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Stanford students are short-circuiting VC firms by investing in their peers
Stanford’s success in spinning out startup founders is a well-known adage in Silicon Valley, with alumni founding companies like Google, Cisco, LinkedIn, YouTube, Snapchat, Instagram and, yes, even TechCrunch. And venture capitalists routinely back more founders coming out of the Stanford business program than any other university in the country.
One group of Stanford graduate students is well-aware of their favorable odds, and think that they should be able to cash in their classmates, too — not just accredited investors and the super-wealthy.
They have put together Stanford 2020, a new fund created entirely by Stanford classmates to invest in their fellow students’ ventures.
The idea was spurred by six students, who after a year of working with Fenwick & West law firm to find a suitable legal structure landed on creating an investment club — multiple parties can invest together as long as they have some form of shared ties.
Steph Mui, a founding member of Stanford 2020 and former venture capital associate at VC firm NEA, formed the club in defiance of the inaccessibility of angel investing, which she described as an elite Silicon Valley status symbol.
“Especially in Silicon Valley where it seems kind of a status symbol and only accredited people can do it, it feels very elite” she said. “We started thinking more about if we can actually make this something that the whole class could participate in, or at least make it more accessible to more than just like these small pockets of people that do it behind closed doors.”
Stanford 2020 club members must put up a minimum of $3,000 to join the investment club, and any eventual returns will be distributed proportionally to the investment each makes. So far, Mui tells TechCrunch that $1.5 million has been raised across 175 investors, with 50 investors willing to give $500,000 on the waitlist. In fact, the club is so “oversubscribed” that it is working to give money back.
Mui estimates that roughly 40% of the class is participating in the club. The founding members are being defined as “board members” who were recruited for passion and for diversity in background, professional interests and past leadership experience.
The group plans to invest $50,000 to $100,000 in startups depending on round size and valuation.
Mui thinks that Stanford 2020’s competitive advantage is largely the personal relationship it has with the companies it will invest in. After all, success might be just an arm’s reach away. Indeed, Cloudflare, Rent the Runway and ThredUp were all born in the same HBS classroom after being assigned a class project, according to Cloudflare CEO Matthew Prince.
“We have such strong pre-existing relationships, we know what people are working on way before they even raise,” Mui said.
Anyone who has been part of a club or team knows that loyalty runs deep, but we’ll see if that closeness is enough for a founder to dole out a stake in their company. While Stanford 2020 doesn’t take any management fee or carry, equity isn’t casual; in that vein, a famed Silicon Valley firm might be of better utility than your classmates.
Stanford 2020’s set up sounds similar to StartX, the university’s attempt at investing in its own, leafy backyard, which shut down in 2019. Launched in 2013, StartX offered to invest money in exchange for equity in any startup that went through its auxiliary accelerator and has $500,000 from professional investors.
Looking at Stanford 2020’s set up, the rules are almost exactly the same. Mui tells TechCrunch that startups must fulfill two criteria in order to automatically invest: first, the co-founder must be a member of the class, and second, they must raise a round of $750,000 or more from a reputable institutional investor. They define reputable as a list of 80 investors they got guidance on from advisors in the industry.
The concept of a rule-based automatic investment strategy comes with a big red flag: what if the founder has a bad idea or is a bad person, and still meets the criteria?
“I actually literally can’t think of a single person and I’m like, that person is so bad or so immoral, that we wouldn’t invest in them,” Mui said. “That’s part of the benefit of investing only in your classmates.”
But in case a Stanford-born class does have a problematic founder, Stanford 2020 has a veto voting mechanism.
In the grand scheme of things, Stanford-born startups are in a better spot than most when it comes to securing cash. They don’t desperately need another fund to invest in them. Mui’s ambition for Stanford 2020 is that other schools can copy and paste the legal structure they took a year (and a lot of hard work) to figure out.
She says they’re already getting inbound from incoming Stanford classes, other Stanford Schools and undergraduates. Now that it’s closed, she hopes they hear from other business schools, too.
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Labster’s latest partnership, and what it tells us about the future of remote learning
Labster, a virtual science lab edtech company, today announced that it is partnering with California’s community college network to bring its software to 2.1 million students.
