Cybereason raises $200 million for its enterprise security platform

Posted by on 6 August, 2019

This post was originally published on this site

Cybereason, which uses machine learning to increase the number of endpoints a single analyst can manage across a network of distributed resources, has raised $200 million in new financing from SoftBank Group and its affiliates. 

It’s a sign of the belief that SoftBank has in the technology, since the Japanese investment firm is basically doubling down on commitments it made to the Boston-based company four years ago.

The company first came to our attention five years ago when it raised a $25 million financing from investors, including CRV, Spark Capital and Lockheed Martin.

Cybereason’s technology processes and analyzes data in real time across an organization’s daily operations and relationships. It looks for anomalies in behavior across nodes on networks and uses those anomalies to flag suspicious activity.

The company also provides reporting tools to inform customers of the root cause, the timeline, the person involved in the breach or breaches, which tools they use and what information was being disseminated within and outside of the organization.

For co-founder Lior Div, Cybereason’s work is the continuation of the six years of training and service he spent working with the Israeli army’s 8200 Unit, the military incubator for half of the security startups pitching their wares today. After his time in the military, Div worked for the Israeli government as a private contractor reverse-engineering hacking operations.

Over the last two years, Cybereason has expanded the scope of its service to a network that spans 6 million endpoints tracked by 500 employees, with offices in Boston, Tel Aviv, Tokyo and London.

“Cybereason’s big data analytics approach to mitigating cyber risk has fueled explosive expansion at the leading edge of the EDR domain, disrupting the EPP market. We are leading the wave, becoming the world’s most reliable and effective endpoint prevention and detection solution because of our technology, our people and our partners,” said Div, in a statement. “We help all security teams prevent more attacks, sooner, in ways that enable understanding and taking decisive action faster.”

The company said it will use the new funding to accelerate its sales and marketing efforts across all geographies and push further ahead with research and development to make more of its security operations autonomous.

“Today, there is a shortage of more than three million level 1-3 analysts,” said Yonatan Striem-Amit, chief technology officer and co-founder, Cybereason, in a statement. “The new autonomous SOC enables SOC teams of the future to harness technology where manual work is being relied on today and it will elevate  L1 analysts to spend time on higher value tasks and accelerate the advanced analysis L3 analysts do.”

Most recently the company was behind the discovery of Operation SoftCell, the largest nation-state cyber espionage attack on telecommunications companies. 

That attack, which was either conducted by Chinese-backed actors or made to look like it was conducted by Chinese-backed actors, according to Cybereason, targeted a select group of users in an effort to acquire cell phone records.

As we wrote at the time:

… hackers have systematically broken in to more than 10 cell networks around the world to date over the past seven years to obtain massive amounts of call records — including times and dates of calls, and their cell-based locations — on at least 20 individuals.

Researchers at Boston-based Cybereason, who discovered the operation and shared their findings with TechCrunch, said the hackers could track the physical location of any customer of the hacked telcos — including spies and politicians — using the call records.

Lior Div, Cybereason’s co-founder and chief executive, told TechCrunch it’s “massive-scale” espionage.

Call detail records — or CDRs — are the crown jewels of any intelligence agency’s collection efforts. These call records are highly detailed metadata logs generated by a phone provider to connect calls and messages from one person to another. Although they don’t include the recordings of calls or the contents of messages, they can offer detailed insight into a person’s life. The National Security Agency  has for years controversially collected the call records of Americans from cell providers like AT&T and Verizon (which owns TechCrunch), despite the questionable legality.

It’s not the first time that Cybereason has uncovered major security threats.

Back when it had just raised capital from CRV and Spark, Cybereason’s chief executive was touting its work with a defense contractor who’d been hacked. Again, the suspected culprit was the Chinese government.

As we reported, during one of the early product demos for a private defense contractor, Cybereason identified a full-blown attack by the Chinese — 10,000 thousand usernames and passwords were leaked, and the attackers had access to nearly half of the organization on a daily basis.

