizes and many funds with limited track records or undifferentiated strategies will shut down. And companies will have to be built more efficiently and raise at more reasonable valuations. They’ll be designed knowing that capital is scarce and scaled with capital efficiency top of mind.

Eric Newcomer’s data on who is and who is not investing is full of insights. Jordan Nel of Hummingbird Ventures reinforces the analysis by focusing on the crazy idea that venture capital can be invested in like an index. He points out that the power law of returns means that a venture capital index would rely on a very small number of winners.

Firstly, the power law applies to both managers and their portfolios. Trying to index a power law without access to, or knowledge of, the top 1%, will leave you with very mediocre returns.1

Secondly, most attempts at indexing are done with what has worked in mind. But what has worked isn’t usually what will work. The market is too efficient and funds swell too quickly. New LPs won’t have the same asymmetry the old ones did.2

All of the articles mentioned above and linked below have solutions and remedies. I agree with some and less with others. But the drive to think, and act, is the right response to a difficult market. The only alternative is to be a victim, and there will be many of those.

Much of the narrative describing how things are is accurate. It is also why finding the outliers is crucial to venture success. Seed fund managers are the core of that process, and the best of them are very good at it. Indeed, only seed managers can solve the problem. They are the earliest spotters of future behemoths. Sam Lessin is right that YC-style factory investing will make less sense as later-stage capital is harder to find and slower to deploy at compressed valuations.

The value will still flow to the best “pickers.” And they will excel at being one step ahead of innovation and finding the founders who represent what comes next.

More in this week’s Video and Podcast

Essays of the Week

Venture Capital — We’re Still Not Normal

David Coats

Published in VC by the Numbers

One graph from our proprietary dataset has consistently received the most interest over the years. Some of our VC peers have requested it for their LP communications, universities have requested it for research and course materials, and it’s been published in several books.

We most recently published this graph in a 2019 blog post called “Venture Capital — No, We’re Not Normal.” Particularly given the changes that have occurred in U.S. venture in the past few years, we thought it would be helpful to provide an updated version:

The distribution of outcomes in U.S. venture is still far from a “normal” distribution. It remains highly right-skewed in that a relatively small number of winners drive returns. Less than 4% of the capital invested into venture-funded companies exiting over the last decade generated a 10X or greater multiple, while thirty-seven percent generated a less than 1X return (i.e., lost money).

The distribution is even more skewed when we calculate it by financings rather than dollars. For example, nearly half of financings lost money for investors over the past decade.

So how have these results changed over time, and how do the last few years look in an historical context?

The green line in the graph below plots the percent of invested dollars by exit year that realized a greater than 10X return (the “winners”), while the black line plots the percent of invested dollars that realized a less than 1X return (the “losses”).

Our takeaways from this analysis are:

Consistent with the experience of many VCs and LPs during the early 2000’s, the “Dot Com Bust” was a challenging time in which to harvest portfolios as there were few winners and the vast majority of invested dollars resulted in losses.

From the 2008 Financial Crisis through around 2012, the risk/return profile of realized venture investments steadily improved, with the percent of invested capital in winners increasing and in losers decreasing. These statistics have remained relatively constant since then.

The pandemic years (2020 and 2021) were glaring exceptions. While the economy suffered, venture thrived. These two years were “off-the-charts” in terms of both much higher percent winners, and much lower percent losses, than we’d seen historically.

The distribution of outcomes that we saw last year, despite feeling like a “reset”, was only a reset when compared with the exceptional pandemic years. The statistics last year were very similar to what saw over the prior decade.

The data for 2023 is too limited so far to draw solid conclusions. However, early indications are that we might see a more significant reset. Also, while not plotted on the graph, we found it interesting that the number of companies that exited peaked during the Dot Com Bust, steadily declined to a low point during the 2008 Financial Crisis, and then has steadily increased each year since then, with 2021 and 2022 being the two largest exit years on record.

U.S. venture continues to be a hits-driven business. Overall industry returns, and most fund returns, are driven by the relatively small percent of outcomes that are the winners.

Seed investing can’t turn back on unless the public market changes how it values ‘run of the mill’ tech companies. And that ain’t happening.

Posted by Sam Lessin

Intern – Slow Ventures

About 15 months ago I wrote a post on how seed investing was pretty clearly going to be in an 18 month timeout … that the capital ‘factory’ line would be shutdown until the inventory of dramatically over-marked late-stage private deals got worked through / washed out / expired on the line.

This is basically how the world has looked for the last almost year-and-a-half with the noted exception of an AI ‘death spasm’, where a bunch of funds decided to pour untold amounts of capital into AI companies on the factory model they were used to (with even higher valuations and more hype!)

The thing I think seed investors need to come to terms with at this point, is that this isn’t an 18 month timeout, it is likely much much longer — and perhaps what even the death of systematic / thematic seed investing as we knew it between 2010-ish and 2022-ish…

Why? because run-of-the-mill public tech companies just aren’t worth that much it turns out – and if the bulk of so-called unicorns can’t get public / or do and are disappointing, the whole model of seed investing starts to look way way less attractive as an asset class.

Shoot the Moon vs. Mars

Tech has undeniably produced in the last several decades a few of the most important companies in the world… Microsoft, Apple, Oracle, Adobe long ago.. Google, Facebook, and Tesla in professional generational memory… you want to be invested in those if you can / obviously.

But, even seed investors can’t really make the numbers work at any scale having everything fail but 1 in a thousand companies / plays… (the last person that made that even marginally work was Ron Conway, who in his early fund had all zeros but then a tiny tiny slice of google that paid for everything else – as the story goes)…

you can be playing ‘shoot mars’ in thesis, but if you really don’t get paid on hitting the moon instead, the probability math of mars just doesn’t work.

Practically — seed investing from 2010 – 2020 worked in theory because you could ‘stamp out’ good companies that could get public as unicorns on not too much capital invested, and then every once in a few funds if you are lucky you get Yahtzee on a winner, which is capital efficient enough to not dilute you to all hell.

Really, it was the Snap-Allbirds-Robinhood-Lyft-Box-Dropbox-Buzzfeed-Zoom-Oscar-BlueApron etc. Etc at deca-billion outcomes that made all the math work for seed … and it turns out that those companies just relatively aren’t work that much (some less than capital invested!)

So what happens?

Will seed investing still exist… absolutely. Are there big opportunities to start new businesses. Yes. I think so.

But will clubby seed investing on a capital pipeline through series A to Z firms to public exist in the future — I actually think no… will the YC playbook of how to start a company and finance it work any more? IMHO certainly not — I think the whole factory is going to need to be shut-down and reconstituted.

What will take its place? Well, I think we will be back to where seed investing was before the last decade … which is high risk capital owning lots of high risk ventures — and those ‘high risk ventures’ in general will be tuned to build sustainably big businesses that owners and operators will want to own and operate vs. just packaging for the next buyer.

Some of those owner and operated companies will end up getting very very large — and given the amazing platforms that now exist in the world to scale businesses — some of them will get very large very quickly — creating tons of value and eventually being the large profitable high growth companies that public shareholders want to own! Yay liquidity!

