Ideaforge

So-called ‘EdTech’ has seen many false dawns over the years. After being lauded as the teaching platforms of the future, most MOOCs (Massive Open Online Course platforms) have not quite lived up to the superlatives made for them, and the sector has had trouble coming up with more innovative ideas for a while.

But that appears to be changing if a new wave of startups is any indication. In Dubai this weekend I was invited to judge a number of education startups which are really trying to move the need on EdTech, and in particular on a sector with almost unlimited potential. That is, education platforms aimed at the emerging world, where the hunger for scalable education is almost incalculable.

Consider this: Ethopia, now a far more stable country that it once was, contains more people under 25 than almost anywhere else, and it has a population of over 100 million people. And consider the potential for EdTech to transform countries like India, for instance. This is going to be a very interesting market in the future, as well as being an urgent issue. According to UNESCO, 264 million children do not have access to schooling, while at least 600 million more are “in school but not learning”. These are children who are not achieving even basic skills in maths and reading, which the World Bank calls a “learning crisis”.

A taste of what is to be found in this sector was showcased today at the “Next Billion Edtech Prize,” launched at the Global Education & Skills Forum (think: Davos/WEF for Education) by the Varkey Foundation to recognize the most innovative technology startups destined to have a radical impact on education in low income and emerging world countries.

The overall winner in the competition was Chatterbox, an online language school powered by refugees

This web platform harnesses the wasted talent of unemployed professionals who are refugees, offering them work as online and in-person language tutors. Based in the UK, where there is a language skills shortage estimated to cost the economy £48bn every year, Chatterbox has now signed up several UK universities and major non-profits and corporations to use its services. Having raised a seed round from impact-fund Bethnal Green Ventures, it’s now looking for further funding to expand.

Co-founder and CEO Mursal Hedayat was three years old when she arrived in the UK as a refugee from Afghanistan with her mother, a civil engineer who spoke English and three other languages fluently. “I watched her become unemployed in the UK for more than a decade. Refugees with degrees and valuable skills still face shockingly high levels of underemployment. An idea like Chatterbox has never been more urgently needed,” she says. (Indeed, the conference later heard from Al Gore who quoted research that showed millions of people will become refugees due to climate change in the next few decades).

Chatterbox’s fellow finalists for the $25,000 prize on offer were equally interesting.

Dot Learn was almost literally the same as ‘Silicon Valley’s PiedPiper. It makes online video e-learning far more accessible on slow connections for users in low-income countries, especially because it compresses educational video so making it cheaper to access. Its technology reduces the file-size of learning videos, requiring 1/100th of the bandwidth to watch. At current data prices in Kenya and Nigeria, this means a student or learner can access 5 hrs of online learning for about the cost of sending a single text message ($0.014). The startup was a notable finalist during TechCrunch’s Battlefield Africa.

TeachMeNow is a gig-economy platform for teachers. This marketplace connects teachers, experts, and mentors to students. The technology combines scheduling, payments and live virtual sessions that can connect on any device allows tens of thousands of teachers to create their own online businesses, with some earning over $100,000 last year. In addition, schools and companies including Microsoft use TeachMeNow software to create their own-branded online learning communities.

Sunny Varkey, Founder of the Varkey Foundation and the Next Billion Prize says he launched the prize because “over a billion young people – a number growing every day – are being denied what should be the birthright of every single child. The prize will highlight technology’s potential to tackle the problems that have proven too difficult for successive generations of politicians to solve.”

Other notable finalists included Learning Machine. This using the blockchain as a secure anchor of trust makes verifying the authenticity of a document instantaneously, specifically education documents like university degrees. They are now working to put all the educational records of Malta online.

Localized is a new platform for college students and aspiring professionals in emerging economies to find career guidance, role models and expertise from global professionals who share language and roots (think Slack meets Quora for college students in emerging markets, drawing on diaspora expertise).

The Biz Nation is an EdTech startup focused on empowering youth with technology skills, soft skills, entrepreneurship and financial intelligence through a methodology that improves user’s learning about creating a business.

Source: Tech Crunch

Facebook is a breeding ground for fake news and polarized outrage, accused of corrupting democracy and spurring genocide. Twitter knows it has become a seething battleground of widespread, targeted abuse — but has no solution. YouTube videos are messing with the minds of children and adults alike — so YouTube decided to pass the buck to Wikipedia, without telling them.

All three of those sentences would have seemed nearly unimaginable five years ago. What the hell is going on? Ev Williams says, of the growth of social media: “We laid down fundamental architectures that had assumptions that didn’t account for bad behavior.” What changed? And perhaps the most important question is: have people always been this awful, or have social networks actually made us collectively worse?

I have two somewhat related theories. Let me explain.

The Uncanny Social Valley Theory

“Social media is poison,” a close friend of mine said to me a couple of years ago, and since then more and more of my acquaintances seem to have come around to her point of view, and are abandoning or greatly reducing their time spent on Facebook and/or Twitter.

Why is it poison? Because this technology meant to provoke human connection actually dehumanizes. Not always, of course; not consistently. It remains a wonderful way to keep in contact with distant friends, and to enhance your relationship and understanding of those you regularly see in the flesh. What’s more, there are some people with whom you just ‘click’ online, and real friendships grow. There are people I’ve never met who I’d unhesitatingly trust with the keys to my car and home, because of our interactions on various social networks.

And yet — having stipulated all the good things — a lot of online interactions can and do reduce other people to awful caricatures of themselves. In person we tend to manage a kind of mammalian empathy, a baseline understanding that we’re all just a bunch of overgrown apes with hyperactive amygdalas trying to figure things out as best we can, and that relatively few of us are evil stereotypes. (Though see below.) Online, though, all we see are a few projections of those mammal brains, generally in the form of hastily constructed, low-context text and images … as mediated and amplified by the outrage machines, those timeline algorithms which think that “engagement” is the highest goal to which one can possibly aspire online.

I am reminded of the concept of the Uncanny Valley: “humanoid objects which appear almost, but not exactly, like real human beings elicit uncanny, or strangely familiar, feelings of eeriness and revulsion in observers.” Sometimes you ‘click’ with people online such that they’re fully human to you, even if you’ve never met. Sometimes you see them fairly often in real life, so their online projections are just a new dimension to their existing humanity. But a lot of the time, all you get of them is that projection … which falls squarely into an empathy-free, not-quite-human, uncanny social valley.