The security breach was too sensitive to be shared with the press, but Div says that the FBI was involved and that the company had no indication that they were being hacked until Cybereason detected it.

Posted Under: Tech News
Segment CEO Peter Reinhardt is coming to TechCrunch Sessions: Enterprise to discuss customer experience management

Posted by on 5 August, 2019

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There are few topics as hot right now in the enterprise as customer experience management, that ability to collect detailed data about your customers, then deliver customized experiences based on what you have learned about them. To help understand the challenges companies face building this kind of experience, we are bringing Segment CEO Peter Reinhardt to TechCrunch Sessions: Enterprise on September 5 in San Francisco (p.s. early-bird sales end this Friday, August 9).

At the root of customer experience management is data — tons and tons of data. It may come from the customer journey through a website or app, basic information you know about the customer or the customer’s transaction history. It’s hundreds of signals and collecting that data in order to build the experience where Reinhardt’s company comes in.

Segment wants to provide the infrastructure to collect and understand all of that data. Once you have that in place, you can build data models and then develop applications that make use of the data to drive a better experience.

Reinhardt, and a panel that includes Qualtrics’ Julie Larson-Green and Adobe’s Amit Ahuja, will discuss with TechCrunch editors the difficulties companies face collecting all of that data to build a picture of the customer, then using it to deliver more meaningful experiences for them. See the full agenda here.

Segment was born in the proverbial dorm room at MIT when Reinhardt and his co-founders were students there. They have raised more than $280 million since inception. Customers include Atlassian, Bonobos, Instacart, Levis and Intuit .

Early-bird tickets to see Peter and our lineup of enterprise influencers at TC Sessions: Enterprise are on sale for just $249 when you book here; but hurry, prices go up by $100 after this Friday!

Are you an early-stage startup in the enterprise-tech space? Book a demo table for $2,000 and get in front of TechCrunch editors and future customers/investors. Each demo table comes with four tickets to enjoy the show.

Posted Under: Tech News
Four days left for early-bird tickets to TC Sessions: Enterprise 2019

Posted by on 5 August, 2019

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We’re just one month away from TC Sessions: Enterprise, which takes place on September 5 at the Yerba Buena Center in San Francisco. But you have only four days left to score an early-bird ticket and save yourself $100. Right now, you pay $249, but once the clock strikes 11:59 p.m. (PT) on August 9, the bird flies south and the price flies north. Get your early-bird ticket today and save.

Focused on the current and future state of enterprise software, this day-long conference offers tremendous value — even at full price. Considering the rate at which this $500 billion industry acquires startups — and how quickly it’s evolving — TC Sessions: Enterprise makes perfect sense for enterprise-minded founders, investors, CTOs, CIOs, engineers and MBA students (student tickets cost $75).

We’ve packed the conference with interviews, panel discussions, Q&As and breakout sessions. TechCrunch editors will dig deep to separate hype from reality as they explore crucial issues, complex technologies and investment trends with both industry giants and up-and-coming startups.

Here’s a sample of just some of what we have planned. You can also check out the agenda — and we might add a few surprises along the way.

Curious about the latest in enterprise investment? TechCrunch editor Connie Loizos will interview VCs Jason Green, founder and general partner at Emergence; Maha Ibrahim, general partner at Canaan Partners; and Rebecca Lynn, co-founder and general partner at Canvas Ventures. They’ll examine trends in early-stage enterprise investments and discuss different sectors and companies that have their attention.

Maybe you want to learn from a founder who’s been there and done that. Don’t miss Aaron Levie, Box co-founder, chairman and CEO, as he outlines what it took to travel the entire startup journey. He’ll also offer his take on the future of data platforms.

Want to cover more ground at TC Sessions: Enterprise? Take advantage of our group discount and bring the whole team. Buy four or more tickets at once and save 20%. Don’t forget: For every ticket you buy to TC Sessions: Enterprise, we’ll register you for a free Expo Only pass to TechCrunch Disrupt SF on October 2-4.

