Year: 2018

On a mild Thursday night at the Los Angeles Forum, Nike’s public relations team and a group of journalists from some of the country’s leading lifestyle, tech, and general interest websites gathered to see the debut of Nike’s most ambitious SNKRS stash drop.

Launched in conjunction with Kendrick Lamar’s Top Dawg Entertainment, the collaboration between Nike and Lamar marks a series of firsts for the world’s largest sports and lifestyle brand.

The combined effort is the first capsule collection that Nike has done with a musician. It’s also the first time that anyone currently working at the company can remember the apparel company signing on with a musician for select tour merchandise, and the debut of the stash drop through the SNKRS app was the largest the company’s tech had tried to tackle.

For concertgoers, rolling up to the concert in Supreme sweats, Yeezys, Adidas, Pumas… and, of course, Nikes, the SNKRS stash drop would be a surprise. For folks who had downloaded Nike’s SNKRS app, they’d be able to buy and reserve a pair of Kendrick Lamar’s limited edition Cortez Kenny IIIs at the concert.

At least on the first night, things didn’t go as planned.

Working with live events like concerts, where timing is less regimented than at a typical sporting event (which are marked by tip offs and halftimes that adhere to a pretty regimented schedule), proved too much for the initial rollout of the company’s stash drop.

Select NikePlus members received an initial push notification of the Stash drop and a card in the SNKRS feed also advertised the special stash drop, in addition to a notification that flashed onscreen between the (amazing)  SchoolboyQ set and SZA’s (equally amazing) performance.

There will be other chances to get the timing down, but for the first concert in Los Angeles, concertgoers were prompted to launch the SNKRS app and try and snag a pair of the limited edition shoes well before the activation actually went live.

Once the shoes did go on sale, the user interface for finding and reserving the shoes didn’t work for everyone there — in fact, only one reporter from the group was able to reserve a pair of the shoes (since that reporter hadn’t saved payment information onto the SNKRS app, those shoes were released).

“I can’t get the app to do what I need,” said one concertgoer trying to snag a pair of shoes.

The team at Nike said the concert’s late start caused the miscue. Roughly 30 minutes after the sneakers were supposed to onsale, the activation went live — something journalists were only made aware of when notified by Nike’s public relations team.

Once the sale did go live, the shoes sold out within the first five minutes, although it’s unclear how many were made available through the stash drop (Nike declined to provide a number).

Nike’s repeating the stash drop for shows in Houston, New York, Boston and Chicago.

The SNKRS app is only one example of Nike’s innovative approach to integrating technology and fashion. In April, Nike launched the first sneaker that’s integrated with its NikeConnect technology.

Unveiled earlier this year through a collaboration with the NBA, the NikeConnect app allows users to access information on players and stats through a label enabled with near field communications chips.

Nike’s Air Force Ones enabled with the NikeConnect tech will open a special limited release sneaker sale opportunity called “The Choice”, but Nike has higher hopes for the technology.

“We would love to be able to award sweat equity with access to exclusive products or a partnership,” said a spokesperson for the company in an interview last year.

“NikeConnect [is] a great way for us to get interesting data about our members and deliver unlocks that are relevant to those members,” the spokesperson said.

Beyond the unlocks for exclusive sneaker offers, Nike is thinking about ways to include all of its technology partners in ways that benefit NikeConnect, NikePlus, and SNKRS users.

“We’re excited to learn how unlocks are being received right now,” said the spokesperson. “There is a pretty comprehensive ecosystem of value that we’ve been building for our members… Members who are really active with us are getting rewards or achievements [and] that could include partners like Apple… that we’ll be bringing to the table to round out your whole holistic sport experience.”

VC investing is a game of putting money into a company and hopefully getting more out. In an ideal world, the value placed on a company at acquisition or initial public offering would be some large multiple of the amount of money its investors committed.

As it happens, that multiple on invested capital (MOIC) makes for a fairly decent heuristic for measuring company and investor performance. Most critically, it provides a handy metric to use for answering these questions: For US-based companies, have exit multiples changed in a meaningful way over time? And, if so, does this suggest something about the investment landscape overall?

Coming up with an answer to this question required a specific subset of funding and exit data from Crunchbase. If you’re interested in the how and why behind the data, check out the Data and Methodology section at the very end of the article. If not, we’ll cut right to the chase.

Exit multiples may be on the rise

A rather conservative analysis of Crunchbase data suggests that, over the past decade or so, exit multiples were on the rise before leveling off somewhat.

Below, you can see a chart depicting median MOIC for a set of U.S.-based companies with complete (as best we can tell) equity funding histories stretching back to Series A or earlier, which also have a known valuation at time of exit. That valuation is either the price paid by an acquirer or the value of the company at the time it went public. In an effort to reduce the impact of outliers, we only used companies with two or more recorded funding rounds. With that throat-clearing out of the way, here’s median MOIC over time:

It should be noted for the record that the shape of the above chart somewhat changes depending on the data is filtered. Including exit multiples for companies with only one reported funding round resulted in slightly higher median figures for each year and a more steady linear climb upward. But that’s probably due to the number of comically-high multiples some companies with single small rounds and large exit values produced. There are surely examples of companies that raised $1 million once and later sold for $100 million, but those are fewer and further between than companies with missing data from later rounds.

What might be driving the rise in exit multiples?

The rise in exit multiples may have to do with the fact that more companies are getting acquired at earlier stages.

Crunchbase data suggests that startups earlier in the funding cycle tend to deliver better exit multiples. In an effort to denoise the data a bit, we took the Crunchbase exit dataset and filtered out the companies that raised only one round. (Companies that raised only one round produced a lot of crazy outlier data points that skewed final results.)

This suggests that, in general, the earlier a startup is acquired in the funding cycle the more likely it is to deliver larger multiples on invested capital.

Now, granted, we’re working off of small sample sets with a fair amount of variability here, particularly for startups on opposite ends of the funding lifecycle. There is going to be some sampling bias here. Founders and investors are less likely to self-report disappointing numbers; therefore, these findings aren’t ironclad from the perspective of statistical significance.

