Samsung to invest $205B in semiconductor, biopharma and telco units by 2023, creating 40,000 jobs

Samsung Group, South Korea’s tech giant, announced on Tuesday that it will invest $205 billion (240 trillion won) in their semiconductor, biopharmaceuticals and telecommunications units over the next three years to enhance its global presence and lead in new industries such as next-generation telecommunication and robotics.

The investment will be led by Samsung affiliates including Samsung Electronics and Samsung Biologics. It also unveiled mergers and acquisitions plan to fortify its technology and market leadership.

With setting aside $154.3 billion (180 trillion won) for home ground, Samsung expects to create 40,000 new jobs by 2023 through the investment.

This announcement comes days after Samsung Electronics vice chairman Jay Y. Lee was released on parole on 13 August right before South Korea’s Liberation Day. People speculated Samsung would be able to move forward with major investment once he was freed from prison, according to local media reports.

Samsung’s latest investment will be used for semiconductor, biopharmaceuticals and the next-generation telco units, according to the company’s statement.

Samsung Electronics plans to develop advanced process technology and expand the business with artificial intelligence (AI) and data centers for its system semiconductors while it will focus on up-to-date technology such as EUV-based sub14-nanometer DRAM and over 200-layer V-NAND products for the memory business. Samsung had announced in May the company will invest $151 billion in its logic chip and foundry sector, to be the top logic chip maker, by 2030.

Samsung Biologics and Samsung Bioepis plans to establish additional two new plants, in addition to a fourth factory that is under construction, for expanding the contract development manufacturing organization (CDMO) business, the statement said.

South Korea’s largest conglomerate also will support its ongoing R&D in new technologies and emerging application in areas such as AI and robotics along with the next generation OLED, quantum-dot display and high-energy density batteries development.


By Kate Park

German Bionic raises $20M led by Samsung for exoskeleton tech to supercharge human labor

Exoskeleton technology has been one of the more interesting developments in the world of robotics: instead of building machines that replace humans altogether, build hardware that humans can wear to supercharge their abilities. Today, German Bionic, one of the startups designing exoskeletons specifically aimed at industrial and physical applications — it describes its Cray X robot as “the world’s first connected exoskeleton for industrial use,” that is, to help people lifting and working with heavy objects with more power, precision and safety — is announcing a funding round that underscores the opportunity ahead.

The Augsburg, Germany-based company has raised $20 million, funding that it plans to use to continue building out its business, as well as its technology, both in terms of the hardware and the cloud-based software platform, German Bionic IO, that works with the exoskeletons to optimize them and help them “learn” to work better.

The Cray X currently can compensate up to 30 kg for each lifting movement, the company says.

“With our groundbreaking robotic technology that combines human work with the industrial Internet of Things (IIoT), we literally strengthen the shop floor workers’ backs in an immediate and sustainable way. Measurable data underscores that this ultimately increases productivity and the efficiency of the work done,” says Armin G. Schmidt, CEO of German Bionic, in a statement. “The market for smart human-machine systems is huge and we are now perfectly positioned to take a major share and substantially improve numerous working lives.”

The Series A is being co-led by Samsung Catalyst Fund, a strategic investment arm from the hardware giant, and German investor MIG AG, one of the original backers of BioNtech, the breakthrough company that’s developed the first Covid-19 vaccine to be rolled out globally.

Storm Ventures, Benhamou Global Ventures (founded and led by Eric Benhamou, who was the founding CEO of Palm and before that the CEO of 3com), and IT Farm all also participated. Previously, German Bionic had only raised $3.5 million in seed funding (with IT Farm, Atlantic Labs, and individual investors participating).

German Bionic’s rise comes at an interesting moment in terms of how automation and cloud technology are sweeping the world of work. When people talk about the next generation of industrial work, the focus is usually on more automation and the rise of robots to replace humans in different stages of production.

But at the same time, some robotics technologists have worked on another idea. Since we’re still probably still a long way away unable to make robots that are just like humans but better in terms of cognition and all movements, instead, create hardware that doesn’t replace, but augments, live laborers, to help make them stronger while still being able to retain the reliable and fine-tuned expertise of those humans.

The argument for more automation in industrial settings has taken on a more pointed urgency in recent times, with the rise of the Covid-19 global health pandemic: factories have been one of the focus points for outbreaks, and the tendency has been to reduce physical contact and proximity to reduce the spread of the virus.

Exoskeletons don’t really address that aspect of Covid-19 — even if you might require less of them as a result of using exoskeletons, you still require humans to wear them, after all — but the general focus that automation has had has brought more attention to the opportunity of using them.

And in any case, even putting the pandemic to one side, we are still a long way away from cost-effective robots that completely replace humans in all situations. So, as we roll out vaccinations and develop a better understanding of how the virus operates, this still means a strong market for the exoskeleton concept, which analysts (quoted by German Bionic) predict could be worth as much as $20 billion by 2030.

In that context, it’s interesting to consider Samsung as an investor: the company itself, as one of the world’s leading consumer electronics and industrial electronics providers, is a manufacturing powerhouse in its own right. But it also makes equipment for others to use in their industrial work, both as a direct brand and through subsidiaries like Harman. It’s not clear which of these use cases interests Samsung: whether to use the Cray X in its own manufacturing and logistics work, or whether to become a strategic partner in manufacturing these for others. It could easily be both.

“We are pleased to support German Bionic in its continued development of world-leading exoskeleton technology,” says Young Sohn, Corporate President and Chief Strategy Officer for Samsung Electronics and Chairman of the Board, Harman, in a statement. “Exoskeleton technologies have great promise in enhancing human’s health, wellbeing and productivity. We believe that it can be a transformative technology with mass market potential.”

German Bionic describes its Cray X as a “self-learning power suit” aimed primarily at reinforcing lifting movements and to safeguard the wearer from making bad calls that could cause injuries. That could apply both to those in factories, or those in warehouses, or even sole trader mechanics working in your local garage. The company is not disclosing a list of customers, except to note that it includes, in the words of a spokesperson, “a big logistics player, industrial producers and infrastructure hubs.” One of these, the Stuttgart Airport, is highlighted on its site.  

“Previously, efficiency gains and health promotion in manual labor were often at odds with one another. German Bionic Systems managed to not only break through this paradigm, but also to make manual labor a part of the digital transformation and elegantly integrate it into the smart factory,” says Michael Motschmann, managing partner with MIG in a statement. “We see immense potential with the company and are particularly happy to be working together with a first-class team of experienced entrepreneurs and engineers.”

Exoskeletons as a concept have been around for over a decade already — MIT developed its first exoskeleton, aimed to help soldiers carrying heavy loads — back in 2007, but advancements in cloud computing, smaller processors for the hardware itself, and artificial intelligence have really opened up the idea of where and how these might augment humans. In addition to industry, some of the other applications have included helping people with knee injuries (or looking to avoid knee injuries!) ski better, and for medical purposes, although the recent pandemic has put a strain on some of these use cases, leading to indefinite pauses in production.


