Web feature developers told to dial up attention on privacy and security – gpgmail


Web feature developers are being warned to step up attention to privacy and security as they design contributions.

Writing in a blog post about “evolving threats” to Internet users’ privacy and security, the W3C standards body’s technical architecture group (TAG) and Privacy Interest Group (PING) set out a series of revisions to the W3C’s Security and Privacy Questionnaire for web feature developers.

The questionnaire itself is not new. But the latest updates place greater emphasis on the need for contributors to assess and mitigate privacy impacts, with developers warned that “features may not be implemented if risks are found impossible or unsatisfactorily mitigated”.

In the blog post, independent researcher Lukasz Olejnik, currently serving as an invited expert at the W3C TAG; and Apple’s Jason Novak, representing the PING, write that the intent with the update is to make it “clear that feature developers should consider security and privacy early in the feature’s lifecycle” [emphasis theirs].

“The TAG will be carefully considering the security and privacy of a feature in their design reviews,” they further warn, adding: “A security and privacy considerations section of a specification is more than answers to the questionnaire.”

The revisions to the questionnaire include updates to the threat model and specific threats a specification author should consider — including a new high level type of threat dubbed “legitimate misuse“, where the document stipulates that: “When designing a specification with security and privacy in mind, all both use and misuse cases should be in scope.”

“Including this threat into the Security and Privacy Questionnaire is meant to highlight that just because a feature is possible does not mean that the feature should necessarily be developed, particularly if the benefitting audience is outnumbered by the adversely impacted audience, especially in the long term,” they write. “As a result, one mitigation for the privacy impact of a feature is for a user agent to drop the feature (or not implement it).”

Features should be secure and private by default and issues mitigated in their design,” they further emphasize. “User agents should not be afraid of undermining their users’ privacy by implementing new web standards or need to resort to breaking specifications in implementation to preserve user privacy.”

The pair also urge specification authors to avoid blanket treatment of first and third parties, suggesting: “Specification authors may want to consider first and third parties separately in their feature to protect user security and privacy.”

The revisions to the questionnaire come at a time when browser makers are dialling up their response to privacy threats — encouraged by rising public awareness of the risks posed by data leaks, as well as increased regulatory action on data protection.

Last month the open source WebKit browser engine (which underpins Apple’s Safari browser) announced a new tracking prevention policy that takes the strictest line yet on background and cross-site tracking, saying it would treat attempts to circumvent the policy as akin to hacking — essentially putting privacy protection on a par with security.

Earlier this month Mozilla also pushed out an update to its Firefox browser that enables an anti-tracking cookie feature across the board, for existing users too — demoting third party cookies to default junk.

Even Google’s Chrome browser has made some tentative steps towards enhancing privacy — announcing changes to how it handles cookies earlier this year. Though the adtech giant has studiously avoided flipping on privacy by default in Chrome where third party tracking cookies are concerned, leading to accusations that the move is mostly privacy-washing.

More recently Google announced a long term plan to involve its Chromium browser engine in developing a new open standard for privacy — sparking concerns it’s trying to both kick the can on privacy protection and muddy the waters by shaping and pushing self-interested definitions which align with its core data-mining business interests.

There’s more activity to consider too. Earlier this year another data-mining adtech giant, Facebook, made its first major API contribution to Google’s Chrome browser — which it also brought to the W3C Performance Working Group.

Facebook does not have its own browser, of course. Which means that authoring contributions to web technologies offers the company an alternative conduit to try to influence Internet architecture in its favor.

The W3C TAG’s latest move to focus minds on privacy and security by default is timely.

It chimes with a wider industry shift towards pro-actively defending user data, and should rule out any rubberstamping of tech giants contributions to Internet architecture which is obviously a good thing. Scrutiny remains the best defence against self-interest.




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Clubhouse announces new collaboration tool and free version of its project management platform – gpgmail


Clubhouse — the software project management platform focused on team collaboration, workflow transparency and ease of integration — is taking another big step towards its goal of democratizing efficient software development.

Traditionally, legacy project management programs in software development can often appear like an engineer feeding frenzy around a clunky stack of to-dos. Engineers have limited clarity into the work being done by other members of their team or into project tasks that fall outside of their own silo.

