Gecko Robotics aims to save human lives at our nation’s power plants with its wall-climbing robots. To continue doing so, the startup tells TechCrunch it has just secured $7 million from a cadre of high-profile sources, including Founders Fund, Mark Cuban, The Westly Group, Justin Kan and Y Combinator.

We first reported on the Pittsburgh-based company when co-founder Jake Loosararian came to the TechCrunch TV studios to show off his device for the camera. Back then, Gecko was in the YC Spring 2016 cohort, working with several U.S. power plants and headed toward profitability, according to Loosararian. 

You can see the original interview below:

The type of robots Gecko makes are an important part of ensuring safety in industrial and power plant facilities as they are able to go ahead of humans to check for potential hazards. The robots can climb tanks, boilers, pipelines and other industrial equipment using proprietary magnetic adhesion, ultra-sonics, lasers and a variety of sensors to inspect structural integrity, according to a company release.

While not cheap — the robots run anywhere from $50,000 to $100,000 — they are also obviously a minuscule cost compared to human life.

Loosararian also mentioned his technology was faster and more accurate than what is out there at the moment by using machine learning “to solve some of the most difficult problems,” he told TechCrunch.

It’s also a unique enough idea to get the attention from several seasoned investors.

You wouldn’t expect a medical app to get its start as a Snapchat competitor. Neither did video chat startup TapTalk’s founder Onno Faber. But four years ago he was diagnosed with a rare disease called neurofibromatosis type 2 that caused tumors, leading Onno to lose hearing in one ear. He’s amongst the one in 10 people with an uncommon health condition suffering from the lack of data designed to invent treatments for their ails. And he’s now the co-founder of RDMD.

Emerging from stealth today, RDMD aggregates and analyzes medical records and sells the de-identified data to pharmaceutical companies to help them develop medicines. In exchange for access to the data, patients gets their fragmented medical records organized into an app they can use to track their treatment and get second opinions. It’s like Flatiron Health, the Google-backed cancer data startup that just got bought for $2 billion, but for rare diseases.

Now RDMD is announcing it’s raised a $3 million seed round led by Lux Capital and joined by Village Global, Shasta, Garuda, First Round’s Healthcare Coop and a ton of top healthtech angels, including Flatiron investors and board members. The cash will help RDMD expand to build out its product and address more rare diseases.

“We believe that the traditional way rare disease R&D is done needs to change,” RDMD CEO Nancy Yu tells TechCrunch. The former head of corp dev at 23andMe explains that, “There are over 7,000 rare diseases and growing, yet <5% of them have an FDA-approved therapy . . . it’s a massive problem.” 

While data infrastructure supports development of treatments for more common diseases like cancer and diabetes, rare diseases have been ignored because it’s wildly expensive and difficult to collect the high-quality data required to invent new medicines. But “RDMD generates research-grade, regulatory-grade data from patient medical records for use in rare disease drug R&D,” says Yu. The more data it can collect, the more pharma companies can do to help patients.

Trading utility for patient data

With RDMD’s app, a patient’s medical data that’s strewn across hospitals and health facilities can be compiled, organized and synthesized. Handwritten physicians’ notes and faxes are digitized with optical character recognition, structuring the data for scientific research. RDMD lays out a patients’ records in a disease-specific timeline that summarizes their data that can be kept updated, delivered to specialists for consultations or shared with their family and caregivers.

If users opt in, that data can be anonymized and provided to research organizations, hospitals and pharma companies that pay RDMD, though these patients can delete their accounts at any time. Because it’s straight from the medical records, the data is reliable enough to be regulation-compliant and research-ready. That allows it to accelerate the drug development process that’s both lucrative and life-saving. “It normally takes millions of dollars over several years to gather this type of data in rare diseases,” Yu notes. “For the first time, we have a centralized and consented set of data for use in translational research, in a fraction of the time and cost.”

So far, RDMD has enrolled 150 patients with neurofibromatosis. But the potential to expand to other rare diseases attracted a previous pre-seed round from Village Global and new funding from angels like Clover Health CEO and Flatiron board member Vivek Garipalli, Flatiron product director and GV (Google Ventures) partner Vineeta Agarwala, Twitter CTO Parag Agrawal, former 23andMe president Andy Page and the husband and wife duo of former Instagram VP of product Kevin Weil and 137 Ventures managing director Elizabeth Weil.

“Onno and Nancy realized there’s an opportunity to do in rare diseases what Flatiron has done in oncology — to aggregate clinical data from patients, and to leverage that data in clinical trials and other use cases for biotech and pharma,” says Shasta partner Nikhil Basu Trivedi. RDMD will be competing against pharma contract research organizations that incur high costs for collecting data the startup gets for free from patients in exchange for its product. Luckily, Flatiron’s exit paved the way for industry acceptance of RDMD’s model.

