Skydio partners with EagleView for autonomous residential roof inspections via drone

Skydio only just recently announced its expansion into the enterprise and commercial market with hardware and software tools for its autonomous drone technology, and now it’s taking the lid off a brand new big partnership with one commercial partner. Skydio will work with EagleView to deploy automated residential roof inspection using Skydio drones, with service initially provide via EagleView’s Assess product, launching first in the Dallas/Ft. Worth area of Texas.

The plan is to expand coverage to additional metro areas starting next year, and then broaden to rural customers as well. The partners will use AI-based analysis, paired with Skydio’s high-resolution, precision imaging to provide roofing status information to insurance companies, claims adjustment companies and government agencies, providing a new level of quality and accuracy for property inspections that don’t even require an in-person roof inspection component.

Skydio announced its enterprise product expansion in July, alongside a new $100 million funding round. The startup, which has already delivered two generations of its groundbreaking fully autonomous consumer drone, also debuted the X2, a commercial drone that includes additional features like a thermal imaging camera. It’s also offering a suite of “enterprise skills,” software features that can provide its partners with automated workflows and AI analysis and processing, including a House Scan feature for residential roof inspection, which is core to this new partnership.


By Darrell Etherington

NUVIA raises $240M from Mithril to make climate-ready enterprise chips

Climate change is on everyone’s minds these days, what with the outer Bay Area on fire, orange skies above San Francisco, and a hurricane season that is bearing down on the East Coast with alacrity (and that’s just the United States in the past two weeks).

A major — and growing — source of those emissions is data centers, the cloud infrastructure that powers most of our devices and experiences. That’s led to some novel ideas, such as Microsoft’s underwater data center Project Natick, which just came back to the surface for testing a bit more than a week ago.

Yet, for all the fun experiments, there is a bit more of an obvious solution: just make the chips more energy efficient.

That’s the thesis of NUVIA, which was founded by three ex-Apple chip designers who led the design of the “A” series chip line for the company’s iPhones and iPads for years. Those chips are wicked fast within a very tight energy envelope, and NUVIA’s premise is essentially what happens when you take those sorts of energy constraints (and the experience of its chip design team) and apply them to the data center.

We did a deep profile of the company last year when it announced its $53 million Series A, so definitely read that to understand the founding story and the company’s mission. Now about one year later, it’s coming back to us with news of a whole bunch of more funding.

NUVIA announced today that it has closed on a $240 million Series B round led by Mithril Capital, with a bunch of others involved listed below.

Since we last chatted with the company, we now have a bit more detail of what it’s working on. It has two products under development, a system-on-chip (SoC) unit dubbed “Orion” and a CPU core dubbed “Phoenix.” The company previewed a bit of Phoenix’s performance last month, although as with most chip companies, it is almost certainly too early to make any long-term predictions about how the technology will settle in with existing and future chips coming to the market.

NUVIA’s view is that chips are limited to about 250-300 watts of power given the cooling and power constraints of most data centers. As more cores become common pre chip, each core is going to have to make do with less power availability while maintaining performance. NUVIA’s tech is trying to solve that problem, lowering total cost of ownership for data center operators while also improving overall energy efficiency.

There’s a lot more work to be done of course, so expect to see more product announcements and previews from the company as it gets its technology further finalized. With $240 million more dollars in the bank though, it certainly has the resources to make some progress.

Shortly after we chatted with the company last year, Apple sued company founder and CEO Gerald Williams III for breach of contract, with the company arguing that its former chip designer was trying to poach employees for his nascent startup. Williams counter-sued earlier this year, and the two parties are now in the discovery phase of their lawsuit, which remains ongoing.

In addition to lead Mithril, the round was done “in partnership with” the founders of semiconductor giant Marvell (Sehat Sutardja and Weili Dai), funds managed by BlackRock, Fidelity, and Temasek, plus Atlantic Bridge and Redline Capital along with Series A investors Capricorn Investment Group, Dell Technologies Capital, Mayfield, Nepenthe LLC, and WRVI Capital.


By Danny Crichton

Quantum startup CEO suggests we are only five years away from a quantum desktop computer

Today at TechCrunch Disrupt 2020, leaders from three quantum computing startups joined TechCrunch editor Frederic Lardinois to discuss the future of the technology. IonQ CEO and president Peter Chapman suggested we could be as little as five years away from a desktop quantum computer, but not everyone agreed on that optimistic timeline.

“I think within the next several years, five years or so, you’ll start to see [desktop quantum machines]. Our goal is to get to a rack-mounted quantum computer,” Chapman said.

But that seemed a tad optimistic to Alan Baratz, CEO at D-Wave Systems. He says that when it comes to developing the super-conducting technology that his company is building, it requires a special kind of rather large quantum refrigeration unit called a dilution fridge, and that unit would make a five-year goal of having a desktop quantum PC highly unlikely.

Itamar Sivan, CEO at Quantum Machines, too, believes we have a lot of steps to go before we see that kind of technology, and a lot of hurdles to overcome to make that happen.

“This challenge is not within a specific, singular problem about finding the right material or solving some very specific equation, or anything. It’s really a challenge, which is multidisciplinary to be solved here,” Sivan said.

Chapman also sees a day when we could have edge quantum machines, for instance on a military plane, that couldn’t access quantum machines from the cloud efficiently.

“You know, you can’t rely on a system which is sitting in a cloud. So it needs to be on the plane itself. If you’re going to apply quantum to military applications, then you’re going to need edge-deployed quantum computers,” he said.