Clubhouse has long been focused on easing the headaches of software development workflows by providing full visibility into the status of specific tasks, the work being done by all team members across a project, as well as higher-level project plans and goals. Clubhouse also offers easy integration with other development tools as well as its own API to better support the cross-functionality a new user may want.

Today, Clubhouse released a free version of its project management platform, that offers teams of up to 10 people unlimited access to the product’s full suite of features, as well as unlimited app integrations.

The company also announced it will be launching an engineer focused collaboration and documentation tool later this year, that will be fully integrated with the Clubhouse project management product. The new product dubbed “Clubhouse Write” is currently in beta, but will allow development teams to collaborate, organize and comment on project documentation in real-time, enabling further inter-team communication and a more open workflow.

The broader mission behind the Clubhouse Write tool and the core product’s free plan is to support more key functions in the development process for more people, ultimately making it easier for anyone to start dynamic and distributed software teams and ideate on projects.

“Clubhouse Write” Beta Version. Image via Clubhouse

In an interview with gpgmail, Clubhouse also discussed how the offerings will provide key competitive positioning against larger incumbents in the software project management space. Clubhouse has long competed with Atlassian’s project management tool “Jira”, but now the company is doubling down by launching Clubhouse Write which will compete head-on with Atlassian’s team collaboration product Confluence.

According to recent Atlassian investor presentations, Jira and Confluence make up the lion’s share of the Atlassian’s business and revenues. And with Atlassian’s market capitalization of ~$30 billion, Clubhouse has its sights set on what it views as a significant market share opportunity.

According to Clubhouse, the company believes it’s in pole position to capture a serious chunk of Atlassian’s foothold given it designed its two products to have tighter integration than existing legacy platforms, and since Clubhouse is essentially providing free versions of what many are already paying for to date.

And while Atlassian is far from the only competitor in the cluttered project management space, few if any competing platforms are offering a full project tool kit for free, according to the company. Clubhouse is also encouraged by the strong support it has received from the engineering community to date. In a previous interview with gpgmail’s Danny Crichton, the company told gpgmail it had reached at least 700 enterprise customers using the platform before hiring a single salesperson, and users of the platform already include Nubank, Dataiku, and Atrium amongst thousands of others.

Clubhouse has ambitious plans to further expand its footprint, having raised $16 million to date through its Series A according to Crunchbase, with investments from a long list of Silicon Valley mainstays including Battery Ventures, Resolute Ventures, Lerer Hippeau, RRE Ventures, BoxGroup, and others.

A former CTO himself, Clubhouse cofounder and CEO Kurt Schrader is dearly familiar with the opacity in product development that frustrates engineers and complicates release schedules. Schrader and Clubhouse CMO Mitch Wainer believe Clubhouse can maintain its organic growth by that staying hyperfocused on designing for project managers and keeping engineers happy. According to Schrader, the company ultimately wants to be the “default [destination] for modern software teams to plan and build software.”

“Clubhouse is the best software project management app in the world,” he said. “We want all teams to have access to a world-class tool from day one whether it’s a 5 or 5,000 person team.”


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Web host Hostinger says data breach may affect 14 million customers – gpgmail


Hostinger said it has reset user passwords as a “precautionary measure” after it detected unauthorized access to a database containing information on millions of its customers.

The breach is said to have happened on Thursday. The company said in a blog post it received an alert that one of its servers was improperly accessed. Using an access token found on the server, which can give access to systems without needing a username or a password, the hacker gained further access to the company’s systems, including an API database containing customer usernames, email addresses, and scrambled passwords.

Hostinger said the API database stored about 14 million customers records. The company has more than 29 million customers on its books.

“We have restricted the vulnerable system, and such access is no longer available,” said Daugirdas Jankus, Hostinger’s chief marketing officer.

“We are in contact with the respective authorities,” said Jankus.

An email from Hostinger explaining the data breach. (Image: supplied)

News of the breach broke overnight. According to the company’s status page, affected customers have already received an email to reset their passwords.

The company said that financial data wasn’t taken in the breach, nor was customer website files or data affected.

But one customer who was affected by the breach accused the company of being potentially “misleading” about the scope of the breach.

A chat log seen by gpgmail shows a customer support representative telling the customer it was “correct” that customers’ financial data can be retrieved by the API but that the company does “not store any payment data.” Hostinger uses multiple payment processors, the representative told the customer, but did not name them.