By Ingrid Lunden

Industrial drone maker Percepto raises $45M and integrates with Boston Dynamics’ Spot

Consumer drones have over the years struggled with an image of being no more than expensive and delicate toys. But applications in industrial, military and enterprise scenarios have shown that there is indeed a market for unmanned aerial vehicles, and today, a startup that makes drones for some of those latter purposes is announcing a large round of funding and a partnership that provides a picture of how the drone industry will look in years to come.

Percepto, which makes drones — both the hardware and software — to monitor and analyze industrial sites and other physical work areas largely unattended by people, has raised $45 million in a Series B round of funding.

Alongside this, it is now working with Boston Dynamics  and has integrated its Spot robots with Percepto’s Sparrow drones, with the aim being better infrastructure assessments, and potentially more as Spot’s agility improves.

The funding is being led by a strategic backer, Koch Disruptive Technologies, the investment arm of industrial giant Koch Industries (which has interests in energy, minerals, chemicals and related areas), with participation also from new investors State of Mind Ventures, Atento Capital, Summit Peak Investments, Delek-US. Previous investors U.S. Venture Partners, Spider Capital and Arkin Holdings also participated. (It appears that Boston Dynamics and SoftBank are not part of this investment.)

Israel-based Percepto has now raised $72.5 million since it was founded in 2014, and it’s not disclosing its valuation, but CEO and founder Dor Abuhasira described as “a very good round.”

“It gives us the ability to create a category leader,” Abuhasira said in an interview. It has customers in around 10 countries, with the list including ENEL, Florida Power and Light and Verizon.

While some drone makers have focused on building hardware, and others are working specifically on the analytics, computer vision and other critical technology that needs to be in place on the software side for drones to work correctly and safely, Percepto has taken what I referred to, and Abuhasira confirmed, as the “Apple approach”: vertical integration as far as Percepto can take it on its own.

That has included hiring teams with specializations in AI, computer vision, navigation and analytics as well as those strong in industrial hardware — all strong areas in the Israel tech landscape, by virtue of it being so closely tied with its military investments. (Note: Percepto does not make its own chips: these are currently acquired from Nvidia, he confirmed to me.)

“The Apple approach is the only one that works in drones,” he said. “That’s because it is all still too complicated. For those offering an Android-style approach, there are cracks in the complete flow.”

It presents the product as a “drone-in-a-box”, which means in part that those buying it have little work to do to set it up to work, but also refers to how it works: its drones leave the box to make a flight to collect data, and then return to the box to recharge and transfer more information, alongside the data that is picked up in real time.

The drones themselves operate on an on-demand basis: they fly in part for regular monitoring, to detect changes that could point to issues; and they can also be launched to collect data as a result of engineers requesting information. The product is marketed by Percepto as “AIM”, short for autonomous site inspection and monitoring.

News broke last week that Amazon has been reorganising its Prime Air efforts — one sign of how some more consumer-facing business applications — despite many developments — may still have some turbulence ahead before they are commercially viable. Businesses like Percepto’s stand in contrast to that, with their focus specifically on flying over, and collecting data, in areas where there are precisely no people present.

It has dovetailed with a bigger focus from industries on the efficiencies (and cost savings) you can get with automation, which in turn has become the centerpiece of how industry is investing in the buzz phrase of the moment, “digital transformation.”

“We believe Percepto AIM addresses a multi-billion-dollar issue for numerous industries and will change the way manufacturing sites are managed in the IoT, Industry 4.0 era,” said Chase Koch, President of Koch Disruptive Technologies, in a statement. “Percepto’s track record in autonomous technology and data analytics is impressive, and we believe it is uniquely positioned to deliver the remote operations center of the future. We look forward to partnering with the Percepto team to make this happen.”

The partnership with Boston Dynamics is notable for a couple of reasons: it speaks to how various robotics hardware will work together in tandem in an automated, unmanned world; and it speaks to how Boston Dynamics is pulling up its socks.

On the latter front, the company has been making waves in the world of robotics for years, specifically with its agile and strong dog-like (with names like “Spot” and “Big Dog”) robots that can cover rugged terrains and handle tussles without falling apart.

That led it into the arms of Google, which acquired it as part of its own secretive moonshot efforts, in 2013. That never panned out into a business, and probably gave Google more complicated optics at a time when it was already being seen as too powerful. Then, SoftBank stepped in to pick it up, along with other robotics assets, in 2017. That hasn’t really gone anywhere either, it seems, and just this month it was reported that Boston Dynamics was reportedly facing yet another suitor, Hyundai.

All of this is to say that partnerships with third parties that are going places (quite literally) become strong signs of how Boston Dynamics’ extensive R&D investments might finally pay off with enterprising dividends.

Indeed, while Percepto has focused on its own vertical integration, longer term and more generally there is an argument to be made for more interoperability and collaboration between the various companies building “connected” and smart hardware for industrial, physical applications. It means that specific industries can focus on the special equipment and expertise they require, while at the same time complementing that with hardware and software that are recognised as best-in-class. Abuhasira said that he expects the Boston Dynamics partnership to be the first of many.

That makes this first one an interesting template. It will see Spot carrying Percepto’s payloads for high resolution imaging and thermal vision “to detect issues including hot spots on machines or electrical conductors, water and steam leaks around plants and equipment with degraded performance, with the data relayed via AIM.” It will also mean a more thorough picture, beyond what you get from the air, and potentially a point at which the data that the pairing sources results even in repairs or other work to fix issues.

“Combining Percepto’s Sparrow drone with Spot creates a unique solution for remote inspection,” said Michael Perry, VP of Business Development at Boston Dynamics, in a statement. “This partnership demonstrates the value of harnessing robotic collaborations and the insurmountable benefits to worker safety and cost savings that robotics can bring to industries that involve hazardous or remote work.”


By Ingrid Lunden

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

Microsoft launches Project Bonsai, its new machine teaching service for building autonomous systems

At its Build developer conference, Microsoft today announced that Project Bonsai, its new machine teaching service, is now in public preview.

If that name sounds familiar, it’s probably because you remember that Microsoft acquired Bonsai, a company that focuses on machine teaching, back in 2018. Bonsai combined simulation tools with different machine learning techniques to build a general-purpose deep reinforcement learning platform, with a focus on industrial control systems.

It’s maybe no surprise then that Project Bonsai, too, has a similar focus on helping businesses teach and manage their autonomous machines. “With Project Bonsai, subject-matter experts can add state-of-the-art intelligence to their most dynamic physical systems and processes without needing a background in AI,” the company notes in its press materials.

“The public preview of Project Bonsai builds on top of the Bonsai acquisition and the autonomous systems private preview announcements made at Build and Ignite of last year,” a Microsoft spokesperson told me.