One thing worth mentioning is that IonQ’s approach to quantum is very different from D-Wave’s and Quantum Machines’ .

IonQ relies on technology pioneered in atomic clocks for its form of quantum computing. Quantum Machines doesn’t build quantum processors. Instead, it builds the hardware and software layer to control these machines, which are reaching a point where that can’t be done with classical computers anymore.

D-Wave, on the other hand, uses a concept called quantum annealing, which allows it to create thousands of qubits, but at the cost of higher error rates.

As the technology develops further in the coming decades, these companies believe they are offering value by giving customers a starting point into this powerful form of computing, which when harnessed will change the way we think of computing in a classical sense. But Sivan says there are many steps to get there.

“This is a huge challenge that would also require focused and highly specialized teams that specialize in each layer of the quantum computing stack,” he said. One way to help solve that is by partnering broadly to help solve some of these fundamental problems, and working with the cloud companies to bring quantum computing, however they choose to build it today, to a wider audience.

“In this regard, I think that this year we’ve seen some very interesting partnerships form which are essential for this to happen. We’ve seen companies like IonQ and D-Wave, and others partnering with cloud providers who deliver their own quantum computers through other companies’ cloud service,” Sivan said. And he said his company would be announcing some partnerships of its own in the coming weeks.

The ultimate goal of all three companies is to eventually build a universal quantum computer, one that can achieve the goal of providing true quantum power. “We can and should continue marching toward universal quantum to get to the point where we can do things that just can’t be done classically,” Baratz said. But he and the others recognize we are still in the very early stages of reaching that end game.


By Ron Miller

Zoom introduces all-in-one home communications appliance for $599

Zoom has become the de facto standard for online communications during the pandemic, but the company has found that it’s still a struggle for many employees to set up the equipment and the software to run a meeting effectively. The company’s answer is an all-in-one communications appliance with Zoom software ready to roll in a simple touch interface.

The device dubbed the Zoom for Home – DTEN ME, is being produced by partner DTEN. It consists of a stand-alone 27 inch screen, essentially a large tablet equipped with three wide-angle cameras designed for high-resolution video and 8 microphones. Zoom software is pre-loaded on the device and the interface is designed to provide easy access to popular Zoom features.

Zoom for Home – DTEN ME with screen sharing on. Image Credit: Zoom

Jeff Smith, head of Zoom Rooms, says that the idea is to offer an appliance that you can pull out of the box and it’s ready to use with minimal fuss. “Zoom for Home is an initiative from Zoom that allows any Zoom user to deploy a personal collaboration device for their video meetings, phone calls, interactive whiteboard annotation — all the good stuff that you want to do on Zoom, you can do with a dedicated purpose-built device,” Smith told TechCrunch.

He says this is designed with simplicity in mind, so that you pull it out of the box and launch the interface by entering a pairing code on a website on your laptop or mobile phone. Once the interface appears, you simply touch the function you want such as making a phone call or starting a meeting and it connects automatically.

Image Credits: Zoom

You can link it to your calendar so that all your meetings appear in a sidebar, and you just touch the next meeting to connect. If you need to share your screen it includes ultrasonic pairing between the appliance and your laptop or mobile phone. This works like Bluetooth, but instead of sending out a radio signal, it sends out a sound between 18 and 22 kHz, which most people can’t hear, to connect the two devices, Smith said.

Smith says Zoom will launch with two additional partners including the Neat Bar and the Poly Studio X Series, and could add other partners in the future.

The DTEN appliance will cost $599 and works with an existing Zoom license. The company is taking pre-orders and the devices are expected to ship next month.


By Ron Miller

Analog Devices to acquire rival chipmaker Maxim Integrated for $21 billion

Analog Devices didn’t waste any time kicking off the week with a bang when it announced this morning it was acquiring rival chipmaker Maxim Integrated Products for $20.91 billion (according to multiple reports). The company had a market cap of $17.09 billion as of Friday’s close.

The deal, which has already been approved by both company’s boards, would create a chip making behemoth worth $68 billion, according to the Analog. The idea behind the transaction is that bigger is better and the combined companies will increase Analog’s revenue by $8.2 billion.

What’s more, the two companies should combine well together in that there isn’t much overlap in their businesses. Maxim’s strength is in the automotive and datacenter spaces, while Analog is more concentrated in industrial and healthcare.

Vincent Roche, President and CEO of ADI was enthusiastic about the potential of the combined organizations. “ADI and Maxim share a passion for solving our customers’ most complex problems, and with the increased breadth and depth of our combined technology and talent, we will be able to develop more complete, cutting-edge solutions,” he said in a statement.

Maxim was founded back in 1983 and went public in 1988. It made 9 acquisitions between 2002 and 2013 with the most recent being Voltera in 2013, according to Crunchbase data.

As with all deals of this sort, it needs to pass regulator muster first, but the companies expect the deal to close by next summer.


By Ron Miller

Zoom announces new Hardware as a Service offering to run on ServiceNow

Zoom announced a new Hardware as a Service offering today that will run on the ServiceNow platform. At the same time the company announced a deal with ServiceNow to standardize on Zoom and Zoom Phone for its 11,000 employees in another case of SaaS cooperation.

For starters, the new Hardware as a Service offering allows customers, who use the Zoom Phone and Zoom Rooms software to acquire related hardware from the company for a fixed monthly cost. The company announced that initial solutions providers will include DTEN, Neat, Poly and Yealink.