And so many of us spend so much time online, checking Twitter, chatting on Facebook, that we’ve all practically built little cottages in the uncanny social valley. Hell, sometimes we spend so much time there that we begin to believe that even people we know in real life are best described as neighbors in that valley … which is how friendships fracture and communities sunder online. A lot of online outrage and fury — the majority, I’d estimate, though not all — is caused not by its targets’ inherent awfulness but by an absence, on both sides, of context, nuance, and above all, empathy and compassion.

The majority. But not all. Because this isn’t just a story of lack of compassion. This is also a story of truly, genuinely awful people doing truly, genuinely awful things. That aspect is explained by…

The Intransigent Asshole Theory

Of course the Internet was always full of awful. Assholes have been trolling since at least 1993. “Don’t read the comments” is way older than five years old. But it’s different now; the assholes are more organized, their victims are often knowingly and strategically targeted, and many seem to have calcified from assholedom into actual evil. What’s changed?

The Intransigent Asshole Theory holds that the only thing that’s changed is that more assholes are online and they’ve had more time to find each other and agglomerate into a kind of noxious movement. They aren’t that large in number. Say that a mere three percent of the online population are, actually, the evil stereotypes that we perceive so many to be.

If three of 100 people are known to be terrible human beings, the other 97 can identify them and organize to defend themselves with relative ease. 97 is well within Dunbar’s number after all. But what about 30 of a 1,000? That gets more challenging, if those thirty band together; the non-awful people have to form fairly large groups. How about 300 of 10,000? Or 3,000 of 100,000? 3 million of 100 million? Suddenly three percent doesn’t seem like such a small number after all.

I chose three percent because it’s the example used by Nassim Taleb in his essay/chapter “The Most Intolerant Wins: The Dictatorship of the Small Minority.” Adopting his argument slightly, if only 3% of the online population really wants the online world to be horrible, ultimately they can force it to be, because the other 97% can — as empirical evidence shows — live with a world in which the Internet is often basically a cesspool, whereas those 3% apparently cannot live with a world in which it is not.

Only a very small number of people comment on articles. But they are devoted to it; and, as a result, “don’t read the comments,” became a cliché. Is it really so surprising that “don’t read the comments” spread to “Facebook is for fake outrage and Twitter is for abuse,” given that Facebook and Twitter are explicitly designed to spread high-engagement items, i.e. the most outrageous ones? Really the only thing that’s surprising is that it took this long to become so widespread.

Worst of all — when you combine the Uncanny Social Valley Theory with the Intransigent Asshole Theory and the high-engagement outrage-machine algorithms, you get the situation where, even if only 3% of people actually are irredeemable assholes, a full 30% or more of them seem that way to us. And the situation spirals ever downwards.

“Wait,” you may think, “but what if they didn’t design their social networks that way?” Well, that takes us to the third argument, which isn’t a theory so much as an inarguable fact:

The Outrage Machine Money Maker

Outrage equals engagement equals profit. This is not at all new; this goes back to the ‘glory’ days of yellow journalism and “if it bleeds, it leads.” Today, though, it’s more personal; today everyone gets a customized set of screaming tabloid headlines, from which a diverse set of manipulative publishers profit.

This is explicit for YouTube, whose creators make money directly from their highest-engagement, and thus (often) most-outrageous videos, and for Macedonian teenagers creating fake news and raking in the resulting ad income. This is explicit for the politically motivated, for Russian trolls and Burmese hate groups, who get profits in the form of the confusion and mayhem they want.

This is implicit for the platforms themselves, for Facebook and Twitter and YouTube, all of whom rake in huge amounts of money. Their income and profits are, of course, inextricably connected to the “engagement” of their users. And if there are social costs — and it’s become clear that the social costs are immense — then they have to be externalized. You could hardly get a more on-the-nose example of this than YouTube deciding that Wikipedia is the solution to its social costs.

The social costs have to be externalized because human moderation simply doesn’t scale to the gargantuan amount of data we’re talking about; any algorithmic solution can and will be gamed; and the actual solution — which is to stop optimizing for ever-higher engagement — is so completely anathema to the platforms’ business models that they literally cannot conceive of it, and instead claim “we don’t know what to do.”

In Summary

• Only ~3% of people are truly terrible, but if we are sufficiently compliant with their awfulness, that’s enough to ruin the world for the rest of us. History shows that we have been more than sufficiently compliant.
• Social networks often dehumanize their participants; this plus their outrage-machine engagement optimization makes fully 30% of people seem like they’re part of those 3%, which breeds rancor and even, honestly no fooling not exaggerating, genocide.
• (Are those the exact numbers? Almost certainly not! My point is that social networks cause “you are an awful, irredeemable human being” to be massively overdiagnosed, by an order of magnitude or more.)
• A solution is for social networks to ramp down their outrage machine, i.e. to stop optimizing for engagement.
• They will not implement this solution.
• Since they won’t implement this solution, then unless they somehow find another one — possible, but unlikely  — our collective online milieu will just keep getting worse.
• Sorry about that. Hang in there. There are still a lot of good things about social networks, after all, and it’s not like things can get much worse than they already are. Right?
• …Right?

Source: Tech Crunch

The epic battle between Qualcomm and Broadcom seems to have reached its armistice, with President Trump using the power of CFIUS to block the transaction this past week, ending what would have been the largest tech M&A transaction of all time.

It may be all quiet on the semiconductor front, but Qualcomm and Broadcom will now need to find a path forward to win the peace and secure access to the coming 5G wireless market. Qualcomm faces a daunting number of challenges, including a potential takeover battle waged by the spurned son of its founder. Broadcom will have to find a new path to use acquisitions to continue its growth.

As with any war though, the damage from this conflict isn’t exclusive to the two enemy combatants. The future of corporate governance and shareholder autonomy is now being reevaluated in light of the actions used by Qualcomm in its defense against Broadcom’s hostile takeover. In addition, America’s openness to foreign investment is increasingly under scrutiny.

Qualcomm picks up the pieces

Hostile takeovers are always going to be damaging affairs, no matter the outcome. The most important mandate for any board of directors — and particularly for the boards of technology companies — is to identify long-term threats and opportunities facing a company, and guide the executive team toward the best possible outcome for shareholders. Hostile takeovers are firefighting affairs — the discussions of the board are jolted from roadmaps, strategy, and vision to the minute-by-minute tactics of defending the company from marauding invaders.