TC Sessions: Enterprise takes place on September 5, but your chance to save $100 ends in just four short days. Don’t wait — buy an early-bird ticket today, and we’ll see you in September!

Is your company interested in sponsoring or exhibiting at TC Sessions: Enterprise? Contact our sponsorship sales team by filling out this form.

Posted Under: Tech News
Mesosphere changes name to D2IQ, shifts focus to Kubernetes, cloud native

Posted by on 5 August, 2019

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Mesosphere was born as the commercial face of the open source Mesos project. It was surely a clever solution to make virtual machines run much more efficiently, but times change and companies change. Today the company announced it was changing its name to Day2IQ or D2IQ for short, and fixing its sights on Kubernetes and cloud native, which have grown quickly in the years since Mesos appeared on the scene.

D2IQ CEO Mike Fey says that the name reflects the company’s new approach. Instead of focusing entirely on the Mesos project, it wants to concentrate on helping more mature organizations adopt cloud native technologies.

“We felt like the Mesosphere name was somewhat of constrictive. It made statements about the company that really allocated us to a given technology, instead of to our core mission, which is supporting successful Day Two operations, making cloud native a viable approach not just for the early adopters, but for everybody,” Fey explained.

Fey is careful to point out that the company will continue to support the Mesos-driven DC/OS solution, but the general focus of the company has shifted, and the new name is meant to illustrate that. “The Mesos product line is still doing well, and there are things that it does that nothing else can deliver on yet. So we’re not abandoning that totally, but we do see that Kubernetes is very powerful, and the community behind it is amazing, and we want to be a value added member of that community,” he said.

He adds that this is not about jumping on the cloud native bandwagon all of a sudden. He points out his company has had a Kubernetes product for more than a year running on top of DC/OS, and it has been a contributing member to the cloud native community.

It’s not just about a name change and refocusing the company and the brand, it also involves several new cloud native products that the company has built to serve the type of audience, the more mature organization, that the new name was inspired by.

For starters, it’s introducing its own flavor of Kubernetes called Konvoy, which it says, provides an “enterprise-grade Kubernetes experience.” The company will also provide a support and training layer, which it believes is a key missing piece, and one that is required by larger organizations looking to move to cloud native.

In addition, it is offering a data integration layer, which is designed to help integrate large amounts of data in a cloud-native fashion. To that end, it is introducing a Beta of Kudo, an open source cloud-native tool for building stateful operations in Kubernetes. The company has already donated this tool to the Cloud Native Computing foundation, the open source organization that houses Kubernetes and other cloud native projects.

The company faces stiff competition in this space from some heavy hitters like the newly combined IBM and Red Hat, but it believes by adhering to a strong open source ethos, it can move beyond its Mesos roots to become a player in the cloud native space. Time will tell if it made a good bet.

Posted Under: Tech News
United Airlines CISO Emily Heath joins TC Sessions: Enterprise this September

Posted by on 2 August, 2019

This post was originally published on this site

In an era of massive data breaches, most recently the Capital One fiasco, the risk of a cyberattack and the costly consequences are the top existential threat to corporations big and small. At TechCrunch’s first-ever enterprise-focused event (p.s. early bird sales end August 9), that topic will be front and center throughout the day.

That’s why we’re delighted to announce United’s chief information security officer Emily Heath will join TC Sessions: Enterprise in San Francisco on September 5, where we will discuss and learn how one of the world’s largest airlines keeps its networks safe.

Joining her to talk enterprise security will be a16z partner Martin Casado and DUO / Cisco’s head of advisory CISO s Wendy Nather, among others still to be announced.

At United, Heath oversees the airline’s cybersecurity program and its IT regulatory, governance and risk management.

The U.S.-based airline has more than 90,000 employees serving 4,500 flights a day to 338 airports, including New York, San Francisco, Los Angeles and Washington D.C.