The new service allows companies to access low-cost hardware and pay for the software and hardware on a single invoice. This could result in lower up-front costs, while simplifying the bookkeeping associated with a customer’s online communications options.

Companies can start small if they wish, then add additional hardware over time as needs change, and they can also opt for a fully managed service, where a third party can deal with installation and management of the hardware if that’s what a customer requires.

Zoom will run the new service on ServiceNow’s Now platform, which provides a way to manage the service requests as they come in. And in a case of one SaaS hand washing the other, ServiceNow has standardized on the Zoom platform for its internal communications tool, which has become increasingly important as the pandemic has moved employees to work from home. The company also plans to replace its current phone system with Zoom Phones.

One of the defining characteristics of SaaS companies, and a major difference from previous generations of tech companies, has been the willingness of these organizations to work together to string together sets of services when it makes sense. These kinds of partnerships, not only benefit the companies involved, they tend to be a win for customers too.

Brent Leary, founder at CRM Essentials sees this as a deal between two rising SaaS stars, and one that benefits both companies. “Everyone and their mother is announcing partnerships with Zoom, focusing on integrating video communications into core focus areas. But this partnership looks to be much more substantial than most with ServiceNow not only partnering with Zoom for tighter video communication capabilities, but also displacing its current phone system with Zoom Phone,” Leary told TechCrunch.


By Ron Miller

Ampere announces latest chip with a 128 core processor

In the chip game, more is usually better and to that end, Ampere announced the next chip on its product roadmap today, the Altra Max, a 128 core processor, the company says is designed specifically to handle cloud native, containerized workloads.

What’s more, the company has designed the chip, so that it will fit in the same slot as their 80 core product announced last year (and in production now). That means that engineers can use the same slot when designing for the new chip, which saves engineering time and eases production, says Jeff Wittich, vp of products at the company,

Wittich says that his company is working with manufacturers today to make sure they can build for all of the requirements for the more powerful chip. “The reason we’re talking about it now, versus waiting until Q4 when we’ve got samples going out the door is because it’s socket compatible, so the same platforms that the Altra 80 core go into, this 128 core product can go into,” he said.

He says that containerized workloads, video encoding, large scale out databases and machine learning inference will all benefit from having these additional cores.

While he wouldn’t comment on any additional funding, the company has raised $40 million, according to Crunchbase data, and Wittich says they have enough funding to to into high-volume production later this year on their existing products.

Like everyone, the company has faced challenges keeping a consistent supply chain throughout the pandemic, but when it started to hit in Asia at the beginning of this year, the company set a plan in motion to find backup suppliers for the parts they would need should they run into pandemic-related shortages. He says that it took a lot of work, planning and coordination, but they feel confident at this point in being able to deliver their products in spite of the uncertainty that exists.

“Back in January we actually already went through [our list of suppliers], and we diversified our supply chain and made sure that we had options for everything. So we were able to get in front of that before it ever became a problem,” he said.

“We’ve had normal kinds of hiccups here and there that everyone’s had in the supply chain, where things get stuck in shipping and they end up a little bit late, but we’re right on schedule with where we were.”

The company is already planning ahead for its 2022 release, which is already in development.
“We’ve got a test chip running through five nanometer right now that has the key IP and some of the key features of that product, so that we can start testing those out in silicon pretty soon,” he said.

Finally, the company announced that it’s working with some new partners including Cloudflare, Packet (which was acquired by Equinix in January) Scaleway and Phoenics Electronics, a division of Avnet. These partnerships provide another way for Ampere to expand its market as it continues to develop.

The company was founded in 2017 by former Intel president Renee James.


By Ron Miller

Nanox, maker of a low-cost scanning service to replace X-rays, expands Series B to $51M

A lot of the attention in medical technology today has been focused on tools and innovations that might help the world better fight the COVID-19 global health pandemic. Today comes news of another startup that is taking on some funding for a disruptive innovation that has the potential to make both COVID-19 as well as other kinds of clinical assessments more accessible.

Nanox, a startup out of Israel that has developed a small, low-cost scanning system and “medical screening as a service” to replace the costly and large machines and corresponding software typically used for X-rays, CAT scans, PET scans and other body imaging services, is today announcing that it has raised $20 million from a strategic investor, South Korean carrier SK Telecom.

SK Telecom in turn plans to help distribute physical scanners equipped with Nanox technology as well as resell the pay-per-scan imaging service, branded Nanox.Cloud, and corresponding 5G wireless network capacity to operate them. Nanox currently licenses its tech to big names in the imaging space like FujiFilm, and Foxconn is also manufacturing its donut-shaped Nanox.Arc scanners.

The funding is technically an extension of Nanox’s previous round, which was announced earlier this year at $26 million with backing from Foxconn, FujiFilm and more. Nanox says that the full round is now closed off at $51 million, with the company having raised $80 million since launching almost a decade ago, in 2011.

Nanox’s valuation is not being publicly disclosed, a but a news report in the Israeli press from December said that one option the startup was considering was an IPO at a $500 million valuation. We understand from sources that the valuation is about $100 million higher now.

The Nanox system is based around proprietary technology related to digital X-rays. Digital radiography is a relatively new area in the world of imaging that relies on digital scans rather than X-ray plates to capture and process images.