Qualcomm should be directing its attention to strategy, but it faces additional wars on nearly every front. It’s fighting shareholders for its future, fighting Apple and Huawei over its revenues, fighting China over its acquisition of NXP, and now potentially fighting its founder’s son from a private takeover attempt.

Many of Qualcomm’s shareholders see the company’s performance as disappointing. While its stock has fluctuated over the past six years, today’s share price is essentially flat from where it stood in January of 2012. Compare that to Broadcom, which in the same timeframe has seen an increase of about 740%, and the PHLX Semiconductor Sector index, a basket index of the industry, which has seen its value increase by about 280%.

Unsurprisingly, shareholders were enticed by the opportunity to suddenly realize a 35% premium on their shares with Broadcom’s $82-a-share offer. Unlike Qualcomm’s board, shareholders were very interested in accepting Broadcom’s offer. In fact, we now know that Qualcomm’s board knew that it has lost the battle against Broadcom with its own shareholders during the acquisition process. As Bloomberg reported this week:

The votes started to come in on Friday, March 2. By Sunday it was clear that Qualcomm’s defense had failed.

Four of the six directors Broadcom had nominated were polling so far ahead of their Qualcomm peers that the race was effectively over, according to data viewed by Bloomberg. The remaining two were winning by less substantial margins. Making it worse, Mollenkopf and Jacobs, the architects of Qualcomm’s standalone plan, had received some of the fewest votes.

Inside the Qualcomm camp, the mood was bleak; assuming the trend continued, the board would lose control of the company at the shareholder meeting.

Broadcom’s message was one of quiet confidence. The company knew it had won, one person close to the discussions said. At that point, the person said, it was just a question of by how many votes, and who was going to leave the board.

Broadcom was winning the battle with shareholders, so Qualcomm’s board shifted to a terrain far more favorable to it: Washington bureaucrats. From the same Bloomberg report, “Federal lobbying disclosures for 2017 showing that Qualcomm spent $8.3 million, or roughly 100 times the $85,000 Broadcom spent…” These weren’t regulators; these were friends.

In late January, Qualcomm’s board submitted a preliminary, voluntary, and confidential notice to CFIUS asking for a review of Broadcom’s potential board coup. When Broadcom attempted to redomicile to the United States to avoid CFIUS purview (as it would no longer be a foreign company but a domestic one after it redomiciled), the government’s anger was palpable and sealed the company’s fate. The board’s original outreach to CFIUS precipitated the sequence of events that led to Trump’s block this past week.

Qualcomm’s board won the war, but it is still facing a rebellion from its own bosses. The board will be up for election unopposed this week at the company’s delayed shareholders meeting. Perhaps taking a page from tomorrow’s Russian presidential election, some shareholders are withholding their votes from the board slate to show their displeasure with the entire saga. From the Wall Street journal, “Institutional Shareholder Services Inc., an influential proxy-advisory firm, … in a note to investors late Wednesday, stood by its original recommendation that shareholders vote for four Broadcom nominees for Qualcomm’s 11-person board, even though the votes won’t count.”

That shareholder meeting will no doubt be eventful. While the board and the company’s execs will argue that they have a strategy moving forward, they confront two other ongoing firefighting challenges and one new one that could be another round of bruising internecine warfare.

Qualcomm is still in the midst of its $44 billion NXP acquisition, which continues to wait on Chinese regulatory approval. The timeline for that approval is still unclear, but even when Qualcomm does receive it, the company will still have to close the deal and actually implement the transaction. That will take significant time and energy.

Even more complicated is the continuing fight with Apple and Huawei over Qualcomm’s IP licensing revenue. Licensing revenue is crucial for Qualcomm, and the litigation around the fight will force the board to continue monitoring the day-to-day legal tactics of the company rather than focus on a longer-term vision of how to work with the largest smartphone producer in the world to generate profits.

On top of those two challenges, another takeover attempt could potentially exhaust the board further. Yesterday, Qualcomm’s board voted to remove board member Paul Jacobs, who is the son of Qualcomm’s founder and the company’s former chief executive from 2005 to 2014. He had been demoted from executive chairman to director just last week. As the New York Times noted, “The split, which means no member of the Jacobs family will be involved at the top echelons of Qualcomm for the first time in 33 years, was not friendly.”

According to reports, Jacobs is attempting to raise more than $100 billion to buy the company, potentially leveraging SoftBank’s Vision Fund in the process. SoftBank, of course, is a Japanese company, and the Vision Fund has significant capital from foreign countries including Saudi Arabia and the United Arab Emirates. Even more ironically, Qualcomm is an investor in the Vision Fund.

Jacobs is following in the footsteps of Michael Dell who bought the eponymous tech company back in 2013 in a take-private transaction worth $24 billion. Can Jacobs even raise the required amount of capital, four times more than Dell? Will Qualcomm be forced to run back to the Trump administration in order to avoid a “foreign” takeover of the firm yet again, this time by the son of the company’s founder?

My guess — fairly weakly held — is that the answers are yes and no. Jacobs will find the money, and the board won’t fight a distinguished former executive — even if Jacobs was running seriously behind in shareholder approval in the Broadcom fight. We will learn more in the coming weeks, but expect more strategic actions here (maybe from Intel) as well.

Broadcom regroups

Despite its very public failure, Broadcom is in a much stronger position coming out of this battle. It beat analyst estimates this week for its Q1 earnings, and has seen impressive growth in its wireless communications segment, which were up 88% year-over-year. It also managed to lower expenses, which helped drive an increase in gross margin to 64.8% (aren’t fabless and patents awesome?)

Broadcom continues to deliver strong results, but the big question post-Qualcomm is really what’s next? Qualcomm was the single most important chip company that might have been available for purchase (Intel is out of Broadcom’s league). While it plans to continue to redomicile to the U.S., which should allow it to get back into the acquisition game in America, Broadcom may struggle in the coming years to find the kinds of accretive acquisitions that can keep its growth on the trajectory it has been on over the past few years.

Shareholder power wanes?

The biggest questions coming out of the Qualcomm / Broadcom spat is not related to the companies themselves, but the entire intellectual edifice of shareholder rights and the framework used by American companies to conduct corporate governance.

Qualcomm’s board of directors took extraordinary steps to block the Broadcom acquisition. They unilaterally went to Washington to get an injunction not on a deal — which had never been consummated between the two companies — but to block Broadcom from replacing its board of directors in a standard shareholder vote. This is a very important distinction: Qualcomm’s board saw the direction shareholders wanted to go, and essentially decided to just ignore the election process entirely.