California Community Colleges claims to be the largest system of higher education in the country. The Labster partnership will provide 115 schools with 130 virtual laboratory simulations in biology, chemistry, physics and general sciences.
As COVID-19 has forced schools to shutter, edtech companies have largely responded by offering their software for free or through extended free trials. What’s new and notable about Labster’s partnership today is that it shows the first few signs of how that momentum can lead to a business deal.
Based in Copenhagen, Labster sells virtual STEM labs to institutions. The startup has raised $34.7 million in known venture capital to date, according to Crunchbase data. Labster customers include California State University, Harvard, Gwinnett Technical College, MIT, Trinity College and Stanford.
Lab equipment is expensive, and budget constraints mean that schools struggle to afford the latest technology. So Labster’s value proposition is that it is a cheaper alternative (plus, if students spill a testing vial in a virtual lab, there’s less clean up).
That pitch has slightly changed since COVID-19 forced schools across the world to shut down to limit the spread of the pandemic. Now, it’s pitching itself as the only currently viable alternative to science labs.
For many edtech companies, the surge of remote learning has been a large experiment. Often, edtech companies are giving away their product and technology for free to help as schools scramble to move operations completely digital.
For example, last week self-serve learning platforms Codecademy, Duolingo, Quizlet, Skillshare and Brainly launched a Learn From Home Club for students and teachers. Before that, Wize made its exam content and homework services available for free. And Zoom offered its video-conferencing software for free to K through 12 schools, which had mixed results.
Labster itself gave $5 million in free Labster credits to schools across the country. The list continues.
Labster’s new deal shows edtech companies can secure new customers right now — without breaking the bank.
Labster CEO and co-founder Michael Bodekaer declined to give specifics on what the deal is worth. He did share that Labster works with schools one by one to understand how much they can, or want to, invest in teacher training and webinar support. He also confirmed that Labster does profit from the deal.
“We want to make sure that we set ourselves up for supporting our partners but still also make sure that Labster as a financial institution can pay our salaries,” Bodekaer said. “But again, heavy discounts that help us cover our costs.”
The long game for Labster, like many edtech companies, is that schools like the platform so much that these short-term stints have a better chance to lead to long-term relationships.
“We’ll be keeping these discounts as long as we possibly can sustain as a company,” he said. “It looks like initially the discount was until August and now we’re extending it until the end of the year. If that continues, we may extend it even further.”
Pricing aside, the real struggle toward implementation for Labster, and honestly any other edtech company focused on remote learning, is the digital divide. Some students do not have access to a computer for video conferencing or even internet connection for assignments.
The COVID-19 pandemic has highlighted how many households across America lack access to the technology needed for remote learning. In California, Google donated free Chromebooks and 100,000 mobile hotspots to students in need.
Bodekaer said that Labster is currently working on providing its software on mobile, and has worked with Google to make sure its product works on low-end computers like Chromebooks.
“We really want to be hardware agnostic and support any system or any platform that the students already have,” he said. “So that hardware does not become a barrier.”
While today’s partnership brings 2.1 million students access to Labster’s technology, it does not directly account for the percentage of that same group that might not have access to a computer in the first place. The true test, and perhaps success, of edtech will rely on a true hybrid of hardware and software, not one or the other.
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R&D Roundup: Ultrasound/AI medical imaging, assistive exoskeletons and neural weather modeling
In the time of COVID-19, much of what transpires from the science world to the general public relates to the virus, and understandably so. But other domains, even within medical research, are still active — and as usual, there are tons of interesting (and heartening) stories out there that shouldn’t be lost in the furious activity of coronavirus coverage. This last week brought good news for several medical conditions as well as some innovations that could improve weather reporting and maybe save a few lives in Cambodia.
Ultrasound and AI promise better diagnosis of arrhythmia
Arrhythmia is a relatively common condition in which the heart beats at an abnormal rate, causing a variety of effects, including, potentially, death. Detecting it is done using an electrocardiogram, and while the technique is sound and widely used, it has its limitations: first, it relies heavily on an expert interpreting the signal, and second, even an expert’s diagnosis doesn’t give a good idea of what the issue looks like in that particular heart. Knowing exactly where the flaw is makes treatment much easier.
