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Main article: Natural language processing

<< Back Forward >>
Topics from 1 to 10 | in all: 102

Lightspeed leads Laiye’s $42M round to bet on Chinese enterprise IT

06:49 | 24 February

Laiye, a Chinese startup that offers robotic process automation services to several major tech firms in the nation and government agencies, has raised $42 million in a new funding round as it looks to scale its business.

The new financing round, Series C, was co-led by Lightspeed Venture Partners and Lightspeed China Partners. Cathay Innovation, which led the startup’s Series B+ round and Wu Capital, which led the Series B round, also participated in the new round.

China has been the hub for some of the cheapest labor in the world. But in recent years, a number of companies and government agencies have started to improve their efficiency with the help of technology.

That’s where Laiye comes into play. Robotic process automation (RPA) allows software to mimic several human behaviors such as keyboard strokes and mouse clicks.

“For instance, a number of banks did not previously offer APIs, so humans had to sign in and fetch the data and then feed it into some other software. Processes like these could be automated by our platform,” said Arvid Wang, co-founder and co-chief executive of Laiye, in an interview with TechCrunch.

The four-and-a-half-year-old startup, which has raised more than $100 million to date, will use the fresh capital to hire talent from across the globe and expand its services. “We believe robotic process automation will achieve its full potential when it combines AI and the best human talent,” he said.

Laiye’s announcement today comes as the market for robotic automation process is still in nascent stage in China. There are a handful of startups looking into this space, but Laiye, which counts Microsoft as an investor, and Sequoia-backed UiPath are the two clear leaders in the market currently.

As my colleague Rita Liao wrote last year, it was only recently that some entrepreneurs and investors in China started to shift their attention from consumer-facing products to business applications.

Globally, RPA has emerged as the fastest growing market in enterprise space. A Gartner report found last year that RPA market grew over 63% in 2018. Recent surveys have shown that most enterprises in China today are also showing interest in enhancing their RPA projects and AI capabilities.

Laiye today has more than 200 partners and more than 200,000 developers have registered to use its multilingual UiBot RPA platform. UiBot enables integration with Laiye’s native and third-party AI capabilities such as natural language processing, optical character recognition, computer vision, chatbot and machine learning.

“We are very bullish on China, and the opportunities there are massive,” said Lightspeed partner Amy Wu in an interview. “Laiye is doing phenomenally there, and with this new fundraise, they can look to expand globally,” she said.

 


0

European founders look to new markets, aim for profitability

09:47 | 12 February

To get a better sense of what lies ahead for the European startup ecosystem, we spoke to several investors and entrepreneurs in the region about their impressions and lessons learned from 2019, along with their predictions for 2020.

We asked for blunt responses — and we weren’t disappointed.

These responses have been edited for clarity and length.


Kenny Ewan, founder/CEO, Wefarm (London)

I’ve often been faced with questions around how we can generate revenue in markets like Africa. There has historically been a view that you can do something good, or you can generate revenue — and companies that talk about developing markets usually get squarely lumped into the former. While mission-led companies achieving tremendous growth has been talked about for a while, 2019 has been a year I have felt conversations with investors and others really begin to shift to the reality of that and it’s thanks to more and more proof points being delivered by startups across the board.

As more and more businesses begin to realize they don’t need to wait for the internet to descend from the sky for these markets to become hubs of commerce and innovation — and see that it’s already happening — I believe 2020 will continue to witness more and more historic tech companies shifting their focus to markets like Africa and that there will be more coverage and discussion as a result.

 


0

Fable Studio founder Edward Saatchi on designing virtual beings

19:42 | 20 January

In films, TV shows and books — and even in video games where characters are designed to respond to user behavior — we don’t perceive characters as beings with whom we can establish two-way relationships. But that’s poised to change, at least in some use cases.

Interactive characters — fictional, virtual personas capable of personalized interactions — are defining new territory in entertainment. In my guide to the concept of “virtual beings,” I outlined two categories of these characters:

  • virtual influencers: fictional characters with real-world social media accounts who build and engage with a mass following of fans.
  • virtual companions: AIs oriented toward one-to-one relationships, much like the tech depicted in the films “Her” and “Ex Machina.” They are personalized enough to engage us in entertaining discussions and respond to our behavior (in the physical world or within games) like a human would.

Part 3 of 3: designing virtual companions

In this discussion, Fable CEO Edward Saatchi addresses the technical and artistic dynamics of virtual companions: AIs created to establish one-to-one relationships with consumers. After mobile, Saatchi says he believes such virtual beings will act as the next paradigm for human-computer interaction.

