Worksome pulls $13M into its high skill freelancer talent platform

More money for the now very buzzy business of reshaping how people work: Worksome is announcing it recently closed a $13 million Series A funding round for its “freelance talent platform” — after racking up 10x growth in revenue since January 2020, just before the COVID-19 pandemic sparked a remote working boom.

The 2017 founded startup, which has a couple of ex-Googlers in its leadership team, has built a platform to connect freelancers looking for professional roles with employers needing tools to find and manage freelancer talent.

It says it’s seeing traction with large enterprise customers that have traditionally used Managed Service Providers (MSPs) to manage and pay external workforces — and views employment agency giants like Randstad, Adecco and Manpower as ripe targets for disruption.

“Most multinational enterprises manage flexible workers using legacy MSPs,” says CEO and co-founder Morten Petersen (one of the Xooglers). “These largely analogue businesses manage complex compliance and processes around hiring and managing freelance workforces with handheld processes and outdated technology that is not built for managing fluid workforces. Worksome tackles this industry head on with a better, faster and simpler solution to manage large freelancer and contractor workforces.”

Worksome focuses on helping medium/large companies — who are working with at least 20+ freelancers at a time — fill vacancies within teams rather than helping companies outsource projects, per Petersen, who suggests the latter is the focus for the majority of freelancer platforms.

“Worksome helps [companies] onboard people who will provide necessary skills and will be integral to longer-term business operations. It makes matches between companies and skilled freelancers, which the businesses go on to trust, form relationships with and come back to time and time again,” he goes on.

“When companies hire dozens or hundreds of freelancers at one time, processes can get very complicated,” he adds, arguing that on compliance and payments Worksome “takes on a much greater responsibility than other freelancing platforms to make big hires easier”.

The startup also says it’s concerned with looking out for (and looking after) its freelancer talent pool — saying it wants to create “a world of meaningful work” on its platform, and ensure freelancers are paid fairly and competitively. (And also that they are paid faster than they otherwise might be, given it takes care of their payroll so they don’t have to chase payments from employers.)

The business started life in Copenhagen — and its Series A has a distinctly Nordic flavor, with investment coming from the Danish business angel and investor on the local version of the Dragons’ Den TV program Løvens Hule; the former Minister for Higher Education and Science, Tommy Ahlers; and family home manufacturer Lind & Risør.

It had raised just under $6M prior to thus round, per Crunchbase, and also counts some (unnamed) Google executives among its earlier investors.

Freelancer platforms (and marketplaces) aren’t new, of course. There are also an increasing number of players in this space — buoyed by a new flush of VC dollars chasing the ‘future of work’, whatever hybrid home-office flexible shape that might take. So Worksome is by no means alone in offering tech tools to streamline the interface between freelancers and businesses.

A few others that spring to mind include Lystable (now Kalo), Malt, Fiverr — or, for techie job matching specifically, the likes of HackerRank — plus, on the blue collar work side, Jobandtalent. There’s also a growing number of startups focusing on helping freelancer teams specifically (e.g. Collective), so there’s a trend towards increasing specialism.

Worksome says it differentiates vs other players (legacy and startups) by combining services like tax compliance, background and ID checks and handling payroll and other admin with an AI powered platform that matches talent to projects.

Although it’s not the only startup offering to do the back-office admin/payroll piece, either, nor the only one using AI to match skilled professionals to projects. But it claims it’s going further than rival ‘freelancer-as-a-service’ platforms — saying it wants to “address the entire value chain” (aka: “everything from the hiring of freelance talent to onboarding and payment”).

Worksome has 550 active clients (i.e. employers in the market for freelancer talent) at this stage; and has accepted 30,000 freelancers into its marketplace so far.

Its current talent pool can take on work across 12 categories, and collectively offers more than 39,000 unique skills, per Petersen.

The biggest categories of freelancer talent on the platform are in Software and IT; Design and Creative Work; Finance and Management Consulting; plus “a long tail of niche skills” within engineering and pharmaceuticals.

While its largest customers are found in the creative industries, tech and IT, pharma and consumer goods. And its biggest markets are the U.K. and U.S.

“We are currently trailing at +20,000 yearly placements,” says Petersen, adding: “The average yearly spend per client is $300,000.”

Worksome says the Series A funding will go on stoking growth by investing in marketing. It also plans to spend on product dev and on building out its team globally (it also has offices in London and New York).