Ultrasound is used for internal imaging in lots of ways, but two recent studies establish it as perhaps the next major step in arrhythmia treatment. Researchers at Columbia University used a form of ultrasound monitoring called Electromechanical Wave Imaging to create 3D animations of the patient’s heart as it beat, which helped specialists predict 96% of arrhythmia locations compared with 71% when using the ECG. The two could be used together to provide a more accurate picture of the heart’s condition before undergoing treatment.
Another approach from Stanford applies deep learning techniques to ultrasound imagery and shows that an AI agent can recognize the parts of the heart and record the efficiency with which it is moving blood with accuracy comparable to experts. As with other medical imagery AIs, this isn’t about replacing a doctor but augmenting them; an automated system can help triage and prioritize effectively, suggest things the doctor might have missed or provide an impartial concurrence with their opinion. The code and data set of EchoNet are available for download and inspection.
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Lumineye helps first responders identify people through walls
Any first responder knows that situational awareness is key. In domestic violence disputes, hostage rescue or human trafficking situations, first responders often need help determining where humans are behind closed doors.
That’s why Megan Lacy, Corbin Hennen and Rob Kleffner developed Lumineye, a 3D-printed radar device that uses signal analysis software to differentiate moving and breathing humans from other objects, through walls.
Lumineye uses pulse radar technology that works like echolocation (how bats and dolphins communicate). It sends signals and listens for how long it takes for a pulse to bounce back. The software analyzes these pulses to determine the approximate size, range and movement characteristics of a signal.
On the software side, Lumineye’s app will tell a user how far away a person is when they’re moving and breathing. It’s one dimensional, so it doesn’t tell the user whether the subject is to the right or left. But the device can detect humans out to 50 feet in open air; that range decreases depending upon the materials placed in between, like drywall, brick or concrete.
One scenario the team gave to describe the advantages of using Lumineye was the instance of hostage rescue. In this type of situation, it’s crucial for first responders to know how many people are in a room and how far away they are from one another. That’s where the use of multiple devices and triangulation from something like Lumineye could change a responding team’s tactical rescue approach.
Machines that currently exist to make these kind of detections are heavy and cumbersome. The team behind Lumineye was inspired to manufacture a more portable option that won’t weigh down teams during longer emergency response situations that can sometimes last for up to 12 hours or overnight. The prototype combines the detection hardware with an ordinary smartphone. It’s about 10 x 5 inches and weighs 1.5 pounds.
Lumineye wants to grow out its functionality to become more of a ubiquitous device. The team of four is planning to continue manufacturing the device, selling it directly to customers.
Lumineye’s device can detect humans through walls using radio frequencies
Lumineye has just started its pilot programs, and recently spent a Saturday at a FEMA event testing out the the device’s ability to detect people covered in rubble piles. The company was born out of the Boise, Idaho cohort of Stanford’s Hacking4Defense program, a course meant to connect Silicon Valley innovations with the U.S. Department of Defense and Intelligence Community. The Idaho-based startup is graduating from Y Combinator’s Summer 2019 class.
Megan Lacy, Corbin Hennen and Rob Kleffner
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WW launches Kurbo, a hotly debated ‘healthy eating’ app aimed at kids
Kurbo Health, a mobile weight loss solution designed to tackle childhood obesity which was acquired for $3 million by WW (the rebranded Weight Watchers), has now relaunched as Kurbo by WW — and not without some controversy. Pre-acquisition, the startup was focused on democratizing access to research, behavior modification techniques and other tools that were previously only available through expensive programs run by hospitals or other centers.
As a WW product, however, there are concerns that parents putting kids on “diets” will lead to increased anxiety, stress and disordered eating — in other words, Kurbo will make the problem worse, rather than solving it.
*If* you are worried about your child’s health/lifestyle, give them plenty of nutritious food and make sure they get plenty of fun exercise that helps their mental health. And don’t weigh them. Don’t burden them with numbers, charts or “success/failure.” It’s a slippery slope.
— Jameela Jamil
(@jameelajamil) August 14, 2019
The Kurbo app first launched at TechCrunch Disrupt NY 2014. Founder Joanna Strober, a venture investor and board member at BlueNile and eToys, explained she was driven to develop Kurbo after struggling to help her own child. Mainly, she came across programs that cost money, were held at inconvenient times for working parents or were dubbed “obesity centers” — with which no child wanted to be associated.