But seed investors of the future aren’t going to be in the game of packing things for series A, and they will be investing in novel important crazy ideas where they – along with the founders – are going to be very happy to own for a very very long time.

The Broken Venture Value Chain

Here Are The Venture Capital Firms That Are Investing Much Less

Tiger, Index & Insight Rank Among Firms That Most Dramatically Slowed Investing Pace. Y Combinator & Sequoia top resilient list.


It can be difficult to know which investors are really open for business.

As the startup slowdown drags into its second year, a number of investors have quietly gone dark, cutting down on their investments and taking long and lazy summer vacations.

Some venture capital funds will never raise another funding round. Venture capital firms die slow deaths.

Crossover funds can be fair-weather friends.

Other firms will live to fight another day, but are being much pickier about what checks they write.

I’ve got my hands on a list of ten investors that have slowed down the pace of their investing most dramatically.

I reached out to some of the firms who made the list to understand why they’d curbed their dealmaking of late.

Slow Ventures ranks third on a new list of venture capital firms that had most dramatically slowed down their pace of investing in the past six months relative to the 12 months before that.

Managing partner Sam Lessin wrote me an email about their high ranking with the subject line, “pace lol.”

He wrote, “it is easy to understand  … we think seed investing in AI is for suckers.”

Slow Ventures’ Kevin Colleran, who manages the firm’s relationship with its limited partners, hopped on the phone with me to explain Slow’s slowdown.

“We’ve made a specific choice not to chase AI right now and I think the majority of activity that other firms are doing are AI,” Colleran said. (Lessin has called generative AI “fools gold” and has written that “seed investing isn’t coming back … at least not as it existed in the last decade.”)

Colleran explained that outside of artificial intelligence deals, “there’s little-to-no signal about what unlocks a Series A term sheet these days.”

“We like to do investments when we have good signal from the Series A market,” Colleran said.

Even as the NASDAQ Composite has climbed 35% so far this year, the startup ecosystem remains in a weird place.

Generative artificial intelligence companies — the sort of startups that Slow is avoiding — have raised humongous fundraising rounds, gobbling up a large share of the venture market. (The $25 billion AI companies raised in the first half of this year accounted for 18% of global funding, according to Crunchbase.)

Meanwhile, many other startups, including software startups and remote work-oriented companies, have seen investors sour on their high-multiples and aggressive cash burn.

Rising interest rates and limited partner scrutiny on venture capital firms has put a damper on much of the startup ecosystem. There are many startups valued in excess of $1 billion that seem ill-equipped to show profitability.

Source: Coatue via The Information

AngelList — which sees a large volume of early stage funding rounds, including deals that go unannounced for many months — is tracking investor activity closely. The number of active investors has fallen by roughly 20% compared to what was typical in 2019 and 2020.

For a firm to be considered active, they need only have invested in one deal visible to AngelList in the past six months. The percentage of active co-investors has fallen from about 75% active in 2019 and 2020 to about 60% active.

Source: AngelList

As I was looking into which firms slowed down their pace of investing, AngelList provided me with two lists that reflect the activity levels of individual venture capital firms based on the number of deals they’re doing.


One list shows the firms that have slowed down their pace of investing the most in the past six months relative to the 12 months before that. Global Founders Capital, Tiger Global Management, and Slow Ventures rank 1st, 2nd, and 3rd on that list. (Paying subscribers can see the full list below.)

Then, AngelList created a second list: the firms that have proved most resilient by maintaining an investing pace in the past six months most similar to their pace in the 12 months prior. Y Combinator, Sequoia Capital, and Unpopular Ventures came in 1st, 2nd, and 3rd. (Paying subscribers can see the full list below.)

Top Ten Biggest Drop-Off in Investment Pace

Global Founders Capital

Tiger Global Management

Slow Ventures

Tribe Capital

Index Ventures

Insight Partners


Coatue Management

Soma Capital


Most Resilient

Y Combinator

Sequoia Capital

Unpopular Ventures


Boost VC

Nexus Venture Partners

South Park Commons

Andreessen Horowitz

General Catalyst

Fifty Years

AngelList’s head of data science Abe Othman, who compiled the data, wrote me in an email:

Over the past year I’ve noticed a lot fewer responses from VCs when I try to broker introductions to startups raising money. Not “no thanks, not for us” but just silence.

We can’t know for sure but early-stage investment activity appears to have dropped about 40% over the past year. Our data also suggests that about 20% of early-stage investors have completely fallen off the map and have stopped making any new investments.

Some of the investors with the biggest drops in recent deal counts have been public with their struggles and are not surprising to see. However, there are a handful of names here that I still see regularly on founders’ desired introduction lists. It’s my hope that by sharing the information we can glean from our enormous timely database of early-stage venture investments we can help save founders time and emotional energy as they raise money.

It’s also interesting to look at the flip side: those investors that have maintained or increased their recent investment volume. We can still see pockets of strength — accelerators, India, deep tech, AI — in what has been the worst early-stage venture market since AngelList started doing investments more than ten years ago.

Indexing Venture and Other Fool’s Errands

Why most fund of funds aren’t worth the fees – embracing nomadism – good seed investors don’t compete for deals – looking for bottlenecks – and napkin art!


JUL 21, 2023

Jordan’s writings
Indexing Venture and Other Fool’s Errands
The point of this essay is to explain why venture is different from other asset classes (you cannot “index” it) why many fund-of-funds aren’t worth the fees (they try to index it) why some fund-of-funds are (they concentrate where others don’t…
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The point of this essay is to explain

why venture is different from other asset classes (you cannot “index” it)

why many fund-of-funds aren’t worth the fees (they try to index it)

why some fund-of-funds are (they concentrate where others don’t)

Pledge your support

It’s a mistake to think of venture like other asset classes.

Firstly, the power law applies to both managers and their portfolios. Trying to index a power law without access to, or knowledge of, the top 1%, will leave you with very mediocre returns.1

Secondly, most attempts at indexing are done with what has worked in mind. But what has worked isn’t usually what will work. The market is too efficient and funds swell too quickly. New LPs won’t have the same asymmetry the old ones did.2

Avoiding overly efficient markets and concentrating on spaces with asymmetric upside (usually the emerging domains others aren’t investing in) is one of the few ways a fund of funds can justify their fees.

If a fund of funds is even 15% better than their LPs, picking top decile rather than top quartile managers, the return difference is huge. Source: Morgan Stanley & Pitchbook (4Q22)

The thing that makes venture such a rough asset class is also what makes it so appealing. At the earliest stages of a company’s life the asymmetry in investing in it is the highest. Here information is murky, it is harder to distil signal from noise, networks matter more, and as prices are lower you have the most amount of upside potential.

The earlier you can source, pick, and win a great founder over, the better your returns will be. But everyone else is trying to do the same. Usually you have to see something they don’t in either the product, market, or person. This is how the best seed funds differentiate themselves – they pick differently.

