Shape Security hits $1B valuation with $51M Series F – gpgmail


Anti-fraud startup Shape Security has tipped over the $1 billion valuation mark following its latest Series F round of $51 million.

The Mountain View, Calif.-based company announced the fundraise Thursday, bringing the total amount of outside investment to $183 million since the company debuted in 2011.

C5 Capital led the round, along with several other new and returning investors, including Kleiner Perkins, HPE Growth and Norwest Ventures Partners.

Shape Security protects companies against automated and imitation attacks, which often employ bots to break into networks using stolen or reused credentials. Shape uses artificial intelligence to discern bots from ordinary users by comparing known information such as a user’s location, and collected data, like mouse movements, to shut down attempted automated logins in real time.

The company said it now protects against two billion fraudulent logins daily.

C5 managing partner André Pienaar said he believes Shape will become the “definitive” anti-fraud platform for the world’s largest companies.

“While we expect a strong financial return, we also believe that we can bring Shape’s platform into many of the leading companies in Europe who look to us for strategic ideas that benefit the entire value-chain where B2C applications are used,” Pienaar told gpgmail.

Shape’s chief executive Derek Smith said the $51 million injection will go toward the company’s international expansion and product development — particularly the capabilities of its AI system.

He added that Shape was preparing for an IPO.

Correction: A draft of the company’s funding news said Shape had raised $173 million to date. The company said this was a typo and has in fact raised $183 million.


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Audi’s off-roading electric concept would be perfect for Tatooine – gpgmail


The all-electric concept, which has a range of up to 310 miles, is about 13.5 feet long and 7 feet wide and is outfitted with beefy 22-inch wheels. And because it’s a vehicle meant to off road, designers gave it ground clearance of 13.4 inches. This concept, if it really existed beyond the showroom floor, can ford through water more than half a meter deep. The range of the vehicle does drop on rough roads to about 155 miles, which would theoretically (if this vehicle actually existed) make wilderness travel more difficult.

The battery unit is integrated into the floor providing a spacious interior that sits four people. Glass surrounds the cabin to provide unrivaled views of the environment, whether it’s an earthly vista or the binary sunset over the fictional Tatooine desert.

The remaining exterior body is made of a mixture of high-tech steel, aluminum and carbon fiber, giving it a total weight of 3,858 pounds.

The concept vehicle is equipped with four electric motors, systems for assisted and automated driving and all-wheel drive. What you won’t find are any screens for streaming video. This concept was designed for viewing the outside world.

The interior, which uses recycled materials, is scant. There are pedals, a yoke for a steering wheel, a few buttons, and a smartphone attached to the steering column as a display and control center for vehicle functions and navigation.

The second row features seats that are designed to function like hammocks — and can be removed and used as mobile outdoor chairs.

Drones as headlights!

Perhaps the most interesting feature is the inclusion of five rotorless electrically operated drones, which serve a variety of purposes. The drones, which have matrix LED lighting, can dock on the roof to get more power with the inductive charging elements.

Audi calls these drones Audi Light Pathfinders because of their ability to fly and illuminate the path ahead. These drones, Audi says replace headlights altogether. When the vehicle is parked, the drones can be used ti light up the surrounding area.

Occupants control the drones through their smartphones in this theoretical use case. The on-board cameras can generate a video image that can be transmitted to the display in front of the driver via Wi-Fi, turning the Pathfinders into “eyes in the sky,” Audi says.


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Hatebase catalogues the world’s hate speech in real time so you don’t have to – gpgmail


Policing hate speech is something nearly every online communication platform struggles with. Because to police it, you must detect it; and to detect it, you must understand it. Hatebase is a company that has made understanding hate speech its primary mission, and it provides that understanding as a service — an increasingly valuable one.

Essentially Hatebase analyzes language use on the web, structures and contextualizes the resulting data, and sells (or provides) the resulting database to companies and researchers that don’t have the expertise to do this themselves.