 


0

Compound’s Mike Dempsey on virtual influencers and AI characters

19:27 | 18 January

In films, TV shows and books — and even in video games where characters are designed to respond to user behavior — we don’t perceive characters as beings with whom we can establish two-way relationships. But that’s poised to change, at least in some use cases.

Interactive characters — fictional, virtual personas capable of personalized interactions — are defining new territory in entertainment. In my guide to the concept of “virtual beings,” I outlined two categories of these characters:

  • virtual influencers: fictional characters with real-world social media accounts who build and engage with a mass following of fans.
  • virtual companions: AIs oriented toward one-to-one relationships, much like the tech depicted in the films “Her” and “Ex Machina.” They are personalized enough to engage us in entertaining discussions and respond to our behavior (in the physical world or within games) like a human would.

Part 1 of 3: the investor perspective

In a series of three interviews, I’m exploring the startup opportunities in both of these spaces in greater depth. First, Michael Dempsey, a partner at VC firm Compound who has blogged extensively about digital characters, avatars and animation, offers his perspective as an investor hunting for startup opportunities within these spaces.

 


0

Hugging Face raises $15 million to build the definitive natural language processing library

19:26 | 17 December

Hugging Face has raised a $15 million funding round led by Lux Capital. The company first built a mobile app that let you chat with an artificial BFF, a sort of chatbot for bored teenagers. More recently, the startup released an open-source library for natural language processing applications. And that library has been massively successful.

A.Capital, Betaworks, Richard Socher, Greg Brockman, Kevin Durant and others are also participating in today’s funding round.

Hugging Face launched its original chatbot app back in early 2017. After months of work, the startup wanted to prove that chatbots don’t have to be a glorified command line interface for customer support.

With the app, you could generate a digital friend and text back and forth with your companion. And it wasn’t just about understanding what you meant — the app tried to detect your emotions to adapt answers based on your feelings.

It turns out that the technology behind that chatbot app is solid. As Brandon Reeves from Lux Capital wrote, there’s been a ton of progress when it comes to computer vision and image processing, but natural language processing has been lagging behind.

Hugging Face’s open-source framework Transformers has been downloaded over a million times. The Github project has amassed 19,000 stars, proving that the open-source community thinks this is a useful brick to build upon. Researchers at Google, Microsoft and Facebook has been playing around with it.

Some companies even use it in production, such as challenger bank Monzo for its customer support chatbot and Microsoft Bing. You can leverage Transformers for text classification, information extraction, summarization, text generation and conversational artificial intelligence.

With today’s funding round, the company plans to triple its headcount in New York and Paris.

 


0

These new data sources are creating high-impact tools for investors

22:39 | 4 December

David Teten Contributor
David Teten is an advisor to emerging investment managers and a Venture Partner with HOF Capital. He was previously a partner for 8 years with HOF Capital and ff Venture Capital. David writes regularly at teten.com and @dteten.

Venture capitalists tout themselves as frontier technology investors, but most of us are using the same infrastructure tools we’ve used for the past 20+ years — Excel and recent college grads searching Google .

We’ve seen some modest progress in people upgrading from Excel to Google Sheets, along with the use of CRM and cloud-based storage services, but according to Sebastian Soler, who oversees data science at Lux Capital, less than 5% of American VCs have a full-time team member who’s focused on technology.

“While the arguments for adopting the latest technology are now too compelling to ignore, finding the required budget for specialized tools can often prove to be a major challenge, especially for smaller managers,” said Tim Friedman, founder of PEStack. “Comprehensive market data can cost upwards of $25k for a leading service, portfolio monitoring can be double that, add in front office tools and you’re quickly into six-figure sums. My advice is: there are now more products than ever which focus on quick implementation and offer a lot of functionality at a fraction of the cost of some of the larger legacy providers.

TotemVC* is one example of a high-quality solution that offers a powerful platform with a transparent, affordable monthly rate. One piece of advice would be to use a service like [PEStack’s] free Vendor Profiles platform to identify viable providers and build up a shortlist. We also track sample clients so that our users can see what their peers are using. I would always advise managers to talk to other professionals to get the real inside scoop on which products work well, how painful the implementation was, and how good the ongoing support is.”

Jonathan Balkin, founder of Lionpoint Group, observed that the highest-impact technology initiative for a new PE/VC fund is typically to configure and enforce usage of a CRM system. The next most impactful initiative is usually to create an easy-to-use LP portal.

 


0

Alexa, where are the legal limits on what Amazon can do with my health data?

13:46 | 24 October

The contract between the UK’s National Health Service (NHS) and ecommerce giant Amazon — for a health information licensing partnership involving its Alexa voice AI — has been released following a Freedom of Information request.

The government announced the partnership this summer. But the date on the contract, which was published on the gov.uk contracts finder site months after the FOI was filed, shows the open-ended arrangement to funnel nipped-and-tucked health advice from the NHS’ website to Alexa users in audio form was inked back in December 2018.