Interestingly, Microsoft notes that project Bonsai is only the first block of a larger vision to help its customers build these autonomous systems. The company also stresses the advantages of machine teaching over other machine learning approach, especially the fact that it’s less of a black box approach than other methods, which makes it easier for developers and engineers to debug systems that don’t work as expected.

In addition to Bonsai, Microsoft also today announced Project Moab, an open-source balancing robot that is meant to help engineers and developers learn the basics of how to build a real-world control system. The idea here is to teach the robot to keep a ball balanced on top of a platform that is held by three arms.

Potential users will be able to either 3D print the robot themselves or buy one when it goes on sale later this year. There is also a simulation, developed by MathWorks, that developers can try out immediately.

“You can very quickly take it into areas where doing it in traditional ways would not be easy, such as balancing an egg instead,” said Mark Hammond, Microsoft General Manager
for Autonomous Systems. “The point of the Project Moab system is to provide that
playground where engineers tackling various problems can learn how to use the tooling and simulation models. Once they understand the concepts, they can apply it to their novel use case.”


By Frederic Lardinois

Will China’s coronavirus-related trends shape the future for American VCs?

For the past month, VC investment pace seems to have slacked off in the U.S., but deal activities in China are picking up following a slowdown prompted by the COVID-19 outbreak.

According to PitchBook, “Chinese firms recorded 66 venture capital deals for the week ended March 28, the most of any week in 2020 and just below figures from the same time last year,” (although 2019 was a slow year). There is a natural lag between when deals are made and when they are announced, but still, there are some interesting trends that I couldn’t help noticing.

While many U.S.-based VCs haven’t had a chance to focus on new deals, recent investment trends coming out of China may indicate which shifts might persist after the crisis and what it could mean for the U.S. investor community.

Image Credits: PitchBook


By Walter Thompson

Zebra’s SmartSight inventory robot keeps an eye on store shelves

How many times have you gone into a store and found the shelves need restocking of the very item you came in for? This is a frequent problem and it’s difficult, especially in larger retail establishments, to keep on top of stocking requirements. Zebra Technologies has a solution: a robot that scans the shelves and reports stock gaps to human associates.

The SmartSight robot is a hardware solution that roams the aisles of the store checking the shelves, using a combination of computer vision, machine learning, workflow automation and robotic capabilities. It can find inventory problems, pricing glitches and display issues. When it finds a problem, it sends a message to human associates via a Zebra mobile computer with the location and nature of the issue.

The robot takes advantage of Zebra’s EMA50 mobile automation technology and links to other store systems including inventory and online ordering systems. Zebra claims it increases available inventory by 95%, while reducing human time spent wandering the aisles to do inventory manually by an average of 65 hours.

While it will likely reduce the number of humans required to perform this type of task, Zebra’s Senior Vice President and General Manager of Enterprise Mobile Computing, Joe White, says it’s not always easy to find people to fill these types of positions.

“SmartSight and the EMA50 were developed to help retailers fully capitalize on the opportunities presented by the on-demand economy despite heightened competition and ongoing labor shortage concerns,” White said in a statement.

This is a solution that takes advantage of robotics to help humans keep store shelves stocked and find other issues. The SmartSight robot will be available on a subscription basis. That means retailers won’t have to worry about owning and maintaining the robot. If anything goes wrong, Zebra would be responsible for fixing it.


By Ron Miller

Ten questions for 2020 presidential candidate John Delaney

In November 2020, America will go to the polls to vote in perhaps the most consequential election in a generation. The winner will lead the country amid great social, economic and ecological unrest. The 2020 election will be a referendum on both the current White House and the direction of the country at large.

Nearly 20 years into the young century, technology has become a pervasive element in all of our lives, and will continue to only grow more important. Whoever takes the oath of office in January 2021 will have to answer some difficult questions, raging from an impending climate disaster to concerns about job loss at the hands of robotics and automation.

Many of these questions are overlooked in day to day coverage of candidates and during debates. In order to better address the issues, TechCrunch staff has compiled a 10-part questionnaire across a wide range of tech-centric topics. The questions have been sent to national candidates, regardless of party. We will be publishing the answers as we receive them. Candidates are not required to answer all 10 in order for us to publish, but we will be noting which answers have been left blank.

First up is former Congressman John Delaney. Prior to being elected to Maryland’s 6th Congressional District, Delaney co-founded and led healthcare loan service Health Care Financial Partners (HCFP) and  commercial lender CapitalSource. He was elected to Congress in 2013, beating out a 10-term Republican incumbent. Rumored to be running against Maryland governor Larry Hogan for a 2018 bid, Delaney instead announced plans to run for president in 2020.

1. Which initiatives will you prioritize to limit humankind’s impact on climate and avoid potential climate catastrophe?

My $4 trillion Climate Plan will enable us to reach the goal of net zero emissions by 2050, which the IPCC says is the necessary target to avoid the worst effects of climate change. The centerpiece of my plan is a carbon-fee-and-dividend that will put a price on carbon emissions and return the money to the American people through a dividend. My plan also includes increased federal funding for renewable energy research, advanced nuclear technologies, direct air capture, a new Climate Corps program, and the construction of the Carbon Throughway, which would transport captured carbon from all over the country to the Permian Basin for reuse and permanent sequestration.

2. What is your plan to increase black and Latinx startup founders’ access to funding?

As a former entrepreneur who started two companies that went on to be publicly traded, I am a firm believer in the importance of entrepreneurship. To ensure people from all backgrounds have the support they need to start a new business, I will create nonprofit banks to serve economically distressed communities, launch a new SBIC program to help provide access to capital to minority entrepreneurs, and create a grant program to fund business incubators and accelerators at HBCUs. Additionally, I pledge to appoint an Entrepreneurship Czar who will be responsible for promoting entrepreneurship-friendly policies at all levels of government and encouraging entrepreneurship in rural and urban communities that have been left behind by venture capital investment.

3. Why do you think low-income students are underrepresented in STEM fields and how do you think the government can help fix that problem?

I think a major part of the problem is that schools serving low-income communities don’t have the resources they need to provide a quality STEM education to every student. To fix that, I have an education plan that will increase investment in STEM education and use Title I funding to eliminate the $23 billion annual funding gap between predominantly white and predominantly black school districts. To encourage students to continue their education after they graduate from high school and ensure every student learns the skills they need, my plan also provides two years of free in-state tuition and fees at a public university, community college, or technical school to everyone who completes one year of my mandatory national service program.

4. Do you plan on backing and rolling out paper-only ballots or paper-verified election machines? With many stakeholders in the private sector and the government, how do you aim to coordinate and achieve that?

Making sure that our elections are secure is vital, and I think using voting machines that create a voter-verified paper record could improve security and increase voters’ confidence in the integrity of our elections. To address other facets of the election security issue, I have proposed creating a Department of Cybersecurity to help protect our election systems, and while in Congress I introduced election security legislation to ensure that election vendors are solely owned and controlled by American citizens.