The gap to do this is not long-lasting. The window of arbitrage opens and closes as firms move in and out and folk take on different risk profiles to avoid the competition. Some sectors (such as neobanks and consumer marketplaces) have lost a lot of the arbitrage in the last decade. Big funds have come earlier and applied a standard-higher pricing, the number of GPs have increased, and folk know what underwriting lens to apply. I wrote about this in a previous essay.

These dynamics – the asymmetry of the early stage and arbitrage of different picking – are what many of the top 1% of investors capitalise on. Either they cement themselves as the best in that sector (think Alfred Lin and SaaS) and reap the rewards of the asymmetry by virtue of their brand, or they move on to arbitrage new hunting grounds before the window closes. Sometimes it’s a mix of both. Either way, the best seed investors don’t really compete for deals.3

Most investors struggle with the tension between this constant re-invention and dominating a space. This, I suspect, is why less than half the “good” ones stay good. They overestimate their domination and underestimate the speed at which their knowledge and networks are arbitraged. It is easy to tell yourself, as prices creep up, that “venture is still asymmetric, this is just the market as it is, my LPs pay me to deploy”.

The math gets really hard really quickly. As prices rise, a fund’s portfolio moves from convex (unbounded upside, bounded downside) closer to a concave profile (trimmed upside given the opportunity is priced in at entry valuations).

This, I also suspect, is why it’s nearly impossible to index venture. Most funds can’t capitalise on the asymmetry to begin with. Those who can, usually only do it for one or two vintages. If a fund manages to do well over multiple cycles, they inevitably become access constrained and out of reach for most LPs.

So most LPs are forced to try index the top quartile funds. They don’t know what it looks like to pick differently, and so need to rely on track records and brand to judge funds. Only looking at what has worked will almost never get you into funds above top quartile. Because of that, most people will continue to lose money in venture.4

Most fund-of-funds can’t justify the fees they charge.

They’re expensive, too diversified to capitalise on great funds, and anchor their value prop around diversification and/or access. Most are ossified, have no underwriting edge of their own, don’t have real access and invest through the rear-view mirror. If your goal is a diversified spread of top quartile funds, then you’re may not know it but you’re trying to index venture.

If you are adversely selected out of the well-known high-performing funds and you can’t pick the right lesser-known ones, then your diversification is worse than market beta. Say you take a public market index, for example the S&P 500, and you remove the 7 best performers, you net nearly zero year to date. Venture is far, far more power law than the public market – removing the top performers removes almost all the performance.

So what do you do to try and find the outliers?


Manager Selection in Venture Capital

Backing Mean, rather than Median, Managers is Good Enough


The Power Law, popularized by investor Peter Thiel and then immortalized into the eponymous book title by author Sebastian Mallaby, drives venture capital returns. Venture capital empirically operates according to this principle, with singular outliers in most portfolios returning more capital than the entire portfolio’s remainder. Those VC managers who wish to outperform are therefore almost entirely beholden to not just the existence of the outlier they back, but to its scale and amplitude.

“The biggest secret in venture capital is that the best investment in a successful fund equals or outperforms the entire rest of the fund combined. This implies two very strange rules for VCs. First, only invest in companies that have the potential to return the value of the entire fund. This is a scary rule, because it eliminates the vast majority of possible investments. (Even quite successful companies usually succeed on a more humble scale.) This leads to rule number two: because rule number one is so restrictive, there can’t be any other rules.” – Peter Thiel

Everywhere with Scott Hartley
Manager Selection in Venture Capital
The Power Law, popularized by investor Peter Thiel and then immortalized into the eponymous book title by author Sebastian Mallaby, drives venture capital returns. Venture capital empirically operates according to this principle, with singular outliers in most portfolios returning more capital than the entire portfolio’s remainder. Those VC managers who…
Read more

The other great truth, called out by Level Ventures’s Jake Kupperman in his comprehensive piece which we’ll further explore below is the notion from Michael Mauboussin that, “A lesson inherent in any probabilistic exercise: the frequency of correctness does not matter; it is the magnitude of correctness that matters.” In other words, even though many if not most of pre-seed investments will go to zero, the log-normal, or long tail distribution of outcomes means that Power Law, and the magnitude of that outlier, is really what matters in early-stage investing.

Percentage of zero-return companies by vintage (Source: Level Ventures)

Pundits also point to the rising nominal interest rate environment and pose the rather drab and predictable question, “with risk-free returns going up, why would anyone invest in venture capital?” The answer I usually give first points out that the risk-free interest rate is actually the nominal rate minus the inflation premium, and at least based on my own experience of CPI it’s a rather glib figure that factors out the real costs of life in a policy-convenient way so as to hoodwink the majority. So the real risk free rate of return isn’t as large a plate of free lunch as one might think.

The second point I make is that there is very little dispersion in the risk-free rate of return, in other words mean and median are identical, but the dispersion in venture capital returns is massive. The difference between an under-performing and an over-performing VC manager can be significant. Moreover, the distribution of venture returns is not Gaussian or “Normal.” It’s positively skewed, with outlier managers significantly outperforming the median managers. In other words, the Mean performance is many levels higher than the Median performance in venture capital.

Dispersion of venture capital returns vis-a-vis other asset classes. (Source: Nomads)

Abe Othman, head of Data Science at AngelList published a study in 2019 demonstrating that by making a higher (n) number of bets significantly increased the chance of getting mean, rather than median returns, in venture capital. So if you’re a manager trying to outperform, taking more shots on goal is an effective strategy. My co-founder Jenny Fielding and I have discussed this for years, and this is the reason why we’ve written one check every five days for the last half decade. This is a cadence that indexes around 8 percent of companies we’re introduced to by a founder in our community. We’ve invested about 400 times out of about 5,000 opportunities. You have a greater chance of finding a successful company, and the amplitude of that winner will determine the extent to which the Power Law holds true, with that one winner being more valuable than the remainder of your venture portfolio.

Mean manager performance heavily outperforms Median performance.

For LPs, particularly funds of funds backing numerous managers, they also focus on this notion of differentiating between Median and Mean managers. By looking at what differentiates a manager insofar as how they Source, Select, and Support, LPs can determine if a manager has some, or many, characteristics to outperform others. LPs need not have to predict the future of which managers will perform best; they simply need to back a portfolio of managers who have the right characteristics to outperform. Performance dispersion is so wide, and the positive skew so great that the Mean performance is multiples of the Median. In fact, Morgan Creek has done research that suggests that the mean performance of the Top 50% of venture funds exceeds the top-quartile of all VC funds. This again, is because of the skewness, and how much top performing managers outperform. The average of their performance is better than the bottom 75% of firms. The argument for “why invest in venture capital” is clear if LPs can identify a few key characteristics to identify and isolate better managers. Then they only need the average of those managers to outperform the top quartile of firms. And top quartile venture capital returns far outpace alternatives in equities or fixed income, making VC a worthy allocation strategy. Of course if you’re unable to access or select for outlier manager performance, you’re also probably better off consolidating your capital in asset classes barely-shielded from inflation. As with many things, it comes down manager selection access, process, and execution.