“The biggest risk for our company is if we lose our focus on providing real, immediate value to rare disease patients and families. Patients are the reason we are all here, and only with their trust can we fundamentally change how rare disease drug research is done,” says Yu. RDMD will have to ensure it can protect the privacy of patients, the security of data and the efficacy of its application to drug development.

Hindering this process is just one more consequence of our fractured medical records. Hopefully if startups like RDMD and Flatiron can demonstrate the massive value created by unifying medical data, it will pressure the healthcare power players to cooperate on a true industry standard.

Early this month, social messaging service Snap (NYSE: SNAP) reported its second quarter results that beat estimates. However, the market is diappointed with the sequential decline in the number of...

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Responding to a popular request, we are now sharing transcripts of our investor podcast interviews in this new series. The following interview with Gary Little of Canvas Ventures was recorded in...

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Qutoutiao, a news aggregator app backed by Tencent, has filed for an initial public offering of up to $300 million in the United States. In its F-1 form, the company, whose name means “fun headlines,” said it is the number two mobile content aggregator in China. Its main rivals are Jinri Toutiao, China’s top news aggregator, Tencent’s Kuaibao and Yidianzixun.

Based in Shanghai, Qutoutiao reportedly reached unicorn status in March, when it raised a Series B of about $200 million led by Tencent. For Tencent, Qutoutiao and Kuaibao represent opportunities to take market share away from Jinri Toutiao, which is owned by ByteDance. ByteDance is reportedly planning a Hong Kong IPO that could value it at over $45 billion.

In its SEC filing, Qutoutiao said that since launching in July 2016, it has achieved monthly average users of about 48.8 million and daily average users of about 17.1 million, with the average time users spend on the app each day totaling about 55.6 minutes in July 2018. To compete with Jinri Toutiao and other rivals, Qutoutiao targets users from China’s smaller Tier 3 cities. Despite increasing levels of disposable income, Qutoutiao says Tier 3 cities, many of which are located in the west of China, are still underserved markets.

Qutoutiao also said in its filing that its net revenues increased from RMB 58.0 million (about $8.8 million) in 2016 to RMB 517.1 million (about $78.1 million) in 2017, and from RMB 107.3 million (about $16.2 million) in the six months ended June 30, 2017 to RMB 717.8 million (about $108.5 million) in the same period in 2018.

The app uses an AI-based content recommendation engine to display articles and videos based on user profiles and plans to use money raised from its IPO to add more content offerings, increase monetization opportunities and look for acquisition and investment opportunities. Qutoutiao plans to list on Nasdaq under the ticker symbol QTT. The IPO will be underwritten by Citigroup Global Markets, Deutsche Bank Securities, China Merchants Securities and UBS Securities and KeyBanc Capital Markets.

This feature from Benzinga looks at the best and worst IPOs in the first half of 2018, which saw about 118 companies raising an aggregate $35.2 billion, the most since 2014. For this week’s...

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According to a report by the American Cancer Society, an estimated 266,120 women will be newly diagnosed with breast cancer in the United States this year and (according to a 2016 estimate) can expect to pay between $60,000 and $134,000 on average for treatment and care. But, after hundreds of thousands of dollars and non-quantifiable emotional stress for them and their families, the American Cancer Society still estimates 40,920 women will lose their battle to the disease this year.

Worldwide, roughly 1.7 million women will be diagnosed with the disease yearly, according to a 2012 estimate by The World Cancer Research Fund International.

While these numbers are stark, they do little to fully capture just how devastating a breast cancer diagnosis is for women and their loved ones. This is a feeling that Higia Technologies‘ co-founder and CEO Julián Ríos Cantú is unfortunately very familiar with.

“My mom is a two-time breast cancer survivor,” Cantú told TechCrunch. “The first time she was diagnosed I was eight years old.”

Cantú says that his mother’s second diagnosis was originally missed through standard screenings because her high breast density obscured the tumors from the X-ray. As a result, she lost both of her breasts, but has since fully recovered.

“At that moment I realized that if that was the case for a woman with private insurance and a prevention mindset, then for most women in developing countries, like Mexico where we’re from, the outcome could’ve not been a mastectomy but death,” said Cantú.

Following his mother’s experience, Cantú resolved to develop a way to improve the value of women’s lives and support them in identifying breast abnormalities and cancers early in order to ensure the highest likelihood of survival.

To do this, at the age of 18 Cantú designed EVA — a bio-sensing bra insert that uses thermal sensing and artificial intelligence to identify abnormal temperatures in the breast that can correlate to tumor growth. Cantú says that EVA is not only an easy tool for self-screening but also fills in gaps in current screening technology.