A native of Manchester, U.K., Heath served as a former police detective in the U.K. Financial Crimes Unit where she led investigations into international investment fraud, money laundering, and large scale cases of identity theft — and running join investigations with the FBI, SEC, and London’s Serious Fraud Office.

Heath and her teams have been the recipients of CSO Magazine’s CSO50 Awards for their work in cybersecurity and risk.

At TC Sessions: Enterprise, Heath will join an expert panel of cybersecurity experts to discuss security on enterprise networks large and small — from preventing data from leaking to keeping bad actors out of their network — where we’ll lear how a modern CSO moves fast without breaking things.

Join hundreds of today’s leading enterprise experts for this single-day event when you purchase a ticket to the show. $249 Early Bird sale ends Friday, August 9. Make sure to grab your tickets today and save $100 before prices go up.

Posted Under: Tech News
Early-bird pricing ends next week for TC Sessions: Enterprise 2019

Posted by on 2 August, 2019

This post was originally published on this site

Here are five words you’ll never hear spring from the mouth of an early-stage startupper. “I don’t mind paying more.” We feel you, and that’s why we’re letting you know that the price of admission to TC Sessions Enterprise 2019, which takes place on September 5, goes up next week.

Our $249 early-bird ticket price remains in play until 11:59 p.m. (PT) on August 9. Buy your ticket now and save $100.

Now that you’ve scored the best possible price, get ready to experience a full day focused on what’s around the corner for enterprise — the biggest and richest startup category in Silicon Valley. More than 1,000 attendees, including many of the industry’s top founders, CEOs, investors and technologists, will join TechCrunch’s editors onstage for interviews covering all the big enterprise topics — AI, the cloud, Kubernetes, data and security, marketing automation and event quantum computing, to name a few.

This conference features more than 20 sessions on the main stage, plus separate Q&As with the speakers and breakout sessions. Check out the agenda here.

Just to peek at one session, TechCrunch’s Connie Loizos will interview three top VCs — Jason Green (Emergence Capital), Maha Ibrahim (Canaan Partners) and Rebecca Lynn (Canvas Ventures) — in a session entitled Investing with an Eye to the Future. In an ever-changing technological landscape, it’s not easy for VCs to know what’s coming next and how to place their bets. Yet, it’s the job of investors to peer around the corner and find the next big thing, whether that’s in AI, serverless, blockchain, edge computing or other emerging technologies. Our panel will look at the challenges of enterprise investing, what they look for in enterprise startups and how they decide where to put their money.

Want to boost your ROI? Take advantage of our group discount — save 20% when you buy four or more tickets at once. And remember, for every ticket you buy to TC Sessions: Enterprise, we’ll register you for a free Expo Only pass to TechCrunch Disrupt SF on October 2-4.

TC Sessions: Enterprise takes place September 5, but your chance to save $100 ends next week. No one enjoys paying more, so buy an early-bird ticket today, cross it off your to-do list and enjoy your savings.

Is your company interested in sponsoring or exhibiting at TC Sessions: Enterprise 2019? Contact our sponsorship sales team by filling out this form.

Posted Under: Tech News
Dasha AI is calling so you don’t have to

Posted by on 1 August, 2019

This post was originally published on this site

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.

Posted Under: Tech News
President throws latest wrench in $10B JEDI cloud contract selection process

Posted by on 1 August, 2019

This post was originally published on this site

The $10 billion, decade-long JEDI cloud contract drama continues. It’s a process that has been dogged by complaints, regulatory oversight and court cases. Throughout the months-long selection process, the Pentagon has repeatedly denied accusations that the contract was somehow written to make Amazon a favored vendor, but today The Washington Post reports President Trump has asked the newly appointed Defense Secretary, Mark T. Esper, to examine the process because of concerns over that very matter.

The Defense Department called for bids last year for a $10 billion, decade-long contract. From the beginning, Oracle in particular complained that the process favored Amazon. Even before the RFP process began Oracle executive Safra Catz took her concerns directly to the president, but at that time he did not intervene. Later, the company filed a complaint with the Government Accountability Office, which ruled that the procurement process was fair.