The contract is between the UK government and Amazon US (Amazon Digital Services, Delaware) — rather than Amazon UK. 

Nor is it a standard NHS Choices content syndication contract. A spokeswoman for the Department of Health and Social Care (DHSC) confirmed the legal agreement uses an Amazon contract template. She told us the department had worked jointly with Amazon to adapt the template to fit the intended use — i.e. access to publicly funded healthcare information from the NHS’ website.

The NHS does make the same information freely available on its website, of course. As well as via API — to some 1,500 organizations. But Amazon is not just any organization; It’s a powerful US platform giant with a massive ecommerce business.

The contract reflects that power imbalance; not being a standard NHS content syndication agreement — but rather DHSC tweaking Amazon’s standard terms.

“It was drawn up between both Amazon UK and the Department for Health and Social Care,” a department spokeswoman told us. “Given that Amazon is in the business of holding standard agreements with content providers they provided the template that was used as the starting point for the discussions but it was drawn up in negotiation with the Department for Health and Social Care, and obviously it was altered to apply to UK law rather than US law.”

In July, when the government officially announced the Alexa-NHS partnership, its PR provided a few sample queries of how Amazon’s voice AI might respond to what it dubbed “NHS-verified” information — such as: “Alexa, how do I treat a migraine?”; “Alexa, what are the symptoms of flu?”; “Alexa, what are the symptoms of chickenpox?”.

But of course as anyone who’s ever googled a health symptom could tell you, the types of stuff people are actually likely to ask Alexa — once they realize they can treat it as an NHS-verified info-dispensing robot, and go down the symptom-querying rabbit hole — is likely to range very far beyond the common cold.

At the official launch of what the government couched as a ‘collaboration’ with Amazon, it explained its decision to allow NHS content to be freely piped through Alexa by suggesting that voice technology has “the potential to reduce the pressure on the NHS and GPs by providing information for common illnesses”.

Its PR cited an unattributed claim that “by 2020, half of all searches are expected to be made through voice-assisted technology”.

This prediction is frequently attributed to ComScore, a media measurement firm that was last month charged with fraud by the SEC. However it actually appears to originate with computer scientist Andrew Ng, from when he was chief scientist at Chinese tech giant Baidu.

Econsultancy noted last year that Mary Meeker included Ng’s claim on a slide in her 2016 Internet Trends report — which is likely how the prediction got so widely amplified.

But on Meeker’s slide you can see that the prediction is in fact “images or speech”, not voice alone…

Screenshot 2019 10 24 at 10.04.40

So it turns out the UK government incorrectly cited a tech giant prediction to push a claim that “voice search has been increasing rapidly” — in turn its justification for funnelling NHS users towards Amazon.

“We want to empower every patient to take better control of their healthcare and technology like this is a great example of how people can access reliable, world-leading NHS advice from the comfort of their home, reducing the pressure on our hardworking GPs and pharmacists,” said health secretary Matt Hancock in a July statement.

Since landing at the health department, the app-loving former digital minister has been pushing a tech-first agenda for transforming the NHS — promising to plug in “healthtech” apps and services, and touting “preventative, predictive and personalised care”. He’s also announced an AI lab housed within a new unit that’s intended to oversee the digitization of the NHS.

Compared with all that, plugging the NHS’ website into Alexa probably seems like an easy ‘on-message’ win. But immediately the collaboration was announced concerns were raised that the government is recklessly mixing the streams of critical (and sensitive) national healthcare infrastructure with the rapacious data-appetite of a foreign tech giant with both an advertising and ecommerce business, plus major ambitions of its own in the healthcare space.

On the latter front, just yesterday news broke of Amazon’s second health-related acquisition: Health Navigator, a startup with an API platform for integrating with health services, such as telemedicine and medical call centers, which offers natural language processing tools for documenting health complaints and care recommendations.

Last year Amazon also picked up online pharmacy PillPack — for just under $1BN. While last month it launched a pilot of a healthcare service offering to its own employees in and around Seattle, called Amazon Care. That looks intended to be a road-test for addressing the broader U.S. market down the line. So the company’s commercial designs on healthcare are becoming increasingly clear.

Returning to the UK, in response to early critical feedback on the Alexa-NHS arrangement, the IT delivery arm of the service, NHS Digital, published a blog post going into more detail about the arrangement — following what it couched as “interesting discussion about the challenges for the NHS of working with large commercial organisations like Amazon”.

A core critical “discussion” point is the question of what Amazon will do with people’s medical voice query data, given the partnership is clearly encouraging people to get used to asking Alexa for health advice.