Her child found eventual success with the Stanford Pediatric Weight Loss Program, but this involved in-person visits and pen-and-paper documentation.
Together with Kurbo Health’s co-founder Thea Runyan, who has a Master’s in Public Health and had worked at the Stanford center for 12 years, the team realized the opportunity to bring the research to more people by creating a mobile, data-driven program for kids and families.
They licensed Stanford’s program, which then became Kurbo Health.
The company raised funds from investors, including Signia Ventures, Data Collective, Bessemer Venture Partners and Promus Ventures, as well as angels like Susan Wojcicki, CEO of YouTube; Greg Badros, former VP Engineering and Product at Facebook; and Esther Dyson (EdVenture), among others.
At launch, the app was designed to encourage healthier eating patterns without parents actually being able to see the child’s food diary. Instead, parents set a reward that was doled out simply for the child’s participation. That is, the parents couldn’t see what the child ate, specifically, which allowed them to stop playing “food police.”
Unlike adult-oriented apps like MyFitnessPal or Noom, kids wouldn’t see metrics like calories, sugars, carbs and fat, but instead had their food choices categorized as “red,” “yellow” and “green.” However, no foods were designated as “off limits,” as it instead encouraged fewer reds and more greens.
The program also included an option for virtual coaching.
As a WW product, the program has remained somewhat the same. There are still the color-coded food categorizations and optional live coaching, via a subscription. Parents are still involved, now with updates after coaching calls or the option to join coaching sessions. The app also now includes tools that teach meditation, recipe videos and games that focus on healthy lifestyles. Subscribers gain access to one-on-one 15-minute virtual sessions with coaches whose professional backgrounds include counseling, fitness and other nutrition-related fields.
However, there are also things like a place to track measurements, goals like “lose weight” and Snapchat-style “tracking streaks.”
While the original program was designed to be a solution for parents with children who would have otherwise had to seek expensive medical help for obesity issues, the association with parent company and acquirer WW has led to some backlash.
Today, body positivity and fat acceptance movements have gone mainstream, encouraging people to be confident in their own bodies and not hate themselves for being overweight. The general thinking is that when people respect themselves, they become more likely to care for themselves — and this will extend to making healthier food and lifestyle choices.
Meanwhile, food tracking and dieting programs often lead to failure and shame — especially when people start to think of some food as “bad” or a “cheat,” instead of just something to be eaten in moderation. And excessive tracking can even lead to disordered eating patterns for some people, studies have found.
In addition, WW has already been under fire for extending its weight loss program to teens 13-17 for free, and the launch of what’s seen as a “dieting app for kids” as part of WW’s broader family-focused agenda certainly isn’t helping the backlash.
That said, when positive reinforcement is used correctly, it can work for weight loss. As TIME reported, the red-yellow-green traffic light approach was effective in adults in one independent study by Massachusetts General Hospital and another presented at the Biennial Childhood Obesity Conference worked in children, with 84% reducing their BMI after 21 weeks.
“According to recent reports from the World Health Organization, childhood obesity is one of the most serious public health challenges of the 21st century. This is a global public health crisis that needs to be addressed at scale,” said Joanna Strober, co-founder of Kurbo, in a statement about the launch. “As a mom whose son struggled with his weight at a young age, I can personally attest to the importance and significance of having a solution like Kurbo by WW, which is inherently designed to be simple, fun and effective,” she said.
KURBO.
I thought that I hated Weight Watchers. I have not hated them as much as I do right now.
Making weight loss trendy for children is making the development of eating disorders easier and trendier. I am not here for this.
— Anna Sweeney MS, CEDRD-S (@DietitianAnna) August 13, 2019
That said, it’s one thing for a parent to work in conjunction with a doctor to help a child with a health issue, but parents who foist a food tracking app on their kids may not get the same results. In fact, they may even cause the child to develop eating disorders that weren’t present before. (And no, just because a child is overweight, that doesn’t necessarily mean they’re suffering from an “eating disorder.”)
