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3 perspectives on the future of SF and NYC as startup hubs



It has been an incredibly tough period for everyone the past few months as the global COVID-19 pandemic has wiped out whole industries from the economic map.

While tech has been among the most resilient industries in the face of this cataclysm, the extreme mobility of the industry’s workforce begs large questions about what the future of startups and work will look like moving forward.

We’ve debated what COVID-19 will do to the rise of the college town as startup hubs and how the pandemic will change the way we work in coffee shops and neighborhoods. Now, we want to address one of the larger questions that has been bugging us: Will tech continue to centralize in hubs like San Francisco and New York City, or will remote work and all the other second-order effects lead to a more decentralized startup ecosystem?

We have three perspectives from our writers, with wildly different predictions about what the future has in store.

First, we have Danny Crichton, who believes that tech, and particularly the VC industry, will remain as concentrated as ever, although where it is concentrated will perhaps shift a bit. Meanwhile, Alex Wilhelm asserts that startup growth outside major hubs will actually accelerate, spreading tech wealth even farther outside the metropolises. Finally, Natasha Mascarenhas argues that the combination of the economic dislocation of COVID-19 and the increasing attention to equity in tech will lead to more intense investment outside core startup hubs.

Danny Crichton: A new Napa Valley café shows why in-person networks matter

First there was Sand Hill Road. Then there was South Park. And now there’s Solbar at Solage in Calistoga.

Despite the wide availability of remote work tools over the past two decades, VCs have always miraculously congregated in extraordinarily tight quarters. VCs weren’t attracted to Sand Hill’s low-slung office buildings for the architecture, which were and are a terror to eyes with a taste for anything more sophisticated than “here be four walls and a roof.” VCs didn’t head to South Park to enjoy what Google Maps calls a “tree-lined oval garden” nestled between light industrial buildings. And they aren’t heading to Solbar in Napa Valley for Californian cuisine and a dining room conveniently closed on Partner Mondays.



Raquel Urtasun’s Waabi Autonomous Vehicle Software Company is Launched   



Waabi, the autonomous driving software company recently launched by Raquel Urtasun, will initially focus on the trucking industry. (Credit: Getty Images) 

By John P. Desmond, AI Trends Editor  

Raquel Urtasun hit the ground running as an entrepreneur on June 8, with the announcement of her autonomous driving software company Waabi, complete with $83.5 million in backing.  

Raquel Urtasun, Founder and CEO, Waabi

Urtasun has a long track record as a computer scientist, especially working to apply AI to self-driving car software. Uber hired her in May 2017 to lead a research team based in Toronto for the company’s self-driving car program. (See AI Trends, June 29, 2018) 

“Self-driving is one of the most exciting and important technologies of our generation. Once solved at scale, it will change the world as we know it,” stated Urtasun in the Waabi launch press release“Waabi is the culmination of my life’s work to bring commercially viable self-driving technology to society and I’m honoured to be joined by a team of extraordinary scientists, engineers and technologists who are equally committed to executing on this bold vision.”  

The Waabi launch was greeted with some skepticism, given the state of the self-driving car industry working to get off the ground. But Urtasan knows what she’s doing.  

The latest financing round was led by Khosla Ventures, with additional participation from Urtasun’s former employer, Uber, and Aurora, the AV startup that ended up acquiring Uber ATG in a deal last year, according to an account in The Verge. Money was also raised from 8VC, Radical Ventures, Omers Ventures, BDC, AI luminaries Geoffrey Hinton, Fei-Fei Li, Pieter Abbeel, Sanja Fidler, and others, the report said.  

Waabi will initially focus on the trucking industry, offering its software to automate driving on commercial delivery routes. One reason is, the industry has a shortage of truck drivers. Second, the highways are simpler than city streets for autonomous vehicles to navigate.   

Wasabi’s technical approach will lean heavily on simulation, using techniques Urtasan has developed in her research. The company’s simulation approach will reduce the need for the miles of testing on real roads and highways that autonomous driving competitors have logged   

“For us in simulation, we can test the entire system,” Urtasun stated to The Verge.  “We can train an entire system to learn in simulation, and we can produce the simulations with an incredible level of fidelity, such that we can really correlate what happens in simulation with what is happening in the real world.”  