The Canadian company, a small but growing operation, emerged out of research at the Sentinel Project into predicting and preventing atrocities based on analyzing the language used in a conflict-ridden region.

“What Sentinel discovered was that hate speech tends to precede escalation of these conflicts,” explained Timothy Quinn, founder and CEO of Hatebase. “I partnered with them to build Hatebase as a pilot project — basically a lexicon of multilingual hate speech. What surprised us was that a lot of other NGOs [non-governmental organizations] started using our data for the same purpose. Then we started getting a lot of commercial entities using our data. So last year we decided to spin it out as a startup.”

You might be thinking, “what’s so hard about detecting a handful ethnic slurs and hateful phrases?” And sure, anyone can tell you (perhaps reluctantly) the most common slurs and offensive things to say — in their language… that they know of. There’s much more to hate speech than just a couple ugly words. It’s an entire genre of slang, and the slang of a single language would fill a dictionary. What about the slang of all languages?

A shifting lexicon

As Victor Hugo pointed out in Les Miserables, slang (or “argot” in French) is the most mutable part of any language. These words can be “solitary, barbarous, sometimes hideous words… Argot, being the idiom of corruption, is easily corrupted. Moreover, as it always seeks disguise so soon as it perceives it is understood, it transforms itself.”

Not only is slang and hate speech voluminous, but it is ever-shifting. So the task of cataloguing it is a continuous one.

Hatebase uses a combination of human and automated processes to scrape the public web for uses of hate-related terms. “We go out to a bunch of sources — the biggest, as you might imagine, is Twitter — and we pull it all in and turn it over to Hatebrain. It’s a natural language program that goes through the post and returns true, false, or unknown.”

True means it’s pretty sure it’s hate speech — as you can imagine, there are plenty of examples of this. False means no, of course. And unknown means it can’t be sure; perhaps it’s sarcasm, or academic chatter about a phrase, or someone using a word who belongs to the group and is attempting to reclaim it or rebuke others who use it. Those are the values that go out via the API, and users can choose to look up more information or context in the larger database, including location, frequency, level of offensiveness, and so on. With that kind of data you can understand global trends, correlate activity with other events, or simply keep abreast of the fast-moving world of ethnic slurs.

Hate speech being flagged all around the world — these were a handful detected today, along with the latitude and longitude of the IP they came from.

Quinn doesn’t pretend the process is magical or perfect, though. “There are very few 100 percents coming out of Hatebrain,” he explained. “It varies a little from the machine learning approach others use. ML is great when you have an unambiguous training set, but with human speech, and hate speech, which can be so nuanced, that’s when you get bias floating in. We just don’t have a massive corpus of hate speech, because no one can agree on what hate speech is.”

That’s part of the problem faced by companies like Google, Twitter, and Facebook — you can’t automate what can’t be automatically understood.

Fortunately Hatebrain also employs human intelligence, in the form of a corps of volunteers and partners who authenticate, adjudicate, and aggregate the more ambiguous data points.

“We have a bunch of NGOs that partner with us in linguistically diverse regions around the world, and we just launched our ‘citizen linguists’ program, which is a volunteer arm of our company, and they’re constantly updating and approving and cleaning up definitions,” Quinn said. “We place a high degree of authenticity on the data they provide us.”

That local perspective can be crucial for understanding the context of a word. He gave the example of a word in Nigeria, which when used between members of one group means friend, but when used by that group to refer to someone else means uneducated. It’s unlikely anyone but a Nigerian would be able to tell you that. Currently Hatebase covers 95 languages in 200 countries, and they’re adding to that all the time.

Furthermore there are “intensifiers,” words or phrases that are not offensive on their own but serve to indicate whether someone is emphasizing the slur or phrase. Other factors enter into it too, some of which a natural language engine may not be able to recognize because it has so little data concerning them. So in addition to keeping definitions up to date, the team is also constantly working on improving the parameters used to categorize speech Hatebrain encounters.