Over the past 12 months the startup doubled the size of its team to 50 — and wants to do so again within 12 months so it can ramp up its enterprise client base in the U.S., U.K. and euro-zone.

“Yes, there are a lot of freelancer platforms out there but a lot of these don’t appreciate that hiring is only the tip of the iceberg when it comes to reducing the friction in working with freelancers,” argues Petersen. “Of the time that goes into hiring, managing and paying freelancers, 75% is currently spent on admin such as timesheet approvals, invoicing and compliance checks, leaving only a tiny fraction of time to actually finding talent.”

Worksome woos employers with a “one-click-hire” offer — touting its ability to find and hire freelancers “within seconds”.

If hiring a stranger in seconds sounds ill-advised, Worksome greases this external employment transaction by taking care of vetting the freelancers itself (including carrying out background checks; and using proprietary technology to asses freelancers’ skills and suitability for its marketplace).

“We have a two-step vetting process to ensure that we only allow the best freelance talent onto the Worksome platform,” Petersen tells TechCrunch. “For step one, an inhouse-built robot assesses our freelancer applicants. It analyses their skillset, social media profiles, profile completeness and hourly or daily rate, as well as their CV and work history, to decide whether each person is a good fit for Worksome.

“For step two, our team of talent specialists manually review and decline or approve the freelancers that pass through step one with a score of 85% or more. We have just approved our 30,000th freelancer and will be able to both scale and improve our vetting procedure as we grow.”

A majority of freelancer applicants fail Worksome’s proprietary vetting processes. This is clear because it says it has received 80,000 applicants so far — but only approved 30,000.

That raises interesting questions about how it’s making decisions on who is (and isn’t) an ‘appropriate fit’ for its talent marketplace.

It says its candidate assessing “robot” looks at “whether freelancers can demonstrate the skillset, matching work history, industry experience and profile depth” deemed necessary to meet its quality criteria — giving the example that it would not accept a freelancer who says they can lead complex IT infrastructure projects if they do not have evidence of relevant work, education and skills.

On the AI freelancer-to-project matching side, Worksome says its technology aims to match freelancers “who have the highest likelihood of completing a job with high satisfaction, based on their work-history, and performance and skills used on previous jobs”.

“This creates a feedback loop that… ensure that both clients and freelancers are matched with great people and great work,” is its circular suggestion when we ask about this.

But it also emphasizes that its AI is not making hiring decisions on its own — and is only ever supporting humans in making a choice. (An interesting caveat since existing EU data protection rules, under Article 22 of the GDPR, provide for a right for individuals to object to automated decision making if significant decisions are being taken without meaningful human interaction.) 

Using automation technologies (like AI) to make assessments that determine whether a person gains access to employment opportunities or doesn’t can certainly risk scaled discrimination. So the devil really is in the detail of how these algorithmic assessments are done.

That’s why such uses of technology are set to face close regulatory scrutiny in the European Union — under incoming rules on ‘high risk’ users of artificial intelligence — including the use of AI to match candidates to jobs.

The EU’s current legislative proposals in this area specifically categorize “employment, workers management and access to self-employment” as a high risk use of AI, meaning applications like Worksome are likely to face some of the highest levels of regulatory supervision in the future.

Nonetheless, Worksome is bullish when we ask about the risks associated with using AI as an intermediary for employment opportunities.

“We utilise fairly advanced matching algorithms to very effectively shortlist candidates for a role based solely on objective criteria, rinsed from human bias,” claims Petersen. “Our algorithms don’t take into account gender, ethnicity, name of educational institutions or other aspects that are usually connected to human bias.”

“AI has immense potential in solving major industry challenges such as recruitment bias, low worker mobility and low access to digital skills among small to medium sized businesses. We are firm believers that technology should be utilized to remove human bias’ from any hiring process,” he goes on, adding: “Our tech was built to this very purpose from the beginning, and the new proposed legislation has the potential to serve as a validator for the hard work we’ve put into this.

“The obvious potential downside would be if new legislation would limit innovation by making it harder for startups to experiment with new technologies. As always, legislation like this will impact the Davids more than the Goliaths, even though the intentions may have been the opposite.”

Zooming back out to consider the pandemic-fuelled remote working boom, Worksome confirms that most of the projects for which it supplied freelancers last year were conducted remotely.