From Dealpolitik columnist Ronald Barusch:

This change threatens over three decades of a carefully balanced governance system. Since the Delaware Supreme Court approved the use of the poison-pill takeover defense in 1985, the courts have basically blessed the following tradeoff: On the one hand, corporate directors can fight tooth and nail to stop a deal and the courts will give only limited scrutiny to defensive tactics.

However, the board is strictly limited in any moves to interfere with shareholders’ ability to replace directors and force a company to change course that way. In the vernacular of a leading Delaware case, a “just say no” defense doesn’t mean “just say never.” A bidder with enough patience who can convince a target’s shareholders to change directors has a path at least toward cooperation on resolving regulatory impediments to a deal.

This is a unique case as Barusch notes, but at what point can boards use every method at their disposal to prevent their own shareholders — the people they have a fiduciary duty to represent — from taking charge of the company? This past week presents one of the most complex examples to date, and it wouldn’t surprise me if a shareholder decides to attempt a legal attack on Qualcomm.

The other side of the potential waning of power for shareholders is CFIUS itself. The Trump administration ended a potential deal for a company that shareholders were widely in favor of. Where do the rights of shareholders to realize a return on their equity end and the right of America as a nation to control national security technology start?

We are on new terrain, and there are no clear answers here. In many ways, it depends on what happens over the next few years of the Trump administration. If there are more blocks like what we saw this week, we could see a radical change in the corporate calculus that would have a long-term negative effect on the value of some American companies.

Hostile takeovers may be incredible drama for writers like yours truly, but they have enormous consequences for companies and the employees who work at them. Qualcomm is going to have to shore up its support with a whole host of stakeholders in the coming months (while dealing with a potential take-private fight), while Broadcom needs to find its next strategy for further growth. All of us are going to have to deal with new uncertainty around the power of shareholders to shape the destiny of their companies. The war is over, but the aftermath and its consequences have just begun.

Source: Tech Crunch

Compelling virtual reality shipped to developers and consumers nearly two years ago. The first flagship headsets arrived from Oculus and HTC back in the spring of 2016, offering enough resolution, frame rate, field of view, latency mitigation and position-tracking to produce believable visual immersion.

But no one seems to know what to do with it. To date, no killer app has extended the promise of VR from a novelty to a sticky experience or utility that reaches beyond enthusiasts to resonate with the consumer center of mass.

This isn’t to say that great experiences don’t exist. Apps like Tilt Brush, Elite: Dangerous and Google Earth VR have earned rave reviews and plaudits from enthusiasts. But we have yet to see a household phenomenon like Halo or Lotus 1-2-3 — applications that single-handedly propelled their respective platforms to wide use. At CES 2018, one industry analyst referred to VR as “drawerware,” referring to the likelihood of headsets to be stuffed in a drawer after a few forays into jejune worlds.

In an attempt to shed some light on the case of the missing VR killer app, I want to offer a few thoughts on why VR matters to users, and what that implies for entrepreneurs and investors interested in building or funding the VR killer app.

Why VR matters: Presence

Why is virtual reality valuable? In a word, presence: Immersion is the heart of the incremental value of VR versus existing platforms. Most forms of expressive media provide a third-person perspective of an experience, or convey sufficient information to help a user imagine a first-person perspective on their own.

When done right (6DoF tracking, room-scale movement, sufficiently high-resolution/FOV/low latency, spatial audio), virtual reality helps a user feel like they are really there. Rather than convey an impression of an experience, VR manipulates our visual and auditory senses (and soon our tactile sense) to transmit experience itself.

Presence is valuable in two ways

The idea that VR is valuable because it generates presence is well understood. But why does presence matter? What need does being there fill for users?

The quality of presence has clear intrinsic value. With few exceptions, subjective immersion is the best way to fully grasp what a certain experience is like. Being at the mountaintop generates the maximum degree of sensory throughput, and is a better way to understand the truth of your relationship to that place than watching a video of the mountain, which is better than seeing a picture of the mountain.

But presence also can have instrumental value, where being there is valuable in an objective sense. Being present at a meeting with a potential business partner sends a positive signal separate from the fidelity of your experience. Actually visiting the mountaintop can impress your friends, mattering beyond the sensation of being there.

Put another way, and borrowing the language of philosophy, it seems like we value presence for its experiential worth — being for the sake of experience — as well as for its ontological worth, or being for the sake of being. Another way to describe the ontological value of presence is authenticity. The philosopher Robert Nozick suggested as much in his refutation of ethical hedonism, employing the notion of the “experience machine” to suggest we care about more than our feelings. What this all means is that for many kinds of experience, the objective fact of being somewhere matters as much or more than the subjective feeling of being there.

VR’s killer app will deliver both types of presence value

How does identifying the two ways that presence drives user value help us imagine the use case that a VR killer app might address?

First, it illuminates why many first-order VR applications may not be suited for adoption by a non-enthusiast audience. When examining some of the typical mass market use cases forwarded by VR aficionados — enterprise or personal telepresence, virtual tourism and travel, virtual attendance at sports and entertainment events, virtual social environments and rec rooms — it seems clear that authenticity matters a great deal to consumers of these experiences, meaning that simply porting them to VR may not be compelling beyond an initial sense of novelty.

I believe that the value of ontological presence is largely driven by social norms. As and when the quality of VR experience converges on metaphysically “real” experience, those norms will evolve. Perhaps our children will label us “substratist” for claiming that hanging out in VR is less satisfying than visiting in person. But with regards to the next generation or two of VR tech and applications, I’m not bullish on social VR experiences that merely replicate the ways we interact in real life. By generating experiential presence without authenticity, they seem to fall into an uncanny valley somewhere between interactive video chat and in-person interaction.

It’s tempting to believe, then, that the VR killer app will skirt the issue of authenticity by solving for problems where the subjective feeling of presence, and not the objective fact of it, matters most — for example, virtual training for a factory worker, touring new construction homes for sale or checking out a car in a virtual showroom. VR is already finding fruitful use in the enterprise and select consumer applications. But when considering potential killer applications, the problem is that arenas of experience where experiential presence matters but authenticity does not usually aren’t important or frequently accessed parts of our life.

Ultimately, I think the first VR blockbuster will deliver both the experiential and ontological value of presence. In other words, VR’s killer app will generate a powerful feeling of being there for a compelling experience, in a way that also feels completely authentic.