But it’s a finding that nonetheless echoes a prior Crunchbase News analysis, which found a slight but statistically significant inverse relationship between the amount of capital a startup raises and the multiple its exit delivers to investors and other stakeholders. In other words, startups that raise less money (such as those at seed and early-stage) tend to deliver better multiples on invested capital.

The changing population of companies finding exits

So does the tendency for earlier-stage companies to deliver better investment multiples have anything to do with upward movement in MOIC ratios? It could, particularly if more seed and early-stage startups are headed to the exit these days. And as it turns out, our data suggest that’s happening.

The chart below shows the breakdown of exits for venture-backed companies based on the last stage of funding the company raised prior to being acquired or going public. We show a decade’s worth of funding data, this time including all exits from U.S. companies with known venture funding histories since seed or early stage—some 5,275 liquidity events in all. For 2018, we also include stats for exits through the beginning of May. Given reporting delays and the fact that there are still eight months left in the year, this is certainly subject to change.

Now, to be clear, over the past decade, there has been some notable growth in the overall number of exits for U.S.-based venture-backed companies across all stages.

But, in some ways, the raw number of deals doesn’t much matter. After all, figures from several years ago aren’t really actionable to founders and investors looking for an exit sometime this year. What matters, then, is what the mix of exits looks like, and at least for the set of companies we analyzed here, the past ten years brought an ultimately small but nonetheless notable shift in the mix of companies that get acquired or go public.

Seed and early-stage companies now make up a larger proportion of the population of exited companies now than in the past. And since companies at that stage tend to deliver higher multiples, it is likely responsible for part of the increase over time.

There are certainly other factors besides the influx of seed and early-stage ventures into the mix of exits, but sussing those out will require further investigation.

It should go without saying that any venture-backed company that gets acquired or goes public is a success, at least of some sort. After all, a tiny fraction of new businesses secure outside funding from angel investors or venture capitalists, and only a small proportion of those get acquired.

Any exit is better than none.

Data and methodology

Let’s start by saying that there is probably no canonically correct way to do this sort of analysis and that since Crunchbase News is working off of private company data, what hasn’t been aggregated programmatically is subject to self-reporting bias. Founders and investors are more likely to disclose exit valuations that make them look good, so this may skew our findings higher.

Definition of funding stages

Here, we use the same funding stage definitions as Crunchbase News does in its quarterly reporting.

• Seed/Angel-stage deals include financings that are classified as a seed or angel, including accelerator fundings and equity crowdfunding below $5 million.
• Early stage venture include financings that are classified as a Series A or B, venture rounds without a designated series that are below $15M, and equity crowdfunding above $5 million.
• Late stage venture include financings that are classified as a Series C+ and venture rounds greater than $15M.
• Technology Growth include private equity investments in companies that have previously raised venture capital rounds.

Building the base dataset

Here are the basic process we used:

1. We started by aggregating pre-IPO venture funding raised by U.S.-based companies. We focused only on equity funding only (angel, seed, convertible notes, equity crowdfunding, Series A, Series B, etc.), and did not include debt financing, grants, product crowdfunding, or other non-equity funding events. We did include private equity rounds, if and only if PE was the terminal round and the company had raised a seed, angel, or VC round prior to raising PE.
2. For each company, we recorded the stage of its first and last known funding rounds.
3. We excluded any company whose first round was Series B or later.
4. We excluded companies that were missing dollar amounts for any of their equity funding rounds.
5. We then retrieved the valuations at acquisition or IPO for each of the companies, again excluding any companies for which terminal private market valuation was not known.
6. Finally, for each company, we divided valuation at exit by the amount of known venture funding, resulting in the multiple on invested capital from equity financing events.

In conjunction with choosing to start with Series A and earlier funding events, we believe this produced a set of companies with reasonably complete funding histories. Granted, there are “unknown unknowns,” like later rounds that weren’t captured in Crunchbase, but there is no good way to control for those.

VC investing is a game of putting money into a company and hopefully getting more out. In an ideal world, the value placed on a company at acquisition or initial public offering would be some large multiple of the amount of money its investors committed.

As it happens, that multiple on invested capital (MOIC) makes for a fairly decent heuristic for measuring company and investor performance. Most critically, it provides a handy metric to use for answering these questions: For US-based companies, have exit multiples changed in a meaningful way over time? And, if so, does this suggest something about the investment landscape overall?

Coming up with an answer to this question required a specific subset of funding and exit data from Crunchbase. If you’re interested in the how and why behind the data, check out the Data and Methodology section at the very end of the article. If not, we’ll cut right to the chase.

Exit multiples may be on the rise

A rather conservative analysis of Crunchbase data suggests that, over the past decade or so, exit multiples were on the rise before leveling off somewhat.

Below, you can see a chart depicting median MOIC for a set of U.S.-based companies with complete (as best we can tell) equity funding histories stretching back to Series A or earlier, which also have a known valuation at time of exit. That valuation is either the price paid by an acquirer or the value of the company at the time it went public. In an effort to reduce the impact of outliers, we only used companies with two or more recorded funding rounds. With that throat-clearing out of the way, here’s median MOIC over time:

It should be noted for the record that the shape of the above chart somewhat changes depending on the data is filtered. Including exit multiples for companies with only one reported funding round resulted in slightly higher median figures for each year and a more steady linear climb upward. But that’s probably due to the number of comically-high multiples some companies with single small rounds and large exit values produced. There are surely examples of companies that raised $1 million once and later sold for $100 million, but those are fewer and further between than companies with missing data from later rounds.

What might be driving the rise in exit multiples?

The rise in exit multiples may have to do with the fact that more companies are getting acquired at earlier stages.

Crunchbase data suggests that startups earlier in the funding cycle tend to deliver better exit multiples. In an effort to denoise the data a bit, we took the Crunchbase exit dataset and filtered out the companies that raised only one round. (Companies that raised only one round produced a lot of crazy outlier data points that skewed final results.)