Nanox says the ARC comes in at 70 kg versus 2,000 kg for the average CT scanner, and production costs are around $10,000 compared to $1-3 million for the CT scanner.

But in addition to being smaller (and thus cheaper) machines with much of the processing of images done in the cloud, the Nanox system, according to CEO and founder Ran Poliakine, can make its images in a tiny fraction of a second, making them significantly safer in terms of radiation exposure compared to existing methods.

Imaging has been in the news a lot of late because it has so far been one of the most accurate methods for detecting the progress of COVID-19 in patients or would-be patients in terms of how it is affecting patients’ lungs and other organs. While the dissemination of equipment like Nanox’s definitely could play a role in handling those cases better, the ultimate goal of the startup is much wider than that.

Ultimately, the company hopes to make its devices and cloud-based scanning service ubiquitous enough that it would be possible to run early detection, preventative scans for a much wider proportion of the population.

“What is the best way to fight cancer today? Early detection. But with two-thirds of the world without access to imaging, you may need to wait weeks and months for those scans today,” said Poliakine.

The startup’s mission is to distribute some 15,000 of its machines over the next several years to bridge that gap, and it’s getting there through partnerships. In addition to the SK Telecom deal it’s announcing today, last March, Nanox inked a $174 million deal to distribute 1,000 machines across Australia, New Zealand and Norway in partnership with a company called the Gateway Group.

The SK Telecom investment is an interesting development that underscores how carriers see 5G as an opportunity to revisit what kinds of services they resell and offer to businesses and individuals, and SK Telecom specifically has singled out healthcare as one obvious and big opportunity.

“Telecoms carriers are looking for opportunities around how to sell 5G,” said Ilung Kim, SK Telecom’s president, in an interview. “Now you can imagine a scanner of this size being used in an ambulance, using 5G data. It’s a game changer for the industry.”

Looking ahead, Nanox will continue to ink partnerships for distributing its hardware and reselling its cloud-based services for processing the scans, but Poliakine said it does not plan to develop its own  technology beyond that to gain insights from the raw data. For that, it’s working with third parties — currently three AI companies – that plug into its APIs, and it plans to add more to the ecosystem over time.


By Ingrid Lunden

Scandit raises $80M as COVID-19 drives demand for contactless deliveries

Enterprise barcode scanner company Scandit has closed an $80 million Series C round, led by Silicon Valley VC firm G2VP. Atomico, GV, Kreos, NGP Capital, Salesforce Ventures and Swisscom Ventures also participated in the round — which brings its total raised to date to $123M.

The Zurich-based firm offers a platform that combines computer vision and machine learning tech with barcode scanning, text recognition (OCR), object recognition and augmented reality which is designed for any camera-equipped smart device — from smartphones to drones, wearables (e.g. AR glasses for warehouse workers) and even robots.

Use-cases include mobile apps or websites for mobile shopping; self checkout; inventory management; proof of delivery; asset tracking and maintenance — including in healthcare where its tech can be used to power the scanning of patient IDs, samples, medication and supplies.

It bills its software as “unmatched” in terms of speed and accuracy, as well as the ability to scan in bad light; at any angle; and with damaged labels. Target industries include retail, healthcare, industrial/manufacturing, travel, transport & logistics and more.

The latest funding injection follows a $30M Series B round back in 2018. Since then Scandit says it’s tripled recurring revenues, more than doubling the number of blue-chip enterprise customers, and doubling the size of its global team.

Global customers for its tech include the likes of 7-Eleven, Alaska Airlines, Carrefour, DPD, FedEx, Instacart, Johns Hopkins Hospital, La Poste, Levi Strauss & Co, Mount Sinai Hospital and Toyota — with the company touting “tens of billions of scans” per year on 100+ million active devices at this stage of its business.

It says the new funding will go on further pressing on the gas to grow in new markets, including APAC and Latin America, as well as building out its footprint and ops in North America and Europe. Also on the slate: Funding more R&D to devise new ways for enterprises to transform their core business processes using computer vision and AR.

The need for social distancing during the coronavirus pandemic has also accelerated demand for mobile computer vision on personal smart devices, according to Scandit, which says customers are looking for ways to enable more contactless interactions.

Another demand spike it’s seeing is coming from the pandemic-related boom in ‘Click & Collect’ retail and “millions” of extra home deliveries — something its tech is well positioned to cater to because its scanning apps support BYOD (bring your own device), rather than requiring proprietary hardware.

“COVID-19 has shone a spotlight on the need for rapid digital transformation in these uncertain times, and the need to blend the physical and digital plays a crucial role,” said CEO Samuel Mueller in a statement. “Our new funding makes it possible for us to help even more enterprises to quickly adapt to the new demand for ‘contactless business’, and be better positioned to succeed, whatever the new normal is.”

Also commenting on the funding in a supporting statement, Ben Kortlang, general partner at G2VP, added: “Scandit’s platform puts an enterprise-grade scanning solution in the pocket of every employee and customer without requiring legacy hardware. This bridge between the physical and digital worlds will be increasingly critical as the world accelerates its shift to online purchasing and delivery, distributed supply chains and cashierless retail.”


By Natasha Lomas

VAST Data lands $100M Series C on $1.2B valuation to turn storage on its head

VAST Data, a startup that has come up with a cost-effective way to deliver flash storage, announced a $100 million Series C investment today on a $1.2 billion valuation, both unusually big numbers for an enterprise startup in Series C territory.