I believe that the experience in question will lack an analogue in the real world. In other words, the VR killer app won’t be a multiplayer simulation of New York City in the present day, or a virtual movie theater, or a virtual Giants Stadium where you can kick back in a box and watch the Super Bowl. The application that sells the mass market on virtual reality will be fully native to the platform, such that the only way to know what it is really like will be donning a headset and stepping inside.

An engaging VR experience that isn’t simulating something in the real world, but exists solely in its own right, can immerse a user in both senses of the word: After all, authenticity is implied when the virtual substrate is the only home for a certain experience. The real question is making the experience interesting or fun or cool enough that the feeling of presence is appealing, too.

Concluding thoughts

If it sounds like I’m describing a video game, I think I am, too. But video games are a focal use case for every VR headset in production. What’s missing?

Quality, accessibility and ecosystem maturity are probably the biggest practical barriers gating the VR killer app. The current generation of flagship headsets are cumbersome and expensive to set up and run. Though deep price cuts across flagship wearables powered sales of more than a million VR headsets in Q3 2017, and both Oculus and HTC moved hundreds of thousands of high-end, PC-based units, individual install bases remain low enough to deter AAA studios.

Bootstrapping a two-sided ecosystem — in the case of VR, headsets/users and content, with more of the former increasing the incentive to invest in the latter and vice versa — is never easy. But better technology is on the way: HTC recently announced the Vive Pro, sporting improved resolution, spatial audio and a wireless adapter to do away with clunky wires. Google, Samsung, Lenovo and Oculus are working on standalone headsets that run without a PC or smartphone under the hood. Dozens of startups are developing peripherals and software to improve the VR experience, from haptics that mimic touch to pupil tracking that enables realistic eye contact.

Each new iteration of core VR hardware is a rising tide that makes any VR application more appealing to users on the margin. But killer apps often emerge on imperfect versions of the platforms they bring to life. The charting function of Lotus 1-2-3 strained the limits of the early graphics hardware on x86 PCs, but until 1-2-3, no one knew that programmatic generation of charts and graphs was even possible.

A killer app doesn’t need to be a perfect encapsulation of a new technology’s potential. All it needs to do is hint at the grand vision by providing a single, irresistible demonstration of value over the status quo.

In the case of VR, I’m not certain if that demonstration will occur on this generation of hardware or the next. But I believe it will be an experience that compares in intensity or joy or uniqueness to the best experiences we can access in reality. If you’re working on VR content or applications, consider this advice: Give us the ability to be present in a vision of the past, or a counterfactual world. Give us the feeling of life underwater or in space. Give us the sense of being present for an experience completely native to virtual reality, not merely an emulation of experiences we can already inhabit. Give us something real in its own right. That’s when the mass market will start to believe — and buy.

Source: Tech Crunch

Happy Saturday, everyone! While many things in the world are very bad today, if you were on the Internet last night, you probably caught wind of a pretty cool historic moment in college basketball: UMBC — University of Maryland, Baltimore County — knocked off the overall number one seed in the annual NCAA men’s basketball championship tournament in an absolute landslide.

So, naturally, I absolutely had to find the tech angle here, and if you owned a smartphone, you probably saw a series of extremely excellent tweets from UMBC’s twitter account, which went absolutely ballistic last night. So, we wanted to recognize the other star of the show: UMBC’s twitter account. You probably would too if, as a 21-point underdog, beat what most consider the best team in the country. Most tweet compilations are not great, but this one is very great.

University of Virginia was absolutely crushed during the second half of the game after dominating the world of college basketball for the entire regular season and throughout the conference tournament on the way to the overall number one seed — a system in place where teams are placed in the tournament based on favorable matchups as a reward for their performance. The system is still ripe for upsets, and there have been a lot this year, but this one is arguably one of the biggest upsets of all time.

So, without further ado:

Alarming bucket of truth, that one. We’ll end with this one:

Happy March Madness, all! May fortune favor (the rest) of your brackets.

Source: Tech Crunch

It seems like startup news is full of overnight success stories and sudden failures, like the scooter rental company that went from zero to a $300 million valuation in months or the blood-testing unicorn that went from billions to nearly naught.

But what about those other companies that mature more gradually? Is there such a thing as slow and successful in startup-land?

To contemplate that question, Crunchbase News set out to assemble a data set of top late-blooming startups. We looked at companies that were founded in or before 2010 that raised large amounts of capital after 2015, and we also looked at companies founded a least five years ago that raised large early-stage funds in the last year. (For more details on the rules we used to select the companies, check “Data Methods” at the end of the post.)

The exercise was a counterpoint to a data set we did a couple of weeks ago, looking at characteristics of the fastest growing startups by capital raised. For that list, we found plenty of similarities between members, including a preponderance of companies in a few hot sectors, many famous founders and a lot of cancer drug developers.

For the late bloomers, however, patterns were harder to pinpoint. The breakdown wasn’t too different from venture-backed companies overall. Slower-growing companies could come from major venture hubs as well as cities with smaller startup ecosystems. They could be in biotech, medical devices, mobile gaming or even meditation.

What we did find, however, was an interesting and inspiring collection of stories for those of us who’ve been toiling away at something for a long time, with hopes still of striking it big.

Pivots and patience

Even youthful startups have been known to make a major pivot or two. So it’s not surprising to see a lot of pivots among late bloomers that have had more time to tinker with their business models.

One that fits this mold is Headspace, provider of a popular meditation app. The company, founded in 2010 by a British-born Buddhist monk with a degree in circus arts, started as a meditation-focused events startup. But it turned out people wanted to build on their learning on their own time, so Headspace put together some online lessons. Today, Santa Monica-based Headspace has millions of users and has raised $75 million in venture funding.

For late bloomers, the pivot can mean going from a model with limited scalability to one that can attract a much wider audience. That’s the case with Headspace, which would have been limited in its events business to those who could physically show up. Its online model, with instant, global reach, turns the business into something venture investors can line up behind.

Sometimes your sector becomes hip

They say if you wait long enough, everything comes back in style. That mantra usually works as an excuse for hoarding ’80s clothes in the attic. But it also can apply to entrepreneurial companies, which may have launched years before their industry evolved into something venture investors were competing to back.