“We have stuck to the fundamental principle of not agreeing a way of working with Amazon that we would not be willing to consider with any single partner – large or small. We have been careful about data, commercialisation, privacy and liability, and we have spent months working with knowledgeable colleagues to get it right,” NHS Digital claimed in July.

In another section of the blog post, responding to questions about what Amazon will do with the data and “what about privacy”, it further asserted there would be no health profiling of customers — writing:

We have worked with the Amazon team to ensure that we can be totally confident that Amazon is not sharing any of this information with third parties. Amazon has been very clear that it is not selling products or making product recommendations based on this health information, nor is it building a health profile on customers. All information is treated with high confidentiality. Amazon restrict access through multi-factor authentication, services are all encrypted, and regular audits run on their control environment to protect it.

Yet it turns out the contract DHSC signed with Amazon is just a content licensing agreement. There are no terms contained in it concerning what can or can’t be done with the medical voice query data Alexa is collecting with the help of “NHS-verified” information.

Per the contract terms, Amazon is required to attribute content to the NHS when Alexa responds to a query with information from the service’s website. (Though the company says Alexa also makes use of medical content from the Mayo Clinic and Wikipedia.) So, from the user’s point of view, they will at times feel like they’re talking to an NHS-branded service.

But without any legally binding confidentiality clauses around what can be done with their medical voice queries it’s not clear how NHS Digital can confidently assert that Amazon isn’t creating health profiles.

The situation seems to sum to, er, trust Amazon. (NHS Digital wouldn’t comment; saying it’s only responsible for delivery not policy setting, and referring us to the DHSC.)

Asked what it does with medical voice query data generated as a result of the NHS collaboration an Amazon spokesperson told us: “We do not build customer health profiles based on interactions with nhs.uk content or use such requests for marketing purposes.”

But the spokesperson could not point to any legally binding contract clauses in the licensing agreement that restrict what Amazon can do with people’s medical queries.

We’ve also asked the company to confirm whether medical voice queries that return NHS content are being processed in the US.

“This collaboration only provides content already available on the NHS.UK website, and absolutely no personal data is being shared by NHS to Amazon or vice versa,” Amazon also told us, eliding the key point that it’s not NHS data being shared with Amazon but NHS users, reassured by the presence of a trusted public brand, being encouraged to feed Alexa sensitive personal data by asking about their ailments and health concerns.

Bizarrely, the Department of Health and Social Care went further. Its spokeswoman claimed in an email that “there will be no data shared, collected or processed by Amazon and this is just an alternative way of providing readily available information from NHS.UK.”

When we spoke to DHSC on the phone prior to this, to raise the issue of medical voice query data generated via the partnership and fed to Amazon — also asking where in the contract are clauses to protect people’s data — the spokeswoman said she would have to get back to us.

All of which suggests the government has a very vague idea (to put it generously) of how cloud-powered voice AIs function.

Presumably no one at DHSC bothered to read the information on Amazon’s own Alexa privacy page — although the department spokeswomen was at least aware this page existed (because she knew Amazon had pointed us to what she called its “privacy notice”, which she said “sets out how customers are in control of their data and utterances”).

If you do read the page you’ll find Amazon offers some broad-brush explanation there which tells you that after an Alexa device has been woken by its wake word, the AI will “begin recording and sending your request to Amazon’s secure cloud”.

Ergo data is collected and processed. And indeed stored on Amazon’s servers. So, yes, data is ‘shared’.

The more detailed Alexa Internet Privacy Notice, meanwhile, sets out broad-brush parameters to enable Amazon’s reuse of Alexa user data — stating that “the information we learn from users helps us personalize and continually improve your Alexa experience and provide information about Internet trends, website popularity and traffic, and related content”. [emphasis ours]

The DHSC sees the matter very differently, though.

With no contractual binds covering health-related queries UK users of Alexa are being encouraged to whisper into Amazon’s robotic ears — data that’s naturally linked to Alexa and Amazon account IDs (and which the Alexa Internet Privacy Notice also specifies can be accessed by “a limited number of employees”) — the government is accepting the tech giant’s standard data processing terms for a commercial, consumer product which is deeply integrated into its increasingly sprawling business empire.

Terms such as indefinite retention of audio recordings — unless users pro-actively request that they are deleted. And even then Amazon admitted this summer it doesn’t always delete the text transcripts of recordings. So even if you keep deleting all your audio snippets, traces of medical queries may well remain on Amazon’s servers.

Earlier this year it also emerged the company employs contractors around the world to listen in to Alexa recordings as part of internal efforts to improve the performance of the AI.

A number of tech giants recently admitted to the presence of such ‘speech grading’ programs, as they’re sometimes called — though none had been up front and transparent about the fact their shiny AIs needed an army of external human eavesdroppers to pull off a show of faux intelligence.