“We are currently seeing a slow shift back towards a combination of remote and onsite work and expect this combination to stick amongst most of our clients,” Petersen goes on. “Whenever we are in uncertain economic times, we see a rise in the number of freelancers that companies are using. However, this trend is dwarfed by a much larger overall trend towards flexible work, which drives the real shift in the market. This shift has been accelerated by COVID-19 but has been underway for many years.

“While remote work has unlocked an enormous potential for accessing talent everywhere, 70% of the executives expect to use more temporary workers and contractors onsite than they did before COVID-19, according to a recent McKinsey study. This shows that businesses really value the flexibility in using an on-demand workforce of highly skilled specialists that can interact directly with their own teams.”

Asked whether it’s expecting growth in freelancing to sustain even after we (hopefully) move beyond the pandemic — including if there’s a return to physical offices — Petersen suggests the underlying trend is for businesses to need increased flexibility, regardless of the exact blend of full-time and freelancer staff. So platforms like Worksome are confidently poised to keep growing.

“When you ask business leaders, 90% believe that shifting their talent model to a blend of full-time and freelancers can give a future competitive advantage (Source: BCG),” he says. “We see two major trends driving this sentiment; access to talent, and building an agile and flexible organization. This has become all the more true during the pandemic — a high degree of flexibility is allowing organisations to better navigate both the initial phase of the pandemic as well the current pick up of business activity.

“With the amount of change that we’re currently seeing in the world, and with businesses are constantly re-inventing themselves, the access to highly skilled and flexible talent is absolutely essential — now, in the next 5 years, and beyond.”


By Natasha Lomas

Microsoft launches Edge Zones for Azure

Microsoft today announced the launch of Azure Edge Zones, which will allow Azure users to bring their applications to the company’s edge locations. The focus here is on enabling real-time low-latency 5G applications. The company is also launching a version of Edge Zones with carriers (starting with AT&T) in preview, which connects these zones directly to 5G networks in the carrier’s data center. And to round it all out, Azure is also getting Private Edge Zones for those who are deploying private 5G/LTE networks in combination with Azure Stack Edge.

In addition to partnering with carriers like AT&T, as well as Rogers, SK Telecom, Telstra and Vodafone, Microsoft is also launching new standalone Azure Edge Zones in more than 10 cities over the next year, starting with L.A., Miami and New York later this summer.

“For the last few decades, carriers and operators have pioneered how we connect with each other, laying the foundation for telephony and cellular,” the company notes in today’s announcement. “With cloud and 5G, there are new possibilities by combining cloud services, like compute and AI with high bandwidth and ultra-low latency. Microsoft is partnering with them bring 5G to life in immersive applications built by organization and developers.”

This may all sound a bit familiar and that’s because only a few weeks ago, Google launched Anthos for Telecom and its Global Mobile Edge Cloud, which at first glance offers a similar promise of bringing applications close to that cloud’s edge locations for 5G and telco usage. Microsoft argues that its offering is more comprehensive in terms of its partner ecosystem and geographic availability. But it’s clear that 5G is a trend all of the large cloud providers are trying to tap into. Microsoft’s own acquisition of 5G cloud specialist Affirmed Networks is yet another example of how it is looking to position itself in this market.

As far as the details of the various Edge Zone versions go, the focus of Edge Zones is mostly on IoT and AI workloads, while Microsoft notes that Edge Zones with Carriers is more about low-latency online gaming, remote meetings and events, as well as smart infrastructure. Private Edge Zones, which combine private carrier networks with Azure Stack Edge, is something only a small number of large enterprise companies is likely to look into, given the cost and complexity of rolling out a system like this.

 


By Frederic Lardinois

Proxyclick raises $15M Series B for its visitor management platform

If you’ve ever entered a company’s office as a visitor or contractor, you probably know the routine: check in with a receptionist, figure out who invited you, print out a badge and get on your merry way. Brussels, Belgium- and New York-based Proxyclick aims to streamline this process, while also helping businesses keep their people and assets secure. As the company announced today, it has raised a $15 million Series B round led by Five Elms Capital, together with previous investor Join Capital.

In total, Proxyclick says it’s systems have now been used to register over 30 million visitors in 7,000 locations around the world. In the UK alone, over 1,000 locations use the company’s tools. Current customers include L’Oreal, Vodafone, Revolut, PepsiCo and Airbnb, as well as a number of other Fortune 500 firms.