Building a better database for science and profit

The system just ingested its millionth hate speech sighting (out of perhaps tens times that many phrases evaluated), which sounds simultaneously like a lot and a little. It’s a little because the volume of speech on the internet is so vast that one rather expects even the tiny proportion of it constituting hate speech to add up to millions and millions.

But it’s a lot because no one else has put together a database of this size and quality. A vetted, million-data-point set of words and phrases classified as hate speech or not hate speech is a valuable commodity all on its own. That’s why Hatebase provides it for free to researchers and institutions using it for humanitarian or scientific purposes.

hatebase how

But companies and larger organizations looking to outsource hate speech detection for moderation purposes pay a license fee, which keeps the lights on and allows the free tier to exist.

“We’ve got, I think, four of the world’s ten largest social networks pulling our data. We’ve got the UN pulling data, NGOs, the hyper local ones working in conflict areas. We’ve been pulling data for the LAPD for the last couple years. And we’re increasingly talking to government departments,” Quinn said.

They have a number of commercial clients, many of which are under NDA, Quinn noted, but the most recent to join up did so publicly, and that’s TikTok. As you can imagine, a popular platform like that has a great need for quick, accurate moderation.

In fact it’s something of a crisis, since there are laws coming into play that penalize companies enormous amounts if they don’t promptly remove offending content. That kind of threat really loosens the purse strings; If a fine could be in the tens of millions of dollars, paying a significant fraction of that for a service like Hatebase’s is a good investment.

“These big online ecosystems need to get this stuff off their platforms, and they need to automate a certain percentage of their content moderation,” Quinn said. “We don’t ever think we’ll be able to get rid of human moderation, that’s a ridiculous and unachievable goal; What we want to do is help automation that’s already in place. It’s increasingly unrealistic that every online community under the sun is going to build up their own massive database of multilingual hate speech, their own AI. The same way companies don’t have their own mail server any more, they use Gmail, or they don’t have server rooms, they use AWS — that’s our model, we call ourselves hate speech as a service. About half of us love that term, half don’t, but that really is our model.”

Hatebase’s commercial clients have made the company profitable from day one, but they’re “not rolling in cash by any means.”

“We were nonprofit until we spun out, and we’re not walking away from that, but we wanted to be self-funding,” Quinn said. Relying on the kindness of rich strangers is no way to stay in business, after all. The company is hiring and investing in its infrastructure, but Quinn indicated that they’re not looking to juice growth or anything — just make sure the jobs that need doing have someone to do them.

In the meantime it seems clear to Quinn and everyone else that this kind of information has real value, though it’s rarely simple.

“It’s a really, it’s a really complicated problem. We always grapple with it, you know, in terms of, well, what role does hate speech play? What role does misinformation play? What role do socioeconomics play?” he said. “There’s a great paper that came out of the University of Warwick, they studied the correlation between hate speech and violence against immigrants in Germany over, I want to say, 2015 to 2017. They graph it out. And its peak for peak, you know, valid for Valley. It’s amazing. We don’t do a hell of a lot of analysis — we’re a data provider.”

“But now have like, almost 300 universities pulling the data, and they do those kinds of those kinds of analyses. So that’s very validating for us.”

You can learn more about Hatebase, join the Citizen Linguists or research partnership, or see recent sightings and updates to the database at the company’s website.


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Forty-nine states and the District of Columbia are pushing an antitrust investigation against Google – gpgmail


Fifty attorneys general are pushing forward with an antitrust investigation against Google, led by the Texas state Attorney General Ken Paxton.

In an announcement on the steps of the U.S. Supreme Court building, Paxton and a gathering of attorneys general said that the focus of the investigation would be on Google’s advertising practices, but that other points of inquiry could be included in the investigation.

The investigation into Google comes as big technology companies find themselves increasingly under the regulatory microscope for everything from anticompetitive business practices to violations of users’ privacy and security, to accusations of political bias.