It’s been journalists highlighting the privacy risks for users of AI assistants; and media exposure leading to public pressure on tech giants to force changes to concealed internal processes that have, by default, treated people’s information as an owned commodity that exists to serve and reserve their own corporate interests.

Data protection? Only if you interpret the term as meaning your personal data is theirs to capture and that they’ll aggressively defend the IP they generate from it.

So, in other words, actual humans — both employed by Amazon directly and not — may be listening to the medical stuff you’re telling Alexa. Unless the user finds and activates a recently added ‘no human review’ option buried in Alexa settings.

Many of these arrangements remain under regulatory scrutiny in Europe. Amazon’s lead data protection regulator in Europe confirmed in August it’s in discussions with it over concerns related to its manual reviews of Alexa recordings. So UK citizens — whose taxes fund the NHS — might be forgiven for expecting more care from their own government around such a ‘collaboration’.

Rather than a wholesale swallowing of tech giant T&Cs in exchange for free access to the NHS brand and  “NHS-verified” information which helps Amazon burnish Alexa’s utility and credibility, allowing it to gather valuable insights for its commercial healthcare ambitions.

To date there has been no recognition from DHSC the government has a duty of care towards NHS users as regards potential risks its content partnership might generate as Alexa harvests their voice queries via a commercial conduit that only affords users very partial controls over what happens to their personal data.

Nor is DHSC considering the value being generously gifted by the state to Amazon — in exchange for a vague supposition that a few citizens might go to the doctor a bit less if a robot tells them what flu symptoms look like.

“The NHS logo is supposed to mean something,” says Sam Smith, coordinator at patient data privacy advocacy group, MedConfidential — one of the organizations that makes use of the NHS’ free APIs for health content (but which he points out did not write its own contract for the government to sign).

“When DHSC signed Amazon’s template contract to put the NHS logo on anything Amazon chooses to do, it left patients to fend for themselves against the business model of Amazon in America.”

In a related development this week, Europe’s data protection supervisor has warned of serious data protection concerns related to standard contracts EU institutions have inked with another tech giant, Microsoft, to use its software and services.

The watchdog recently created a strategic forum that’s intended to bring together the region’s public administrations to work on drawing up standard contracts with fairer terms for the public sector — to shrink the risk of institutions feeling outgunned and pressured into accepting T&Cs written by the same few powerful tech providers.

Such an effort is sorely needed — though it comes too late to hand-hold the UK government into striking more patient-sensitive terms with Amazon US.

 


0

Jobpal pockets $2.7M for its enterprise recruitment chatbot

09:00 | 1 October

Berlin-based recruitment chatbot startup Jobpal has closed a €2.5 million (~$2.7M) seed round of funding from InReach Ventures and Acadian Ventures.

The company, which was founded back in 2016, has built a cross-platform chatbot to automate candidate support and increase efficiency around hiring by applying machine learning and natural language processing for what it dubs “talent interaction”.

The target customers are large enterprises with Jobpal offering the product as a managed service.

For these employers the pitch is increased efficiency by being able to rapidly respond to and engage potential job applicants whenever they’re reaching out for more info via an always-on channel (i.e. the chatbot) which is primed to respond to common questions.

Candidates can also apply for vacancies via the Jobpal chatbot by answering a series of questions in the familiar messaging thread format. Jobpal says its chatbot can also be used to screen applicants’ CVs and recommend the most promising candidates.

It takes care of the logistical legwork of scheduling interview appointments — leaving HR departments with more time to spend on more meaningful portions of the recruitment process.

Co-founder and CEO Luc Dudler tells TechCrunch it has more than 30 enterprise clients at this stage, generating “thousands of conversations” per day. Customers he name checks include the likes of Airbus, Deutsche Telekom and McDonald’s.

The software works on popular messaging platforms including WhatsApp, Facebook Messenger, WeChat and SMS, and is available in 15+ languages — though Jobpal confirms the German market remains its largest so far.

“The sheer volume of interest and number of questions enterprises receive from prospective talent is often difficult to deal with, which results in a suboptimal experience and frustrated candidates. Conversational interfaces and Natural Language Processing enable us to deliver a candidate-centric experience and increase the efficiency of the recruiting function,” says Dudler, arguing that the recruitment landscape has become “candidate first” — putting the onus on enterprises to get the “candidate experience” right.

“This technology allows employers to engage with candidates when they want and on the platforms they use, such as WhatsApp. This gives control to the candidates, meaning they can get answers in a matter of seconds, instead of days or weeks. For Internal HR teams, they can spend time more time finding the best talent, as jobpal automates tedious and time-consuming tasks, allowing recruitment teams to focus on more value-add tasks.”