5. What, if any, federal regulation should be enacted for autonomous vehicles?

I was proud to be the founder of the Congressional Artificial Intelligence Caucus, a bipartisan group of lawmakers dedicated to understanding the impacts of advances in AI technology and educating other legislators so they have the knowledge they need to enact policies that ensure these innovations benefit Americans. We need to use the legislative process to have a real conversation involving experts and other stakeholders in order to develop a comprehensive set of regulations regarding autonomous vehicles, which should include standards that address data collection practices and other privacy issues as well as more fundamental questions about public safety.

6. How do you plan to achieve and maintain U.S. superiority in space, both in government programs and private industry?

Space exploration is tremendously important to me as a former Congressman from Maryland, the home of NASA’s Goddard Space Flight Center, major space research centers at the University of Maryland, and many companies that develop crucial aerospace technologies. As president, I will support the NASA budget and will continue to encourage innovation in the private sector.

7. Increased capital in startups founded by American entrepreneurs is a net positive, but should the U.S. allow its businesses to be part-owned by foreign governments, particularly the government of Saudi Arabia?

I am concerned that joint ventures between U.S. businesses and foreign governments, including state-owned enterprises, could facilitate the theft of intellectual property, potentially allowing foreign governments to benefit from taxpayer-funded research. We need to put in place greater protections that defend American innovation from theft.

8. Will U.S.-China technology decoupling harm or benefit U.S. innovation and why?

In general, I am in favor of international technology cooperation but in the case of China, it engages in predatory economic behavior and disregards international rules. Intellectual property theft has become a big problem for American businesses as China allows its companies to steal IP through joint ventures. In theory, U.S.-China collaboration could advance technology and innovation but without proper IP and economic protections, U.S.-China joint ventures and partnerships can be detrimental to the U.S.

9. How large a threat does automation represent to American jobs? Do you have a plan to help train low-skilled workers and otherwise offset job loss?

Automation could lead to the disruption of up to 54 million American jobs if we aren’t prepared and we don’t have the right policies. To help American workers transition to the high-tech, high-skill future economy, I am calling for a national AI strategy that will support public/private AI partnerships, develop a social contract with the communities that are negatively impacted by technology and globalization, and create updated education and job training programs that will help students and those currently in the workforce learn the skills they need.

To help provide jobs to displaced workers and drive economic growth in communities that suffer negative effects from automation, I have proposed a $2 trillion infrastructure plan that would create an infrastructure bank to facilitate state and local government investment, increase the Highway Trust Fund, create a Climate Infrastructure Fund, and create five new matching funds to support water infrastructure, school infrastructure, deferred maintenance projects, rural broadband, and infrastructure projects in disadvantaged communities in urban and rural areas. In addition, my proposed national service program will create new opportunities that allow young adults to learn new skills and gain valuable work experience. For example, my proposal includes a new national infrastructure apprenticeship program that will award a professional certificate proving mastery of particular skill sets for those who complete the program.

10. What steps will you take to restore net neutrality and assure internet users that their traffic and data are safe from manipulation by broadband providers?

I support the Save Net Neutrality Act to restore net neutrality, and I will appoint FCC commissioners who are committed to maintaining a fair and open internet. Additionally, I would work with Congress to update our digital privacy laws and regulations to protect consumers, especially children, from their data being collected without consent.


By Brian Heater

Dasha AI is calling so you don’t have to

While you’d be hard pressed to find any startup not brimming with confidence over the disruptive idea they’re chasing, it’s not often you come across a young company as calmly convinced it’s engineering the future as Dasha AI.

The team is building a platform for designing human-like voice interactions to automate business processes. Put simply, it’s using AI to make machine voices a whole lot less robotic.

“What we definitely know is this will definitely happen,” says CEO and co-founder Vladislav Chernyshov. “Sooner or later the conversational AI/voice AI will replace people everywhere where the technology will allow. And it’s better for us to be the first mover than the last in this field.”

“In 2018 in the US alone there were 30 million people doing some kind of repetitive tasks over the phone. We can automate these jobs now or we are going to be able to automate it in two years,” he goes on. “If you multiple it with Europe and the massive call centers in India, Pakistan and the Philippines you will probably have something like close to 120M people worldwide… and they are all subject for disruption, potentially.”

The New York based startup has been operating in relative stealth up to now. But it’s breaking cover to talk to TechCrunch — announcing a $2M seed round, led by RTP Ventures and RTP Global: An early stage investor that’s backed the likes of Datadog and RingCentral. RTP’s venture arm, also based in NY, writes on its website that it prefers engineer-founded companies — that “solve big problems with technology”. “We like technology, not gimmicks,” the fund warns with added emphasis.

Dasha’s core tech right now includes what Chernyshov describes as “a human-level, voice-first conversation modelling engine”; a hybrid text-to-speech engine which he says enables it to model speech disfluencies (aka, the ums and ahs, pitch changes etc that characterize human chatter); plus “a fast and accurate” real-time voice activity detection algorithm which detects speech in under 100 milliseconds, meaning the AI can turn-take and handle interruptions in the conversation flow. The platform can also detect a caller’s gender — a feature that can be useful for healthcare use-cases, for example.

Another component Chernyshov flags is “an end-to-end pipeline for semi-supervised learning” — so it can retrain the models in real time “and fix mistakes as they go” — until Dasha hits the claimed “human-level” conversational capability for each business process niche. (To be clear, the AI cannot adapt its speech to an interlocutor in real-time — as human speakers naturally shift their accents closer to bridge any dialect gap — but Chernyshov suggests it’s on the roadmap.)

“For instance, we can start with 70% correct conversations and then gradually improve the model up to say 95% of correct conversations,” he says of the learning element, though he admits there are a lot of variables that can impact error rates — not least the call environment itself. Even cutting edge AI is going to struggle with a bad line.

The platform also has an open API so customers can plug the conversation AI into their existing systems — be it telephony, Salesforce software or a developer environment, such as Microsoft Visual Studio.

Currently they’re focused on English, though Chernyshov says the architecture is “basically language agnostic” — but does requires “a big amount of data”.

The next step will be to open up the dev platform to enterprise customers, beyond the initial 20 beta testers, which include companies in the banking, healthcare and insurance sectors — with a release slated for later this year or Q1 2020.

Test use-cases so far include banks using the conversation engine for brand loyalty management to run customer satisfaction surveys that can turnaround negative feedback by fast-tracking a response to a bad rating — by providing (human) customer support agents with an automated categorization of the complaint so they can follow up more quickly. “This usually leads to a wow effect,” says Chernyshov.

Ultimately, he believes there will be two or three major AI platforms globally providing businesses with an automated, customizable conversational layer — sweeping away the patchwork of chatbots currently filling in the gap. And of course Dasha intends their ‘Digital Assistant Super Human Alike’ to be one of those few.

“There is clearly no platform [yet],” he says. “Five years from now this will sound very weird that all companies now are trying to build something. Because in five years it will be obvious — why do you need all this stuff? Just take Dasha and build what you want.”