This suggests that, in general, the earlier a startup is acquired in the funding cycle the more likely it is to deliver larger multiples on invested capital.

Now, granted, we’re working off of small sample sets with a fair amount of variability here, particularly for startups on opposite ends of the funding lifecycle. There is going to be some sampling bias here. Founders and investors are less likely to self-report disappointing numbers; therefore, these findings aren’t ironclad from the perspective of statistical significance.

But it’s a finding that nonetheless echoes a prior Crunchbase News analysis, which found a slight but statistically significant inverse relationship between the amount of capital a startup raises and the multiple its exit delivers to investors and other stakeholders. In other words, startups that raise less money (such as those at seed and early-stage) tend to deliver better multiples on invested capital.

The changing population of companies finding exits

So does the tendency for earlier-stage companies to deliver better investment multiples have anything to do with upward movement in MOIC ratios? It could, particularly if more seed and early-stage startups are headed to the exit these days. And as it turns out, our data suggest that’s happening.

The chart below shows the breakdown of exits for venture-backed companies based on the last stage of funding the company raised prior to being acquired or going public. We show a decade’s worth of funding data, this time including all exits from U.S. companies with known venture funding histories since seed or early stage—some 5,275 liquidity events in all. For 2018, we also include stats for exits through the beginning of May. Given reporting delays and the fact that there are still eight months left in the year, this is certainly subject to change.

Now, to be clear, over the past decade, there has been some notable growth in the overall number of exits for U.S.-based venture-backed companies across all stages.

But, in some ways, the raw number of deals doesn’t much matter. After all, figures from several years ago aren’t really actionable to founders and investors looking for an exit sometime this year. What matters, then, is what the mix of exits looks like, and at least for the set of companies we analyzed here, the past ten years brought an ultimately small but nonetheless notable shift in the mix of companies that get acquired or go public.

Seed and early-stage companies now make up a larger proportion of the population of exited companies now than in the past. And since companies at that stage tend to deliver higher multiples, it is likely responsible for part of the increase over time.

There are certainly other factors besides the influx of seed and early-stage ventures into the mix of exits, but sussing those out will require further investigation.

It should go without saying that any venture-backed company that gets acquired or goes public is a success, at least of some sort. After all, a tiny fraction of new businesses secure outside funding from angel investors or venture capitalists, and only a small proportion of those get acquired.

Any exit is better than none.

Data and methodology

Let’s start by saying that there is probably no canonically correct way to do this sort of analysis and that since Crunchbase News is working off of private company data, what hasn’t been aggregated programmatically is subject to self-reporting bias. Founders and investors are more likely to disclose exit valuations that make them look good, so this may skew our findings higher.

Definition of funding stages

Here, we use the same funding stage definitions as Crunchbase News does in its quarterly reporting.

• Seed/Angel-stage deals include financings that are classified as a seed or angel, including accelerator fundings and equity crowdfunding below $5 million.
• Early stage venture include financings that are classified as a Series A or B, venture rounds without a designated series that are below $15M, and equity crowdfunding above $5 million.
• Late stage venture include financings that are classified as a Series C+ and venture rounds greater than $15M.
• Technology Growth include private equity investments in companies that have previously raised venture capital rounds.

Building the base dataset

Here are the basic process we used:

1. We started by aggregating pre-IPO venture funding raised by U.S.-based companies. We focused only on equity funding only (angel, seed, convertible notes, equity crowdfunding, Series A, Series B, etc.), and did not include debt financing, grants, product crowdfunding, or other non-equity funding events. We did include private equity rounds, if and only if PE was the terminal round and the company had raised a seed, angel, or VC round prior to raising PE.
2. For each company, we recorded the stage of its first and last known funding rounds.
3. We excluded any company whose first round was Series B or later.
4. We excluded companies that were missing dollar amounts for any of their equity funding rounds.
5. We then retrieved the valuations at acquisition or IPO for each of the companies, again excluding any companies for which terminal private market valuation was not known.
6. Finally, for each company, we divided valuation at exit by the amount of known venture funding, resulting in the multiple on invested capital from equity financing events.

In conjunction with choosing to start with Series A and earlier funding events, we believe this produced a set of companies with reasonably complete funding histories. Granted, there are “unknown unknowns,” like later rounds that weren’t captured in Crunchbase, but there is no good way to control for those.

The UK and the USA have always had an enduring bond, with diplomatic, cultural and economic ties that have remained firm for centuries.

We live in an era of profound change, and are living with technologies set to change things ever faster. If Britain and America work together to develop these technologies for the good of mankind, in a way that is open and free, yet also safe and good for our citizens, we can maintain the global lead our nations have enjoyed in the fields of innovation.

Over past months we have seen some very significant strides forward in this business relationship. All of the biggest US companies have made decisions to invest in the UK. Apple is developing a new HQ in the iconic Battersea Power Station, close to the new US embassy, while Google is building a billion dollar new HQ in the increasingly fashionable King’s Cross. Facebook, Amazon, IBM and Microsoft are all extending their operations, and a multitude of smaller US firms are basing their international headquarters in London.

They are all coming here because as we prepare to leave the EU we are building a forward looking Britain that is open to the wider world, and tech is at the heart of this.

Similarly, there have been major expansions or new investment from British firms into the US. Jaguar Land Rover, the UK’s largest automotive manufacturer, supports more than 9,000 jobs in the USA and have recently opened their new multimillion-dollar corporate North America HQ in New Jersey.  iProov, a leading British provider of biometric facial verification technology, became the first international company to be awarded a contract from the US Department of Homeland Security Science & Technology Directorate’s Silicon Valley Innovation Program last month.

We want to work with our global partners – to share expertise, and encourage investment – as we harness technology for the wider good. And that of course includes our old friend and closest ally, the USA.

We have a great deal to offer.

The UK was recently ranked the most AI ready nation among all the OECD countries. In the past three years, new AI start-ups have been created in the UK on an almost weekly basis.