Illustrative chart modified from Frank Tanner’s work at Morgan Creek.

The team at Hummingbird VC have titled these fund outliers “nomads,” and built a fund of funds around it to target funds that look distinctly different. These are decidedly not your household names, because to find true alpha you need to be non-consensus, meaning you stick out. And you need to be correct. So outlier funds will, by definition, be the odd balls, those that come across as a bit strange. As entrepreneurs ourselves, the best fund managers probably won’t shy away from this. At Everywhere Ventures, for one, I heard a panelist recently state, “we would never back a global generalist pre-seed fund,” and the room broke into laughter. This is exactly what we do, and we’re not afraid to be contrarian. That statement didn’t make me question what we do; it bolstered my confidence because we have a model that uniquely allows us to do this unlike just about any other firm. This irreverence, and self-belief is what we look for in startup founders, and it’s certain to be a characteristic in nomadic, truly differentiated fund managers. Jordan Nel at Nomads and Hummingbird VC has written an excellent summary of this.

So if you’re a VC manager what should you do?

Focus on what differentiates you from other managers in how you Source, Select, and Support. This is how you can differentiate from the Median.

Your irreverence, your uniqueness, is your comparative advantage.

Make a high number of investments to maximize your chance of Power Law distributions whereby one investment is worth as much as the remainder. This statement itself is irreverent in a high ownership-consensus world.

Recognize that many early-stage bets won’t work out, but you’re trying to maximize the existence, and amplitude, of a few outliers.

And if you’re an asset manager or LP making fund investments?

Focus on trying to back truly unique managers, as they have a greater likelihood of being outliers in terms of performance. These are your nomads.

Data suggests that the highest returns are pre-seed and seed investments, and managers selecting from within this stage are most likely to outperform later stage and growth returns (as is a function of entry valuation). Moreover, emerging managers (on funds I or II, or consolidating managers on funds III or IV) tend to outperform, but it’s hard to select them from the nearly 3,000 funds that have been raised since 2018. As such backing funds of funds may be the best strategy rather than selecting managers yourself if you don’t truly have great access.

You don’t need to be able to control everything or predict the future. You simply need to be able to isolate and identify characteristics that differentiate.

Back a small basket of funds of funds with great access, or if you can go directly, build a portfolio of emerging managers taking novel approaches, and back a variety of strategies such as ownership heavy, or high volume portfolios. As suggested above, earlier-stage, and earlier-vintage managers generally perform better than higher AUM funds particularly after Fund V (just about when you know their name, and all your peers give you more confirmation bias). Again being both contrarian, not consensus, and right is how you make alpha.

The question of what characteristics drive alpha is well trodden, and Heather Hartnett, founder of Human Ventures, has done a good job laying it out in her recent Forbes piece on “alpha generators.” There are over 2,700 VC managers with under $100 million AUM, predominately focused on the early stage. Many of them are known as “emerging,” but she makes the point that these managers who have deep networks, access to accelerators, and a core proposition for why they are accretive to the industry, providing something different, might be better called “alpha generators.” After all, if LPs can identify such characteristics to select top half managers, because of the highly skewed distribution this fact alone will allow them to isolate and consistently achieve top quartile venture returns outperforming other asset classes.

The meeting that showed me the truth about VCs

Tomer Dean3:00 PM PDT•June 1, 2017


Tomer DeanContributor

Tomer Dean is a serial tech entrepreneur currently based in Tel Aviv. He is co-founder and CEO of Bllush.

I recently had a meeting with a well-known Israeli startup investor. The talk somehow pivoted from my seed-seeking startup into talking about the macro view of venture capital and how it doesn’t actually make sense.

“Ninety-five percent of VCs aren’t profitable,” he said. It took me a while to understand what this really means.

I’ll clarify: Ninety-five percent of VCs aren’t actually returning enough money to justify the risk, fees and illiquidity their investors (LPs) are taking on by investing in their funds.

Who’s actually succeeding in making money?

A VC fund needs a 3x return to achieve a “venture rate of return” and be considered a good investment ($100 million fund => 3x => $300 million return). The graph below shows what percentage of VC firms accomplish this. As we can see, only the small green slice is bringing it home. The other 95 percent are juggling somewhere between breaking even and downright losing money (remember to adjust for inflation).

Source:  Money Talks, Gil Ben-Artzy

The graph was hard for me to take in at first. But once you run the numbers, it all makes sense. I’ll attempt to reconstruct the arguments leading to this hard-to-grasp realization of an industry so often idealized from the outside. Ready? Let’s have some fun.


Before starting, let’s define what success and failure actually mean and list our assumptions:

Success = 12 percent return per year

Venture capitals get their money from limited partners, who are usually traditional investors such as banks, institutions, pension funds, etc. In their eyes, throwing $50 million into a startup fund is “risky” business compared to their other options, such as the stock market/real estate, which are lower cost, liquid and could “safely” return 7-8 percent per year. For them, 12 percent return on their money per year is good. Anything below that? Not worth the high risk they’re taking.

That brings us to…

A 10-year fund needs to return 3x the fund size

We agreed VCs need to earn 12 percent return a year, right? Most funds, while only actively investing 3-5 years, are bound to 10 years. Many newer studies are showing that 12-14 year funds are more accurate for today, but let’s stick with 10 just to give the VCs a fighting chance. That annual 12 percent rapidly grows, showing the power of compounded interest. Let’s see the math:

Don’t forget Pareto: 80 percent of returns come from 20 percent of startups

Facts of life are that startups are hard. Breaking even is hard. Profits are hard. Keeping profits growing year over year (YoY) is even harder. Out of 10 companies, only two will really explode and IPO/M&A, giving our dear VCs some of their money back. The rest, as we’ll see, will fizzle out and die — or have a small liquidation event, which is pretty much the same.

Let’s start

So we have 10 startups and a fund that needs to return 3x within 10 years. Let’s assume it’s a $100 million fund, with $10 million invested in each company over the course of its life and a desired return of $300 million. To be fair, let’s also assume the VC jumped in on the A round, followed up on B and has 25 percent ownership at the end, with non-participating liquidation preferences.

Let’s look at a few different outcomes of our 10 startups after 10 years…..

All-In Podcast on the Venture Business

In Defense of Strategy

Not Boring by Packy McCormick
In Defense of Strategy
Welcome to the 579 newly Not Boring people who have joined us since last Tuesday! If you haven’t subscribed, join 208,497 smart, curious folks by subscribing here…
Read more

There’s a belief in tech that execution is all that matters, that strategy is for wimpy MBAs. 

That belief is wrong, and I have the scars to prove it. 

Before Not Boring, I worked at a flexible workspace startup called Breather. I’ve written about my time there before. We ran a well-oiled machine across 500 spaces in 10 markets with bookings by the hour, non-stop operations, the best tech in the industry, and an NPS consistently in the 70s and 80s. We were great at some things and bad at other things, but one thing was undeniable: we could fucking execute.