Today, women have fairly limited options when it comes to breast cancer screening. They can opt for a breast ultrasound (which has lower specificity than other options), or a breast MRI (which has higher associated costs), but the standard option is a yearly or bi-yearly mammogram for women 45 and older. This method requires a visit to a doctor, manual manipulation of the breasts by a technologist and exposure to low-levels of radiation for an X-ray scan of the breast tissue.

While this method is relatively reliable, there are still crucial shortcomings, Higia Technologies’ medical adviser Dr. Richard Kaszynski M.D., PhD told TechCrunch.

“We need to identify a real-world solution to diagnosing breast cancer earlier,” said Dr. Kaszynski. “It’s always a trade-off when we’re talking about mammography because you have the radiation exposure, discomfort and anxiety in regards to exposing yourself to a third-party.”

Dr. Kaszynski continued to say that these yearly or bi-yearly mammograms also leave a gap in care in which interval cancers — cancers that begin to take hold between screenings — have time to grow unhindered.

Additionally, Dr. Kaszynski says mammograms are not highly sensitive when it comes to detecting tumors in dense breast tissue, like that of Cantú’s mom. Dense breast tissue, which is more common in younger women and is present in 40 percent of women globally and 80 percent of Asian women, can mask the presence of tumors in the breast from mammograms.

Through its use of non-invasive, thermal sensors EVA is able to collect thermal data from a variety of breast densities that can enable women of all ages to more easily (and more frequently) perform breast examinations.

Here’s how it works:

To start, the user inserts the thermal sensing cups (which come in three standard sizes ranging from A-D) into a sports bra, open EVA’s associated EVA Health App, follow the instructions and wait for 60 minutes while the cup collects thermal data. From there, EVA will send the data via Bluetooth to the app and an AI will analyze the results to provide the user with an evaluation. If EVA believes the user may have an abnormality that puts them at risk, the app will recommend follow-up steps for further screening with a healthcare professional.

While sacrificing your personal health data to the whims of an AI might seem like a scary (and dangerous, if the device were to be hacked) idea to some, Cantú says Higia Technologies has taken steps to protect its users’ data, including advanced encryption of its server and a HIPAA-compliant privacy infrastructure.

So far, EVA has undergone clinical trials in Mexico, and through these trials has seen 87.9 percent sensibility and 81.7 percent specificity from the device. In Mexico, the company has already sold 5,000 devices and plans to begin shipping the first several hundred by October of this year.

And the momentum for EVA is only increasing. In 2017, Cantú was awarded Mexico’s Presidential Medal for Science and Technology and so far this year Higia Technologies has won first place in the SXSW’s International Pitch Competition, been named one of “30 Most Promising Businesses of 2018” by Forbes Magazine Mexico and this summer received a $120,000 investment from Y Combinator.

Moving forward, the company is looking to enter the U.S. market and has plans to begin clinical trials with Stanford Medicine X in October 2018 that should run for about a year. Following these trials, Dr. Kaszynski says that Higia Technologies will continue the process of seeking FDA approval to sell the inserts first as a medical device, accessible at a doctor’s office, and then as a device that users can have at home.

The final pricing for the device is still being decided, but Cantú says he wants the product to be as affordable and accessible as possible so it can be the first choice for women in developing countries where preventative cancer screening is desperately needed.

The Movado Group, which sells multiple brands, including Lacoste, Tommy Hilfiger and Hugo Boss, has purchased MVMT, a small watch company founded by Jacob Kassan and Kramer LaPlante in 2013. The company, which advertised heavily on Facebook, logged $71 million in revenue in 2017. Movado purchased the company for $100 million.

“The acquisition of MVMT will provide us greater access to millennials and advances our Digital Center of Excellence initiative with the addition of a powerful brand managed by a successful team of highly creative, passionate and talented individuals,” Movado Chief Executive Efraim Grinberg said.

MVMT makes simple watches for the millennial market in the vein of Fossil or Daniel Wellington. However, the company carved out a niche by advertising heavily on social media and being one of the first microbrands with a solid online presence.

“It provides an opportunity to Movado Group’s portfolio as MVMT continues to cross-sell products within its existing portfolio, expand product offerings within its core categories of watches, sunglasses and accessories, and grow its presence in new markets through its direct-to-consumer and wholesale business,” said Grinberg.

MVMT is well-known as a “fashion brand,” namely a brand that sells cheaper quartz watches that are sold on style versus complexity or cost. Their pieces include standard three-handed models and newer quartz chronographs.

Mutiny, which is part of the current batch of startups at accelerator Y Combinator, helps business-to-business, software-as-a-service companies present a message that’s customized to each visitor on their website.