Recently, UK government and industry together committed over $1 billion to support our AI sector, much of which will go towards entrepreneurs. Funding has been set aside to create a nationwide network of tech incubators, that we’re calling “Tech Nation”, which will support new AI businesses as they get off the ground.

We are also excited by — and I am a firm advocate for — the development of blockchain and similar technologies. The UK is leading the way in many areas where blockchain has the potential to be used, such as Fintech. There are now more people working in UK Fintech than in New York or in Singapore, Hong Kong and Australia combined.

And we are eminent in the development of immersive technologies, like Augmented and Virtual Reality, which look set to radically improve many areas of life in coming years, with applications as varied as flight simulation and surgical training techniques.

There is so much to be gained from close collaboration between our two countries on these new technologies and from sharing our expertise.

Together, we can reap the economic benefits of stealing an early lead in their development. We estimate that AI, for example, if widely adopted, could add $33 billion to the UK economy. But, perhaps most importantly, we can also work together to build a strong regulatory and ethical frameworks for their wider application.

It is the role of governments across the world, the UK and US included, to set frameworks for these decentralised, cross border systems so we can manage their use in a safe and effective way.

Our aim should be to harness the power and capability of technology but always for the benefit of, and in service to the populace.

We in the UK are avowedly pro-tech, always seeking to put its power in the hands of our citizens.

We have all learned valuable lessons from the recent scandals regarding data use, most recently around Facebook’s use of data.

We want to build a system that protects and cherishes the freedom of the Internet while protecting the rights of individuals, and their property, including intellectual property.

We want to see freedom in a framework; where our tech entrepreneurs have the space to innovate, knowing they do so with full public trust. Trust underpins a strong economy, and trust in data underpins a strong digital economy.

So in the UK we are developing a Digital Charter, to agree norms and rules for the online world and put them into practice. Our starting point is that what is unacceptable offline should not be tolerated in the online world. That includes how tech companies treat private citizens and use their data, as well as how people treat each other online.

Important changes like these cannot be agreed by one country alone. It is more important than ever that we work together and find common ground so we can make sure that tech continues to change the world for the better. Based on our mutual love of freedom and individual rights Britain and America have through history risen to challenges together. I firmly believe working together we can build that brighter future.

We are in a subscription hell. Paywalls are going up across the internet, at aggregated prices few but Jeff Bezos can afford. The software I used to pay for once now requires an annual tax, because … “updates.” We are getting less every day, and paying more for it, all the while the core openness that made the world wide web such a dynamic and interesting place is rapidly disappearing.

I’m not a subscription hater. Far from it: subscriptions are vital, because they provide sustainability to the content and software I care about. Regular, recurring income helps make the business of creation more predictable, ensuring that creators can do what they do best — create — rather than stress about whether the next book or app is going to generate their yearly earnings.

Greed, though, has managed to make subscriptions deeply unpalatable. Sustainability has become usurious, with news subscriptions jumping in price and app developers suddenly demanding a fee where none existed before. This avarice for our wallets though is not misdirected. Ultimately, one group of people is to blame for this situation, and it isn’t the bean counters in the accounting department.

It’s us.

And by us, I mean the proverbial 99% consuming public who refuses to pay for any content or software — except for Netflix or Amazon Prime, of course.

Just take a look at the abysmal conversion rates for online content. The New York Times gets 89 million uniques per month, but only has 2.2 million subscribers, excluding crossword and other app subscribers. The Guardian has 800,000 financial supporters, but about 140 million unique visitors at a peak a few years ago. Last year, the Wikimedia Foundation received donations from 6.1 million donors, yet just the English language edition of Wikipedia received 7.7 billion page views last month. That’s 1,300 April page views per annual donor.

The implied conversion rates here are in the very low single digits, if not lower. And that’s no surprise given the extreme lengths people go to get content for free. A friend of mine uses AWS to rent IP addresses to reset his article meter on popular news pages, allowing him to download web pages through a Singapore data center using a custom command line utility. Engineers who make hundreds of thousands of dollars are suddenly tantalized by the challenge of trying to break through a porous paywall. I have less technical friends Googling URLs, setting up proxies, and other tactics to get to the same outcome.

The problem with these minuscule conversion rates is that it dramatically raises the cost of acquiring a customer (CAC). When only 1% of people convert, it concentrates all of that sales and marketing spend on a very small sliver of customers. That forces subscription prices to rise so that the CAC:LTV ratios make rational sense.

What we get then is a classic case of economic unraveling. A company could offer an affordably priced subscription, but users hesitate, and so the company tries to do more marketing initiatives, which raises the cost of the subscription. That makes the vast majority of users even less willing to purchase it, so marketing gets more budget to go after the highest spending consumers.

Before you know it, what once might have been $1 a month by 20% of a site’s audience is now $20 a month for the 1%.

That’s basically the math of the New York Times. Last year, the company generated $340 million in digital-only revenue from 2.6 million subscribers (including derivatives like crosswords and cooking). That’s $155 a user on average annually, or about $13 a month. The Times had an implied conversion rate of about 2.5% from my earlier calculations. If they could convert 20% at the same sales and marketing cost, they could charge $20 a year and get the same revenue (maybe $22 for added credit card processing fees).

The entire subscription economy is ultimately a 1% economy — it’s focused on a very small subset of users who have demonstrated that they are willing to pay dollars for content. The most likely factor that someone is going to buy a subscription is that they already have a subscription to another service. And so we see pricing that reflects this reality.

There is a class of exceptions around Netflix, Spotify, and Amazon Prime. Spotify, for instance, had 170 million monthly actives in the first quarter this year, and 75 million of those are paid, for an implied conversion of 44%. What’s unique about these products — and why they shouldn’t be used as an example — is that they own the entirety of a content domain. Netflix owns video and Spotify owns music in a way that the New York Times can never hope to own news or your podcast app developer can never hope to own the audio content market.