“This reminds me of the situation in the 1980s when it was obvious that the personal computers are here to stay because they give you an unfair competitive advantage,” he continues. “All large enterprise customers all over the world… were building their own operating systems, they were writing software from scratch, constantly reinventing the wheel just in order to be able to create this spreadsheet for their accountants.

“And then Microsoft with MS-DOS came in… and everything else is history.”

That’s not all they’re building, either. Dasha’s seed financing will be put towards launching a consumer-facing product atop its b2b platform to automate the screening of recorded message robocalls. So, basically, they’re building a robot assistant that can talk to — and put off — other machines on humans’ behalf.

Which does kind of suggest the AI-fuelled future will entail an awful lot of robots talking to each other… 🤖🤖🤖

Chernyshov says this b2c call screening app will most likely be free. But then if your core tech looks set to massively accelerate a non-human caller phenomenon that many consumers already see as a terrible plague on their time and mind then providing free relief — in the form of a counter AI — seems the very least you should do.

Not that Dasha can be accused of causing the robocaller plague, of course. Recorded messages hooked up to call systems have been spamming people with unsolicited calls for far longer than the startup has existed.

Dasha’s PR notes Americans were hit with 26.3BN robocalls in 2018 alone — up “a whopping” 46% on 2017.

Its conversation engine, meanwhile, has only made some 3M calls to date, clocking its first call with a human in January 2017. But the goal from here on in is to scale fast. “We plan to aggressively grow the company and the technology so we can continue to provide the best voice conversational AI to a market which we estimate to exceed $30BN worldwide,” runs a line from its PR.

After the developer platform launch, Chernyshov says the next step will be to open up access to business process owners by letting them automate existing call workflows without needing to be able to code (they’ll just need an analytic grasp of the process, he says).

Later — pegged for 2022 on the current roadmap — will be the launch of “the platform with zero learning curve”, as he puts it. “You will teach Dasha new models just like typing in a natural language and teaching it like you can teach any new team member on your team,” he explains. “Adding a new case will actually look like a word editor — when you’re just describing how you want this AI to work.”

His prediction is that a majority — circa 60% — of all major cases that business face — “like dispatching, like probably upsales, cross sales, some kind of support etc, all those cases” — will be able to be automated “just like typing in a natural language”.

So if Dasha’s AI-fuelled vision of voice-based business process automation come to fruition then humans getting orders of magnitude more calls from machines looks inevitable — as machine learning supercharges artificial speech by making it sound slicker, act smarter and seem, well, almost human.

But perhaps a savvier generation of voice AIs will also help manage the ‘robocaller’ plague by offering advanced call screening? And as non-human voice tech marches on from dumb recorded messages to chatbot-style AIs running on scripted rails to — as Dasha pitches it — fully responsive, emoting, even emotion-sensitive conversation engines that can slip right under the human radar maybe the robocaller problem will eat itself? I mean, if you didn’t even realize you were talking to a robot how are you going to get annoyed about it?

Dasha claims 96.3% of the people who talk to its AI “think it’s human”, though it’s not clear what sample size the claim is based on. (To my ear there are definite ‘tells’ in the current demos on its website. But in a cold-call scenario it’s not hard to imagine the AI passing, if someone’s not paying much attention.)

The alternative scenario, in a future infested with unsolicited machine calls, is that all smartphone OSes add kill switches, such as the one in iOS 13 — which lets people silence calls from unknown numbers.

And/or more humans simply never pick up phone calls unless they know who’s on the end of the line.

So it’s really doubly savvy of Dasha to create an AI capable of managing robot calls — meaning it’s building its own fallback — a piece of software willing to chat to its AI in future, even if actual humans refuse.

Dasha’s robocall screener app, which is slated for release in early 2020, will also be spammer-agnostic — in that it’ll be able to handle and divert human salespeople too, as well as robots. After all, a spammer is a spammer.

“Probably it is the time for somebody to step in and ‘don’t be evil’,” says Chernyshov, echoing Google’s old motto, albeit perhaps not entirely reassuringly given the phrase’s lapsed history — as we talk about the team’s approach to ecosystem development and how machine-to-machine chat might overtake human voice calls.

“At some point in the future we will be talking to various robots much more than we probably talk to each other — because you will have some kind of human-like robots at your house,” he predicts. “Your doctor, gardener, warehouse worker, they all will be robots at some point.”

The logic at work here is that if resistance to an AI-powered Cambrian Explosion of machine speech is futile, it’s better to be at the cutting edge, building the most human-like robots — and making the robots at least sound like they care.

Dasha’s conversational quirks certainly can’t be called a gimmick. Even if the team’s close attention to mimicking the vocal flourishes of human speech — the disfluencies, the ums and ahs, the pitch and tonal changes for emphasis and emotion — might seem so at first airing.

In one of the demos on its website you can hear a clip of a very chipper-sounding male voice, who identifies himself as “John from Acme Dental”, taking an appointment call from a female (human), and smoothly dealing with multiple interruptions and time/date changes as she changes her mind. Before, finally, dealing with a flat cancelation.

A human receptionist might well have got mad that the caller essentially just wasted their time. Not John, though. Oh no. He ends the call as cheerily as he began, signing off with an emphatic: “Thank you! And have a really nice day. Bye!”

If the ultimate goal is Turing Test levels of realism in artificial speech — i.e. a conversation engine so human-like it can pass as human to a human ear — you do have to be able to reproduce, with precision timing, the verbal baggage that’s wrapped around everything humans say to each other.

This tonal layer does essential emotional labor in the business of communication, shading and highlighting words in a way that can adapt or even entirely transform their meaning. It’s an integral part of how we communicate. And thus a common stumbling block for robots.

So if the mission is to power a revolution in artificial speech that humans won’t hate and reject then engineering full spectrum nuance is just as important a piece of work as having an amazing speech recognition engine. A chatbot that can’t do all that is really the gimmick.

Chernyshov claims Dasha’s conversation engine is “at least several times better and more complex than [Google] Dialogflow, [Amazon] Lex, [Microsoft] Luis or [IBM] Watson”, dropping a laundry list of rival speech engines into the conversation.

He argues none are on a par with what Dasha is being designed to do.

The difference is the “voice-first modelling engine”. “All those [rival engines] were built from scratch with a focus on chatbots — on text,” he says, couching modelling voice conversation “on a human level” as much more complex than the more limited chatbot-approach — and hence what makes Dasha special and superior.

“Imagination is the limit. What we are trying to build is an ultimate voice conversation AI platform so you can model any kind of voice interaction between two or more human beings.”

Google did demo its own stuttering voice AI — Duplex — last year, when it also took flak for a public demo in which it appeared not to have told restaurant staff up front they were going to be talking to a robot.

Chernyshov isn’t worried about Duplex, though, saying it’s a product, not a platform.

“Google recently tried to headhunt one of our developers,” he adds, pausing for effect. “But they failed.”