Co-founder and CEO Jaleh Rezaei said this concept is alive and well in the analog world: When she was at VMware, sales reps were given materials to help them tailor their pitch for each prospective customer. Then, when she was one of the early employees at HR services startup Gusto, she tried to do something similar online, only to find that existing software wasn’t quite up to the task.

There are landing page optimization tools, but Rezaei asked, “Who wants to create a thousand versions of your website?” And there are A/B testing tools, but Rezaei argued that they’re really designed to test “generic content” and use “very little audience intelligence.” And as for creating your own personalization tools, many companies will find that it requires “way too much engineering effort.”

That’s where Mutiny comes in. It integrates with existing data sources to allow businesses to divide their customers into segments. Then they can use Mutiny’s graphical interface to create personalized elements of the webpage for each segment.

For example, when you visit the homepage of Mutiny customer Amplitude, things like the customer testimonials and the call to action will change depending on the size of your company. Or when Brex customers click through from an email marketing campaign, they’ll see a credit card offer tailored to their name and company.

These kinds of changes might not seem all that significant, but Rezaei said that when someone visits a B2B website, they’re probably interested in the product or service already. If they’re not converting, it’s probably because “they didn’t find what they wanted right away.” Mutiny can help surface the right content or the right message for the right customer.

The startup will also compare the personalized results to the generic webpage to help determine what does and doesn’t improve the bottom line. Rezaei said some of Mutiny’s early customers (who include Gusto, Infusionsoft and Brex) have seen conversion rates improve by 20 to 180 percent.

“That’s not to say that every test performs better, but the nice thing here is that you immediately see how something is performing,” she added.

Eventually, Rezaei is hoping to expand Mutiny’s technology so that it can personalize every aspect of the B2B purchase experience, including email and ad retargeting.

“Our passion as a founding team is growth,” she said. “Progress occurs not when you just build something, but when that product makes it into the hands of the person for whom it was intended to help.”

As government regulation for commercial drone usage seems to be trending in a very positive direction for the companies involved, there is an ever-growing opportunity for drone startups to utilize artificial intelligence to deliver insights without requiring much human effort.

Sterblue, a French drone software startup that is launching out of Y Combinator’s latest class of companies, is aiming to get off-the-shelf drones inspecting large outdoor structures up close with automated insights that identify anomalies that need a second look.

The startup’s software is specifically focused on enabling drones to easily inspect large power lines or wind turbines with simple automated trajectories that can get a job done much quicker and with less room for human error. The software also allows the drones to get much closer to the large structures they are scanning so the scanned images are as high-quality as possible.

Compared to navigating a tight urban environment, Sterblue has the benefit of there being very few airborne anomalies around these structures, so autonomously flying along certain flight paths is as easy as having a CAD structure available and enough wiggle room to correct for things like wind condition.

Operators basically just have to connect their drones to the Sterblue cloud platform where they can upload photos and view 3D models of the structures they have scanned while letting the startup’s neural net identify any issues that need further attention. All and all, Sterblue says their software can let drones get within three meters of power lines and wind turbines, which allows their AI systems to easily detect anomalies from the photos being taken. Sterblue says their system can detect defects as small as one millimeter in size.

The startup was initially working on their own custom drone hardware but decided that their efforts were best spent supporting off-the-shelf devices from companies like DJI, with their software solution sitting on top. The founding team is composed of former Airbus employees that are focusing early efforts on utility companies, with some of the first customers based in Europe, Africa and Asia.

Cryptocurrency projects can crash and burn if developers don’t predict how humans will abuse their blockchains. Once a decentralized digital economy is released into the wild and the coins start to fly, it’s tough to implement fixes to the smart contracts that govern them. That’s why Incentivai is coming out of stealth today with its artificial intelligence simulations that test not just for security holes, but for how greedy or illogical humans can crater a blockchain community. Crypto developers can use Incentivai’s service to fix their systems before they go live.

“There are many ways to check the code of a smart contract, but there’s no way to make sure the economy you’ve created works as expected,” says Incentivai’s solo founder Piotr Grudzień. “I came up with the idea to build a simulation with machine learning agents that behave like humans so you can look into the future and see what your system is likely to behave like.”

Incentivai will graduate from Y Combinator next week and already has a few customers. They can either pay Incentivai to audit their project and produce a report, or they can host the AI simulation tool like a software-as-a-service. The first deployments of blockchains it’s checked will go out in a few months, and the startup has released some case studies to prove its worth.

“People do theoretical work or logic to prove that under certain conditions, this is the optimal strategy for the user. But users are not rational. There’s lots of unpredictable behavior that’s difficult to model,” Grudzień explains. Incentivai explores those illogical trading strategies so developers don’t have to tear out their hair trying to imagine them.