Yes, we are living in a subscription hell, but it is also heavily a product of our own decision-making as consumers. We want content and software for free, and in fact, we will go to ridiculous lengths to avoid paying for it. We will protest ads and privacy-invasive tracking, but we will never support the business model that would make that technology obsolete. Even when we will consider buying a service, we will wait so long and make the conversion so expensive that a huge chunk of our individual revenue will simply evaporate in sales and marketing costs.

The solution here is to become more intentional about aligning our content spending with what we read, use, watch, and hear. Put together an annual content budget, and spend it liberally across the publications and creators that you enjoy. Advocate for pricing that makes sense for you individually, but also convert more easily when you find something that you like. The friction has to lower on both sides of the marketplace for the 20% to supplant the 1%.

I don’t want a world filled with gilded walled gardens designed to ensure that the 1% have the best information and entertainment while leaving the rest of us with clickbait fake news and bad covers on YouTube. But creating content and software is expensive, and ultimately, businesses are going to sell to the customers that pay them. It’s on all of us to engage in that market. Maybe then this subscription hell can freeze over.

In a remarkable development, President Trump has thrown an olive branch to controversial Chinese telecom firm ZTE .

The company, which sells telcom network equipment and consumer devices including smartphones, said on Wednesday that it would cease its main business operations after the U.S. Department of Commerce announced a seven-year export restriction for the company, resulting in a ban on U.S. component makers selling to ZTE.

The company has been banned from selling equipment in the U.S., but shutting out supply chain partners like Intel, Qualcomm and Google is potentially catastrophic. (The fact ZTE postponed its earnings tells you all you need to know.)

Reports suggested that the Chinese government was working on ZTE’s behalf to find a compromise, and it looks like Chinese Premier Xi Jinping himself got in touch with the U.S. President, who said today in a tweet that is he “working[…]to give[…]ZTE a way back into business, fast.”

Somewhat bizarrely, Trump cited a loss of jobs in China as a motivating factor.

Given that U.S. sanctions were imposed on ZTE due to threats to national security and its violation of trade sanctions with Iran and North Korea, Trump’s desire to give the company another chance in the U.S. is truly unexpected.

It also doesn’t align with recent events.

The Trump administration has used the premise of national security to block a number of business deals that would see Chinese companies buying up American firms — including Alibaba’s proposed acquisition of MoneyGram and Broadcom’s effort to buy Qualcomm.

Then, of course, the President is involved in an aggressive trade dispute with China, which, on the U.S. side, included tariffs on about $60 billion of Chinese goods, the bulk of which were focused on the high-tech industry.

Granting a reprieve to ZTE — a firm with over 70,000 employees, over $17 billion in annual revenue and close ties to the government — doesn’t fit with the strategy to hurt China, but then Trump’s administration is hardly by the book and often times seemingly pragmatic. Well, the President’s Twitter account, at least.

Potentially, there may be pressure behind the scenes from U.S. suppliers who fear a loss of business as companies like Taiwan’s MediaTek plan to step up in a bid to work with ZTE in the event that it is blocked from U.S. partners.

Even with Trump’s unexpected backing, ZTE is up against it to roll back the sanctions. There’s clearly a gap of thinking between the President and the rest of government.

Trump has frequently lashed out at the House and the Senate, not to mention his own party, over differences of opinion and his frustration with politics. In this case, ZTE’s infringements are so major — trade violations and national security concerns — that it is hard to envisage the company getting a pass, even with support from the White House.

To recap, here’s what FBI Director Chris Wray told the Senate Intelligence Committee in February:

“We’re deeply concerned about the risks of allowing a company or entity that is beholden to foreign governments that don’t share our values to gain positions of power inside our telecommunications networks.”

And Commerce Secretary Wilbur Ross speaking in April about the violation of sanctions on Iran and North Korea, which ZTE pleaded guilty to:

“ZTE made false statements to the U.S. Government when they were originally caught and put on the Entity List, made false statements during the reprieve it was given, and made false statements again during its probation. ZTE misled the Department of Commerce. Instead of reprimanding ZTE staff and senior management, ZTE rewarded them. This egregious behavior cannot be ignored.”

Just another day in Trump’s America.

Suppose, just for a moment, just for argument’s sake, that (some) cryptocurrencies are not a giant scam, and what’s more, they’re not just another kind of financial asset. Come on. Don’t look at me like that. Work with me here. Imagine, just for a moment, that there exist plausible futures in which they matter.

An interesting question to ask is: what exactly do those futures look like? Because if we can’t come up with any compelling answers, then we may conclude, by reductio ad absurdum, that a cryptofuture is awfully unlikely. So let’s walk through a few scenarios, shall we? And then judge how likely each one is.

1. The Crypto Maximalist Future

Situation: Bitcoin is the global currency. Except for “System D,” of course, and transactions hidden for reasons of tax avoidance, which run on ZCash, which is (ineffectively) banned by governments who fear the loss of their tax revenue from earned income hidden by zk-SNARKs. All retail transactions run through Lightning hubs, constantly watched and verified by AIs.

People maintain their own private keys, without which all of their life savings effectively vanish. These keys also maintain all of their own personal data, which they approve for usage by dapps on the Ethereum “world computer,” which performs billions of transactions per second courtesy of Plasma and (again) AIs monitoring the system with fraud proofs at the ready.

Fiat currencies died of hyperinflation. Banks died with them. Nation-states are on life support., and the new generation prefers statelessness to any citizenship. The world is increasingly controlled by a weird combination of libertarian Bitcoin seasteaders and communal Ethereum hacker collectives, who name themselves “phyles” after Neal Stephenson’s The Diamond Age, but call this The Crypto Age.

Likelihood: essentially nil, for many, many reasons, such as: The overwhelming majority of people don’t want to maintain their own private keys, and if you don’t maintain your own private keys, cryptocurrencies are essentially no different from fiat money held in banks, except for the many ways (such as the irrevocability of transactions) in which they are wildly inferior. Credit and cryptocurrencies play poorly together. Most people want strong governments, and strong governments want to control their own currencies, meaning, with only one small logical remove, that most people want fiat currencies. Deflation is actually bad. Etcetera etcetera etcetera etcetera etcetera. I mean come on people.