“They say they do not store payment details locally, but they have an API that can pull this information from the payment processor and the attacker had access to it,” the customer told gpgmail.

We’ve reached out to Hostinger for more, but a spokesperson didn’t immediately comment when reached by gpgmail.

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Backup service IDrive launches a face recognition API for developers – gpgmail


I did a bit of a double take when I first saw this announcement. IDrive, an online cloud storage and backup service, is launching a face recognition API today that goes up against the likes of AWS Rekognition and others. That seems like a bit of an odd move for a backup company, but it turns out that IDrive has actually been in the face recognition game for a while. Last year, the company launched IDrive People to help its users find faces in photos they’ve backed up on its service. With its API, IDrive is targeting a very different market, though, and entering into the API business for the first time.

IDrive Face, as the service is called, includes the standard tools for detecting and analyzing multiple faces within a still image that are at the core of every face detection API. For this, the API provides the usual bounding boxes and metadata for all faces. There are also a face comparison and verification features to identify people by their face, and a gender, age and emotion detection option. All requests to the API are encrypted and using the API looks to be pretty straightforward.

IDrive promises that its tool’s accuracy and performance is comparable to AWS Rekognition, but at a lower price. The company offers a developer plan for $49.50/month plus $0.0001 per transaction, at up to 75 transactions per minute, with unlimited storage included. There’s also a business plan for $124.50/month, $0.0001 per transaction and up to 500 transactions per minute, as well as custom enterprise plans and free trials for those who want to give the service a try.

AWS’ pricing is, as usual, a bit more complicated and while there’s no monthly cost, most serious users will end up paying more for Rekognition than IDrive Face, though Rekognition offers a number of features like text, object, scene and celebrity recognition that aren’t available in the competing product, which only focuses on faces.


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Microsoft Makes It Easier to Bring DirectX 12 Games to Windows 7


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When Microsoft launched Windows 10, it made its stance on DirectX 12 clear: Windows 10 would be the only OS that supported the company’s latest API, period. For years, the company stuck to this stance. Then, earlier this year, Microsoft announced that one game — World of Warcraft — would be allowed to take advantage of the DX12 API while running Windows 7.

The reason for this allowance? Probably China. World of Warcraft has always had a huge Chinese following, and Blizzard’s decision to add DX12 support to WoW was a significant step for both the developer and the API. Now, Microsoft has announced that it’s expanding this program. In a short blog post pointing an array of API documents, Microsoft notes:

We have received warm welcome from the gaming community, and we continued to work with several game studios to further evaluate this work. To better support game developers at larger scales, we are publishing the following resources to allow game developers to run their DirectX 12 games on Windows 7.

The development guidance document for how to move DX12 to Windows 7 actually contains some useful information on how difficult it is to get games running under the older OS and what the differences are between the two. Microsoft states:

We only ported the D3D12 runtime to Windows 7. Therefore, the difference of Graphics Kernel found on Windows 7 still requires some game code changes, mainly around the presentation code path, use of monitored fences, and memory residency management (all of which will be detailed below). Early adopters reported from a few days to two weeks of work to have their D3D12 games up and running on Windows 7, though the actual engineering work required for your game may vary.

There are technical differences between DX12 on Windows 7 and DX12 on Windows 10. DirectML (Direct Machine Learning) is not supported under Windows 7, but all other features implemented in the October 2018 Windows 10 update are supported. There are differences in terms of API usage (D3D12 on Windows 7 uses different Present APIs), and some fence usage patterns are also unsupported.

There are, however, some limits to support. Only 64-bit Windows 7 with SP1 installed is supported. There’s no PIX or D3D12 debug layer on Windows 7, no shared surfaces or cross-API interop, no SLI/LDA support, no D3D12 video, and no WARP support. According to Microsoft, “HDR support is orthogonal to D3D12 and requires DXGI/Kernel/DWM functionalities on Windows 10 but not on Windows 7.” This seems to imply that HDR content can work in Windows 7, but it may be on the developer to implement it properly.

Microsoft has published additional resources on the topic, including a NuGet package and a D3D12 code sample that runs on Windows 7 and 10 with the same binary.

Why Make DX12 More Accessible?