Gregory Blondeau, founder and CEO of Proxyclick, stresses that the company believes that paper logbooks, which are still in use in many companies, are simply not an acceptable solution anymore, not in the least because that record is often permanent and visible to other visitors.

Proxyclick’s founding team.

“We all agree it is not acceptable to have those paper logbooks at the entrance where everyone can see previous visitors,” he said. “It is also not normal for companies to store visitors’ digital data indefinitely. We already propose automatic data deletion in order to respect visitor privacy. In a few weeks, we’ll enable companies to delete sensitive data such as visitor photos sooner than other data. Security should not be an excuse to exploit or hold visitor data longer than required.”

What also makes Proxyclick stand out from similar solutions is that it integrates with a lot of existing systems for access control (including C-Cure and Lenel systems). With that, users can ensure that a visitor only has access to specific parts of a building, too.

In addition, though, it also supports existing meeting rooms, calendaring and parking systems and integrates with Wi-Fi credentialing tools so your visitors don’t have to keep asking for the password to get online.

Like similar systems, Proxyclick provides businesses with a tablet-based sign-in service that also allows them to get consent and NDA signatures right during the sign-in process. If necessary, the system can also compare the photos it takes to print out badges with those on a government-issued ID to ensure your visitors are who they say they are.

Blondeau noted that the whole industry is changing, too. “Visitor management is becoming mainstream, it is transitioning from a local, office-related subject handled by facility managers to a global, security and privacy driven priority handled by Chief Information Security Officers. Scope, decision drivers and key people involved are not the same as in the early days,” he said.

It’s no surprise then that the company plans to use the new funding to accelerate its roadmap. Specifically, it’s looking to integrate its solution with more third-party systems with a focus on physical security features and facial recognition, as well as additional new enterprise features.


By Frederic Lardinois

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

Uber and AT&T team up for always-on connectivity for Uber Copter and Uber Air

Uber is partnering with mobile network operator AT&T on the always-on connectivity it’ll require for its aerial transportation service network. The on-demand mobility company announced the team-up at its annual Elevate Summit, which brings together a number of key players working toward making affordable, accessible in-city aerial transit a reality.

Uber said that it’s already working with AT&T on the network it’ll use for Uber Copter, the Manhattan-to-JFK helicopter-based service that it’s launching in New York in July. The service is promising connection with ground transportation at both ends, and it’s also anticipating travel times and working backwards to provide transportation on-demand as needed to get passengers to their destination at the time they request. So, for instance, Uber Copter customers could say they need to be at JFK by 5 PM and the app will figure out when they need to get a car to get to the heliport to make that work.

This is just the first step in a broader-ranging partnership Uber Elevate Head of Product Nikhil Goel described that will eventually scale to cover all of its needs for Uber Air, the service it aims to provide that will provide on-demand short-distance air travel within cities, with a targeted launch time frame of 2023. Goel noted that this will also include leveraging AT&T’s 5G network as it rolls out, which should provide exactly the kind of high-bandwidth, always-on reliability needed for this kind of aerial and ground-based integrated transportation network.


By Darrell Etherington

VCs bet $12M on Troops, a Slackbot for sales teams

Slack wants to be the new operating system for teams, something it has made clear on more than one occasion, including in its recent S-1 filing. To accomplish that goal, it put together an in-house $80 million venture fund in 2015 to invest in third-party developers building on top of its platform.

Weeks ahead of its direct listing on The New York Stock Exchange, it continues to put that money to work.

Troops is the latest to land additional capital from the enterprise giant. The New York-based startup helps sales teams communicate with a customer relationship management tool plugged directly into Slack. In short, it automates routine sales management activities and creates visibility into important deals through integrations with employee emails and Salesforce.

Troops founder and chief executive officer Dan Reich, who previously co-founded TULA Skincare, told TechCrunch he opted to build a Slackbot rather than create an independent platform because Slack is a rocket ship and he wanted a seat on board: “When you think about where Slack will go in the future, it’s obvious to us that companies all over the world will be using it,” he said.

Troops has raised $12 million in Series B funding in a round led by Aspect Ventures, with participation from the Slack Fund, First Round Capital, Felicis Ventures, Susa Ventures, Chicago Ventures, Hone Capital, InVision founder Clark Valberg and others. The round brings Troops’ total raised to $22 million.