And yet, we failed. After raising $120 million, we sold for $3 million in 2021. What killed Breather wasn’t a lack of execution. It was bad strategy

Execution without strategy is wasteful and tragic. Just as “Companies that have the best products, most talented people, and fastest growth are precisely the ones for which moats are most important,” companies that are the best at execution are precisely the ones for which strategy is most important. They’re the only ones that have a shot. 

The better you are at execution, the faster you can run in any direction. A good strategy helps you run fast in the right direction. 

Execution is necessary but not sufficient. Strategy isn’t sufficient either, but it is necessary. 

For some reason, though, it’s a badge of honor in tech to shit on strategy. 

Well, I am here to defend strategy. 

Strategy is the difference between playing startup and building an enduring business. I’ve racked my brain (and Google, and ChatGPT) for examples of startups that have achieved $10 billion+ outcomes without a good strategy, without moats in place by the time their success became obvious, and I just can’t come up with any.  

If startups need to dig moats before their uncertainty runs out, strategy is how they do it. If moats are the what, strategy is the how. 

Every startup has a window of time during which they must simultaneously build something worth defending and build defenses around it. 

For new startups, strategy is deciding how to use the window wisely. It’s about directing your limited resources towards digging moats before you’ve removed enough uncertainty to attract serious competition.

Like moats, strategy is often thought of as something that bigger companies need to worry about, when they have to coordinate thousands of people and defend against dozens of competitors. Most of the strategy literature is written for those bigger companies, and most of it is overkill for startups. 

That doesn’t mean that strategy is more important for big companies than for startups. The opposite is true: strategy is highest-leverage at Day 0, when all paths are available. 

I made strategy look too clean in that graphic. Under conditions of uncertainty, your strategy will need to change as you learn and as the situation evolves. 

But crafting a strategy upfront lets you throw all of your limited resources in one direction from the start, build the strengths you need to win in the market you’ve chosen, and hopefully, if things go just right, compound all the little actions you take in the course of building your business into something real and defensible by the time your uncertainty window closes. 

If you use the uncertainty window to execute blindly for a while before crafting a strategy, you’ve both wasted precious uncertainty time and made decisions – hired people, signed customers, taken on outside capital – that will make it harder to change direction when you decide you must.

This all seems kind of tautological. Few would disagree that it’s better to execute in a direction than not. And done right, that’s what strategy helps do. 

So why does strategy get such a bad rap? 

Bad Strategy

Most capital-S Strategy, as it’s taught and practiced by people who call it Strategy, is Bad Strategy

When Ben Rollert and I told Breather’s exec team that we were going to spend Christmas break 2017 coming up with a strategy to improve our margins in the face of competition from WeWork and Knotel, our CTO, Ben Nevile, told us to read Good Strategy Bad Strategy by Richard Rumelt. Great rec. 

It’s my favorite strategy book because it was so easy to put into practice, and because I recognized so many of the characteristics of bad strategy. Here are a few:

Mistaking Goals for Strategy: A classic. “Our strategy is to grow revenue by 50% while improving gross margins by 200 bps.” Cool cool… how though? 

Fluff: Using buzzwords and jargon to create the illusion of high-level thinking. If you think strategy is bullshit, fluff is quite likely the culprit. 

Failure to Face the Challenge: There’s often one key thing that really matters for a business – Rumelt calls it the Crux in a new book – but bad strategy dances around it in favor of a bunch of things that matter less but are easier to deal with or measure. 

Ignoring Competition: Companies exist in dynamic markets; a failure to recognize competition or anticipate their response to your moves is lazy and dangerous. 

Before Breather eventually fell victim to bad strategy, Ben and I came up with a good strategy (if I do say so myself). I’ll explain it once we’ve covered good strategy, but for now, I’ll say that our gross margins improved from -25% to +25% in six months by doing something competitors couldn’t easily match. 

Then we brought in a new CEO, who brought in a new exec team, in 2019. A couple weeks into their tenure, Ben and I presented our strategy at an exec team offsite. We were like two minutes in when we got cut off: 

“Why? Why do we need a strategy? This is a big market, we don’t need to worry about moats. We have a brand. That’s what Apple has. Our space plan model is the strategy.” 

The creator economy was already exploding. Then Hollywood went on strike.

The last big strikes reshaped the movie business and fueled the rise of reality TV. The latest walkout likely will help turn established actors into TikTok stars — and vice versa.

By Drew Harwell and Taylor Lorenz

July 23, 2023 at 6:00 a.m. EDT

Writers, actors and supporters march in front of Paramount Studios as part of the strike in New York. (Yana Paskova for The Washington Post)

The historic double strike that is paralyzing Hollywood could supercharge the creator economy, the wildly popular market of online influencers and video makers who increasingly rival industry titans for money, attention and cultural power.

The fast-growing cast of amateur and professional creators — chefs, comedians, models, musicians and many others — already attracts tens of millions of fans on platforms like YouTube and TikTok without the resources or support of more established mass media.

Now, as American film and TV production grinds to a halt, possibly for months, they stand at the center of a major shift that could change entertainment and further blur the lines between traditional and digital fame.

Studios and producers are scrambling to recruit creators to help fill a content void, stoking tensions over scab work and changing styles of storytelling. But striking actors and writers are increasingly less reliant on Hollywood, too, experimenting with new ideas on Instagram, YouTube, TikTok and Twitch in ways that could net them lasting followings — if not steady paychecks — that go beyond traditional industry success.

The last Hollywood strike radically reshaped the media landscape by fueling the rise of unscripted content, like documentary series and reality TV shows, that were cheaper to make and easier to mass-produce, such as “Cops” in the late ’80s and “The Celebrity Apprentice” in 2008.

The ongoing walkout of tens of thousands of actors and writers, Hollywood’s first double strike in 63 years, could have similarly sweeping ripple effects, by potentially eroding Hollywood’s institutional advantages and elevating a new generation of stars.

Creators once saw online virality largely as a way to break into established TV or movie gigs. But some now make so much money selling sponsored content, merchandise or monthly subscriptions that traditional entertainment, with its uncertain paychecks and relevance, can seem like less of a draw.

Hollywood’s business model has rarely looked so precarious, with box office sales, streamer subscriptions and advertising revenue all trending down. Striking actors and writers have also been enraged over industry practices, from high executive salaries and low residual payments to artificial intelligence techniques they worry could erase their jobs.

The changing entertainment scene

The online creator industry, on the other hand, is exploding. Goldman Sachs Research analysts said in April that the market would likely double in size over the next five years, from $250 billion today, thanks to increased spending from advertisers, viewers and tech platforms eager to capitalize on creators’ virality….

Video of the Week

AI of the Week

A Case for Heuristics: Why Simple Solutions Often Win in Data Science

In this defence of heuristics, I examine how simple solutions can often be the best port of call when looking to ship data science products

Holly Emblem

In 2016, Lisa Bodell — the CEO of futurethink and a top speaker at Google events — proposed that “simplicity is fast becoming the advantage of our time”. However, within the field of data science and machine learning, we can often prefer more complex solutions, that while can typically lead to incredible results, can also lead to frustration, failures and long lead times.