Next47, the investment arm of Siemens, led the round with participation from existing investors 83North, Commonfund Capital, Dell Technologies Capital, Goldman Sachs, Greenfield Partners, Mellanox Capital and Norwest Venture Partners. Today’s investment brings the total raised to $180 million.

That’s a lot of cash any time, but especially in the middle of a pandemic. Investors believe that VAST is solving a difficult problem around scaled storage. It’s one where customers tend to deal with petabytes of data and storage price tags beginning at a million dollars, says company founder and CEO Renen Hallak.

As Hallak points out, traditional storage is delivered in tiers with fast, high-cost flash storage at the top of the pyramid all the way down to low-cost archival storage at the bottom. He sees this approach as flawed, especially for modern applications driven by analytics and machine learning that rely on lots of data being at the ready.

VAST built a system they believe addresses these issues around the way storage has traditionally been delivered.”We build a single system. This as fast or faster than your tier one, all-flash system today and as cost effective, or more so, than your lowest tier five hard drives. We do this at scale with the resilience of the entire [traditional storage] pyramid. We make it very, very easy to use, while breaking historical storage trade-offs to enable this next generation of applications,” Hallak told TechCrunch.

The company, which was founded in 2016 and came to market with its first solution in 2018, does this by taking advantage of some modern tools like Intel 3D XPoint technology, a kind of modern non-volatile memory along with consumer-grade QLT flash, NVMe over Fabrics protocol and containerization.

“This new architecture, coupled with a lot of algorithmic work in software and types of metadata structures that we’ve developed on top of it, allows us to break those trade-offs and allows us to make much more efficient use of media, and also allows us to move beyond scalability limits, resiliency limits and problems that other systems have in terms of usability and maintainability,” he said.

They have a large average deal size; as a result, the company can keep its cost of sales and marketing to revenue ratio low. They intend to use the money to grow quickly, which is saying something in the current economic climate.

But Hallak sees vast opportunity for the kinds of companies with large amounts of data who need this kind of solution, and even though the cost is high, he says ultimately switching to VAST should save companies money, something they are always looking to do at this kind of scale, but even more so right now.

You don’t often see a unicorn valuation at Series C, especially right now, but Hallak doesn’t shy away from it at all. “I think it’s an indication of the trust that our investors put in our growth and our success. I think it’s also an indication of our very fast growth in our first year [with a product on the market], and the unprecedented adoption is an indication of the product-market fit that we have, and also of our market efficiency,” he said.

They count The National Institute of Health, General Dynamics and Zebra as customers.


By Ron Miller

To make locks touchless, Proxy bluetooth ID raises $42M

We need to go hands-off in the age of coronavirus. That means touching fewer doors, elevators, and sign-in iPads. But once a building is using phone-based identity for security, there’s opportunities to speed up access to WIFI networks and printers, or personalize conference rooms and video call set-ups. Keyless office entry startup Proxy wants to deliver all of this while keeping your phone in your pocket.

The door is just a starting point” Proxy co-founder and CEO Denis Mars tells me. “We’re . . . empowering a movement to take back control of our privacy, our sense of self, our humanity, our individuality.”

With the contagion concerns and security risks of people rubbing dirty, cloneable, stealable key cards against their office doors, investors see big potential in Proxy. Today it’s announcing here a $42 million Series B led by Scale Venture Partners with participation from former funders Kleiner Perkins and Y Combinator plus new additions Silicon Valley Bank and West Ventures.

The raise brings Proxy to $58.8 million in funding so it can staff up at offices across the world and speed up deployments of its door sensor hardware and access control software. “We’re spread thin” says Mars. “Part of this funding is to try to grow up as quickly as possible and not grow for growth sake. We’re making sure we’re secure, meeting all the privacy requirements.”

How does Proxy work? Employers get their staff to install an app that knows their identity within the company, including when and where they’re allowed entry. Buildings install Proxy’s signal readers, which can either integrate with existing access control software or the startup’s own management dashboard.

Employees can then open doors, elevators, turnstiles, and garages with a Bluetooth low-energy signal without having to even take their phone out. Bosses can also opt to require a facial scan or fingerprint or a wave of the phone near the sensor. Existing keycards and fobs still work with Proxy’s Pro readers. Proxy costs about $300 to $350 per reader, plus installation and a $30 per month per reader subscription to its management software.

Now the company is expanding access to devices once you’re already in the building thanks to its SDK and APIs. Wifi router-makers are starting to pre-provision their hardware to automatically connect the phones of employees or temporarily allow registered guests with Proxy installed — no need for passwords written on whiteboards. Its new Nano sensors can also be hooked up to printers and vending machines to verify access or charge expense accounts. And food delivery companies can add the Proxy SDK so couriers can be granted the momentary ability to open doors when they arrive with lunch.

Rather than just indiscriminately beaming your identity out into the world, Proxy uses tokenized credentials so only its sensors know who you are. Users have to approve of new networks’ ability to read their tokens, Proxy has SOC-2 security audit certification, and complies with GDPR. “We feel very strongly about where the biometrics are stored . . . they should stay on your phone” says Mars.

Yet despite integrating with the technology for two-factor entry unlocks, Mars says “We’re not big fans of facial recognition. You don’t want every random company having your face in their database. The face becomes the password you were supposed to change every 30 days.”