Launched in 2015 by New York tech veterans Reich, Scott Britton and Greg Ratner, the trio weren’t initially sure of Slack’s growth trajectory. It wasn’t until Slack confirmed its intent to support the developer ecosystem with a suite of developer tools and a fund that the team focused its efforts on building a Slackbot.

“People sometimes thought of us, at least in the early days, as a little bit crazy,” Reich said. “But now Slack is the fastest-growing SaaS company ever.”

“We think the biggest opportunity in the [enterprise SaaS] category is going to be tools oriented around the customer-facing employee (CRM), and that’s where we are innovating,” he added.

Troops’ tools are helpful for any customer-facing team, Reich explains. Envoy, WeWork, HubSpot and a few hundred others are monthly paying subscribers of the tool, using it to interact with their CRM in a messaging interface and to receive notifications when a deal has closed. Troops integrates with Salesforce, so employees can use it to search records, schedule automatic reports and celebrate company wins.

Slack, in partnership with a number of venture capital funds, including Accel, Kleiner Perkins and Index, has also deployed capital to a number of other startups, like Lattice, Drafted and Loom.

With Slack’s direct listing afoot, the Troops team is counting on the imminent and long-term growth of the company’s platform.

“We think it’s still early days,” Reich said. “In the future, we see every company using something like Troops to manage their day-to-day.”


By Kate Clark

HQ2 fight continues as New York City and Seattle officials hold anti-Amazon summit

The heated debate around Amazon’s recently announced Long Island City “HQ2” is showing no signs of cooling down.

On Monday morning, the Retail, Wholesale and Department Store Union (RWDSU) hosted a briefing in which labor officials, economic development analysts, Amazon employees and elected New York State and City representatives further underlined concerns around the HQ2 process, the awarded incentives, and the potential impacts Amazon’s presence would have on city workers and residents.

While many of the arguments posed at the Summit weren’t necessarily new, the wide variety of stakeholders that showed up to express concern looked to contextualize the far-reaching risks associated with the deal.

The day began with representatives from New York union groups recounting Amazon’s shaky history with employee working conditions and questioning how the city’s working standards will be impacted if the 50,000 promised jobs do actually show up.

Two current employees working in an existing Amazon New York City warehouse in Staten Island provided poignant examples of improper factory conditions and promised employee benefits that never came to fruition. According to the workers, Amazon has yet to follow through on shuttle services and ride-sharing services that were promised to ease worker commutes, forcing the workers to resort to overcrowded and unreliable public transportation. One of the workers detailed that with his now four-hour commute to get to and from work, coupled with his meaningfully long shifts, he’s been unable to see his daughter for weeks.

Various economic development groups and elected officials including, New York City Comptroller Scott Stringer, City Council Speaker Corey Johnson, City Council Member Jimmy Van Bramer, and New York State Senator Mike Gianaris supported the labor arguments with spirited teardowns of the economic terms of the deal.

Like many critics of the HQ2 process, the speakers’ expressed their beliefs that Amazon knew where it wanted to bring its second quarters throughout the entirety of its auction process, given the talent pool and resources in the chosen locations, and that the entire undertaking was meant to squeeze out the best economic terms possible. And according to City Council Speaker Johnson, New York City “got played”.

Comptroller Stringer argued that Amazon is taking advantage of New York’s Relocation and Employment Assistance Program (REAP) and Industrial and Commercial Abatement Program (ICAP), which Stringer described as outdated and in need of reform, to receive the majority of the $2 billion-plus in promised economic incentives that made it the fourth largest corporate incentive deal in US history.

The speakers continued to argue that the unprecedented level of incentives will be nearly impossible to recoup and that New York will also face economic damages from lower sales tax revenue as improved Amazon service in the city cannibalizes local brick & mortar retail.

Fears over how Amazon’s presence will impact the future of New York were given more credibility with the presence of Seattle City Council members Lisa Herbold & Teresa Mosqueda, who had flown to New York from Seattle to discuss lessons learned from having Amazon’s Headquarters in the city and to warn the city about the negative externalities that have come with it.

Herbold and Mosqueda focused less on an outright rejection of the deal but instead emphasized that New York was in a position to negotiate for better terms focused on equality and corporate social responsibility, which could help the city avoid the socioeconomic turnover that has plagued Seattle and could create a new standard for public-private partnerships.