He says Dasha’s engineering staff make up more than half (28) its total headcount (48), and include two doctorates of science; three PhDs; five PhD students; and ten masters of science in computer science.

It has an R&D office in Russian which Chernyshov says helps makes the funding go further.

“More than 16 people, including myself, are ACM ICPC finalists or semi finalists,” he adds — likening the competition to “an Olympic game but for programmers”. A recent hire — chief research scientist, Dr Alexander Dyakonov — is both a doctor of science professor and former Kaggle No.1 GrandMaster in machine learning. So with in-house AI talent like that you can see why Google, uh, came calling…

Dasha

 

But why not have Dasha ID itself as a robot by default? On that Chernyshov says the platform is flexible — which means disclosure can be added. But in markets where it isn’t a legal requirement the door is being left open for ‘John’ to slip cheerily by. Bladerunner here we come.

The team’s driving conviction is that emphasis on modelling human-like speech will, down the line, allow their AI to deliver universally fluid and natural machine-human speech interactions which in turn open up all sorts of expansive and powerful possibilities for embeddable next-gen voice interfaces. Ones that are much more interesting than the current crop of gadget talkies.

This is where you could raid sci-fi/pop culture for inspiration. Such as Kitt, the dryly witty talking car from the 1980s TV series Knight Rider. Or, to throw in a British TV reference, Holly the self-depreciating yet sardonic human-faced computer in Red Dwarf. (Or indeed Kryten the guilt-ridden android butler.) Chernyshov’s suggestion is to imagine Dasha embedded in a Boston Dynamics robot. But surely no one wants to hear those crawling nightmares scream…

Dasha’s five-year+ roadmap includes the eyebrow-raising ambition to evolve the technology to achieve “a general conversational AI”. “This is a science fiction at this point. It’s a general conversational AI, and only at this point you will be able to pass the whole Turing Test,” he says of that aim.

“Because we have a human level speech recognition, we have human level speech synthesis, we have generative non-rule based behavior, and this is all the parts of this general conversational AI. And I think that we can we can — and scientific society — we can achieve this together in like 2024 or something like that.

“Then the next step, in 2025, this is like autonomous AI — embeddable in any device or a robot. And hopefully by 2025 these devices will be available on the market.”

Of course the team is still dreaming distance away from that AI wonderland/dystopia (depending on your perspective) — even if it’s date-stamped on the roadmap.

But if a conversational engine ends up in command of the full range of human speech — quirks, quibbles and all — then designing a voice AI may come to be thought of as akin to designing a TV character or cartoon personality. So very far from what we currently associate with the word ‘robotic’. (And wouldn’t it be funny if the term ‘robotic’ came to mean ‘hyper entertaining’ or even ‘especially empathetic’ thanks to advances in AI.)

Let’s not get carried away though.

In the meanwhile, there are ‘uncanny valley’ pitfalls of speech disconnect to navigate if the tone being (artificially) struck hits a false note. (And, on that front, if you didn’t know ‘John from Acme Dental’ was a robot you’d be forgiven for misreading his chipper sign off to a total time waster as pure sarcasm. But an AI can’t appreciate irony. Not yet anyway.)

Nor can robots appreciate the difference between ethical and unethical verbal communication they’re being instructed to carry out. Sales calls can easily cross the line into spam. And what about even more dystopic uses for a conversation engine that’s so slick it can convince the vast majority of people it’s human — like fraud, identity theft, even election interference… the potential misuses could be terrible and scale endlessly.

Although if you straight out ask Dasha whether it’s a robot Chernyshov says it has been programmed to confess to being artificial. So it won’t tell you a barefaced lie.

Dasha

How will the team prevent problematic uses of such a powerful technology?

“We have an ethics framework and when we will be releasing the platform we will implement a real-time monitoring system that will monitor potential abuse or scams, and also it will ensure people are not being called too often,” he says. “This is very important. That we understand that this kind of technology can be potentially probably dangerous.”

“At the first stage we are not going to release it to all the public. We are going to release it in a closed alpha or beta. And we will be curating the companies that are going in to explore all the possible problems and prevent them from being massive problems,” he adds. “Our machine learning team are developing those algorithms for detecting abuse, spam and other use cases that we would like to prevent.”

There’s also the issue of verbal ‘deepfakes’ to consider. Especially as Chernyshov suggests the platform will, in time, support cloning a voiceprint for use in the conversation — opening the door to making fake calls in someone else’s voice. Which sounds like a dream come true for scammers of all stripes. Or a way to really supercharge your top performing salesperson.

Safe to say, the counter technologies — and thoughtful regulation — are going to be very important.

There’s little doubt that AI will be regulated. In Europe policymakers have tasked themselves with coming up with a framework for ethical AI. And in the coming years policymakers in many countries will be trying to figure out how to put guardrails on a technology class that, in the consumer sphere, has already demonstrated its wrecking-ball potential — with the automated acceleration of spam, misinformation and political disinformation on social media platforms.

“We have to understand that at some point this kind of technologies will be definitely regulated by the state all over the world. And we as a platform we must comply with all of these requirements,” agrees Chernyshov, suggesting machine learning will also be able to identify whether a speaker is human or not — and that an official caller status could be baked into a telephony protocol so people aren’t left in the dark on the ‘bot or not’ question. 

“It should be human-friendly. Don’t be evil, right?”

Asked whether he considers what will happen to the people working in call centers whose jobs will be disrupted by AI, Chernyshov is quick with the stock answer — that new technologies create jobs too, saying that’s been true right throughout human history. Though he concedes there may be a lag — while the old world catches up to the new.

Time and tide wait for no human, even when the change sounds increasingly like we do.


By Natasha Lomas

Calling all hardware startups! Apply to Hardware Battlefield @ TC Shenzhen

Got hardware? Well then, listen up, because our search continues for boundary-pushing, early-stage hardware startups to join us in Shenzhen, China for an epic opportunity; launch your startup on a global stage and compete in Hardware Battlefield at TC Shenzhen on November 11-12.

Apply here to compete in TC Hardware Battlefield 2019. Why? It’s your chance to demo your product to the top investors and technologists in the world. Hardware Battlefield, cousin to Startup Battlefield, focuses exclusively on innovative hardware because, let’s face it, it’s the backbone of technology. From enterprise solutions to agtech advancements, medical devices to consumer product goods — hardware startups are in the international spotlight.

If you make the cut, you’ll compete against 15 of the world’s most innovative hardware makers for bragging rights, plenty of investor love, media exposure and $25,000 in equity-free cash. Just participating in a Battlefield can change the whole trajectory of your business in the best way possible.

We chose to bring our fifth Hardware Battlefield to Shenzhen because of its outstanding track record of supporting hardware startups. The city achieves this through a combination of accelerators, rapid prototyping and world-class manufacturing. What’s more, TC Hardware Battlefield 2019 takes place as part of the larger TechCrunch Shenzhen that runs November 9-12.