Keeping your data and identity safe as we see an explosion of Internet Of Things devices was actually the impetus for starting Proxy. Mars had sold his teleconferencing startup Bitplay to Jive Software where he met his eventually co-founder Simon Ratner, who’d joined after his video annotation startup  Omnisio was acquired by YouTube. Mars was frustrated about every IoT lightbulb and appliance wanting him to download an app, set up a profile, and give it his data.

The duo founded Proxy in 2013 as a universal identity signal. Today it has over 60 customers. While other apps want you to constantly open them, Proxy’s purpose is to work silently in the background and make people more productive. “We believe the most important technologies in the world don’t seek your attention. They work for you, they empower you, and they get out of the way so you can focus your attention on what matters most — living your life.”

Now Proxy could actually help save lives. “The nature of our product is contactless interactions in commercial buildings and workplaces so there’s a bit of an unintended benefit that helps prevent the spread of the virus” Mars explains. “We have seen an uptick in customers starting to set doors and other experiences in longer-range hands-free mode so that users can walk up to an automated door and not have to touch the handles or badge/reader every time.”

The big challenge facing Proxy is maintaining security and dependability since it’s a mission-critical business. A bug or outage could potentially lock employees out of their workplace (when they eventually return from quarantine). It will have to keep hackers out of employee files. Proxy needs to stay ahead of access control incumbents like ADT and Honeywell as well as smaller direct competitors like $10 million-funded Nexkey and $28 million-funded Openpath.

Luckily, Proxy has found a powerful growth flywheel. First an office in a big building gets set up, then they convince the real estate manager to equip the lobby’s turnstiles and elevators with Proxy. Other tenants in the building start to use it, so they buy Proxy for their office. Then they get their offices in other cities on board…starting the flywheel again. That’s why Proxy is doubling down on sales to commercial real estate owners.

The question is when Proxy will start knocking on consumers’ doors. While leveling up into the enterprise access control software business might be tough for home smartlock companies like August, Proxy could go down market if it built more physical lock hardware. Perhaps we’ll start to get smart homes that know who’s home, and stop having to carry pointy metal sticks in our pockets.


By Josh Constine

HP offers its investors billions in shareholder returns to avoid a Xerox tie-up

To ward off a hostile takeover bid by Xerox, which is a much smaller company, HP (not to be confused with Hewlett Packard Enterprise, a separate public company) is promising its investors billions and billions of dollars.

All investors have to do to get the goods is reject the Xerox deal.

In a letter to investors, HP called Xerox’s offer a “flawed value exchange” that would lead to an “irresponsible capital structure” that was being sold on “overstated synergies.” Here’s what HP is promising its owners if they do allow it to stay independent:

  • About $16 billion worth of “capital return” between its fiscal 2020 and fiscal 2022 (HP’s Q1 fiscal 2020 wrapped January 31, 2020, for reference). According to the company, the figure “represents approximately 50% of HP’s current market capitalization.” TechCrunch rates that as true, before the company’s share-price gains posted after this news became known.
  • That capital return would be made up of a few things, including boosting the company’s share repurchase program to $15 billion (up from $5 billion, previously). More specifically, HP intends to “repurchase of at least $8 billion of HP shares over 12 months” after its fiscal 2020 meeting. The company also intends to raise its “target long-term return of capital to 100% of free cash flow generation,” allowing for the share purchases and a rising dividend payout (“HP intends to maintain dividend per share growth at least in line with earnings.”)

If all that read like a foreign language, let’s untangle it a bit. What HP is telling investors is that it intends to use all of the cash it generates to reward their ownership of shares in its business. This will come in the form of buybacks (concentrating future earnings on fewer shares, raising the value of held equity) and dividends (rising payouts to owners as HP itself makes more money), powered in part by cost-cutting (boosting cash generation and profitability).

HP is saying, in effect: Please do not sell us to Xerox; if you do not, we will do all that we can to make you money. 

Shares of HP are up 6% as of the time of writing, raising the value of HP’s consumer-focused spinout to just under $34 billion. We’ll see what investors choose for the company. But now, how did we get here?

The road to today

You may ask yourself, how did we get here (to paraphrase Talking Heads). It all began last Fall when Xerox made it known that it wanted to merge with HP, offering in the range of $27 billion to buy the much larger company. As we wrote at the time:

What’s odd about this particular deal is that HP is the company with a much larger market cap of $29 billion, while Xerox is just a tad over $8 billion. The canary is eating the cat here.

HP never liked the idea of the hostile takeover attempt and the gloves quickly came off as the two companies wrangled publicly with one another, culminating with HP’s board unanimously rejecting Xerox’s offer. It called the financial underpinnings of the deal “highly conditional and uncertain.” HP also was unhappy with the aggressive nature of the offer, writing that Xerox was, “intent on forcing a potential combination on opportunistic terms and without providing adequate information.”

Just one day later, Xerox responded, saying it would take the bid directly to HP shareholders in an attempt to by-pass the board of directors, writing in yet another public letter, “We plan to engage directly with HP shareholders to solicit their support in urging the HP Board to do the right thing and pursue this compelling opportunity.”

In January, the shenanigans continued when Xerox announced it was putting forth a friendly slate of candidates for the HP board to replace the ones that had rejected the earlier Xerox offer. And more recently, in an attempt to convince shareholders to vote in favor of the deal, Xerox sweetened the deal to $34 billion or $24 a share.

Xerox wrote that it had on-going conversations with large HP shareholders, and this might have gotten HP’s attention— hence the most recent offer on its part to make an offer to shareholders that would be hard to refuse. The company’s next shareholder meeting is taking place on April 1, 2020, and it won’t be an April Fool’s joke when we find out the final reckoning.