While the New York City Council noted it was looking into legal avenues, the opposition seemed to have limited leverage to push back or meaningfully negotiate the deal. According to state officials, the most clear path to fight the deal would be through votes by the state legislature and through the state Public Authorities Control Board who has to unanimously approve the subsidy package.

With the significant turnout seen at Monday’s summit, which included several high-ranking state and city officials, it seems clear that we’re still in the early innings of what’s likely to be a long battle ahead to close the HQ2 deal.

Amazon did not return requests for immediate comment.


By Arman Tabatabai

Forget Watson, the Red Hat acquisition may be the thing that saves IBM

With its latest $34 billion acquisition of Red Hat, IBM may have found something more elementary than “Watson” to save its flagging business.

Though the acquisition of Red Hat  is by no means a guaranteed victory for the Armonk, N.Y.-based computing company that has had more downs than ups over the five years, it seems to be a better bet for “Big Blue” than an artificial intelligence program that was always more hype than reality.

Indeed, commentators are already noting that this may be a case where IBM finally hangs up the Watson hat and returns to the enterprise software and services business that has always been its core competency (albeit one that has been weighted far more heavily on consulting services — to the detriment of the company’s business).

Watson, the business division focused on artificial intelligence whose public claims were always more marketing than actually market-driven, has not performed as well as IBM had hoped and investors were losing their patience.

Critics — including analysts at the investment bank Jefferies (as early as one year ago) — were skeptical of Watson’s ability to deliver IBM from its business woes.

As we wrote at the time:

Jefferies pulls from an audit of a partnership between IBM Watson and MD Anderson as a case study for IBM’s broader problems scaling Watson. MD Anderson cut its ties with IBM after wasting $60 million on a Watson project that was ultimately deemed, “not ready for human investigational or clinical use.”

The MD Anderson nightmare doesn’t stand on its own. I regularly hear from startup founders in the AI space that their own financial services and biotech clients have had similar experiences working with IBM.

The narrative isn’t the product of any single malfunction, but rather the result of overhyped marketing, deficiencies in operating with deep learning and GPUs and intensive data preparation demands.

That’s not the only trouble IBM has had with Watson’s healthcare results. Earlier this year, the online medical journal Stat reported that Watson was giving clinicians recommendations for cancer treatments that were “unsafe and incorrect” — based on the training data it had received from the company’s own engineers and doctors at Sloan-Kettering who were working with the technology.

All of these woes were reflected in the company’s latest earnings call where it reported falling revenues primarily from the Cognitive Solutions business, which includes Watson’s artificial intelligence and supercomputing services. Though IBM chief financial officer pointed to “mid-to-high” single digit growth from Watson’s health business in the quarter, transaction processing software business fell by 8% and the company’s suite of hosted software services is basically an afterthought for business gravitating to Microsoft, Alphabet, and Amazon for cloud services.

To be sure, Watson is only one of the segments that IBM had been hoping to tap for its future growth; and while it was a huge investment area for the company, the company always had its eyes partly fixed on the cloud computing environment as it looked for areas of growth.

It’s this area of cloud computing where IBM hopes that Red Hat can help it gain ground.

“The acquisition of Red Hat is a game-changer. It changes everything about the cloud market,” said Ginni Rometty, IBM Chairman, President and Chief Executive Officer, in a statement announcing the acquisition. “IBM will become the world’s number-one hybrid cloud provider, offering companies the only open cloud solution that will unlock the full value of the cloud for their businesses.”

The acquisition also puts an incredible amount of marketing power behind Red Hat’s various open source services business — giving all of those IBM project managers and consultants new projects to pitch and maybe juicing open source software adoption a bit more aggressively in the enterprise.

As Red Hat chief executive Jim Whitehurst told TheStreet in September, “The big secular driver of Linux is that big data workloads run on Linux. AI workloads run on Linux. DevOps and those platforms, almost exclusively Linux,” he said. “So much of the net new workloads that are being built have an affinity for Linux.”


By Jonathan Shieber

NYC wants to build a cyber army

Empires rise and fall, and none more so than business empires. Whole industries that once dominated the planet are just a figment in memory’s eye, while new industries quietly grow into massive behemoths.

New York City has certainly seen its share of empires. Today, the city is a global center of finance, real estate, legal services, technology, and many, many more industries. It hosts the headquarters of roughly 10% of the Fortune 500, and the metro’s GDP is roughly equivalent to that of Canada.