To have an autonomous vehicle startup founded by a woman who developed the technology and is the CEO is unusual; Urtasan hopes to inspire other women to join the industry. “This is a field that is very dominated by white dudes,” she said. “The way to build integrating knowledge is to build technology with diverse perspectives, because by challenging each other, we build better things.”  

Earlier Career at Uber, Toyota 

Urtasun started at Uber in May 2017, to pursue her work on machine perception for self-driving cars. The work entails machine learning, computer vision, robotics, and remote sensing. Before coming to the university, Urtasun worked at the Toyota Technological Institute at Chicago. Uber committed to hiring dozens of researchers and made a multi-year, multi-million dollar commitment to Toronto’s Vector Institute, which Urtasun co-founded. 

Urtasan has argued that self-driving vehicles need to wean themselves off Lidar (Light Detection and Ranging), a remote sensing method that uses a pulsed laser to measure variable distances. Her research has shown in some cases that vehicles can obtain similar 3D data about the world from ordinary cameras, which are much less expensive than Lidar units, which cost thousands of dollars. 

“If you want to build a reliable self-driving car right now, we should be using all possible sensors,” Urtasun told Wired in an interview published in November 2017. “Longer term, the question is how can we build a fleet of self-driving cars that are not expensive.” 

Ben Dickson, Founder and Editor, TechTalks

The company’s technical “AI-first approach” implies that they will put more emphasis on better machine learning models and less on complementary technologies including Lidar, radar, and mapping data, according to an account in TechTalks. “The benefit of having a software-heavy stack is the very low costs of updating the technology. And there will be a lot of updating in the coming years,” stated Ben Dickson, author of the report and founder of TechTalks.  

Urtasun described the AI system the company uses as a “family of algorithms,” in an account of the launch in TechCrunch. Its closed-loop simulation environment is a replacement for sending real cars on real roads.  

“I’m a bit on the fence on the simulation component,” Dickson stated  “Most self-driving car companies are using simulations as part of the training regime of their deep learning models. But creating simulation environments that are exact replications of the real world is virtually impossible, which is why self-driving car companies continue to use heavy road testing.”  

Waymo Leads in Simulated and Real Testing Miles 

Waymo has at least 20 billion miles of simulated driving to go with its 20 million miles of real-road testing, a record in the industry, according to Dickson. To gain more insight into Waabi’s technology, he looked at some of Urtasun’s recent academic work at the University of Toronto. Her name appears on many papers about autonomous driving; one, uploaded on the arXiv preprint server in January, caught Dickson’s attention.  

Titled “MP3: A Unified Model to Map, Perceive, Predict and Plan,” the paper discusses an approach to self-driving close to the description in Waabi’s launch press release. 

The researchers describe MP3 as “an end-to-end approach to mapless driving that is interpretable, does not incur any information loss, and reasons about uncertainty in the intermediate representations.” In the paper, researchers also discuss the use of “probabilistic spatial layers to model the static and dynamic parts of the environment.” 

MP3 is end-to-end trainable. It uses Lidar input to create scene representations, predict future states and plan trajectories. “The machine learning model obviates the need for finely detailed mapping data that companies like Waymo use in their self-driving vehicles,” Dickson stated. 

Urtasun posted a video, A Future with Self-Driving Vehicles,  on her YouTube channel that provides a brief explanation of how MP3 works. Some researchers commented that it is a clever combination of existing techniques. “There’s also a sizable gap between academic AI research and applied AI,” Dickson stated. How the Waabi model performs in practical settings will be interesting to watch.   

Read the source articles and information in AI Trends, the Waabi launch press release, in The Verge, in TechTalks, in TechCrunch and in a YouTube video, A Future with Self-Driving Vehicles.