 


By Alex Wilhelm

Nomagic, a startup out of Poland, picks up $8.6M for its pick-and-place warehouse robots

Factories and warehouses have been two of the biggest markets for robots in the last several years, with machines taking on mundane, if limited, processes to speed up work and free up humans to do other, more complex tasks. Now, a startup out of Poland that is widening the scope of what those robots can do is announcing funding, a sign not just of how robotic technology has been evolving, but of the growing demand for more automation, specifically in the world of logistics and fulfilment.

Nomagic, which has developed way for a robotic arm to identify an item from an unordered selection, pick it up and then pack it into a box, is today announcing that it has raised $8.6 million in funding, one of the largest-ever seed rounds for a Polish startup. Co-led by Khosla Ventures and Hoxton Ventures, the round also included participation from DN Capital, Capnamic Ventures and Manta Ray, all previous backers of Nomagic.

There are a number of robotic arms on the market today that can be programmed to pick up and deposit items from Point A to Point B. But we are only starting to see a new wave of companies focus on bringing these to fulfilment environments because of the limitations of those arms: they can only work when the items are already “ordered” in a predictable way, such as on an assembly line, which has mean that fulfilment of, for example, online orders is usually carried out by humans.

Nomagic has incorporated a new degree of computer vision, machine learning and other AI-based technologies to  elevate the capabilities of those robotic arm. Robots powered by its tech can successfully select items from an “unstructured” group of objects — that is, not an assembly line, but potentially another box — before picking it up and placing it elsewhere.

Kacper Nowicki, the ex-Googler CEO of Nomagic who co-founded the company with Marek Cygan (formerly of Climate Corporation) and Tristan d’Orgeval (an academic), noted that while there has been some work on the problem of unstructured objects and industrial robots — in the US, there are some live implementations taking shape, with one, Covariant, recently exiting stealth mode — it has been mostly a “missing piece” in terms of the innovation that has been done to make logistics and fulfilment more efficient.

That is to say, there has been little in the way of bigger commercial roll outs of the technology, creating an opportunity in what is a huge market: fulfilment services are projected to be a $56 billion market by 2021 (currently the US is the biggest single region, estimated at between $13.5 billion and $15.5 billion).

“If every product were a tablet or phone, you could automate a regular robotic arm to pick and pack,” Nowicki said. “But if you have something else, say something in plastic, or a really huge diversity of products, then that is where the problems come in.”

Nowicki was a longtime Googler who moved from Silicon Valley back to Poland to build the company’s first engineering team in the country. In his years at Google, Nowicki worked in areas including Google Cloud and search, but also saw the AI developments underway at Google’s DeepMind subsidiary, and decided he wanted to tackle a new problem for his next challenge.

His interest underscores what has been something of a fork in artificial intelligence in recent years. While some of the earliest implementations of the principles of AI were indeed on robots, these days a lot of robotic hardware seems clunky and even outmoded, while much more of the focus of AI has shifted to software and “non-physical” systems aimed at replicating and improving upon human thought. Even the word “robot” is now just as likely to be seen in the phrase “robotic process automation”, which in fact has nothing to do with physical robots, but software.

“A lot of AI applications are not that appealing,” Nowicki simply noted (indeed, while Nowicki didn’t spell it out, DeepMind in particular has faced a lot of controversy over its own work in areas like healthcare). “But improvements in existing robotics systems by applying machine learning and computer vision so that they can operate in unstructured environments caught my attention. There has been so little automation actually in physical systems, and I believe it’s a place where we still will see a lot of change.”

Interestingly, while the company is focusing on hardware, it’s not actually building hardware per se, but is working on software that can run on the most popular robotic arms in the market today to make them “smarter”.

“We believe that most of the intellectual property in in AI is in the software stack, not the hardware,” said Orgeval. “We look at it as a mechatronics problem, but even there, we believe that this is mainly a software problem.”

Having Khosla as a backer is notable given that a very large part of the VC’s prolific investing has been in North America up to now. Nowicki said he had a connection to the firm by way of his time in the Bay Area, where before Google, Vinod Khosla backed a startup of his (which went bust in one of the dot-com downturns).

While there is an opportunity for Nomagic to take its idea global, for now Khosla’s interested because of the a closer opportunity at home, where Nomagic is already working with third-party logistics and fulfilment providers, as well as retailers like Cdiscount, a French Amazon-style, soup-to-nuts online marketplace.

“The Nomagic team has made significant strides since its founding in 2017,” says Sven Strohband, Managing Director of Khosla Ventures, in a statement. “There’s a massive opportunity within the European market for warehouse robotics and automation, and NoMagic is well-positioned to capture some of that market share.”

WARSAW, POLAND – Feb 4, 2020 – Nomagic, provider of smart pick & place robots for warehouses, announced today the closing of a $8.6 million Seed investment round led by Khosla Ventures. The round is one of the biggest seed rounds for a Polish startup yet. Hoxton Ventures (London) co-led the round with existing investors DN Capital (London), Capnamic Ventures (Cologne) and Manta Ray (London).

“The Nomagic team has made significant strides since its founding in 2017,” says Sven Strohband, Managing Director of Khosla Ventures. “There’s a massive opportunity within the European market for warehouse robotics and automation, and NoMagic is well-positioned to capture some of that market share.”