2. The Wall Street Crypto Future

Situation: Ordinary people don’t use cryptocurrencies. Why would they? But the financial world has gone full crypto; you always go full crypto. Stocks live only on the Ethereum blockchain. Bonds, too. Anyone who can qualify for a “security token” — a proof of your identity and valid investordom — can trade any stock, and any bond, in any market, from any country, anywhere in the world, in near real time, without asking for permission. Mostly via fully decentralized exchanges, though in certain markets centralized ones still have their advantages. Few people do it directly, though; their stock AIdvisors handle it for them.

Bitcoin is the global settlement and reserve currency; nobody cares about gold any more. Your credit card may be charged in dollars but that money is promptly converted to Bitcoin, and some satoshis are sent to the card issuer and the merchant bank (in a single transaction) before being converted back to dollars and sent to the vendor — the Lightning fees are so tiny, courtesy of the volume being so immense, that this is cheaper than the alternative. Ordinary people still don’t even know what Lightning is but the payment channels which connect banks, both within and between nations, pulse with hundreds of millions of dollars every single day.

Likelihood: slim to none. I personally see the irrevocability of crypto transactions, and the awkward “how do you provide cryptocurrency credit” issues as twin dealbreakers here — but I’m an engineer not a financier, so you could maybe persuade me that I’m wrong. We can at least see some of the advantages of cryptocurrencies here; why squander fortunes on running and maintaining hundreds to thousands of various financial databases and messaging buses around the world, when in theory we could have … well … one?

3. The Dapper Dapp Future

Situation: Financially, cryptocurrencies are just an asset class and a counterculture, but tokenized “fat protocols” powering decentralized apps have conquered the Internet. Facebook, Twitter, and increasingly even Google have been replaced by vast peer-to-peer networks in which processing and data are coordinated and optimized in real time by token transfers orchestrated by AI proxies. The rules of these systems are determined by frequent votes, which, again, are tokenized.

All of your personal data is packetized in many redundant tranches scattered across the Internet, protected by your private key(s) and various aspects of it are made available to services that wish to use it only as and when you or your proxies approve that access. You are rewarded with tokens for this access, which can then spend on other services. You maintain a portfolio of hundreds, sometimes thousands, of different kinds of tokens, and your AI proxy frequently trades between them so as to optimize this portfolio for your behavior.

Similar tokenized protocol infrastructures are beginning to creep offline and to organize meatspace projects, too, ranging from hardware development to massive-scale art collectives to urban planning and the transformation of entire cities. Token economics increasingly govern all of human behavior.

Likelihood: Yeah I don’t think so. I concede that in its way it’s an inspiring notion, but: most people want and like centralized solutions, which give them an authority to complain to, and to introduce and enforce rules, without having to vote on every single administrative detail of every network they connect to. (California ballot propositions are bad enough; imagine having to deal with their equivalent every day.) Dapps are by their very nature more complex, more fragile, and harder/slower to evolve than capps. (Imagine having to fork every time a feature changes. Now imagine some of those being hard forks.) Rewards to decentralized users are trivial — Facebook makes maybe $10/user/quarter, which is, to understate, not enough reward for the hassle of decentralization. Centralized solutions also have the advantages of things like “economies of scale” and “data centers which are more efficient than personal computers” and “databases which are vastly more efficient than blockchains.” And nobody wants to have to keep track of a portfolio of hundreds of different kinds of tokens no matter how useful their AI assistant may become.

4. The Global Crypto South Future

Situation: North America and Europe still use dollars and euros. Wall Street still uses its own systems, though it dabbles some in crypto assets. Facebook still rules the social media of the wealthy world. Cryptocurrencies are an afterthought, a curiosity, a fringe investment.

But the global South is different. Venezuela and Zimbabwe were the first to replace their currencies with cryptocurrencies that literally cannot hyperinflate. (I.e. a real cryptocurrency, not Venezuala’s what-even-is-that recent grotesquerie) Others soon followed; it was an easy and natural evolution from M-Pesa, Orange Money, and the like. There were some catastrophic failures in the early days, eg the BGP attack that took out most of the miners / validators of the Ethiopian cryptobirr and enabled a successful 51% attack that made a few hackers very wealthy at the expense of Addis Ababa’s treasury, but a few hard forks and version 2.0s later, stable prosperity was achieved.

The local stock and bond markets followed. As did the local Internet, where bandwidth costs far greater than those of the USA, plus the relatively greater size of potential dapp rewards, led to efficient local dapps, mostly using national cryptocurrencies (which can be traded for one another in real time on a vast decentralized exchange of atomic cross-chain payment channels), which have all but replaced centralized Western local services. Nowadays when Zimbabweans visit London and New York they’re taken aback by how backward those legacy financial systems seem.

Likelihood: I’m going to go out on a limb here and suggest that this is actually plausible. Not likely, necessarily, but plausible. In New York and London and Toronto and Paris, deflationary cryptocurrencies and real-time cross-country payment channels are basically solutions looking for a problem; I’d rather just use any one of my several no-international-usage-fees credit cards in Paris, and get the bonus miles / points, the ability to contest and reverse charges, the credit float, the extended warranty and other card bonuses, etc., rather than transact with the “global currency” Bitcoin over a Lightning payment channel, as cool as that sounds. But when you don’t have the mature, rewards-laden international payment system to hand, when you’re treated as suspicious and denied credit just because you’re from the most populous country in Africa, when your national currency’s inflation rate crosses double digits heading for triple … then, suddenly, the calculation looks very different indeed.

5. The Crypto Counterculture Future

Situation: Bitcoin did not conquer. Ethereum did not conquer. Tezos did not, EOS did not, Hashgraph did not. People around the world use credit cards, US dollars, euros, reals, yuan, etc., just as they always did. Wall Street might use some private / permissioned blockchains, as may some supply-chain enterprises, but their effect consists of an uptick in enterprise efficiency and a decrease in some costs, not the global revolution we were promised.