Weight Watchers has a new dieting app for kids as young as 8 and it is truly disturbing https://t.co/GjPl4PHwSv pic.twitter.com/ZMkZmFr9X6
— Dr. Yasmin (@DoctorYasmin) August 14, 2019
There can be many other factors that could be causing a child’s unexpected weight gain, beyond just their interest in eating high-calorie foods. This includes health ailments, hormone or chemical imbalances, medication side effects, puberty and other growth spurts (which can’t always be determined through BMI changes, which are tracked in-app), genetics, and more.
Parents may also be part of the problem, by simply bringing unhealthy food into the house because it’s more affordable or because they aren’t aware of things like hidden sugars or how to avoid them. Or perhaps they’re putting money into a child’s school lunch account, without realizing the child is able to spend it on vending machine snacks, sodas or off-menu items like pizza and chips.
The child may also suffer from health problems like asthma or allergies that have become an underlying issue, making it more difficult for them to be active.
In other words, a program like this is something that parents should approach with caution. And it’s certainly one where the child’s doctor should be involved at every stage — including in determining whether or not an app is actually needed at all.
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Biotech researchers venture into the wild to start their own business
Jorge Conde is a General Partner at Andreessen Horowitz where he leads investments at the cross section of biology, computer science and engineering.
Much of Silicon Valley mythology is centered on the founder-as-hero narrative. But historically, scientific founders leading the charge for bio companies have been far less common.
Developing new drugs is slow, risky and expensive. Big clinical failures are all too common. As such, bio requires incredibly specialized knowledge and experience. But at the same time, the potential for value creation is enormous today more than ever with breakthrough new medicines like engineered cell, gene and digital therapies.
What these breakthroughs are bringing along with them are entirely new models — of founders, of company creation, of the businesses themselves — that will require scientists, entrepreneurs and investors to reimagine and reinvent how they create bio companies.
In the past, biotech VC firms handled this combination of specialized knowledge + binary risk + outsized opportunity with a unique “company creation” model. In this model, there are scientific founders, yes; but the VC firm essentially founded and built the company itself — all the way from matching a scientific advance with an unmet medical need, to licensing IP, to having partners take on key roles such as CEO in the early stages, to then recruiting a seasoned management team to execute on the vision.
Image: PASIEKA/SCIENCE PHOTO LIBRARY/Getty Images
You could call this the startup equivalent of being born and bred in captivity — where great care and feeding early in life helps ensure that the company is able to thrive. Here the scientific founders tend to play more of an advisory role (usually keeping day jobs in academia to create new knowledge and frontiers), while experienced “drug hunters” operate the machinery of bringing new discoveries to the patient’s bedside. This model’s core purpose is to bring the right expertise to the table to de-risk these incredibly challenging enterprises — nobody is born knowing how to make a medicine.
But the ecosystem this model evolved from is evolving itself. Emerging fields like computational biology and biological engineering have created a new breed of founder, native to biology, engineering and computer science, that are already, by definition, the leading experts in their fledgling fields. Their advances are helping change the industry, shifting drug discovery away from a highly bespoke process — where little knowledge carries over from the success or failure of one drug to the next — to a more iterative, building-block approach like engineering.
Take gene therapy: once we learn how to deliver a gene to a specific cell in a given disease, it is significantly more likely we will be able to deliver a different gene to a different cell for another disease. Which means there’s an opportunity not only for novel therapies but also the potential for new business models. Imagine a company that provides gene delivery capability to an entire industry — GaaS: gene-delivery as a service!
Once a founder has an idea, the costs of testing it out have changed too. The days of having to set up an entire lab before you could run your first experiments are gone. In the same way that AWS made starting a tech company vastly faster and easier, innovations like shared lab spaces and wetlab accelerators have dramatically reduced the cost and speed required to get a bio startup off the ground. Today it costs thousands, not millions, for a “killer experiment” that will give a founding team (and investors) early conviction.
What all this amounts to is scientific founders now have the option of launching bio companies without relying on VCs to create them on their behalf. And many are. The new generation of bio companies being launched by these founders are more akin to being born in the wild. It isn’t easy; in fact, it’s a jungle out there, so you need to make mistakes, learn quickly, hone your instincts, and be well-equipped for survival. On the other hand, given the transformative potential of engineering-based bio platforms, the cubs that do survive can grow into lions.