Founded on the premise that order fulfillment in warehouses requires repetitive manual tasks for which it is harder and harder to find operators, Nomagic develops AI-based solutions using robotic arms to reliably pick and place millions of different products. Their smart robots are able to determine how to pick never seen products and detect rare anomalies such as robots picking two items at once. In 2019, Nomagic deployed its solution at Cdiscount, the leading French e-commerce platform, to build the first fully automated packing line for e-commerce.


By Ingrid Lunden

The Cerebras CS-1 computes deep learning AI problems by being bigger, bigger, and bigger than any other chip

Deep learning is all the rage these days in enterprise circles, and it isn’t hard to understand why. Whether it is optimizing ad spend, finding new drugs to cure cancer, or just offering better, more intelligent products to customers, machine learning — and particularly deep learning models — have the potential to massively improve a range of products and applications.

The key word though is ‘potential.’ While we have heard oodles of words sprayed across enterprise conferences the last few years about deep learning, there remain huge roadblocks to making these techniques widely available. Deep learning models are highly networked, with dense graphs of nodes that don’t “fit” well with the traditional ways computers process information. Plus, holding all of the information required for a deep learning model can take petabytes of storage and racks upon racks of processors in order to be usable.

There are lots of approaches underway right now to solve this next-generation compute problem, and Cerebras has to be among the most interesting.

As we talked about in August with the announcement of the company’s “Wafer Scale Engine” — the world’s largest silicon chip according to the company — Cerebras’ theory is that the way forward for deep learning is to essentially just get the entire machine learning model to fit on one massive chip. And so the company aimed to go big — really big.

Today, the company announced the launch of its end-user compute product, the Cerebras CS-1, and also announced its first customer of Argonne National Laboratory.

The CS-1 is a “complete solution” product designed to be added to a data center to handle AI workflows. It includes the Wafer Scale Engine (or WSE, i.e. the actual processing core) plus all the cooling, networking, storage, and other equipment required to operate and integrate the processor into the data center. It’s 26.25 inches tall (15 rack units), and includes 400,000 processing cores, 18 gigabytes of on-chip memory, 9 petabytes per second of on-die memory bandwidth, 12 gigabit ethernet connections to move data in and out of the CS-1 system, and sucks just 20 kilowatts of power.

A cross-section look at the CS-1. Photo via Cerebras

Cerebras claims that the CS-1 delivers the performance of more than 1,000 leading GPUs combined — a claim that TechCrunch hasn’t verified, although we are intently waiting for industry-standard benchmarks in the coming months when testers get their hands on these units.

In addition to the hardware itself, Cerebras also announced the release of a comprehensive software platform that allows developers to use popular ML libraries like TensorFlow and PyTorch to integrate their AI workflows with the CS-1 system.

In designing the system, CEO and co-founder Andrew Feldman said that “We’ve talked to more than 100 customers over the past year and a bit,“ in order to determine the needs for a new AI system and the software layer that should go on top of it. “What we’ve learned over the years is that you want to meet the software community where they are rather than asking them to move to you.”

I asked Feldman why the company was rebuilding so much of the hardware to power their system, rather than using already existing components. “If you were to build a Ferrari engine and put it in a Toyota, you cannot make a race car,” Feldman analogized. “Putting fast chips in Dell or [other] servers does not make fast compute. What it does is it moves the bottleneck.” Feldman explained that the CS-1 was meant to take the underlying WSE chip and give it the infrastructure required to allow it to perform to its full capability.

A diagram of the Cerebras CS-1 cooling system. Photo via Cerebras.

That infrastructure includes a high-performance water cooling system to keep this massive chip and platform operating at the right temperatures. I asked Feldman why Cerebras chose water, given that water cooling has traditionally been complicated in the data center. He said, “We looked at other technologies — freon. We looked at immersive solutions, we looked at phase-change solutions. And what we found was that water is extraordinary at moving heat.”

A side view of the CS-1 with its water and air cooling systems visible. Photo via Cerebras.

Why then make such a massive chip, which as we discussed back in August, has huge engineering requirements to operate compared to smaller chips that have better yield from wafers. Feldman said that “ it massively reduces communication time by using locality.”

In computer science, locality is placing data and compute in the right places within, let’s say a cloud, that minimizes delays and processing friction. By having a chip that can theoretically host an entire ML model on it, there’s no need for data to flow through multiple storage clusters or ethernet cables — everything that the chip needs to work with is available almost immediately.

According to a statement from Cerebras and Argonne National Laboratory, Cerebras is helping to power research in “cancer, traumatic brain injury and many other areas important to society today” at the lab. Feldman said that “It was very satisfying that right away customers were using this for things that are important and not for 17-year-old girls to find each other on Instagram or some shit like that.”

(Of course, one hopes that cancer research pays as well as influencer marketing when it comes to the value of deep learning models).

Cerebras itself has grown rapidly, reaching 181 engineers today according to the company. Feldman says that the company is hands down on customer sales and additional product development.

It has certainly been a busy time for startups in the next-generation artificial intelligence workflow space. Graphcore just announced this weekend that it was being installed in Microsoft’s Azure cloud, while I covered the funding of NUVIA, a startup led by the former lead chip designers from Apple who hope to apply their mobile backgrounds to solve the extreme power requirements these AI chips force on data centers.

Expect ever more announcements and activity in this space as deep learning continues to find new adherents in the enterprise.


By Danny Crichton