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Start Ups

Orbion, manufacturer of in-space plasma propulsion systems, raises $20M Series B



Electric propulsion developer Orbion Space Technology has raised $20 million in a Series B funding round, which it says it will use to scale production capacity of its Aurora propulsion system.

The Michigan-based startup manufactures Hall effect plasma thrusters for use in small and cube satellites. Thrusters are used throughout the lifespan of a satellite (or any object in space that needs to maintain its orbit, like the space station) to adjust orbital altitude, avoid collisions, and de-orbit the craft once it has reached the end of its useful life. Hall thrusters use a magnetic field to ionize a propellant and produce plasma.

While they have long been used in space, this type of thruster has mostly been too expensive for small satellite operators. Orbion says it has created a cost-effective production capacity to meet the growing demand of startups and developers launching to low Earth orbit. Orbion CEO Brad King said in a statement that the company considered contract manufacturers but ultimately chose a vertically integrated manufacturing model. Now, the company says it has outgrown its existing manufacturing space.

The company is facing “unprecedented market demand” for its Aurora system, King said. With the boom of the so-called new space economy, driven in part by the decreased costs of processors, components and even launch, it’s no surprise that there’s been a concurrent uptick in demand for efficient in-space propulsion systems.

The company had previously raised a $9.2 million Series A in August 2019. Since that time, the company secured a research partnership with the U.S. Department of Defense that’s testing the resiliency of American space systems. Orbion also landed a contract with satellite manufacturer Blue Canyon Technologies last September.

This most recent funding round was led by the US-India VC firm Inventus Capital Partners, with additional participation from Material Impact, Beringea and Wakestream Ventures.

“The space game is changing,” Inventus Capital Partners investor Kanwal Rekhi said in a statement. “Large satellites are being replaced by a multitude of nano-satellites; just like the PCs replaced mainframes. Orbion is providing these nano-satellites maneuverability to get into more precise orbits and stay there longer.”

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Fintech secures $90M in debt and equity to scale its digital mortgage lending platform



A lot of startups were built to help people make all-cash offers on homes with the purpose of gaining an edge against other buyers, especially in ultra-competitive markets. is a Denver-based company that is attempting to create a new category in real estate technology. To help scale its digital mortgage lending platform, the company announced today that it has secured $90 million in debt and equity – with $78 million in debt and $12 million in equity. Signal Fire led the equity portion of its financing, which also included participation from existing seed investors Y Combinator and DN Capital. describes itself as an iLender, or a “technology-enabled lender” that gives people a way to submit all-cash offers on a home upon qualifying for a mortgage.

Using its platform, a buyer gets qualified first and then can start looking for homes that fall at or under the amount he or she is approved for. They can purchase a more expensive home, but any amount above what they are approved for would have to come out of pocket. Historically, most buyers don’t know that they will have to pay out of pocket until they’ve made an offer on a specific home and an appraisal comes under the amount of the price they are paying for a home. In those cases, the buyer has to cough up the difference out of pocket. With, its execs tout, buyers know upfront how much they are approved for and can spend on a new home “so there are no surprises later.”

SignalFire Founding Partner and CTO Ilya Kirnos describes as “the first and only iLender.”

He points out that since it is a lender, doesn’t make its money by charging buyers fees like some others in the all-cash offer space.

“Unlike ‘iBuyers’ or ‘alternative iBuyers,’ fronts the cash to buy a house and then makes money off mortgage origination and title, meaning sellers, homebuyers and their agents pay no additional cost for the service,” he told TechCrunch.

IBuyers instead buy homes from sellers who signed up online, make a profit by often fixing up and selling those homes and then helping people purchase a different home with all cash. They also make money by charging transaction fees. A slew of companies operate in the space including established players such as Opendoor and Zillow and newer players such as Homelight.

Image credit: Left to right: Co-founders Adam Pollack, Nick Friedman and Ian Perrex.

Since its 2016 inception, says it has helped thousands of buyers, agents and sellers close on “hundreds of millions of dollars” in homes. The company saw ”14x” growth in 2020 and from June 2020 to June 2021, it achieved “10x” growth in terms of the size of its team and number of transactions and revenue, according to CEO and co-founder Adam Pollack. wants to use its new capital to build on that momentum and meet demand.