…That is, for 98% of the population. 2% however, are different. Maybe because they’re libertarians who mistrust the government, or hackers fascinated by the technology, or because they believe in the prospect of a better world. They’re willing to go through the struggle of dealing with private keys, funding payment channels, acquiring tokens to set up and pay for dapps and federate their data, and so forth. Only 2% of the population. But worldwide, that means 140 million people.

Only 140 million people use uncensorable, independent, decentralized social media. But that’s a big enough number that it means censorship doesn’t really fly on centralized media, either, because it can be transposed to the decentralized alternative. Only 140 million use cryptocurrencies for their day-to-day expenses and long-term savings. But that’s a big enough alternative to keep national currencies honest, because they know that if they start to degrade, a viable alternative already exists, and if the pain of centralized fiat money grows great enough, people can and will move to that alternative. Only 140 million people use permissionless systems; but that’s enough that if you get locked out of or kicked out of your nation’s permissioned infrastructure, there’s an alternative that you can adopt without your life being entirely ruined.

In short, only 2% of the population use cryptocurrencies … but that 2% performs an enormous service for the other 98%, by keeping censors, and governments, and central banks, honest. Providing a viable decentralized alternative, in and of itself, mitigates many of the flaws of centralized systems. It could be, actually, the best of both worlds.

Likelihood: Call me an optimist, but I think this is the most likely outcome of all.

Every once in a while, a college student or recent graduate dares to launch a robotics startup and . . . everything goes as well as could be expected. Such is the case, for example, with Alex Rodrigues and Brandon Moak, two former University of Waterloo students who worked on self-driving technologies together in college and formed their now venture-backed, self-driving truck company, Embark, instead of graduating. (Originally called Varden Labs, the startup’s trip through Y Combinator undoubtedly helped.)

Still, to capture the sustained interest of robotics investors, it helps to either have experience in a particular industry or to pull in someone, quickly, who does. That much was established yesterday at UC Berkeley, when three veteran investors — Renata Quintini of Lux Capital, Rob Coneybeer of Shasta Ventures, and Chris Evdemon of Sinovation Ventures — took the stage of a packed Zellerbach Hall to talk about where they’ve invested previously, and where they are shopping now and why.

Though the three expressed interest in a wide range of technologies and plenty of optimism about what’s to come, each lingered a bit on one point in particular, which was the difficulty robotics founders face who are completely unfamiliar with the particular industry they may hope to help reshape with their innovation.

You can catch the entire interview below, but we  thought college students — and their professors and mentors — might want to pay particularly close attention to this concern if they’re thinking about hitting up investors in the not-too-distant future.

Quintini on how comfortable she and her colleagues at Lux are when it comes to backing recent college graduates:

What we care the most about what is your unique insight and what do you know about tackling a certain market or problem that’s not obvious or easy to replicate. In some cases, it’s very fair for someone right out of university who finds a technological breakthrough and . . . that breakthrough alone is understandable and comprehensible to the market and it’s a very backable company, and we’ve done that in the past.

But in some cases, and you’ve heard today, [CEO] Patrick [Sobalvarro] from Veo Robotics speak — and [Veo is] actually giving robotic arms perception sensors to allow people and robots to work together — all his insights came because he came from industry. He was at Rethink Robotics; he’s been in the robotics industry, selling to people who use robots as part of the manufacturing process. And so he actually understands the importance of safety and the selling of those systems to customers. Because he knew that, it made a big difference in how he approaches his go-to-market strategy and how he approaches building a product. And somebody who’s just thinking about, ‘Oh, let me figure out the technology and how to understand when a human is close or not’ and who didn’t think about the other angle wouldn’t be so successful or differentiated in our opinion.

Coneybeer sounded a similar tone. In fact, when asked if he felt there were other overlooked opportunities like that identified by Veo — which is refitting existing robotic arms, rather than trying to remake them from scratch — Coneybeer said the most attractive thing of all to him are startups in search of a problem that actually exists: 

What we’re very cognizant of is people who love robots and are trying to invent a market or invent a need and kind of force fit it, as opposed to people who understand a need and are using robotics as a tool to truly solve that need. That’s a really key differentiator.

We directed an entirely different question to Evdemon, about how Sinovation thinks about domestic versus industrial robots and whether it expects to commit more capital to one or the other. But Evdemon first took the time to note that the problem of founders who don’t know their industries is a very big one, and deserved more discussion:

Chiming in to what Renata and Rob were saying, you understated [the issue]. The majority of the teams that we are looking on both the consumer and industrial robot [worlds] at the moment are more of a technology trying to find a fit in the market, and that’s obviously a very big problem from a venture point of view.

We also see a lot of teams that are fresh out of school, usually a supervising professor with a couple of his or her PhD students having come across some kind of technological breakthrough in university and trying to commercialize that. But robotics are all about what sectors they are being applied to. An ag tech team that knows nothing about agriculture, or a security robot that has a team that’s come up with a great computer vision breakthrough around security issues but that has no idea how the security industry in the U.S. or other parts of the world is structured, is obviously not a good starting point — at least not from a business-minded point of view.

And all of these companies run across tremendous difficulty when it comes to sales. Complementary of teams and market fit [both, are] important for [students] who are thinking about such a move straight out of school.

There isn’t a software company out there worth its salt that doesn’t have some kind of artificial intelligence initiative in progress right now. These organizations understand that AI is going to be a game-changer, even if they might not have a full understanding of how that’s going to work just yet.

In March at the Adobe Summit, I sat down with Adobe executive vice president and CTO Abhay Parasnis, and talked about a range of subjects with him including the company’s goal to build a cloud platform for the next decade — and how AI is a big part of that.