Protecting crypto from the human x-factor

There’s no rewind button in the blockchain world. The immutable and irreversible qualities of this decentralized technology prevent inventors from meddling with it once in use, for better or worse. If developers don’t foresee how users could make false claims and bribe others to approve them, or take other actions to screw over the system, they might not be able to thwart the attack. But given the right open-ended incentives (hence the startup’s name), AI agents will try everything they can to earn the most money, exposing the conceptual flaws in the project’s architecture.

“The strategy is the same as what DeepMind does with AlphaGo, testing different strategies,” Grudzień explains. He developed his AI chops earning a masters at Cambridge before working on natural language processing research for Microsoft.

Here’s how Incentivai works. First a developer writes the smart contracts they want to test for a product like selling insurance on the blockchain. Incentivai tells its AI agents what to optimize for and lays out all the possible actions they could take. The agents can have different identities, like a hacker trying to grab as much money as they can, a faker filing false claims or a speculator that cares about maximizing coin price while ignoring its functionality.

Incentivai then tweaks these agents to make them more or less risk averse, or care more or less about whether they disrupt the blockchain system in its totality. The startup monitors the agents and pulls out insights about how to change the system.

For example, Incentivai might learn that uneven token distribution leads to pump and dump schemes, so the developer should more evenly divide tokens and give fewer to early users. Or it might find that an insurance product where users vote on what claims should be approved needs to increase its bond price that voters pay for verifying a false claim so that it’s not profitable for voters to take bribes from fraudsters.

Grudzień has done some predictions about his own startup too. He thinks that if the use of decentralized apps rises, there will be a lot of startups trying to copy his approach to security services. He says there are already some doing token engineering audits, incentive design and consultancy, but he hasn’t seen anyone else with a functional simulation product that’s produced case studies. “As the industry matures, I think we’ll see more and more complex economic systems that need this.”

Klarity, a member of the Y Combinator 2018 Summer class, wants to automate much of the contract review process by applying artificial intelligence, specifically natural language processing.

Company co-founder and CEO Andrew Antos has experienced the pain of contract reviews first hand. After graduating from Harvard Law, he landed a job spending 16 hours a day reviewing contract language, a process he called mind-numbing. He figured there had to be a way to put technology to bear on the problem and Klarity was born.

“A lot of companies are employing internal or external lawyers because their customers, vendors or suppliers are sending them a contract to sign,” Antos explained They have to get somebody to read it, understand it and figure out whether it’s something that they can sign or if it requires specific changes.

You may think that this kind of work would be difficult to automate, but Antos said that  contracts have fairly standard language and most companies use ‘playbooks.’ “Think of the playbook as a checklist for NDAs, sales agreements and vendor agreements — what they are looking for and specific preferences on what they agree to or what needs to be changed,” Antos explained.

Klarity is a subscription cloud service that checks contracts in Microsoft Word documents using NLP. It makes suggestions when it sees something that doesn’t match up with the playbook checklist. The product then generates a document, and a human lawyer reviews and signs off on the suggested changes, reducing the review time from an hour or more to 10 or 15 minutes.

They launched the first iteration of the product last year and have 14 companies using it with 4 paying customers so far including one of the world’s largest private equity funds. These companies signed on because they have to process huge numbers of contracts. Klarity is helping them save time and money, while applying their preferences in a consistent fashion, something that a human reviewer can have trouble doing.

He acknowledges the solution could be taking away work from human lawyers, something they think about quite a bit. Ultimately though, they believe that contract reviewing is so tedious, it is freeing up lawyers for work that requires a greater level of intellectual rigor and creativity.

Antos met his co-founder and CTO, Nischal Nadhamuni, at an MIT entrepreneurship class in 2016 and the two became fast friends. In fact, he says that they pretty much decided to start a company the first day. “We spent 3 hours walking around Cambridge and decided to work together to solve this real problem people are having.”

They applied to Y Combinator two other times before being accepted in this summer’s cohort. The third time was the charm. He says the primary value of being in YC is the community and friendships they have formed and the help they have had in refining their approach.

“It’s like having a constant mirror that helps you realize any mistakes or any suboptimal things in your business on a high speed basis,” he said.

President Trump’s time in office has been punctuated by rising tension with China on a host of economic issues. He’s received bipartisan criticism for the impact of tariffs on Chinese goods and the resulting retaliation against American exports.

Democrats and Republicans have also unified over concerns about how Chinese state-associated actors are using minority investments in critical technology companies to gain sensitive information — like IP and know-how — about startups, many of them VC-backed. Policymakers are worried this technology is being used to propel Chinese advancement in emerging technology like artificial intelligence and robotics.