Image via Getty Images / KTSDESIGN/SCIENCE PHOTO LIBRARY
So, which is better for a bio startup today: to be born in the wild — with all the risk and reward that entails — or to be raised in captivity
The “bred in captivity” model promises sureness, safety, security. A VC-created bio company has cache and credibility right off the bat. Launch capital is essentially guaranteed. It attracts all-star scientists, executives and advisors — drawn by the balance of an innovative, agile environment and a well-funded, well-connected support network. I was fortunate enough to be an early executive in one of these companies, giving me the opportunity to work alongside industry luminaries and benefit from their well-versed knowledge of how to build a world-class bio company with all its complex component parts: basic, translational, clinical research, from scratch. But this all comes at a price.
Because it’s a heavy lift for the VCs, scientific founders are usually left with a relatively small slug of equity — even founding CEOs can end up with ~5% ownership. While these companies often launch with headline-grabbing funding rounds of $50m or above, the capital is tranched — meaning money is doled out as planned milestones are achieved. But the problem is, things rarely go according to plan. Tranched capital can be a safety net, but you can get tangled in that net if you miss a milestone.
Being born in the wild, on the other hand, trades safety for freedom. No one is building the company on your behalf; you’re in charge, and you bear the risk. As a recent graduate, I co-founded a company with Harvard geneticist George Church. The company was bootstrapped — a funding strategy that was more famine than feast — but we were at liberty to try new things and run (un)controlled experiments like sequencing heavy metal wildman Ozzy Osbourne.
It was the early, Wild West days of the genomics revolution and many of the earliest biotech companies mirrored that experience — they weren’t incepted by VCs; they were created by scrappy entrepreneurs and scientists-turned-CEO. Take Joshua Boger, organic chemist and founder of Vertex Pharmaceuticals: starting in 1989 his efforts to will into existence a new way to develop drugs, thrillingly captured in Barry Werth’s The Billion-Dollar Molecule and its sequel The Antidote in all its warts and nail-biting glory, ultimately transformed how we treat HIV, hepatitis C and cystic fibrosis.
Today we’re in a back-to-the-future moment and the industry is being increasingly pushed forward by this new breed of scientist-entrepreneur. Students-turned-founder like Diego Rey of in vitro diagnostics company GeneWEAVE and Ramji Srinivasan of clinical laboratory Counsyl helped transform how we diagnose disease and each led their companies to successful acquisitions by larger rivals.
Popular accelerators like Y Combinator and IndieBio are filled with bio companies driven by this founder phenotype. Ginkgo Bioworks, the first bio company in Y Combinator and today a unicorn, was founded by Jason Kelly and three of his MIT biological engineering classmates, along with former MIT professor and synthetic biology legend Tom Knight. The company is not only innovating new ways to program biology in order to disrupt a broad range of industries, but it’s also pioneering an innovative conglomerate business model it has dubbed the “Berkshire for biotech.”
Like the Ginkgo founders, Alec Nielsen and Raja Srinivas launched their startup Asimov, an ambitious effort to program cells using genetic circuits, shortly after receiving their PhDs in biological engineering from MIT. And, like Boger, renowned machine learning Stanford professor Daphne Koller is working to once again transform drug discovery as the founder and CEO of Instiro.
Just like making a medicine, no one is born knowing how to build a company. But in this new world, these technical founders with deep domain expertise may even be more capable of traversing the idea maze than seasoned operators. Engineering-based platforms have the potential to create entirely new applications with unprecedented productivity, creating opportunities for new breakthroughs, novel business models, and new ways to build bio companies. The well-worn playbooks may be out of date.
Founders that choose to create their own companies still need investors to scrub in and contribute to the arduous labor of company-building — but via support, guidance, and with access to networks instead. And like this new generation of founders, bio investors today need to rethink (and re-value) the promise of the new, and still appreciate the hard-earned wisdom of the old. In other words, bio investors also need to be multidisciplinary. And they need to be comfortable with a different kind of risk: backing an unproven founder in a new, emerging space. As a founder, if you’re willing to take your chances in the wild, you should have an investor that understands you, believes in you, can support you and, importantly, is willing to dream big with you.