Creativity and innovation no know boundaries, and that’s why we’re opening this competition to any early-stage hardware startup from any country. While we’ve seen amazing hardware in previous Battlefields — like robotic armsfood testing devicesmalaria diagnostic tools, smart socks for diabetics and e-motorcycles, we can’t wait to see the next generation of hardware, so bring it on!

Meet the minimum requirements listed below, and we’ll consider your startup:

Here’s how Hardware Battlefield works. TechCrunch editors vet every qualified application and pick 15 startups to compete. Those startups receive six rigorous weeks of free coaching. Forget stage fright. You’ll be prepped and ready to step into the spotlight.

Teams have six minutes to pitch and demo their products, which is immediately followed by an in-depth Q&A with the judges. If you make it to the final round, you’ll repeat the process in front of a new set of judges.

The judges will name one outstanding startup the Hardware Battlefield champion. Hoist the Battlefield Cup, claim those bragging rights and the $25,000. This nerve-wracking thrill-ride takes place in front of a live audience, and we capture the entire event on video and post it to our global audience on TechCrunch.

Hardware Battlefield at TC Shenzhen takes place on November 11-12. Don’t hide your hardware or miss your chance to show us — and the entire tech world — your startup magic. Apply to compete in TC Hardware Battlefield 2019, and join us in Shenzhen!

Is your company interested in sponsoring or exhibiting at Hardware Battlefield at TC Shenzhen? Contact our sponsorship sales team by filling out this form.


By Neesha A. Tambe

Blue Prism acquires UK’s Thoughtonomy for up to $100M to expand its RPA platform with more AI

Robotic process automation — which lets organizations shift repetitive back office tasks to machines to complete — has been a hot area of growth in the world of enterprise IT, and now one of the companies that’s making waves in the area has acquired a smaller startup to continue extending its capabilities.

Blue Prism, which helped coin the term RPA when it was founded back in 2001, has announced that it is buying Thoughtonomy, which has built a cloud-based AI engine that delivers RPA-based solutions on an SaaS framework. Blue Prism is publicly traded on the London Stock Exchange — where its market cap is around £1.3 billion ($1.6 billion) and in a statement to the market alongside its half-year earnings, it said it would be paying up to £80 million ($100 million) for the firm.

The deal is coming in a combination of cash and stock: £12.5 million payable on completion of the deal, £23 million in shares payable on completion of the deal, up to £20 million payable a year after the deal closes; up to £4.5 million in cash after 18 months, and a final £20 million on the second anniversary of the deal closing, in shares. Thoughtonomy had never raised outside funding, although that was not for lack of interest:

“We’ve had approaches on a daily basis since the intelligent automation market has exploded,” said Terry Walby, CEO and founder of Thoughtonomy, in an interview, “but getting the best outcome for the company and our customers is not just about taking money and headlines [touting] our valuation.”

The acquisition comes about six months after Blue Prism announced that it would be raising around $130 million (£100 million) to continue growing at a time when RPA is getting a lot of attention in the market. Linda Dotts, the company’s SVP of global partner strategy and programs, today confirmed that it did raise that money, and that part of the proceeds of that are being used to make the Thoughtonomy acquisition. She also confirmed that it would be looking at other opportunities, a sign that we are likely going to see at least a little more consolidation in this space.

On the same day that it had announced that fundraise, Blue Prism also unveiled a new AI initiative, working with partners to execute on that. And indeed that is what it is getting with Thoughtonomy. The companies were already working together before this — Thoughtonomy’s other key partners are companies like Microsoft’s Azure and Google Cloud, used to deliver its services — and according to Walby, the idea is that his startup will be helping Blue Prism get its services to the next level of where RPA is going.

“We provide architectural support and add intelligence,” he said in an interview. “Our platform addresses activities that require understanding or interpretation, and so it expands the use cases for RPA beyond structured processes.”

That’s notable given the position of Blue Prism within the RPA landscape. The company is one of the more legacy providers — one of the consequences of being an early mover — and while that gives it a clear advantage of showing it has staying power, in the world of software that can be a more challenging sell when younger companies are building tech from scratch on newer frameworks. (UiPath, which has made major inroads into RPA both in terms of its customer and partner growth, as well as in terms of its funding, is one example.)

And in a market that is still seeing growth (read: companies often operate at a loss to invest in that growth), its ups and downs are there for everyone to see and scrutinise. In its half-year earnings that it posted today, its negative EBITDA margin widened, while group revenues only inched up slightly to £41.6 million and monthly recurring revenues were flat. The longer term picture is a little more interesting, though, with total customer numbers up 91 percent over the same period a year ago.


By Ingrid Lunden

Over 1,400 self-driving vehicles are now in testing by 80+ companies across the US

In a talk at the Uber Elevate Summit in Washington, D.C., today, U.S. Department of Transportation Secretary Elaine Chao shared a total overall figure for ongoing testing of autonomous vehicles on U.S roads: More than 1,400 self-driving cars, trucks and other vehicles are currently in testing by more than 80 companies across 36 U.S. states, plus DC itself.

This puts some sense of overall scale to the work being done to test and develop self-driving car tech in the U.S. For context, note that California, one of the first states to have implemented AV testing on public roads, currently has 62 companies registered to perform testing — which represents a significant chunk of that 80-plus figure provided by Secretary Chao.

Chao also shared that there are more than 1.59 million registered drones currently in the U.S., of which more than 372,000 are classified as commercial, with more than 136,000 registered commercial drone operators also on the books. That represents a net new job category, Chao noted.

The secretary also later emphasized that the DoT over which she presides and the current administration aim to be “tech neutral, and not command and control” and that the department is not “in the business of picking winners and losers,” something she said the assembled audience of mostly private-sector attendants would be “so pleased to hear.”

Under Chao, the DoT has introduced and continues to overhaul guidelines, rules and programs that favor and unblock industry and commercial access to autonomous driving, drone operation and spacecraft launch capabilities. Recently, Chao has come under fire for potential conflict of interest related to use of her position.


By Darrell Etherington

Microsoft teams up with BMW for the IoT-focused Open Manufacturing Platform

Car companies are making big investments in technology to help ensure that they are not cut out of the next generation of transportation and automotive manufacturing, and today came the latest development in that trend.

The BMW Group and Microsoft announced they would team up in a new effort called the Open Manufacturing Platform, aimed at developing and encouraging more collaborative IoT development in the manufacturing sector, focusing on smart factory solutions and building standards to develop them in areas like machine connectivity and on-premises systems integration.

The two companies have not disclosed how much they intend to invest in the project — we have sent a message to ask. The plan will be to bring in more manufacturers and suppliers — the goal, they say, is to have between four and six others with them, working on 15 use cases by the end of this year — working with open source components, open industrial standards and open data to develop both hardware and software that runs on it.

The two say that future partners do not have to be from within the automotive industry.