“We focus mainly on communication and engagement, and our customers only do in-house recruitment. We don’t work with agencies,” he adds.

Jobpal points to increased engagement from use of its chatbot — claiming companies are seeing more queries from jobseekers than they used to receive emails, as well as arguing the “low-friction” approach is accessible and convenient and leads to increased conversion rates.

With any automated process there could be a risk of biased and unequitable outcomes — depending on the criteria the chatbot is using to sift candidates. Although Jobpal says it’s not using algorithms to take recruitment decisions, so the biggest bias risk looks to be in the hands of the employers setting the criteria.

Misinterpretation of candidates’ queries based on the technology failing to understand what’s being asked could potentially lead to responses that disproportionately disadvantage certain applicants. Though Jobpal says queries that are too complex are routed to a human to deal with.

“We get a lot of queries about the application process/deadline/evaluation, qualifications needed, supporting documents, working hours, growth options and salary that Jobpal is designed to deal with,” says Dudler, of Jobpal candidate users. “Our chatbots don’t answer questions that are too personal, too obscure or anything non-recruitment related such as customer service queries.”

“Jobpal stores the query data but it’s de-associated from the candidate data. This data is used to train AI models which supports general communication as well as company-specific chatbots. We don’t mine or sell candidate profiles, and we don’t do algorithmic decision making in the recruitment process,” he adds.

The software integrates with a number of enterprise Human Capital Management suites at this point, including SAP SuccessFactors, Workday, Oracle (formerly Taleo), Avature and Smartrecruiters.

The seed round follows what Dudler couches as “a huge increase in demand” — with the team spying an opportunity for further growth.

“We’ll be investing in product development and tripling our headcount in the next 12 months. Specifically, we are looking to recruit a VP of marketing,” he tells us.

Chatbots still strike many consumers as robotic — and even irritating — but the technology has nonetheless been flourishing in the customer support and recruitment space for several years now. Business areas where there’s no shortage of repetitive tasks for automating. And where being able to offer some level of service 24/7 is a major plus.

On the hiring front, the power imbalance between employer and job applicant might even make interfacing with a bot more appealing for a candidate than the pressure of talking to an actual human who already works at the target employer.

For certain types of jobs employee churn can also be incredibly high — making hiring essentially a neverending task. Again, chatbots are a natural fit in such a scenario; being scalable, they take the strain out of repeat and formulaic conversations — with the promise of a smooth pipeline of candidate conversions.

Given all that there’s now no shortage of recruitment chatbots touting automated support for HR departments. At the same time there’s unlikely to ever be a one-size fits all approach to the hiring problem. It’s a multifaceted, multi-dimensional challenge on account of the spectrum of work that exists and jobs to be filled, and indeed the human variety of jobseekers.

This is why there are so many different ‘flavors’ and ‘styles’ of chatbots offering to assist, some with algorithmic matching, and/or targeting different types of employers and/or jobs/industry (or indeed jobseekers; passive vs active) — others just super basic tools (such as the Jobo bot which alerts jobseekers to vacancies matching criteria they’ve specified).

Some more sophisticated chatbot examples include MeetFrank (passive job matching); Mya (for recruiting agencies and massive enterprises, including for shift filling); Vahan (low skilled, blue-collar job-matching for high attrition delivery jobs); and AllyO (conversational AI for “end-to-end HR management”).

While a few recruitment chatbots that are closer to what Jobpal is offering include the likes of IdealBrazen and Xor, to name three.

With so much chatbot competition pledging to ‘streamline recruitment’ by applying automation to the hiring task, employers might be forgiven for thinking they have a fresh choice headache on their hands.

But for startups applying AI technology to ‘fix recruitment’ by making talk cheap (and structured), the patchwork of players and approaches still in play suggests there’s ongoing opportunity to grab a slice of a truly massive market. 

 


0

Private search engine Qwant’s new CEO is Mozilla Europe veteran Tristan Nitot

09:00 | 19 September

French startup Qwant, whose non-tracking search engine has been gaining traction in its home market as a privacy-respecting alternative to Google, has made a change to its senior leadership team as it gears up for the next phase of growth.

Former Mozilla Europe president, Tristan Nitot, who joined Qwant last year as VP of advocacy, has been promoted to chief executive, taking over from François Messager — who also joined in 2018 but is now leaving the business. Qwant co-founder, Eric Leandri, meanwhile, continues in the same role as president.

Nitot, an Internet veteran who worked at Netscape and helped to found Mozilla Europe in 1998, where he later served as president and stayed until 2015 before leaving to write a book on surveillance, brings a wealth of experience in product and comms roles, as well as open source.