While this article isn’t a rallying cry to abandon Keras and revert back to Excel, it is a gentle reminder to consider utilising simple heuristics to baseline your solution, and even for you to consider shipping them to start with then building something more advanced.

In this article, I’ll draw from learnings from a recent research project, and how I used these findings from to inform my day-to-day approach when developing data science solutions. I’ll dig into a definition of heuristics, learning from Martin Zinkevich’s Rules of Machine Learning, deep dive into a recent project which looked to identify dangerous photosensitive epilepsy sequences in gifs, and finally summarise the key learnings on utilising heuristics.

A Gentle Introduction to Heuristics

In Rules of Machine Learning, Zinkevich proposes that heuristics are “a simple and quickly implemented solution(s) to a problem”. Heuristics is often used as a catch-all term for rules-based algorithms or metrics that allow you to categorise or infer a class, or decision about data. Heuristics can be applied to solve a variety of problems including:

Categorising if an email is spam (such as using a rules-based approach to detect certain words)

Showing relevant results to a user (such as the most popular results in their country or overall)

Identifying the highest-performing users in an app or game (by ranking actions or engagement)

While heuristics are considered simple and quick, they might not always be a data scientist’s first choice to solve a problem. In my experience, heuristics can be neglected in favour of more complex solutions up front, and then simplicity takes over when the whizzy, more advanced solution fails. Within my own academic and professional career, this is a situation I have experienced first-hand. In this post, I wanted to share my findings of comparing heuristics with a deep learning solution, and why simple heuristics should often be your first port of call.

OpenAI, Google will watermark AI-generated content to hinder deepfakes, misinfo

Seven companies promised Biden they would take concrete steps to enhance AI safety.

ASHLEY BELANGER – 7/21/2023, 10:10 AM

Seven companies—including OpenAI, Microsoft, Google, Meta, Amazon, Anthropic, and Inflection—have committed to developing tech to clearly watermark AI-generated content. That will help make it safer to share AI-generated text, video, audio, and images without misleading others about the authenticity of that content, the Biden administration hopes.

It’s currently unclear how the watermark will work, but it will likely be embedded in the content so that users can trace its origins to the AI tools used to generate it.

Deepfakes have become an emerging concern for Internet users and policymakers alike as tech companies grapple with how to deal with controversial uses of AI tools.

Earlier this year, image-generator Midjourney was used to make fake images of Donald Trump’s arrest, which subsequently went viral. While it was obvious to many that the images were fake, Midjourney still decided to take steps to ban the user who made them. Perhaps if a watermark had been available then, that user, Bellingcat founder Eliot Higgins, never would have faced such steep consequences for what he said was not an attempt to be clever or fake others out but simply have fun with Midjourney.

There are other more serious misuses of AI tools, however, where a watermark might help save some Internet users from pain and strife. Earlier this year, it was reported that AI voice-generating software was used to scam people out of thousands of dollars, and just last month, the FBI warned of increasing use of AI-generated deepfakes in sextortion schemes.

The White House said the watermark will enable “creativity with AI to flourish but reduces the dangers of fraud and deception.”

OpenAI said in a blog that it has agreed “to develop robust mechanisms, including provenance and/or watermarking systems for audio or visual content,” as well as “tools or APIs to determine if a particular piece of content was created with their system.” This will apply to most AI-generated content, with rare exceptions, like not watermarking the default voices of AI assistants.

“Audiovisual content that is readily distinguishable from reality or that is designed to be readily recognizable as generated by a company’s AI system—such as the default voices of AI assistants—is outside the scope of this commitment,” OpenAI said.

Google said that in addition to watermarking, it will also “integrate metadata” and “other innovative techniques” to “promote trustworthy information.”

As concerns over AI misuse mount, President Joe Biden will meet with tech companies today. That should help Biden and Congress field key insights ahead of developing an executive order and bipartisan legislation in efforts to seize back control over rapidly advancing AI technologies.

In a blog, Microsoft praised the Biden administration for creating “a foundation to help ensure the promise of AI stays ahead of its risks” and “bringing the tech industry together to hammer out concrete steps that will help make AI safer, more secure, and more beneficial for the public.”

“None of us can get AI right on our own,” Google’s blog said.

More AI safeguards promised

On top of developing watermarks for AI-generated content, tech companies made a range of other voluntary commitments announced by the White House on Friday.

Among them, tech companies agreed to conduct both internal and external testing on AI systems ahead of their release. They also said they would invest more in cybersecurity and share information across the industry to help reduce AI risks. Those risks include everything from AI enabling bias or discrimination to lowering barriers for advanced weaponry development, OpenAI’s blog said. Microsoft’s blog highlighted additional commitments it has made to the White House, including supporting the development of a national registry documenting high-risk AI systems.

OpenAI said that tech companies making these commitments “is an important step in advancing meaningful and effective AI governance, both in the US and around the world.” The maker of ChatGPT, GPT-4, and DALL-E 2 also promised to “invest in research in areas that can help inform regulation, such as techniques for assessing potentially dangerous capabilities in AI models.”

Meta’s president of global affairs, Nick Clegg, echoed OpenAI, calling tech companies’ commitments an “important first step in ensuring responsible guardrails are established for AI.”

Google described the commitments as “a milestone in bringing the industry together to ensure that AI helps everyone.”

FACT SHEET: Biden-⁠Harris Administration Secures Voluntary Commitments from Leading Artificial Intelligence Companies to Manage the Risks Posed by AI

Voluntary commitments – underscoring safety, security, and trust – mark a critical step toward developing responsible AI

Biden-Harris Administration will continue to take decisive action by developing an Executive Order and pursuing bipartisan legislation to keep Americans safe

Since taking office, President Biden, Vice President Harris, and the entire Biden-Harris Administration have moved with urgency to seize the tremendous promise and manage the risks posed by Artificial Intelligence (AI) and to protect Americans’ rights and safety. As part of this commitment, President Biden is convening seven leading AI companies at the White House today – Amazon, Anthropic, Google, Inflection, Meta, Microsoft, and OpenAI – to announce that the Biden-Harris Administration has secured voluntary commitments from these companies to help move toward safe, secure, and transparent development of AI technology.   

Companies that are developing these emerging technologies have a responsibility to ensure their products are safe. To make the most of AI’s potential, the Biden-Harris Administration is encouraging this industry to uphold the highest standards to ensure that innovation doesn’t come at the expense of Americans’ rights and safety.

These commitments, which the companies have chosen to undertake immediately, underscore three principles that must be fundamental to the future of AI – safety, security, and trust – and mark a critical step toward developing responsible AI. As the pace of innovation continues to accelerate, the Biden-Harris Administration will continue to remind these companies of their responsibilities and take decisive action to keep Americans safe.

There is much more work underway. The Biden-Harris Administration is currently developing an executive order and will pursue bipartisan legislation to help America lead the way in responsible innovation.