Take Vacasa, the vacation rental management provider. The company has been around since 2009, but it began raising VC just a couple of years ago amid a broad expansion of its staff and property portfolio. The Portland-based company has raised more than $140 million to date, all of it after 2016, and most in a $103 million October round led by technology growth investor Riverwood Capital.

CloudCraze, which was acquired by Salesforce earlier this week, also took a long time to take venture funding. The Chicago-based provider of business-to-business e-commerce software launched in 2009, but closed its first VC round in 2015, according to Crunchbase records. Prior to the acquisition, the company raised about $30 million, with most of that coming in just a year ago.

Meanwhile, some late bloomers have always been fashionable, just not necessarily as VC-funded companies. Untuckit, a clothing retailer that specializes in button-down shirts that look good untucked, had been building up its business since 2011, but closed its first venture round, a Series A led by VC firm Kleiner Perkins, last June.

Slow-growing venture-backed startups are still not that common

So yes, there is still capital available for those who wait. However, the truth of the matter is most companies that raise substantial sums of venture capital secure their initial seed rounds within a couple years of founding. Companies that chug along for five-plus years without a round and then scale up are comparatively rare.

That said, our data set, which looks at venture and seed funding, does not come close to capturing the full ecosystem of slow-growing startups. For one, many successful bootstrapped companies could raise venture funding but choose not to. And those who do eventually decide to take investment may look at other sources, like private equity, bank financing or even an IPO.

Additionally, the landscape is full of slow-growing startups that do make it, just not in a venture home run exit kind of way. Many stay local, thriving in the places they know best.

On the flip side, companies that wait a long time to take VC funding have also produced some really big exits.

Take Atlassian, the provider of workplace collaboration tools. Founded in 2002, the Australian company waited eight years to take its first VC financing, despite plentiful offers. It went public two years ago, and currently has a market valuation of nearly $14 billion.

The moral: Those who take it slow can still finish ahead.

Data methods

We primarily looked at companies founded in 2010 or earlier in the U.S. and Canada that raised a seed, Series A or Series B round sometime after the beginning of last year, and included some that first raised rounds in 2015 or later and went on to substantial fundraises. We also looked at companies founded in 2012 or earlier that raised a seed or Series A round after the beginning of last year and have raised $30 million or more to date. The list was culled further from there.

Source: Tech Crunch

It was a big debut for enterprise cloud security company Zscaler, which saw its shares skyrocket 106% on its first day of trading. After pricing at $16, shares opened at $27.50, and closed at $34.

This was also well above the original expected price range for its IPO of $10 to $12. The company ultimately raised $192 million. In other words, there was significantly better-than-expected demand for Zscaler.

But not everyone likes a big pop. This means the company could have technically sold shares for more and raised more money.

Zscaler works with enterprises and says it counts 200 of the Forbes Global 2000 companies as customers. In an interview with TechCrunch, CEO Jay Chaudhry described the business as “the platform which was built in the cloud for the cloud.”

He went on to explain that his business was designed to help companies stay secure with a transient workforce. “We want to work from a hotel, airplane, coffee shop,” said Chaudhry. “The data center is no longer the center of the universe.”

This was the fifth company started by founded by Jay Chaudhry. His other four were acquired.

Zscaler listed on the Nasdaq, under the ticker, “ZS.”

In just the second venture-backed tech IPO of the year, eyes are on Zscaler, which raised $148 million in capital from Lightspeed Venture Partners and TPG ahead of its IPO.

All eyes will be on Dropbox and Spotify, which are expected to debut in the coming weeks.

Source: Tech Crunch

The Tingles team has done much in the way of promotion, but the app has already built a fairly sizable following in its community. That’s one of the nice things about a targeted product — it spreads fast.

In the year since Slovenian co-founders Gasper Kolenc and Miha Mlakar launched, the service has focused almost exclusively on ASMR — autonomous sensory meridian response — those whispered, pleasant-sounding videos that give listeners a sense of low-level euphoria. The service is about to get a big push, with help from Y Combinator.

“We were just trying to figure the best way to build it for artists and the community,” Mlakar, who also serves as the company’s CPO, tells TechCrunch. “We established all of these relationships. All of the features came from the community. We needed time to work on the product.”

In spite of a lack of promotion, the company says it’s pulled in 60,000 monthly active users, bout a third of whom use the product every day. The site’s content is created by more than 200 “artists” (a term taken from the ASMR community’s almost-too-clever “ASMRtist”), many of whom were poached from YouTube.

Google’s video service has, of course, been ground zero for the rise of the ASMR online phenomenon. And while Mlakar admits that it’s proven a valuable resource for the community (it was where he first learned of the concept), the co-founder believes there were still issues unserved by YouTube’s catch-all approach to online video.

“I think YouTube is great for discovery,” says Mlakar. “I discovered ASMR on there. But when you become a regular user, it becomes a problem. The main thing is the ads. If you’re listening to ASMR to fall asleep and you’re just about to doze off, then a loud commercial wakes you up, it’s really unpleasant.”

The other benefits of offering such a hyper-focused service include a better monetization model for creators. The service is available ad-free for free, but the company is working with creators to develop exclusive premium content deals, along with other features like tipping. Creators are vetted through a short approval process, and Tingles does police the videos. But while the app — and most ASMR proponents — are quick to point out that the phenomenon itself isn’t a sexual one, there are indeed “more erotic channels,” according to Mlakar.

For Tingles, ASMR is just the beginning. Mlakar describes the Android/iOS app as “basically the best place to find any video content that helps you relax and fall asleep,” and future plans include a larger push into other relaxation categories, like meditation/mindfulness.

Source: Tech Crunch

Society is beginning to wake up to a tremendous shift in one of the most fundamental underpinnings to how we live our lives: the credit system. Even though it’s not commonly known, credit infrastructure has existed about as long as civilization itself. In one way or another, credit systems have always formalized the one essential basis for relationships between people: trust.

Over millennia, the way credit looks, feels and is used has changed dramatically. Today, buoyed by a plethora of technologies and a golden age for abundant data, credit is undergoing its most radical change yet. But it is being pulled in many directions by competing forces, each with their own vision for the future.

In the beginning, credit was highly personal and subjective — this persisted for thousands of years. Over the last century, a miracle happened: Driven mostly by statistical modeling, credit became for the first time “objective.” Yet today, the cracks in that system are beginning to show, and we now stand on the brink of another revolution — the “Third Age” of credit.