Most recently he spent several years working for personal cloud startup, Cozy Cloud.

“I’m basically here to help [Leandri] grow the company and structure the company,” Nitot tells TechCrunch, describing Qwant’s founder as an “amazing entrepreneur, audacious and visionary”.

Market headwinds have been improving for the privacy-focused Google rival in recent years as concern about foreign data-mining tech giants has stepped up in Europe.

Last year the French government announced it would be switching its search default from Google to Qwant. Buying homegrown digital tech now apparently seen as a savvy product choice as well as good politics.

Meanwhile antitrust attention on dominant search giant Google, both at home and abroad, has led to policy shifts that directly benefit search rivals — such as an update of the default lists baked into its chromium engine which was quietly put out earlier this year.

That behind the scenes change saw Qwant added as an option for users in the French market for the first time. (On hearing the news a sardonic Leandri thanked Google — but suggested Qwant users choose Firefox or the Brave browser for a less creepy web browsing experience.)

“A lot of companies and institutions have decided and have realized basically that they’ve been using a search engine which is not European. Which collects data. Massively. And that makes them uncomfortable,” says Nitot. “They haven’t made a conscious decision about that. Because they bring in a computer which has a browser which has a search engine in it set by default — and in the end you just don’t get to choose which search engine your people use, right.

“And so they’re making a conscious decision to switch to Qwant. And we’ve been spending a lot of time and energy on that — and it’s paying off big time.”

As well as the French administration’s circa 3M desktops being switched by default to Qwant (which it expects will be done this quarter), the pro-privacy search engine has been getting traction from other government departments and regional government, as well as large banks and schools, according to Nitot.

He credits a focus on search products for schoolkids with generating momentum, such as Qwant Junior, which is designed for kids aged 6-12, and excludes sex and violence from search results as well as being ad free. (It’s set to get an update in the next few weeks.) It has also just been supplemented by Qwant School: A school search product aimed at 13-17 year olds.

“All of that creates more users — the kids talk to their parents about Qwant Junior, and the parents install Qwant.com for them. So there’s a lot of momentum creating that growth,” Nitot suggests.

Qwant says it handled more than 18 billion search requests in 2018.

A growing business needs money to fuel it of course. So fundraising efforts involving convertible bonds is one area Nitot says he’ll be focused on in the new role. “We are raising money,” he confirms.

Increasing efficiency — especially on the engineering front — is another key focus for the new CEO.

“The rest will be a focus on the organization, per se, how we structure the organization. How we evolve the company culture. To enable or to improve delivery of the engineering team, for example,” he says. “It’s not that it’s bad it’s just that we need to make sure every dollar or every euro we invest gives as much as possible in return.”

Product wise, Nitot’s attention in the near term will be directed towards shipping a new version of Qwant’s search engine that will involve reengineering core tech to improve the quality of results.

“What we want to do [with v2] is to improve the quality of the results,” he says of the core search product. “You won’t be able to notice any difference, in terms of quality, with the other really good search engines that you may use — except that you know that your privacy is respected by Qwant.

“[As we raise more funding] we will be able to have a lot more infrastructure to run better and more powerful algorithms. And so we plan to improve that internationally… Every language will benefit from the new search engine. It’s also a matter of money and infrastructure to make this work on a web scale. Because the web is huge and it’s growing.

“The new version includes NLP (Natural Language Processing) technology… for understanding language, for understanding intentions — for example do you want to buy something or are you looking for a reference… or a place or a thing. That’s the kind of thing we’re putting in place but it’s going to improve a lot for every language involved.”

Western Europe will be the focus for v2 of the search engine, starting with French, German, Italian, Spanish and English — with a plan to “go beyond that later on”.

Nitot also says there will also be staggered rollouts (starting with France), with Qwant planning to run old and new versions in parallel to quality check the new version before finally switching users over.

“Shipping is hard as we used to say at Mozilla,” he remarks, refusing to be fixed to a launch date for v2 (beyond saying it’ll arrive in “less than a year”). “It’s a universal rule; shipping a new product is hard, and that’s what we want to do with version 2… I’ve been writing software since 1980 and so I know how predictions are when it comes to software release dates. So I’m very careful not to make promises.”

Developing more of its own advertising technologies is another focus for Qwant. On this front the aim is to improve margins by leaning less on partners like Microsoft .

“We’ve been working with partners until now, especially on the search engine result pages,” says Nitot. “We put Microsoft advertising on it. And our goal is to ramp up advertising technologies so that we rely on our own technologies — something that we control. And that hopefully will bring a better return.”

Like Google, Qwant monetizes searches by serving ads alongside results. But unlike Google these are contextual ads, meaning they are based on general location plus the substance of the search itself; rather than targeted ads which entail persistent tracking and profiling of Internet users in order to inform the choice of ad (hence feeling like ads are stalking you around the Internet).