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An autonomous robot EV charger is coming to San Francisco
Electric-vehicle chargers today are designed for human drivers. Electrify America and San Francisco-based startup Stable are preparing for the day when humans are no longer behind the wheel.
Electrify America, the entity set up by Volkswagen as part of its settlement with U.S. regulators over the diesel emissions cheating scandal, is partnering with Stable to test a system that can charge electric vehicles without human intervention.
The autonomous electric-vehicle charging system will combine Electrify America’s 150 kilowatt DC fast charger with Stable’s software and robotics. A robotic arm, which is equipped with computer vision to see the electric vehicle’s charging port, is attached to the EV charger. The two companies plan to open the autonomous charging site in San Francisco by early 2020.
A rendering of an autonomous electric vehicle charging station.
There’s more to this system than a nifty robotic arm. Stable’s software and modeling algorithms are critical components that have applications today, not just the yet-to-be-determined era of ubiquitous robotaxis.
While streets today aren’t flooded with autonomous vehicles, they are filled with thousands of vehicles used by corporate and government fleets, as well as ride-hailing platforms like Uber and Lyft . Those commercial-focused vehicles are increasingly electric, a shift driven by economics and regulations.
“For the first time these fleets are having to think about, ‘how are we going to charge these massive fleets of electric vehicles, whether they are autonomous or not?’ ” Stable co-founder and CEO Rohan Puri told TechCrunch in a recent interview.
Stable, a 10-person company with employees from Tesla, EVgo, Faraday Future, Google, Stanford and MIT universities, has developed data science algorithms to determine the best location for chargers and scheduling software for once the EV stations are deployed.
Its data science algorithms take into account installation costs, available power, real estate costs as well as travel time for the given vehicle to go to the site and then get back on the road to service customers. Stable has figured out that when it comes to commercial fleets, chargers in a distributed network within cities are used more and have a lower cost of operation than one giant centralized charging hub.
Once a site is deployed, Stable’s software directs when, how long and at what speed the electric vehicle should charge.
Stable, which launched in 2017, is backed by Trucks VC, Upside Partnership, MIT’s E14 Fund and a number of angel investors, including NerdWallet co-founder Jake Gibson and Sidecar co-founder and CEO Sunil Paul .
The pilot project in San Francisco is the start of what Puri hopes will lead to more fleet-focused sites with Electrify America, which has largely focused on consumer charging stations. Electrify America has said it will invest $2 billion over 10 years in clean energy infrastructure and education. The VW unit has more than 486 electric vehicle charging stations installed or under development. Of those, 262 charging stations have been commissioned and are now open to the public.
Meanwhile, Stable is keen to demonstrate its autonomous electric-vehicle chargers and lock in additional fleet customers.
“What we set out to do was to reinvent the gas station for this new era of transportation, which will be fleet-dominant and electric,” Puri said. “What’s clear is there just isn’t nearly enough of the right infrastructure installed in the right place.”
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CrunchMatch simplifies networking at TC Sessions: Enterprise 2019
Get ready to experience world-class networking TechCrunch-style at TC Sessions: Enterprise 2019. On September 5, more than 1,000 of the top enterprise software minds and makers, movers and shakers will descend on San Francisco’s Yerba Buena Center for the Arts. It’s a day-long conference featuring distinguished speakers, panel discussions, demos and workshops.
It’s also a prime opportunity to connect and build relationships with enterprise software founders, technologists and investors. Make the most of that opportunity by using CrunchMatch, our free business match-making service.
The automated platform lets you find people based on specific mutual business criteria, goals and interests. It helps you sift through the noise and make the most of your valuable time. After all, connecting with the right people produces better results.
Here’s how CrunchMatch (powered by Brella) works. When CrunchMatch goes live — several weeks before the main event — we’ll email a sign-up link to all ticket holders. You’ll be able to access the platform and create a profile with your specific details — your role (technologist, founder, investor, etc.) and a description of the types of people you want to connect with at the event.
CrunchMatch works its algorithmic magic and suggests meetings, which you can then vet, approve and schedule or decline. It’s an efficient and productive way to network. Take a look at how CrunchMatch helped Yoolox increase distribution.
