Sep
28
2020
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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 inspections 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.

May
19
2020
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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.”

May
15
2020
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(Formerly Augean) Burro is giving a helping hand to field workers

Rather than focusing on robots that will replace human workers outright, the company has created a semi-autonomous robotic cart that saves pickers a long trip.

Apr
21
2020
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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

Jan
13
2020
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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 want? 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, software and services 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 per week.

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 starting later this quarter. 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.

Zebra made the announcement at the NRF 2020 conference taking place this week in New York City.

Sep
13
2019
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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.

Aug
01
2019
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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 U.S. 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 120 million 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 $2 million 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 less than 100 milliseconds, meaning the AI can turn-take and handle interruptions in the conversation flow. The platform also can 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 toward 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-fueled 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 26.3 billion robocalls in 2018 alone — up “a whopping” 46% on 2017.

Its conversation engine, meanwhile, has only made some 3 million 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 $30 billion worldwide,” runs a line from its PR.

After the developer platform launch, Chernyshov says the next step will be to open 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-fueled vision of voice-based business process automation comes 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 on what sample size the claim is based. (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 the 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 cancellation.

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 modeling engine.” “All those [rival engines] were built from scratch with a focus on chatbots — on text,” he says, couching modeling 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 10 masters of science in computer science.

It has an R&D office in Russia, 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 modeling 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 meantime, 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.

Jul
31
2019
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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.

Jun
18
2019
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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 a 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 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 once more — sales, marketing and other business development efforts come at a cost, for one — although group revenues also nearly doubled to £41.6 million from £22.9 million in the same period a year earlier. Total customer numbers are up 91% over the same period a year ago, and with sales returns typically taking about 12 months to come through on the balance sheet, the longer-term picture is worth watching, too.

Apr
02
2019
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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.

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