So much wealth and power, and all under constant attack. The value of technology and data has skyrocketed, and so has the value of stealing and disrupting the services that rely upon it. Cyber crime and cyber wars are adding up: according to a report published jointly between McAfee and the Center for Strategic and International Studies, the costs of these operations are in the hundreds of billions of dollars – and New York’s top industries such as financial services bare the brunt of the losses.

Yet, New York City has hardly been a bastion for the cybersecurity industry. Boston and Washington DC are far stronger today on the Acela corridor, and San Francisco and Israel have both made huge impacts on the space. Now, NYC’s leaders are looking to build a whole new local empire that might just act as a bulwark for its other leading ecosystems.

Today, the New York City Economic Development Corporation (NYCEDC) announced the launch of Cyber NYC, a $30 million “catalyzing” investment designed to rapidly grow the city’s ecosystem and infrastructure for cybersecurity.

James Patchett, CEO of New York City Economic Development Corporation. (Photo from NYCEDC)

James Patchett, CEO of NYCEDC, explained in an interview with TechCrunch that cybersecurity is “both an incredible opportunity and also a huge threat.” He noted that “the financial industry has been the lifeblood of this city for our entire history,” and the costs of cybercrime are rising quickly. “It’s a lose-lose if we fail to invest in the innovation that keeps the city strong” but “it’s a win if we can create all of that innovation here and the corresponding jobs,” he said.

The Cyber NYC program is made up of a constellation of programs:

  • Partnering with Jerusalem Venture Partners, an accelerator called Hub.NYC will develop enterprise cybersecurity companies by connecting them with advisors and customers. The program will be hosted in a nearly 100,000 square foot building in SoHo.
  • Partnering with SOSA, the city will create a new, 15,000 square foot Global Cyber Center co-working facility in Chelsea, where talented individuals in the cyber industry can hang out and learn from each other through event programming and meetups.
  • With Fullstack Academy and Laguardia Community College, a Cyber Boot Camp will be created to enhance the ability of local workers to find jobs in the cybersecurity space.
  • Through an “Applied Learning Initiative,” students will be able to earn a “CUNY-Facebook Master’s Degree” in cybersecurity. The program has participation from the City University of New York, New York University, Columbia University, Cornell Tech, and iQ4.
  • With Columbia University’s Technology Ventures, NYCEDC will introduce a program called Inventors to Founders that will work to commercialize university research.

NYCEDC’s map of the NYC Cyber initiative. (Photo from NYCEDC)

In addition to Facebook, other companies have made commitments to the program, including Goldman Sachs, MasterCard, PricewaterhouseCoopers, and edX.org. Two Goldman execs, Chief Operational Risk Officer Phil Venables and Chief Information Security Officer Andy Ozment, have joined the initiative’s advisory boards.

The NYCEDC estimates that there are roughly 6,000 cybersecurity professionals currently employed in New York City. Through these programs, it estimates that the number could increase by another 10,000. Patchett said that “it is as close to a no-brainer in economic development because of the opportunity and the risk.”

From Jerusalem to New York

To tackle its ambitious cybersecurity goals, the NYCEDC is partnering with two venture firms, Jerusalem Venture Partners (JVP) and SOSA, with significant experience investing, operating, and growing companies in the sector.

Jerusalem-based JVP is an established investor that should help founders at Hub.NYC get access to smart capital, sector expertise, and the entrepreneurial experience needed to help their startups scale. JVP invests in early-, late-, and growth-stage companies focused on cybersecurity, big data, media, and enterprise software.

JVP will run Hub.NYC, a startup accelerator that will help cybersecurity startups connect with customers and mentors. (Photo from JVP)

Erel Margalit, who founded the firm in 1993, said that “If you look at what JVP has done … we create ecosystems.” Working with Jerusalem’s metro government, Margalit and the firm pioneered a number of institutions such as accelerators that turned Israel into an economic powerhouse in the cybersecurity industry. His social and economic work eventually led him to the Knesset, Israel’s unicameral legislature, where he served as an MP from 2015-2017 with the Labor Party.

Israel is a very small country with a relative dearth of large companies though, a huge challenge for startups looking to scale up. “Today if you want to build the next-generation leading companies, you have to be not only where the ideas are being brewed, but also where the solutions are being [purchased],” Margalit explained. “You need to be working with the biggest customers in the world.”