All that time-saving efficiency will free you up to enjoy more of the presentations and hear from speakers like the renowned founder, investor, AI expert and Stanford professor, Andrew Ng. You won’t want to miss his take on how AI will transform the enterprise world — like nothing else since the cloud and SaaS. And that’s just a taste of what you can expect.
If you haven’t already done so, buy your tickets now and save $100 before the prices go up on August 9. Early-bird tickets cost $249 and student tickets sell for $75. Buy 4+ tickets to get the group rate and save another 20%.
ROI tip: For every ticket you buy to TC Sessions: Enterprise, we’ll register you for a free Expo-only pass to TechCrunch Disrupt SF 2019.
We can’t wait to see you at TC Sessions: Enterprise 2019 in San Francisco on September 5. Join your community, explore the top enterprise trends and companies and make productive connections with the influential people who can help you reach your goals. Buy your ticket today.
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Andrew Ng to talk about how AI will transform business at TC Sessions: Enterprise
When it comes to applying AI to the world around us, Andrew Ng has few if any peers. We are delighted to announce that the renowned founder, investor, AI expert and Stanford professor will join us onstage at the TechCrunch Sessions: Enterprise show on September 5 at the Yerba Buena Center in San Francisco.
AI promises to transform the $500 billion enterprise world like nothing since the cloud and SaaS. Hundreds of startups are already seizing the AI moment in areas like recruiting, marketing and communications and customer experience. The oceans of data required to power AI are becoming dramatically more valuable, which in turn is fueling the rise of new data platforms, another big topic of the show.
Last year, Ng launched the $175 million AI Fund, backed by big names like Sequoia, NEA, Greylock and SoftBank. The fund’s goal is to develop new AI businesses in a studio model and spin them out when they are ready for prime time. The first of that fund’s cohort is Landing AI, which also launched last year and aims to “empower companies to jumpstart AI and realize practical value.” It’s a wave businesses will want to catch if Ng is anywhere near right in his conviction that AI will generate $13 trillion in GDP growth globally in the next 20 years. You heard that right.
At TC Sessions: Enterprise, TechCrunch’s editors will ask Ng to detail how he believes AI will unfold in the enterprise world and bring big productivity gains to business.
As the former chief scientist at Baidu and the founding lead of Google Brain, Ng led the AI transformation of two of the world’s leading technology companies. Dr. Ng is the co-founder of Coursera, an online learning platform, and founder of deeplearning.ai, an AI education platform. Dr. Ng is also an adjunct professor at Stanford University’s Computer Science Department and holds degrees from Carnegie Mellon University, MIT and the University of California, Berkeley.
Early Bird tickets to see Andrew at TC Sessions: Enterprise are on sale for just $249 when you book here; but hurry, prices go up by $100 soon! Students, grab your discounted tickets for just $75 here.
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Video platform Kaltura adds advanced analytics
You may not be familiar with Kaltura‘s name, but chances are you’ve used the company’s video platform at some point or another, given that it offers a variety of video services for enterprises, educational institutions and video-on-demand platforms, including HBO, Phillips, SAP, Stanford and others. Today, the company announced the launch of an advanced analytics platform for its enterprise and educational users.
This new platform, dubbed Kaltura Analytics for Admins, will provide its users with features like user-level reports. This may sound like a minor feature, because you probably don’t care about the exact details of a given user’s interactions with your video, but it will allow businesses to link this kind of behavior to other metrics. With this, you could measure the ROI of a given video by linking video watch time and sales, for example. This kind of granularity wasn’t possible with the company’s existing analytics systems. Companies and schools using the product will also get access to time-period comparisons to help admins identify trends, deeper technology and geolocation reports, as well as real-time analytics for live events.
“Video is a unique data type in that it has deep engagement indicators for measurement, both around video creation — what types of content are being created by whom, as well as around video consumption and engagement with content — what languages were selected for subtitles, what hot-spots were clicked upon in video,” said Michal Tsur, president and general manager of Enterprise and Learning at Kaltura. “Analytics is a very strategic area for our customers. Both for tech companies who are building on our VPaaS, as well as for large organizations and universities that use our video products for learning, communication, collaboration, knowledge management, marketing and sales.”
Tsur also tells me the company is looking at how to best use machine learning to give its customers even deeper insights into how people watch videos — and potentially even offer predictive analytics in the long run.
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