These concerns led to passage of the Foreign Investment Risk Review Modernization Act (FIRRMA), which was signed into law by the president on August 13. NVCA has been at the table during FIRRMA’s consideration because it stands to have a significant impact on the venture and startup ecosystem.

Who in our industry needs to understand FIRRMA going forward? Many more than you might think. VCs with foreign LPs, VCs with foreign co-investors or startups contemplating taking foreign capital are the prime examples, but given the shifting startup landscape in recent years, FIRRMA will leave a broad mark.

FIRRMA expands the power of the Committee on Foreign Investment in the U.S. (CFIUS) to scrutinize foreign investments into “critical technology” companies for national security implications. Few in the startup world have dealt with CFIUS, but those who have understand its power and implications. It’s the opaque government entity that blew up the Broadcom-Qualcomm transaction for national security reasons and has been called the “ultimate regulatory bazooka.”

Before FIRRMA, CFIUS reviewed foreign investments for national security considerations when the investment resulted in foreign control of a U.S. entity. But minority investments used to obtain sensitive information about a company have been outside the scope of CFIUS because those investments generally don’t deliver control to the foreign investor. FIRRMA is intended to address this blind spot by greatly expanding the transactions that must be disclosed to CFIUS.

NVCA secured hard-fought changes to FIRRMA to lessen the impact on our industry. The bill has come a long way from when it was introduced. For example, under the original version we were concerned foreign LPs might need to file with CFIUS because they would not meet the exemption for passive investment. Furthermore, a sizeable chunk of foreign direct investments into startups would be picked up by the bill. Fortunately, key changes were made in the end.

Ultimately, under FIRRMA, the government will now be able to review — and potentially reject — any investment by a foreign entity in a critical technology company that gives the foreign entity:

Under this approach, the typical venture fund ought to be able to avoid a CFIUS filing because its foreign LPs won’t meet the above factors. And many direct investments into startups will also avoid filing with CFIUS unless they’re leading to board seats, non-public information about the company or decision-making capability.

Still, VCs, LPs, and startups raising capital will need to navigate FIRRMA going forward to make sure they don’t get tripped up by the new law. Doing so will likely trigger a CFIUS filing, leading to delay and expense. The fast-moving startup ecosystem will not welcome the uncertainty that comes with a 45-day initial review that is fraught with uncertainty and costs. And that expense is no small sum, as FIRRMA sets the CFIUS filing fee at 1 percent of the value of the transaction or $300,000 — whichever is less. And that doesn’t include legal fees.

It is imperative the venture industry remain vigilant on FIRRMA and related national security issues. The government is increasingly interested in how our world operates because emerging technology is impacting society and foreign capital is sometimes used to launch high-growth companies.

At NVCA, we are embracing this conversation and will hold a conference named “Emerging Technology Meets National Security” on November 14 in DC.

The NVCA will remain deeply engaged in FIRRMA as regulations are written that will define terms and set practices that affect the thrust of the bill. These issues are happening whether or not the venture industry is part of the conversation, but we only get a chance to impact decisions if we’re in the room.

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Food delivery startup DoorDash announced this afternoon that it has raised $250 million, just five months since the company announced a $535 million round.

Why raise more money so soon? CEO Tony Xu told Axios that he wasn’t actively looking for additional investment, but was open to investor interest because it could help the company expand more quickly. (Maybe he’ll have more to say about those plans at Disrupt SF next month.)

The new funding was led by Coatue Management and DST Global. It sounds like the terms were pretty appealing too, with the valuation growing from $1.4 billion to $4 billion.

In a blog post, the company said it’s had a good 2018, with deliveries increasing 250 percent year-over-year, restaurant chains like Chipotle and IHOP signing up and last week’s launch of the DashPass subscription service, where you can pay $9.99 per month to get unlimited free deliveries.

“As we grow, we will stay true to our values and our mission of connecting people with possibility  —  and, trust us, we’re just getting started,” DoorDash wrote.

Inokyo wants to be the indie Amazon Go. It’s just launched its prototype cashierless autonomous retail store. Cameras track what you grab from shelves, and with a single QR scan of its app on your way in and out of the store, you’re charged for what you got.

Inokyo‘s first store is now open on Mountain View’s Castro Street selling an array of bougie kombuchas, snacks, protein powders and bath products. It’s sparse and a bit confusing, but offers a glimpse of what might be a commonplace shopping experience five years from now. You can get a glimpse yourself in our demo video below:

“Cashierless stores will have the same level of impact on retail as self-driving cars will have on transportation,” Inokyo co-founder Tony Francis tells me. “This is the future of retail. It’s inevitable that stores will become increasingly autonomous.”