This is honestly a little surprising to see. Windows 7 is supposed to be headed for firm retirement in a matter of months. The implication here is that Microsoft is taking this step to cater to gamers that are still using Windows 7, but the Steam Hardware Survey suggests that’s a distinct minority of gamers. Windows 10 has a 71.57 percent market share according to the SHS, while Windows 7 64-bit is pegged at 20.4 percent. What’s interesting here is that the SHS actually tilts much more towards Windows 10 than a generic OS survey.

Chinese-Desktop-Market-Share

StatCounter data puts Windows 10 at 58.63 percent of the market as of July, compared with 31.22 percent of Windows 10. This suggests that gamers tend to update their hardware more quickly than the mass market, which makes sense. But from what we’ve read, the Windows 7 gamers may be concentrated in China, where it remains the most popular OS. 49.46 percent of Chinese gamers are using Windows 7, compared with just 41.13 percent of PC gamingSEEAMAZON_ET_135 See Amazon ET commerce occurring under Windows 10. Even if we assume Chinese gamers are more likely to be using Windows 10 — and it’s not clear they are — there’s still a much larger share of users in that nation.

It’s not clear at all how Microsoft is going to deal with that problem as it relates to overall support, but it could be that this is Microsoft’s way of providing a certain degree of backward-compatibility without being willing to do anything equivalent as far as continuing to provide security features. Microsoft wants its customer base — all of it — to be Windows 10. It’s surprising to see the company extending DX12 backward, but we’d be stunned if they granted Windows 7 a stay of reprieve and kept publishing patches for it.

MS could also be hoping to encourage devs to adopt DX12 more widely. Three years after debut, neither DX12 nor Vulkan has done much to revolutionize APIs or gaming. Developers do use the APIs, but we’ve seen comparatively little use of them to pull off anything unique. The need to support older hardware and a wide range of users, plus the fact that these APIs require developers to be more familiar with the underlying hardware, seems to be a drag on their overall usage.

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Twilio launches SendGrid Ads and new cross-channel messaging API – gpgmail


At its annual Signal developer conference, Twilio today announced a couple of new features for developers on its core messaging platform and users of its recently acquired SendGrid email service. The new Twilio tools now allow developers to create multi-channel messaging tools and to get real-time streams of conversations in order to run them through transcription services, a translation tool or other machine learning models.

The company’s $3 billion acquisition of SendGrid closed less than half a year ago, so it doesn’t come as a surprise that Twilio would use its biggest event of the year to showcase the service to its developer community.

It’s a bit of an odd one, though. See, SendGrid already announced the beta of SendGrid Ads back in November 2018. As best as I can tell, Twilio SendGrid Ads, which is now launching in beta, is the same product, but a Twilio representative tells me that the ads product is now more deeply integrated into SendGrid Marketing Campaigns, and also got a bit of a redesign. A form of this integration already existed in the previous version, though.

The general idea here is to allow SendGrid users to run multichannel display ad campaigns on Facebook, Instagram and Google from their SendGrid accounts. The advantage of this, the company argues, is that marketers will be able to use data from their email campaigns and website data to then retarget users on other channels. Similarly, they can use lead ads on Facebook to get potential customers to sign up for their SendGrid mailing list.

SendGrid Ads will cost $50 per month, plus the cost of the ads. SendGrid will also take its own cut of 5% of any media cost over $500.

The new developer tools are pretty straightforward. Twilio Conversations, now in public beta, is a new API that allows developers to create solutions that integrate various messaging channels like SMS, WhatsApp and other chat tools.

“Over the last two decades, we’ve watched businesses evolve their communications with customers from the phone call, to website chat, to native mobile apps,” said Chee Chew, chief product officer at Twilio. “Leading companies have figured out that the next evolution of great customer experience is through messaging. Twilio Conversations empowers businesses to build personal, long-lived connections with their customers on the channels they prefer.”

Twilio Media Streams does exactly what it promises to do. Previously, you could get a recording to a call. Now, you can tap into the real-time call to analyze that stream in real time. That’s useful for all kinds of AI tools that aim to help call center agents, for example. This service is now also in public beta and will cost $0.004 per minute, in addition to the rest of the fees associated with the call.


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Dasha AI is calling so you don’t have to – gpgmail


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 gpgmail — 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…

 

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.


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