Parasnis told me that he has a broad set of responsibilities starting with the typical CTO role of setting the tone for the company’s technology strategy, but it doesn’t stop there by any means. He also is in charge of operational execution for the core cloud platform and all the engineering building out the platform — including AI and Sensei. That includes managing a multi-thousand person engineering team. Finally, he’s in charge of all the digital infrastructure and the IT organization — just a bit on his plate.

Ten years down the road

The company’s transition from selling boxed software to a subscription-based cloud company began in 2013, long before Parasnis came on board. It has been a highly successful one, but Adobe knew it would take more than simply shedding boxed software to survive long-term. When Parasnis arrived, the next step was to rearchitect the base platform in a way that was flexible enough to last for at least a decade — yes, a decade.

“When we first started thinking about the next generation platform, we had to think about what do we want to build for. It’s a massive lift and we have to architect to last a decade,” he said. There’s a huge challenge because so much can change over time, especially right now when technology is shifting so rapidly.

That meant that they had to build in flexibility to allow for these kinds of changes over time, maybe even ones they can’t anticipate just yet. The company certainly sees immersive technology like AR and VR, as well as voice as something they need to start thinking about as a future bet — and their base platform had to be adaptable enough to support that.

Making Sensei of it all

But Adobe also needed to get its ducks in a row around AI. That’s why around 18 months ago, the company made another strategic decision to develop AI as a core part of the new  platform. They saw a lot of companies looking at a more general AI for developers, but they had a different vision, one tightly focussed on Adobe’s core functionality. Parasnis sees this as the key part of the company’s cloud platform strategy. “AI will be the single most transformational force in technology,” he said, adding that Sensei is by far the thing he is spending the most time on.”

Photo: Ron Miller

The company began thinking about the new cloud platform with the larger artificial intelligence goal in mind, building AI-fueled algorithms to handle core platform functionality. Once they refined them for use in-house, the next step was to open up these algorithms to third-party developers to build their own applications using Adobe’s AI tools.

It’s actually a classic software platform play, whether the service involves AI or not. Every cloud company from Box to Salesforce has been exposing their services for years, letting developers take advantage of their expertise so they can concentrate on their core knowledge. They don’t have to worry about building something like storage or security from scratch because they can grab those features from a platform that has built-in expertise  and provides a way to easily incorporate it into applications.

The difference here is that it involves Adobe’s core functions, so it may be intelligent auto cropping and smart tagging in Adobe Experience Manager or AI-fueled visual stock search in Creative Cloud. These are features that are essential to the Adobe software experience, which the company is packaging as an API and delivering to developers to use in their own software.

Whether or not Sensei can be the technology that drives the Adobe cloud platform for the next 10 years, Parasnis and the company at large are very much committed to that vision. We should see more announcements from Adobe in the coming months and years as they build more AI-powered algorithms into the platform and expose them to developers for use in their own software.

Parasnis certainly recognizes this as an ongoing process. “We still have a lot of work to do, but we are off in an extremely good architectural direction, and AI will be a crucial part,” he said.

There is no degree required to be a CEO of a venture-backed company. But it likely helps to graduate from Harvard, Stanford or one of about a dozen other prominent universities that churn out a high number of top startup executives.

That is the central conclusion from our latest graduation season data crunch. For this exercise, Crunchbase News took a look at top U.S. university affiliations for CEOs of startups that raised $1 million or more in the past year.

In many ways, the findings weren’t too different from what we unearthed almost a year ago, looking at the university backgrounds of funded startup founders. However, there were a few twists. Here are some key findings:

Harvard fares better in its rivalry with Stanford when it comes to educating future CEOs than founders. The two universities essentially tied for first place in the CEO alum ranking. (Stanford was well ahead for founders.)

Business schools are big. While MBA programs may be seeing fewer applicants, the degree remains quite popular among startup CEOs.  At Harvard and the University of Pennsylvania, more than half of the CEOs on our list graduated as business school alum.

University affiliation is influential but not determinative for CEOs. The 20 schools featured on our list graduated CEOs of more than 800 global startups that raised $1M or more in roughly the past year, a minority of the total.
Below, we flesh out the findings in more detail.

Where startup CEOs went to school

First, let’s start with school rankings. There aren’t many big surprises here. Harvard and Stanford far outpace any other institutions on the CEO list. Each counts close to 150 known alum among chief executives of startups that raised $1 million or more over the past year.

MIT, University of Pennsylvania, and Columbia round out the top five. Ivy League schools and large research universities constitute most of the remaining institutions on our list of about twenty with a strong track record for graduating CEOs. The numbers are laid out in the chart below:

Traditional MBA popular with startup CEOs

Yes, Bill Gates and Mark Zuckerberg dropped out of Harvard. And Steve Jobs ditched college after a semester. But they are the exceptions in CEO-land.

The typical path for the leader of a venture-backed company is a bit more staid. Degrees from prestigious universities abound. And MBA degrees, particularly from top-ranked programs, are a pretty popular credential.

Top business schools enroll only a small percentage of students at their respective universities. However, these institutions produce a disproportionately large share of CEOs. Wharton School of Business degrees, for instance, accounted for the majority of CEO alumni from the University of Pennsylvania . Harvard Business School also graduated more than half of the Harvard-affiliated CEOs. And at Northwestern’s Kellogg School of Management, the share was nearly half.

CEO alumni background is really quite varied

While the educational backgrounds of startup CEOs do show a lot of overlap, there is also plenty of room for variance. About 3,000 U.S. startups and nearly 5,000 global startups with listed CEOs raised $1 million or more since last May. In both cases, those startups were largely led by people who didn’t attend a school on the list above.

Admittedly, the math for this is a bit fuzzy. A big chunk of CEO profiles in Crunchbase (probably more than a third) don’t include a university affiliation. Even taking this into account, however, it looks like more than half of the U.S. CEOs were not graduates of schools on the short list. Meanwhile, for non-U.S. CEOs, only a small number attended a school on the list.

So, with that, some words of inspiration for graduates: If your goal is to be a funded startup CEO, the surest path is probably to launch a startup. Degrees matter, but they’re not determinative.