Inokyo (rhymes with Tokyo) is now accepting signups for beta customers who want early access to its Mountain View store. The goal is to collect enough data to dictate the future product array and business model. Inokyo is deciding whether it wants to sell its technology as a service to other retail stores, run its own stores or work with brands to improve their product’s positioning based on in-store sensor data on custom behavior.

“We knew that building this technology in a lab somewhere wouldn’t yield a successful product,” says Francis. “Our hypothesis here is that whoever ships first, learns in the real world and iterates the fastest on this technology will be the ones to make these stores ubiquitous.” Inokyo might never rise into a retail giant ready to compete with Amazon and Whole Foods. But its tech could even the playing field, equipping smaller businesses with the tools to keep tech giants from having a monopoly on autonomous shopping experiences.

It’s about what cashiers do instead

“Amazon isn’t as ahead as we assumed,” Francis remarks. He and his co-founder Rameez Remsudeen took a trip to Seattle to see the Amazon Go store that first traded cashiers for cameras in the U.S. Still, they realized, “This experience can be magical.” The two met at Carnegie Mellon through machine learning classes before they went on to apply that knowledge at Instagram and Uber. The two decided that if they jumped into autonomous retail soon enough, they could still have a say in shaping its direction.

Next week, Inokyo will graduate from Y Combinator’s accelerator that provided its initial seed funding. In six weeks during the program, they found a retail space on Mountain View’s main drag, studied customer behaviors in traditional stores, built an initial product line and developed the technology to track what users are taking off the shelves.

Here’s how the Inokyo store works. You download its app and connect a payment method, and you get a QR code that you wave in front of a little sensor as you stroll into the shop. Overhead cameras will scan your body shape and clothing without facial recognition in order to track you as you move around the store. Meanwhile, on-shelf cameras track when products are picked up or put back. Combined, knowing who’s where and what’s grabbed lets it assign the items to your cart. You scan again on your way out, and later you get a receipt detailing the charges.

Originally, Inokyo actually didn’t make you scan on the way out, but it got the feedback that customers were scared they were actually stealing. The scan-out is more about peace of mind than engineering necessity. There is a subversive pleasure to feeling like, “well, if Inokyo didn’t catch all the stuff I chose, that’s not my problem.” And if you’re overcharged, there’s an in-app support button for getting a refund.

Inokyo was accurate in what it charged me despite me doing a few switcharoos with products I nabbed. But there were only about three people in the room at the time. The real test for these kinds of systems are when a rush of customers floods in and cameras have to differentiate between multiple similar-looking people. Inokyo will likely need to be more than 99 percent accurate to be more of a help than a headache. An autonomous store that constantly over- or undercharges would be more trouble than it’s worth, and patrons would just go to the nearest classic shop.

Just because autonomous retail stores will be cashier-less doesn’t mean they’ll have no staff. To maximize cost-cutting, they could just trust that people won’t loot it. However, Inokyo plans to have someone minding the shop to make sure people scan in the first place and to answer questions about the process. But there’s also an opportunity in reassigning labor from being cashiers to concierges that can recommend the best products or find what’s the right fit for the customer. These stores will be judged by the convenience of the holistic experience, not just the tech. At the very least, a single employee might be able to handle restocking, customer support and store maintenance once freed from cashier duties.

While Amazon Go uses cameras in a similar way to Inokyo, it also relies on weight sensors to track items. There are plenty of other companies chasing the cashierless dream. China’s BingoBox has nearly $100 million in funding and has more than 300 stores, though they use less sophisticated RFID tags. Fellow Y Combinator startup Standard Cognition has raised $5 million to equip old-school stores with autonomous camera-tech. AiFi does the same, but touts that its cameras can detect abnormal behavior that might signal someone is a shoplifter.

The store of the future seems like more and more of a sure thing. The race’s winner will be determined by who builds the most accurate tracking software, easy-to-install hardware and pleasant overall shopping flow. If this modular technology can cut costs and lines without alienating customers, we could see our local brick-and-mortars adapt quickly. The bigger question than if or even when this future arrives is what it will mean for the millions of workers who make their living running the checkout lane.

Sramana Mitra: What is the geographical distribution of these six companies that you have exited? Mark Hasebroock: They’re all in the Midwest – from Texas to Kansas City and between the mountains....

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If you want to have a brutal workout from the comfort of your own home — and have about $3,000 to spend — look no further. Tonal, a strength-training system powered by electromagnetism resistance technology and machine learning, is launching today to let you get ripped and in shape without having to go to the gym.