We are on the verge of an exponential leap. The last year has witnessed a Cambrian explosion in credit innovation, unveiling hundreds of possibilities for the future of credit. Unlike the last two ages, credit of the future will be personal, predictive, self-correcting and universal.

The First Age: credit as trust

Modern anthropologists paint a picture of early agricultural society as a community of unsophisticated barterers, trading goods and services directly. In this picture, there is no room for a credit system: I trade you what I have and you want for what you have and I want. But, as historian David Graeber points out in his excellent etymology of credit, Debt: The First 5,000 Years, this account of early civilization is a myth.

The barter system has one major fault, known as the double coincidence of wants. If I am a chicken farmer, and I want to buy shoes from a cobbler, then my only hope is to find a cobbler who wants some of my chickens. If no cobbler in my town wants chickens, then I have to find out what the cobbler wants and begin bringing third parties into the transaction until all wants are fulfilled.

Today, we have a simple solution to this problem — money. Though it’s not conventionally viewed this way, money is actually a form of credit. The radical innovation of money was to introduce one third-party into every transaction: the government. When the farmer doesn’t have anything that the cobbler wants, he pays the cobbler in dollars; the dollars provide a deferred opportunity for the cobbler to then buy what she wants. All of this is possible because people trust that the value of a dollar will remain the same, and that trust comes from the fact that the government vouches for each dollar’s value. When you accept money as payment, you are giving the government credit for their claim that the money you accept can be redeemed for (about) the same value at a later date.

People take this feature of money for granted, but even today, it’s not ubiquitous — take the example of the three-tier pricing phenomenon in Zimbabwe: The government released bond notes pegged 1:1 to the U.S. dollar, but shops accepted actual U.S. dollars at a premium to the notes (meaning a purchase would be less expensive in U.S. dollars than bond notes). This is the literal embodiment of Zimbabwe’s citizens not giving its government any credit. (Which also led to weird discrepancies in bitcoin prices in the country.)

Money is an amazing financial instrument for so many reasons. It is a medium of exchange. It is a store of value. It is highly divisible. It is fungible across many uses. It is universally coveted. It is liquid. But early societies didn’t have anything resembling modern money, so instead, they used credit. (See a timeline of payments over the course of civilization here.)

Credit has existed as long as human economies have. Some of the earliest writings discovered by archaeologists are debt records. (Historian John Lanchester profiles the history of credit excellently in When Bitcoin Grows Up.) But credit had a lot of issues: How do you give credit to a stranger or foreigner you don’t trust? Even for those you do trust, how do you guarantee they will pay you back? What is the right amount to charge on a loan?

Early debt systems often answered by formalizing rules such as debtors going into slavery or forfeiting their daughters. These conditions artificially constrained debt, meaning that, for most of human history, economies didn’t grow much, their size being capped by a lack of credit.

So, for the first 10,000 years or so, credit was useful… but imperfect.

The Second Age: credit as algorithm

This all changed in 1956. That year, an engineer and a statistician launched a small tech company from their San Francisco apartment. That company, named Fair, Isaac and Co. after its founders, came to be known as FICO.

As Mara Hvistendahl writes, “Before FICO, credit bureaus relied in part on gossip culled from people’s landlords, neighbors, and local grocers. Applicants’ race could be counted against them, as could messiness, poor morals, and ‘effeminate gestures.’ ” Lenders would employ rules such as, “prudence in large transactions with all Jews should be used,” according to Time. “Algorithmic scoring, Fair and Isaac argued, was a more equitable, scientific alternative to this unfair reality.”

It’s hard to overstate how revolutionary FICO really was. Before multivariate credit scoring, a banker couldn’t tell two neighbors apart when pricing a mortgage. The move to statistical underwriting — a movement that had roots as early as the 1800s in the U.S. — had a snowball effect, inspiring lookalike algorithmic credit systems around the world. Credit is all about risk, but until these systems developed in the mid-century, risk-based pricing was almost entirely absent.

Famously, Capital One founder Richard Fairbank launched IBS, his “information-based strategy.” As he noted, “First, the fact that everyone had the same price for credit cards in a risk-based business was strange. […] Secondly, credit cards were a profoundly rich information business because, with the information revolution, there was a huge amount of information that could be acquired about the customers externally.”

Today, algorithmic credit is ubiquitous. Between 90 percent and 95 percent of all financial institutions in the U.S. use FICO. In the last year alone, FICO released new credit scores in Russia, China and India using novel sources of data like utility bills and mobile phone payment records. Banks around the world now implement risk-based pricing for every kind of credit.

Thousands of startups are all finding new ways to apply this same concept of statistical modeling. WeLab in Hong Kong and Kreditech in Germany, for example, use up to 20,000 points of alternative data to process loans (WeLab has provided $28 billion in credit in four years). mPesa and Branch in Kenya provide developing-world credit using mobile data, Lendable does so using psychographic data and Kora does this on blockchain. Young peer-to-peer lending startups like Funding Circle, Lending Club and Lufax have originated more than $100 billion in loans using algorithmic underwriting.

Yet this global credit infrastructure is not without its significant drawbacks, as Americans found out on September 7, 2017, when the credit bureau Equifax announced a hack that exposed the data of 146 million U.S. consumers.

The fallout from the massive breach sparked conversations on credit, forced us to re-evaluate our current credit system and finally inspired the companies to look beyond the Second Age. White House cybersecurity czar Rob Joyce opined that the time has come to get rid of Social Security numbers, so intimately tied to credit scores, which can’t be changed even after identity theft.

Today, we are held hostage by our data. We become vulnerable by being forced to rely on insecure SSNs and PINs that can be stolen. We have no choice how that information is used (more than 100 billion FICO scores have been sold.)

FICO also doesn’t take into account relevant factors such as income or bills, and in some cases only reflects poor payment history and not on-time payments. And on top of that, 50 percent of a person’s score is dependent on their credit history — inherently biasing the system against the younger borrowers who should be leveraging credit the most.

Lastly, as Frank Pasquale writes in The Black Box Society, credit scoring is opaque. This creates disparate impacts on different groups. Algorithms accidentally incorporate human biases, making loans more expensive for minorities. Building credit often requires adherence to unknown rules, such as rewarding “piggybacking” off of others’ credit — a structure that perpetuates economic inequality.

Maybe the Equifax hack was a good thing. It was a jarring reminder that a credit system reliant on historical statistical modeling, opaque algorithms and insecure identifiers is still far from perfect. Were the hackers really Robin Hood in disguise, freeing us from our hostage-like dependence on an outdated scoring system?