Today, these seven leading AI companies are committing to:

Ensuring Products are Safe Before Introducing Them to the Public

The companies commit to internal and external security testing of their AI systems before their release. This testing, which will be carried out in part by independent experts, guards against some of the most significant sources of AI risks, such as biosecurity and cybersecurity, as well as its broader societal effects.

The companies commit to sharing information across the industry and with governments, civil society, and academia on managing AI risks. This includes best practices for safety, information on attempts to circumvent safeguards, and technical collaboration.

Building Systems that Put Security First

The companies commit to investing in cybersecurity and insider threat safeguards to protect proprietary and unreleased model weights. These model weights are the most essential part of an AI system, and the companies agree that it is vital that the model weights be released only when intended and when security risks are considered.

The companies commit to facilitating third-party discovery and reporting of vulnerabilities in their AI systems. Some issues may persist even after an AI system is released and a robust reporting mechanism enables them to be found and fixed quickly.

Earning the Public’s Trust

The companies commit to developing robust technical mechanisms to ensure that users know when content is AI generated, such as a watermarking system. This action enables creativity with AI to flourish but reduces the dangers of fraud and deception.

The companies commit to publicly reporting their AI systems’ capabilities, limitations, and areas of appropriate and inappropriate use. This report will cover both security risks and societal risks, such as the effects on fairness and bias.

The companies commit to prioritizing research on the societal risks that AI systems can pose, including on avoiding harmful bias and discrimination, and protecting privacy. The track record of AI shows the insidiousness and prevalence of these dangers, and the companies commit to rolling out AI that mitigates them.   

The companies commit to develop and deploy advanced AI systems to help address society’s greatest challenges. From cancer prevention to mitigating climate change to so much in between, AI—if properly managed—can contribute enormously to the prosperity, equality, and security of all.

As we advance this agenda at home, the Administration will work with allies and partners to establish a strong international framework to govern the development and use of AI. It has already consulted on the voluntary commitments with Australia, Brazil, Canada, Chile, France, Germany, India, Israel, Italy, Japan, Kenya, Mexico, the Netherlands, New Zealand, Nigeria, the Philippines, Singapore, South Korea, the UAE, and the UK. The United States seeks to ensure that these commitments support and complement Japan’s leadership of the G-7 Hiroshima Process—as a critical forum for developing shared principles for the governance of AI—as well as the United Kingdom’s leadership in hosting a Summit on AI Safety, and India’s leadership as Chair of the Global Partnership on AI. We also are discussing AI with the UN and Member States in various UN fora.

News Of the Week

Sam Altman’s biometrics-based cryptocurrency Worldcoin is now live

The platform aims to “distinguish humans from AI” through what it calls a “proof of personhood”

By Faustine Ngila

Photo: Elizabeth Frantz (Reuters)

OpenAI CEO Sam Altman launched the Worldcoin cryptocurrency today (July 24), promising to provide a tool to “distinguish humans from AI,” tackle online identity challenges, and solve income inequality.

Worldcoin is unique among cryptocurrencies for using a proof of personhood (also known as PoP) credential issued by a custom biometric imaging device called the Orb. The device features a wide angle camera and a telephoto camera that capture a high resolution image of the human iris, and process it into a unique digital identifier.

The cryptocurrency has been under testing in countries such as Chile, Norway, Indonesia, Kenya, Sudan, and Ghana for the past three years. By the end of the year, Worldcoin expects to make 1,500 orbs available in 35 cities across 20 countries to continue onboarding new users for free. Worldcoin has recorded over 2 million registrations since it started doing beta tests, with 40,000 individuals signing up for a verified World ID every week.

After listing in several crypto exchanges on Monday, Worldcoin’s (WLD) token surged as high as 98%, hitting a price of $3.30 per coin, from $1.66 with a trading volume of $239 million, according to Coingecko data.

Worldcoin’s UBI opportunity

In a press statement, Altman and Worldcoin co-founder Alex Blania touted the coin as a tool to enable global democratic processes, and eventually show a potential path to AI-funded universal basic income (UBI). “Worldcoin consists of a privacy-preserving digital identity (World ID) and, where laws allow, a digital currency (WLD) received simply for being human,” the duo said.

Altman has long been an advocate of universal basic income as a way to tackle income inequality. He believes that Worldcoin could help eliminate fraud if governments decide to adopt it in distributing UBI to their citizens. “Worldcoin is an attempt at global scale alignment, the journey will be challenging and the outcome is uncertain. But finding new ways to broadly share the coming technological prosperity is a critical challenge of our time,” the statement by Altman and Blania said.

In May, Worldcoin launched the World App, a crypto wallet designed by the research lab and tech product development company Tools for Humanity (TFH), based in Denver, Colorado and co-founded by Altman and Blania.

The app runs on Ethereum’s Polygon blockchain protocol and presents users with an opportunity to access Polygon-based versions of cryptos like bitcoin, ether, and stablecoins such as the USD-pegged DAI token. However, World App remains limited as a crypto wallet as it was designed purposefully to enable the functionalities of Worldcoin. Volunteers were initially paid in bitcoin.

A fraud-proof digital passport?

As the online world gets increasingly populated with bots, the iris-based unique ID generated by Worldcoin’s Orb is meant to distinguish unique individuals from online AI chatbots and prevent fraud.

The platform effectively offers a solution to a problem Altman’s OpenAI, the creator of ChatGPT helped create, as OpenAI’s paid-for ChatGPT API (application programming interface) has been used by developers to create human-like AI bots across the web.

Altman appears aware of AI development’s catch-22 and he claims to be on a mission to shape AI regulation across the world. In May, he even called upon Congress to regulate AI as the technology could cause harm to the world if allowed to spiral out of control and last week OpenAI committed to a White House-brokered safety pledge.

By focusing on biometrics as a proof of personhood, Altman is wading into another controversial field. Worldcoin is likely to face scrutiny as to how the data has been collected and processed so far, whether it can be safe from hackers in the future, and whether it can truly be fraud-proof—a black market for iris scans has reportedly already flourished.

How Sam Altman’s Worldcoin Engineered Its Token Launch

By Aidan Ryan July 26, 2023 9:23 AM PDT

A lot of ink has been spilled about Sam Altman’s controversial crypto startup Worldcoin and the two million people who have had their eyeballs scanned to gain access to tokens. But an overlooked part of Worldcoin’s token launch is what it’s doing to promote trading of its new tokens.

On Monday, Worldcoin sent 43 million worldcoins to people who signed up as part of the pre-launch period. But most of the tokens distributed in the launch aren’t going to those users. Instead, 100 million tokens are being loaned to market makers, or trading firms that buy and sell large amounts of tokens and make money on the spread.

Loans to market makers are typical for new token projects and are often needed to create an active market in the tokens ahead of listing on crypto exchanges, investors and founders told The Information. Details of such loans are typically scarce, but Worldcoin gave a close look at how it structured the launch in a whitepaper released this week.