There are two key features that make Tonal different from the weightlifting machines you’ll find in the gym. For one, there aren’t actual weights. Instead, Tonal uses electromagnetism to simulate and control weight.

So when you’re doing a bicep curl, for example, “the thing pulling back on you isn’t gravity — it’s an electromagnetic field controlled by a computer algorithm,” Tonal CEO and founder Aly Orady told me at the company’s San Francisco headquarters last week. “It’s digitally controlled weight.”

The other key feature is the built-in personal trainer. For $49 a month, Tonal members get access to personal training sessions, recommended programs and workouts.

“It’s like having an entire gym and a personal trainer in your home,” Orady said. “That’s a pretty big claim, but I’m going to show it to you and you’re going to love it.”

He was right. I loved it in a pure-hate kind of way. I had a chance to try it out and I feel confident saying I had the worst day of my year — but, you know, in a good, yet sadistic way. It’s just that I’m horribly out of shape and this machine isn’t messing around.

Tonal works by first determining your baseline strength with a 10-minute test. The test entails completing four movements (seated lat pulldown, seated overhead press, bench press and neutral grip dead lift) as fast and as powerful as you can. From there, Tonal gives you a baseline score for your core, upper body and lower body.

As you can see from my results below, I’m very strong.

But seriously — my trainer told me I was very strong. From there, I completed my first workout. And that’s when I realized that while I may be strong, my endurance is non-existent.

As I made my way through my first workout, Tonal could automatically tell that I was on the struggle bus headed further into struggle town. That’s because Tonal was constantly monitoring the quality of my reps and, based on that, dynamically adjusted the weight.

Tonal, which mounts to your wall like a TV, is pretty pricey ($2,995), but it joins the likes of startups like Peloton and Mirror. Peloton is an internet-connected cycling bike that retails for $1,995 plus $39 a month for content, while Mirror is similarly an at-home device that lets you see video of a fitness instructor and classmates for exercises like barre, yoga and pilates. Mirror has raised $13 million from Spark Capital, Lerer Hippeau Ventures, First Round Capital and others. The company, however, has yet to launch its product and pricing.

Tonal is not disclosing its amount of funding, but has raised money from Mayfield, Shasta, Bolt Capital, Next Play Capital, Upside Partnership and others.

Credit Karma, the service best known for providing free credit score monitoring and other financial advice (mostly to millennials), is getting into the mortgage business. The company today announced that it has acquired Approved, a mortgage platform that brings modern technology to a process that even today often still involves faxing documents back and forth. The companies did not disclose the financial details of the transaction.

At first glance, this may seem like a bit of an odd acquisition, given that Approved is mostly a service for banks and mortgage brokers. But it also makes perfect sense for Credit Karma to get into the mortgage business.

Indeed, Credit Karma Chief Product Officer Nikhyl Singhal told me that he sees this as the natural next step in the company’s evolution.

“As we’ve expanded, you’ve seen us move from credit cards as a way to help members with that part of their life to first personal loans to auto — meaning auto loans, auto insurance,” he said. “Today, we’re really talking more publicly about mortgage. Mortgage being for many of our members the most important financial decision they’ll make.”

It’s also no secret that Credit Karma’s largest user base is millennials. As they get older and start getting to the point where they consider buying a home (assuming they are in the financial position to do so), the company obviously wants to keep those users engaged on their platform and offer them more services.

Singhal also stressed that 80 percent of Credit Karma members are active on the service before they get a new mortgage — and Credit Karma obviously knows all of this because it is able to collect a lot of very detailed financial data about its users.

As Singhal noted, Credit Karma has been working on getting deeper into the mortgage business for about 18 months. “The acquisition is just the continuing effort of saying, ‘look, we’re serious about taking our scale and being that trusted destination for our members as it relates to helping them with their mortgage.'”

Credit Karma already offers some mortgage brokerage services, and today’s acquisition is meant to help speed up this process with the help of Approved’s technology. “What approved has spent a lot of time doing is working with lenders to help them automate and make them more efficient,” Singhal explained. A more efficient process, Singhal expects, means the lenders can reduce rates and save Credit Karma members money.

Approved CEO Andy Taylor and CTO Navtej Sadhal are both Redfin alums, so they know this business well. Taylor told me that he believes that Credit Karma will allow him to scale his service up beyond what a stand-alone company could’ve done. Taylor tells me that he sees Approved’s mission as helping consumers navigate the often tedious and painful world of getting a mortgage. “Moving to Credit Karma is going to immediately give us the sort of resources and immediate scale to continue to drive that mission-driven work,” he said. “We can reach significantly more people than we could otherwise. We can spend less time focusing in on the minutia of building the lender system and more time focusing on bringing transparency to the transaction and having a better loan application process.”