The time has come to move beyond the weaknesses of the modern credit regime, and technology is today taking the first step.

The Third Age: credit as liberation

What does a new world of credit look like?

In the last year there has been a Cambrian explosion of new ideas to drive modern credit forward. It is too early to tell which system(s) will win out, but the early indications are truly mind-blowing. Credit is on the precipice of an exponential leap in innovation, which will reshape the world of financial inclusion. It will become more personal, predictive instead of reactive and instantaneous.

One of the most revolutionary aspects of the future of credit is that it will increasingly come to look like cash (and cash, conversely, like credit). Consumers won’t have to request credit; rather it will be automatically allocated to them in advance based off many factors, such as behavior, age, assets and needs. It will be liquid, rather than dispersed in fixed tranches. And as it becomes increasingly commoditized, in many cases it will be close to free.

Customers will have one form of payment for all purchases that automatically decides on the back-end what the best type of funding is, cash or credit, optimizing for efficiency and low fees. Imagine Venmo, credit cards, checks, PayPal and cash, all rolled into one payment method.

People will no longer have multiple credit lines, such as separate credit cards, student loans and mortgages. People will have a guaranteed “credit plan” available to them, all linked into one master identity or profile.

Physical instruments like dollar bills and plastic cards will be phased out and live only in museums. Biometric identifiers like fingerprints will be all you need to make a purchase. Prices will become infinitesimally divisible, optimized in some cases for fractional cent values. Denominations and different currencies will become background features.

In the future, people will be paid in real time (Walmart is experimenting with this now), instead of waiting for work credit every two weeks. Payday loans as an industry will evaporate. WISH Finance is building an Ethereum-based blockchain for cash flow-based underwriting. It’s easy to see this applied to consumers: get real-time credit based on your regular pay and expenses.

In the next phase, credit will revolve around the individual. Right now we live in a world of gatekeepers: Centralized data aggregators, such as credit bureaus, act as intermediaries to credit. This advantage will increasingly be eroded by individually permissioned data (a concept known as self-sovereign identity). This is consistent with trends in cross-border work and globalization: In an atomized world, the individual is the core unit and will need to take her information with her, without reliance on third parties. It could reduce some $15 billion in annual fees paid to access data and make information more secure, eliminating single points of failure.

One-size fits all scores like FICO will become disaggregated. Credit is a relational system: Our credit indicates our standing relative to a wide network. But people shouldn’t be represented by averages. Credit will become more multivariate, using machine learning and breaking apart the contributing factors and weights that make up FICO (the company where I work, Petal, is doing this to democratize credit cards).

It makes little sense to set single credit benchmarks — such as the 350 to 850 score range — irrespective of age, so consumers will be compared to their cohort. Per Experian, youngest people have the lowest credit scores. However, youth is when people should be borrowing the most, both to build credit and because they should be saving cash for their spending later in life.

Credit will become contextual. Your maximum available credit will fluctuate based on ever-changing factors such as payroll and bills. It also will be specific to purchases: You will receive different levels and costs of credit based on the value and type of the asset you’re buying. For instance, credit to buy a crib for your newborn may be cheaper than credit to buy a trip to Vegas. Illiquid assets will be automatically usable to secure credit, as Sweetbridge is doing. (The founders of Kora point out that the problem is not that the poor don’t have wealth, it’s that their capital is locked up.)

Credit will be psychographic and predictive. It won’t be enough to look backwards at your past behavior — your creditworthiness will change dynamically as you move around, make purchases and stay active. It will be dynamically assigned to specific needs (like ink if you buy a printer) before you realize you have them.

Naturally, talking about the future of credit, we have to talk about blockchains. They will have three early uses:

• Funds dispersal: It will become much cheaper to disperse credit and accept payments using services like Stellar. There will be no latency from banks having to verify transactions against their own accounts.

• Underwriting: Data will be aggregated into universal profiles (like those being built at uPort and Bloom) from a wide variety of sources, such as credit bureaus, phone bills, academic transcripts and Facebook. As mentioned, these will be self-sovereign, and make it much easier for credit providers to underwrite borrowers.

• Contract enforcement: Smart contracts will be self-enforcing, automatically collecting debt payments, re-adjusting themselves if someone is credit crunched in the short term and refinancing if customers can consolidate or lower their APRs. The universal ID and contract will keep people from “running to Mexico” with their credit funds.

In the future, credit (and capital) will be automatically allocated to people based off predictive AI. Better risk pricing will continue to drop rates at which consumers can borrow, toward 0 percent. The federal funds rate has been around 1 percent for the last couple of years — in 1980 it was 18 percent! A combination of machine learning and what Bain calls “A world awash in money,” with larger investors hunting for lower returns, will continue to drive these rates down.

At a higher level, blockchain protocols like Dharma will set up smart contracts for the credit economy that allocate capital in the most efficient way. Credit will not rely on active investment managers to lend or borrow: Any capital not currently tied into a contract will be programmed to continuously search for the highest risk-adjusted return — including provision of credit.

Credit providers, at scale, will experience massive network effects. “Network effects” describe the condition in which networks become more valuable to users as more users participate. This doesn’t traditionally apply to credit: Just because other people have the same credit card as you, you don’t accrue any benefits. But in the future it will: More data points within credit networks will provide better underwriting, which will create fairer pricing, creating a virtuous cycle of data. User experiences and pricing will benefit tremendously as a result. Initiatives like the U.K.’s Open Banking will accelerate this trend.

Tom Noyes calls this The Democratization of Data. In a world of smaller, local data sets that collaborate (80-90 percent of all our current behavior is local), bridging disparate data gaps will increase credit participation to 100 percent (currently, only about 71 percent of Americans have credit cards).

And these are just some of the more probable, routine ideas. Futurists like Daniel Jeffries envision currencies with built-in features to incentivize different behaviors — like saving versus spending — and universal basic income tokens, to decentralize financial inclusion. Platforms like Bloom, which now has 100 applications being built on it, are reimagining credit at the protocol level. These systems are tackling first-principles questions, such as can the future be entirely meritocratic, or can people inherently create trust with no data.

We are living in the prologue to the Third Age. It’s hard to tell exactly how the future of credit will play out, but from where we stand, we can see that it will represent the biggest departure from the past in credit’s history, and we’re just today taking the first steps.

Source: Tech Crunch