Serving contextual ads is a choice that lets Qwant offer a credible privacy pledge that Mountain View simply can’t match.

Yet up until 2006 Google also served contextual ads, as Nitot points out, before its slide into privacy-hostile microtargeting. “It’s a good old idea,” he argues of contextual ads. “We’re using it. We think it really is a valuable idea.” 

Qwant is also working on privacy-sensitive ad tech. One area of current work there is personalization. It’s developing a client-side, browser-based encrypted data store, called Masq, that’s intended to store and retrieve application data through a WebSocket connection. (Here’s the project Masq Github page.)

“Because we do not know the person that’s using the product it’s hard to make personalization of course. So we plan to do personalization of the product on the client side,” he explains. “Which means the server side will have no more details than we currently do, but on the client side we are producing something which is open source, which stores data locally on your device — whether that’s a laptop or smartphone — in the browser, it is encrypted so that nobody can reuse it unless you decide that you want that to happen.

“And it’s open source so that it’s transparent and can be audited and so that people can trust the technology because it runs on their own device, it stores on their device.”

“Right now it’s at alpha stage,” Nitot adds of Masq, declining to specify when exactly it might be ready for a wider launch.

The new CEO’s ultimate goal for Qwant is to become the search engine for Europe — a hugely ambitious target that remains far out of reach for now, with Google still commanding in excess of 90% regional marketshare. (A dominance that has got its business embroiled in antitrust hot water in Europe.)

Yet the Internet of today is not the same as the Internet of yesterday when Netscape was a browsing staple — until Internet Explorer knocked it off its perch after Microsoft bundled its rival upstart as the default browser on Windows. And the rest, as they say, is Internet history.

Much has changed and much is changing. But abuses of market power are an old story. And as regulators act against today’s self-interested defaults there are savvy alternatives like Qwant primed and waiting to offer consumers a different kind of value.

“Qwant is created in Europe for the European citizens with European values,” says Nitot. “Privacy being one of these values that are central to our mission. It is not random that the CNIL — the French data protection authority — was created in France in 1978. It was the first time that something like that was created. And then GDPR [General Data Protection Regulation] was created in Europe. It doesn’t happen by accident. It’s a matter of values and the way people see their life and things around them, politics and all that. We have a very deep concern about privacy in France. It’s written in the European declaration of human rights.

“We build a product that reflects those values — so it’s appealing to European users.”

 


0

The founders of Robin Healthcare think doctors need smart assistants too

17:16 | 18 September

Robin Healthcare,  a new startup founded by serial entrepreneurs Noah Auerhahn and Emilio Galan, is hoping to harness the power of personal assistants to make the business of healthcare easier for the physicians who practice it

The company’s technology, which works much the same way as a Google Home or Amazon Alexa or Echo, is placed in hospital rooms and transcribes and formats doctor interactions with patients to reduce paperwork and streamline the behind-the-scenes part of the process that can drive doctors to the point of distraction, the company’s co-founder said.

“I had a background doing claims data work in healthcare was at UCSF and finishing my clinical training,” says Galan. “And I was hearing lots of doctors telling me not to practice.”

The problem, says Galan, was the overabundance of paperwork. After school Galan doubled down on his work in claims and billing launching a company called HonestHealth where he worked with institutions and companies . like The Robert Wood Johnson Foundation, Consumer Reports, and the New York State Department of Health to analyze health care claims data and develop consumer applications.

Galan met Auerhahn at the HLTH conference a few years ago just as Auerhahn was looking for his next challenge after the sale of his previous company, ExtraBux.

The two men saw the wave of smart devices coming and figured there must be a way to use the technology to build a fully billable clinical report from monitoring the conversations with patients.

The company currently has dozens of its smart devices installed in hospitals around the country including a large surgical practice in Tennessee, the Campbell Clinic; Duke University Medical Center’s Private Diagnostic Clinic; the University of California San Francisco Medical Center; and Webster Orthopedics in Northern California.

Robin integrates with the major electronic health records companies, Epic and Cerner, through third party integrations that are designed to make it easier to input data automatically as doctors are assessing a patient’s condition and delivering treatments.

Part of why Robin exists is to avoid technology interrupting care,” says Auerhahn. “Having fewer interactions with EMR is a good way to do that.”

Robin’s service is human-assisted natural language processing to make sure that the data is input correctly.

The company’s early vision has been enough to attract investors like Norwest Venture Partners, which led the company’s $11.5 million Series A round.

In all, Robin Healthcare has raised $15 million in financing. The company’s other investors include Social Leverage, the early stage investment firm founded by Howard Lindzon.

 

 


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