The OMP will be built on Microsoft’s industrial IoT platform — part of its Azure cloud business. But this is a natural progression of how Microsoft and BMW were already working together. BMW already has 3,000 machines running on Azure cloud, IoT and AI services in its existing robots and in-factory autonomous transport systems, and it said it will be contributing some of the technology that it had already built — for example around its self-driving systems — into the group as part of the effort.

“Microsoft is joining forces with the BMW Group to transform digital production efficiency across the industry,” Scott Guthrie, executive vice president, Microsoft Cloud + AI Group, said in a presentation in Germany today. “Our commitment to building an open community will create new opportunities for collaboration across the entire manufacturing value chain.”

“Mastering the complex task of producing individualized premium products requires innovative IT and software solutions,” added Oliver Zipse, member of the Board of Management of BMW AG, Production, a statement. “The interconnection of production sites and systems as well as the secure integration of partners and suppliers are particularly important. We have been relying on the cloud since 2016 and are consistently developing new approaches. With the Open Manufacturing Platform as the next step, we want to make our solutions available to other companies and jointly leverage potential in order to secure our strong position in the market in the long term.”

The problem that Microsoft and BMW are going after here is a longstanding one. Much of the computing in the world of IT has been built around open standards, or in any event on very widely-used proprietary platforms that can interface with each other. The same does not go in the world of manufacturing, where proprietary systems are specific to each manufacturer, making them difficult to modify and often impossible to use in conjunction with other proprietary systems.

That ultimately slows down how things have been able to evolve, and will mean that implementing new generations of technology becomes expensive or even in some cases impossible. And given the speed with which things are moving, and the increasing sophistication of the machines that are being built (cars as “hardware”), something had to change.

That is what BMW and Microsoft are addressing. For BMW it will give it a hand in helping shape how standards develop, and for Microsoft it will give it a potential window into expanding its business in this enterprise sector.

The collaborative approach has been a big one for tech companies hoping to find a common way forward in the future of computing. Microsoft may own a lot of proprietary platforms that are not open source, but it’s making efforts to collaborate more in a number of other ways. It works with SAP, Adobe, WPP and others on the Open Data Initiative; with Intel, Google and others it’s working on an open standard for connecting data centers; it’s part of an open standard initiative for software licensing; and it’s part of a new cross-licensing patent database.


By Ingrid Lunden

At cobotics startup Formant, ex-Googlers team up humans & machines

Our distinct skillsets and shortcomings mean people and robots will join forces for the next few decades. Robots are tireless, efficient, and reliable, but in a millisecond through intuition and situational awareness, humans can make decisions machine can’t. Until workplace robots are truly autonomous and don’t require any human thinking, we’ll need software to supervise them at scale. Formant comes out of stealth today to “help people speak robot” says co-founder and CEO Jeff Linnell. “What’s really going to move the needle in the innovation economy is using humans as an empowering element in automation.”

Linnell learned the grace of uniting flesh and steel while working on the movie Gravity. “We put cameras and Sandra Bullock on dollies” he bluntly recalls. Artistic vision and robotic precision combined to create gorgeous zero-gravity scenes that made audiences feel weightless. Google bought his startup Bot & Dolly, and Linnell spent 10 years there as a director of robotics while forming his thesis.

Now with Formant, he wants to make hybrid workforce cooperation feel frictionless.

The company has raised a $6 million seed round from SignalFire, a data driven VC fund with software for recruiting engineers. Formant is launching its closed beta that equips businesses with cloud infrastructure for collecting, making sense of, and acting on data from fleets of robots. It allows a single human to oversee 10, 20, or 100 machines, stepping in to clear confusion when they aren’t sure what to do.

“The tooling is 10 years behind the web” Linnell explains. “If you build a data company today, you’ll use AWS or Google Cloud, but that simply doesn’t exist for robotics. We’re building that layer.”

A Beautiful Marriage

“This is going to sound completely bizarre” Formant co-founder and CTO Anthony Jules warns me. “I had a recurring dream [as a child] in which I was a ship captain and I had a little mechanical parrot on my should that would look at situations and help me decide what to do as we’d sail the seas trying to avoid this octopus. Since then I knew that building intelligent machines is what I do in this world.”

So he went to MIT, left a robotics PhD program to build a startup called Sapient Corporation that he built into a 4000-employee public company, and worked on the Tony Hawk video games. He too joined Google through an acquisition, meeting Linnell after Redwood Robotics where he was COO got acquired. “We came up with some similar beliefs. There are a few places where full autonomy will actually work, but it’s really about creating a beautiful marriage of what machines are good at and what humans are good at” Jules tells me

Formant now has SAAS pilots running with businesses in several verticals to make their “robot-shaped data” usable. They range from food manufacturing to heavy infrastructure inspection to construction, and even training animals. Linnell also foresees retail increasingly employing fleets of robots not just in the warehouse but on the showroom floor, and they’ll require precise coordination.

What’s different about Formant is it doesn’t build the bots. Instead, it builds the reins for people to deftly control them.

First, Formant connects to sensors to fill up a cloud with Lidar, depth imagery, video, photos, log files, metrics, motor torques, and scalar values. The software parses that data and when something goes wrong or the system isn’t sure how to move forward, Formant alerts the human ‘foreman’ that they need to intervene. It can monitor the fleet, sniff out the source of errors, and suggest options for what to do next.

For example, “when an autonomous digger encounters an obstacle in the foundation of a construction site, an operator is necessary to evaluate whether it is safe for the robot to proceed or stop” Linnell writes. “This decision is made in tandem: the rich data gathered by the robot is easily interpreted by a human but difficult or legally questionable for a machine. This choice still depends on the value judgment of the human, and will change depending on if the obstacle is a gas main, a boulder, or an electrical wire.”

Any single data stream alone can’t reveal the mysteries that arise, and people would struggle to juggle the different feeds in their minds. But not only can Formant align the data for humans to act on, it can also turn their choices into valuable training data for artificial intelligence. Formant learns, so next time the machine won’t need assistance.

The industrial revolution, continued

With rockstar talent poached from Google and tides lifting all automated boats, Formant’s biggest threat is competition from tech giants. Old engineering companies like SAP could try to adapt to new real-time data type, yet Formant hopes to out-code them. Google itself has built reliable cloud scaffolding and has robotics experience from Boston Dynamics plus buying Linnell’s and Jules’ companies. But the enterprise customization necessary to connect with different clients isn’t typical for the search juggernaut.

Linnell fears that companies that try to build their own robot management software could get hacked. “I worry about people who do homegrown solutions or don’t have the experience we have from being at a place like Google. Putting robots online in an insecure way is a pretty bad problem.” Formant is looking to squash any bugs before it opens its platform to customers in 2019.

With time, humans will become less and less necessary, and that will surface enormous societal challenges for employment and welfare. “It’s in some ways a continuation of the industrial revolution” Jules opines. “We take some of this for granted but it’s been happening for 100 years. Photographer — that’s a profession that doesn’t exist without the machine that they use. We think that transformation will continue to happen across the workforce.”


By Josh Constine