For starters, the 100 million tokens represents roughly 70% of the initial circulating supply of worldcoin, an unusually high proportion, investors and founders told The Information. The supply of worldcoins is designed to eventually increase to 10 billion once all the tokens are unlocked over the next 15 years. 

Token projects also typically only use one market maker. Worldcoin said in its whitepaper that it has agreements with five market makers. The whitepaper also lays out some terms of the loans, which set the duration at three months. After that, the market makers either return the tokens or can buy them at a price based on a formula, with the market makers paying a higher price the more they want to buy. 

For example, if a market maker got a loan of 20 million tokens, they either return them or pay $2.80 per token to buy the tokens at the end of three months. (The price assumes that they would buy all of the tokens.) So if the market maker can sell between now and then above $2.80, they can profit—if the price falls after they sell, they can buy tokens back on the open market to give them back to Worldcoin, and if token prices continue to rise they still have pocketed the difference between the $2.80 they have to pay back. (The tokens have traded as high as $3.30 and are currently trading around $2.30, according to CoinGecko.) 

“This is a very good deal for market makers if they believe there’s a very high chance that the market cap of Worldcoin ends up being well above 28 billion,” said Sam Trautwein, the CEO of Tristero, a startup that is building what is known as a “dark pool” for large, private token transactions. “If it doesn’t, it’s still not a bad deal, but their actual upside is going to be based on how competitive they are with the other four market makers in terms of capturing spreads on trades.”

Spokespeople for Worldcoin did not immediately respond to a request for comment.

Notably, Worldcoin won’t distribute any tokens to users in the U.S., and while the company hasn’t disclosed which firms it’s tapped as market makers, it says all its market makers are operating outside the country. Altman and Alex Blania, Worldcoin’s CEO, wrote that they “hope that, where the rules are less clear, such as in the U.S., steps will be taken so more people can benefit” from both the worldcoin token and the iris scanning technology. 

While Worldcoin has been under scrutiny over how it handles biometric data—a U.K. data watchdog has already said it would be taking a closer look at how Worldcoin handles personal data—how tokens are sold to U.S. investors also raises thorny regulatory questions. 

Elon Musk Says the Twitter Brand Will be Retired, Renamed ‘X’, Very Soon

Published July 23, 2023

By Andrew Hutchinson Content and Social Media Manager

If it wasn’t already significantly altered from its previous state, Twitter as you know it is about to be no more. 

According to Twitter owner Elon Musk, he’s officially changing the name of the app from ‘Twitter’ to ‘X’, as part of his broader vision for an ‘everything app’ which will eventually facilitate a much broader range of functions, and ideally make X a key interactive component in billions of users’ lives. 

Musk has already previewed the interim X branding, which he chose from a range of user-submitted concepts.

Musk has also flagged changing the app’s default color from blue to black, while tweets themselves will no longer be called such. Musk says they’ll be called an ‘x’.

Why would a company burn years of brand equity, especially when there’s seemingly no need (i.e. no negative association to distance itself from)?

The X name has been part of Musk’s grand plan since the late 90s, when he first started to make a name for himself in online payments. Musk had founded a payments company, which he envisioned would become ‘’, a new platform that would facilitate not only instant, fee-free payments, but also loans, and other banking elements, all in one simplified, streamlined offering.

When his company merged with PayPal, however, his new partners didn’t agree with the X concept, and Musk eventually had to abandon his plan, and move into other ventures. But the idea, and name, has stayed with him, and Musk remains convinced that he can create a disruptive, game-changing app, which would use payments as its backbone to then facilitate all sorts of transactional activity, in addition to social media and entertainment elements.

Musk has repeatedly claimed that buying Twitter is ‘an accelerant to X’, but despite Musk’s long-standing hopes, actually making X happen is not going to be easy.

Because every other social platform has already tried the same. Meta, for example, has been working for years to make in-stream payments a thing, with limited success. The challenges here are that, for one, regulatory bodies are not overly keen to enable payments that side-step existing banking systems. At the same time, Western users have shown little interest in actually making payments, and buying products, within social apps.

Almost 70% of Israeli startups act to shift funds, relocate due to judicial shakeup

Steps by startup heads and investors to withdraw cash reserves and move operations outside Israel have accelerated in past 3 months, according to a poll by Start-Up Nation Central

By SHARON WROBEL 24 July 2023, 4:57 pm

Tech workers march in Tel Aviv to protest against the government’s planned overhaul of the judicial system, January 31, 2023. (Tomer Neuberg/Flash90)

Tech workers march in Tel Aviv to protest against the government’s planned overhaul of the judicial system, January 31, 2023. (Tomer Neuberg/Flash90)

Almost 70 percent of Israeli startups are taking active steps to pull money and shift parts of their businesses outside the country due to the uncertainty created around the proposed judicial overhaul, according to a survey by Start-Up Nation Central, which tracks the local tech ecosystem.

The findings of the survey showed that 68% of Israeli startups have started to take “legal and financial steps,” including the withdrawal of cash reserves, moving their headquarters outside of Israel, relocating employees and conducting layoffs. Overall, 78% of the surveyed startup executives reported that government’s controversial plan to weaken the country’s judicial system is “negatively” impacting their operations, and 84% of venture capital investors said it has a negative influence on their portfolio companies.

“Companies and investors are taking active steps to move activity away from Israel and this behavior has increased significantly over the past three months,” said Start-Up Nation Central CEO Avi Hasson. “Concerning trends like registering a company abroad or launching new startups outside Israel will be hard to reverse.”

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THE WORLD’S LAST internet cafes

Kampala, Uganda

Kathmandu, Nepal

Lagos, Nigeria

Mexico City, Mexico

Salta, Argentina

Hong Kong, China

25 JULY 2023

When the world’s first internet cafe, Cafe Cyberia, first opened its doors in London’s West End in September 1994, its founders could never have imagined what they’d unleashed.

Internet cafes — cheap, accessible venues where just about anyone could explore cyberspace in its infancy — spread slowly across the world at first, and then snowballed in popularity. In the spring of 1996, Sri Lanka got its first two internet cafes: the Cyber Cafe, and the Surf Board. A few months later, Kuwait’s first internet cafe launched with 16 PCs. In 1999, a travel guide promised readers a list of 2,000 cafes in 113 countries.

Within a couple years, it was estimated that there were more than 100 internet cafes in Ghana alone. BusyInternet opened the largest internet cafe in Accra, boasting 100 screens. By 2002, there were more than 200,000 licensed internet cafes in China, and still more operating under the table.

“They were mushrooming,” Ricardo Gomez, an associate professor at the University of Washington who conducted a definitive survey of public internet access in the late 2000s, told Rest of World.

Internet cafes were more than just places to log on. They emerged in the waning years of the 20th century — a post-Cold War moment full of techno-optimism. Sharing a global resource like the internet “was going to bring different people in different cultures together in mutual understanding,” historian and author Margaret O’Mara told Rest of World. It was an era in which, both physically and digitally, “people were moving across borders that before were very difficult, if not impossible, to cross.”

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