That place, in his mind, is New York City. It’s a city he has known since his youth – he worked at Moshe’s Moving IN NYC while attending Columbia as a grad student where he got his PhD in philosophy. Now, he can pack up his own success from Israel and scale it up to an even larger ecosystem.

Since its founding, JVP has successfully raised $1.1 billion across eight funds, including a $60 million fund specifically focused on the cybersecurity space. Over the same period, the firm has seen 32 successful exits, including cybersecurity companies CyberArk (IPO in 2014) and CyActive (Acquired by PayPal in 2013).

JVP’s efforts in the cybersecurity space also go beyond the investment process, with the firm recently establishing an incubator, known as JVP Cyber Labs, specifically focused on identifying, nurturing and building the next wave of Israeli cybersecurity and big data companies.

On average, the firm has focused on deals in the $5-$10 million range, with a general proclivity for earlier-stage companies where the firm can take a more hands-on mentorship role. Some of JVP’s notable active portfolio companies include Source Defense, which uses automation to protect against website supply chain attacks, ThetaRay, which uses big data to analyze threats, and Morphisec, which sells endpoint security solutions.

Opening up innovation with SOSA

The self-described “open-innovation platform,” SOSA is a global network of corporations, investors, and entrepreneurs that connects major institutions with innovative startups tackling core needs.

SOSA works closely with its partner startups, providing investor sourcing, hands-on mentorship and the physical resources needed to achieve growth. The group’s areas of expertise include cybersecurity, fintech, automation, energy, mobility, and logistics. Though headquartered in Tel Aviv, SOSA recently opened an innovation lab in New York, backed by major partners including HP, RBC, and Jefferies.

With the eight-floor Global Cyber Center located in Chelsea, it is turning its attention to an even more ambitious agenda. Uzi Scheffer, CEO of SOSA, said to TechCrunch in a statement that “The Global Cyber Center will serve as a center of gravity for the entire cybersecurity industry where they can meet, interact and connect to the finest talent from New York, the States, Israel and our entire global network.”

SOSA’s new building in Chelsea will be a center for the cybersecurity community (Photo from SOSA)

With an already established presence in New York, SOSA’s local network could help spur the local corporate participation key to the EDC’s plan, while SOSA’s broader global network can help achieve aspirations of turning New York City into a global cybersecurity leader.

It is no coincidence that both of the EDC’s venture partners are familiar with the Israeli cybersecurity ecosystem. Israel has long been viewed as a leader in cybersecurity innovation and policy, and has benefited from the same successful public-private sector coordination New York hopes to replicate.

Furthermore, while New York hopes to create organic growth within its own local ecosystem, the partnerships could also benefit the city if leading Israeli cybersecurity companies look to relocate due to the limited size of the Israeli market.

Big plans, big results?

While we spent comparatively less time discussing them, the NYCEDC’s educational programs are particularly interesting. Students will be able to take classes at any university in the five-member consortium, and transfer credits freely, a concept that the NYCEDC bills as “stackable certificates.”

Meanwhile, Facebook has partnered with the City University of New York to create a professional master’s degree program to train up a new class of cybersecurity leaders. The idea is to provide a pathway to a widely-respected credential without having to take too much time off of work. NYCEDC CEO Patchett said, ”you probably don’t have the time to take two years off to do a masters program,” and so the program’s flexibility should provide better access to more professionals.

Together, all of these disparate programs add up to a bold attempt to put New York City on the map for cybersecurity. Talent development, founder development, customer development – all have been addressed with capital and new initiatives.

Will the community show up at initiatives like the Global Cyber Center, pictured here? (Photo from SOSA)

Yet, despite the time that NYCEDC has spent to put all of these partners together cohesively under one initiative, the real challenge starts with getting the community to participate and build upon these nascent institutions. “What we hear from folks a lot of time,” Patchett said to us, is that “there is no community for cyber professionals in New York City.” Now the buildings have been placed, but the people need to walk through the front doors.

The city wants these programs to be self-sustaining as soon as possible. “In all cases, we don’t want to support these ecosystems forever,” Patchett said. “If we don’t think they’re financially sustainable, we haven’t done our job right.” He believes that “there should be a natural incentive to invest once the ecosystem is off the ground.”

As the world encounters an ever increasing array of cyber threats, old empires can falter – and new empires can grow. Cybersecurity may well be one of the next great industries, and it may just provide the needed defenses to ensure that New York City’s other empires can live another day.


By Arman Tabatabai