Pollack and Nick Friedman met while in college and started building with the goal of “turning every offer into a cash offer.” The pair essentially “failed for two years,” half-jokes Pollack.

“We basically became an encyclopedia of 1,000 ways the idea of helping people make all-cash offers wouldn’t work,” he said.

The team went through Y Combinator in the winter of 2019 and that’s when they created the iLender concept. In the iLender model, the company uses its cash to buy a house for buyers. Once the loan with is ready to close, the company sells back the house to the buyer “at no additional cost or fees.”

“Basically what we learned through those two years is that you have to vertically integrate all of your core competencies, and you can’t rely on third parties to own or manage your special sauce for you,” Pollack told TechCrunch. “We also realized that if you’re going to build a cash offer for anyone who could afford a mortgage, you’ve got to make it a full bona fide cash offer that closes in three days as opposed to a better version of what existed. And you have to own that, and take the risk that comes with it and be comfortable with that.”

The benefits of their model, the pair say, is that buyers get to be cash buyers, sellers can close in as little as 32 hours, and agents “get a guaranteed commission check.” 

“Our mission is that everyone should have an equal chance at homeownership,” Friedman said. “We not only want to level the playing field, we want to create a new standard.”

Buyers using win 6-7 times more frequently, the company claims. With its new capital, It also plans to double its team of 90 and enter new markets outside of its home base of Denver.

SignalFire Partner Chris Scoggins believes that is different from other lenders in that its focus is on “winning the home, not just servicing the loan, with a business model that’s 10x more capital-efficient than other players in the market.

The team is driven…to level the playing field for homebuyers who today lose out against all-cash offers from home-flippers and wealthy individuals,” he added. “We see an enormous opportunity for to become the backbone of the future of mortgage lending.”

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Start Ups

Exclusive: Startup bttn. Takes On Medical Supply Ordering With $1.5M Seed



Three months after launching, health care technology startup bttn. closed on a $1.5 million seed round, anchored by Amol Deshpande, to automate the purchase of medical supplies.

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JT Garwood and Jack Miller started the Seattle-based company in March after seeing health care companies struggle during the global pandemic to pay fair prices for supplies as they competed with other entities due to shortages.

“My background is in software sales at Microsoft, and we started and then sold PPE.Exchange, a marketplace to alleviate supply shortages during the pandemic,” Garwood told Crunchbase News. “As we talked to health care companies, we learned how hard it was to purchase supplies at a fair price. After conversations with vendors, hospitals and clinics, we saw an opportunity to change the medical supply industry.”

Targeting the U.S. wholesale medical supply market, which is predicted to be valued at $243.3 billion this year according to IBISWorld, bttn. developed a platform aimed at cutting out middlemen, offering direct-from-manufacturer pricing and providing a better ordering experience.

Its marketplace eliminates the need for exclusive and restrictive contracts and enables providers to save between 20 percent and 40 percent on their medical supply bills, while also taking advantage of improved shipping and delivery speeds, Garwood said.

“We are taking a process that traditionally involved fax machines or a sales rep, and putting it on a web application for order automation,” he added. “You can build a cart with gowns and syringes and then subscribe on a 30-, 60- or 90-day basis.”

In its first three months of operation, bttn. secured more than 300 customers and did more than $500,000 in sales, he added. In addition, the company formed partnerships with 11 health care associations and have 20 more being finalized.

The company will use the funds to expand its technical, sales and operations teams.

Deshpande, co-founder and CEO of Farmers Business Network, said in an interview that when he met Garwood, he admired his mission-driven approach to lowering costs for health care businesses.

“bttn. is bringing transparency to small businesses,” he added. “JT and Jack understand where small hospital systems are coming from when buying goods, and have easier options for how to do it. I liked the gritty way they launched and got initial traction. They have a big potential to make an impact and be a big company.”

Illustration: Dom Guzman

Stay up to date with recent funding rounds, acquisitions, and more with the Crunchbase Daily.

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