Finally, the company took the case to court, alleging that a person involved in defining the selection process had a conflict of interest, due to being an employee at Amazon before joining the DoD. That case was dismissed last month.

In April, the DoD named Microsoft and Amazon as the two finalists, and the winner was finally expected to be named some time this month. It appeared that we were close to the finish line, but now that the president has intervened at the 11th hour, it’s impossible to know what the outcome will be.

What we do know is that this is a pivotal project for the DoD, which is aimed at modernizing the U.S. military for the next decade and beyond. The fact is that the two finalists made perfect sense. They are the two market leaders, and each has tools, technologies and experience working with sensitive government contracts.

Amazon is the market leader, with 33% market share. Microsoft is No. 2, with 16%. The No. 3 vendor, Google, dropped out before the RFP process began. It is unclear at this point whether the president’s intervention will have any influence on the final decision, but The Washington Post reports it is an unusual departure from government procurement procedures.

Posted Under: Tech News
Microsoft Azure now lets you have a server all to yourself

Posted by on 1 August, 2019

This post was originally published on this site

Microsoft today announced the preview launch of Azure Dedicated Host, a new cloud service that will allow you to run your virtual machines on single-tenant physical services. That means you’re not sharing any resources on that server with anybody else and you’ll get full control over everything that’s running on that machine.

Previously, Azure already offered isolated Virtual Machine sizes for two very large virtual machine types. Those are still available, but their use cases are comparably limited to these new hosts, which offer far more flexibility.

With this move, Microsoft is following in the footsteps of AWS, which also offers Dedicated Hosts with very similar capabilities. Google Cloud, too, offers what it calls ‘sole-tenant nodes.’

Azure Dedicated Host will support Windows, Linux and SQL Server virtual machines and pricing is per host, independent of the number of virtual machines you end up running on them. You can currently opt for machines with up to 144 physical cores and prices start at $4.039 per hour.

To do this, Microsoft is offering two different processors to power these machines. Type 1 is based on the 2.3 GHz Intel Xeon E5-2673 v4 with up to 3.5 gigahertz of clock speed, while Type 2 features the Intel Xeon® Platinum 8168 with single-core clock speeds of up to 3.7 gigahertz. The available memory ranges from 32GiB to 448GiB. You can find more details here.

As Microsoft notes, these new dedicated hosts can help companies reach their compliance requirements for physical security, data integrity and monitoring. The dedicated hosts still share the same underlying infrastructure as any other host in the Azure data centers, but users have full control over any maintenance window that could impact their servers.

These dedicated hosts can also be grouped into larger host groups in a given Azure region, allowing you to build clusters of your own physical servers inside the Azure data center. Since you’re actually renting a physical machine, any hardware issue on that machine will impact the virtual machines you are running on them, so chances are you’ll want to have multiple dedicated hosts for your failover strategy anyway.

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Posted Under: Tech News
Why AWS gains big storage efficiencies with E8 acquisition

Posted by on 1 August, 2019

This post was originally published on this site

AWS is already the clear market leader in the cloud infrastructure market, but it’s never been an organization that rests on its past successes. Whether it’s a flurry of new product announcements and enhancements every year, or making strategic acquisitions.

When it bought Israeli storage startup E8 yesterday, it might have felt like a minor move on its face, but AWS was looking, as it always does, to find an edge and reduce the costs of operations in its data centers. It was also very likely looking forward to the next phase of cloud computing. Reports have pegged the deal at between $50 and $60 million.

What E8 gives AWS for relatively cheap money is highly advanced storage capabilities, says Steve McDowell, senior storage analyst at Moor Research and Strategy. “E8 built a system that delivers extremely high-performance/low-latency flash (and Optane) in a shared-storage environment,” McDowell told TechCrunch.

Posted Under: Tech News
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