Last week, the New York State Attorney General launched an investigation into Facebook.

Action from the states follows movement from the federal government which is investigating just about every major technology company including Google, Apple, Amazon, and Facebook.

This story is developing.




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Why am I seeing this ad? AI, ML & human error in advertising – gpgmail


Ad platforms create equal opportunities for businesses but not equal outcomes.

They’re mostly marketed as self-service and easy to use, however, there are new features added regularly and open-ended ways to set, structure and target. Meaning, countless ways to spend—creating winners and losers in advertising.

This is where machines and digital advertisers are needed, to provide a profitable outcome.

Enter AI, ML and experts as freelancers, via agencies or housed in some of the world’s biggest companies, equipped with ample data, tech and educational resources to match people with companies via ads on search, social, and elsewhere on the web.

But, are the machines still in infancy or too heavily relied upon and do the experts always get it right?

Well, how often are you seeing ads that are irrelevant to what you wanted or where you were or who you are?

An irrelevant ad is an ad paid for by the company advertising but can return zero value as it’s of no use to the person receiving the ad.

As a digital advertiser via my company Adboy.com, I’m always curious as to why I was served an ad and if the company paying makes or loses money from it.

Something I’ve noticed is that in easily avoidable errors, ads can be served to existing customers, people with irrelevant needs and people that can’t be or are far less likely to become customers.

With this article, I’m going to give you the lenses of a fastidious digital advertiser. You’ll spot errors like these for yourself and know how they could occur, what the negative impact could be and how they can be avoided.

Advertising to existing customers


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Adarga closes £5M Series A funding for its Palantir-like AI platform – gpgmail


AI startup Adarga has closed a £5 million Series A fundraising by Allectus Capital. But this news rather cloaks the fact that it’s been building up a head of steam since it’s founding in 2016, building up – what they say – is a £30 million-plus sales pipeline through strategic collaborations with a number of global industrial partners and gradually building its management team.

The proceeds will be used to continue the expansion of Adarga’s data science and software engineering teams and roll out internationally.

Adarga, which comes from the word for an old Moorish shield, is a London and Bristol-based start-up. It uses AI to change the way financial institutions, intelligence agencies and defence companies tackle problems, helping crunch vast amounts of data to identify possible threats even before they occur. The start-up’s proposition sounds similar to that of Palantir, which is known for working with the US military.

What Adarga does is allow organizations to transform normally data-intensive, human knowledge processes by analyzing vast volumes of data more quickly and accurately. Adarga clients can build up a ‘Knowledge Graph’ about subjects, and targets.

The UK government is a client as well as the finance sector, where it’s used for financial analysis and by insurance companies. Founded in 2016, it now has 26 employees – including data scientists from some of the UK’s top universities.

The company has received support from Benevolent AI, one of the key players in the UK AI tech scene. Benevolent AI, which is worth $2bn after a $115m funding round, is a minority shareholder in Adarga. It has not provided financial backing, but support in kind and technical help.

Rob Bassett Cross, CEO of Adarga, commented: “With the completion of this round, Adarga is focused on consolidating its competitive position in the UK defence and security sector. We are positioning ourselves as the software platform of choice for organisations who cannot deal effectively with the scale and complexity of their enterprise data and are actively seeking an alternative to knowledge intensive human processes. Built by experienced sector specialists, the Company has rapidly progressed a real solution to address the challenges of an ever-growing volume of unstructured data.”

Bassett Cross is an interesting guy, to say the least. You won’t find much about him on LinkedIn, but in previous interviews, he has revealed that he is a former army officer and special operations expert who fought in Iraq and Afghanistan, and was awarded military cross.

The company recently held a new annual event, the Adarga AI Symposium at the The Royal Institution, London, which featured futurist Mark Stevenson, Ranju Das of Amazon Web Services, and General Stanley A. McChrystal.

Matthew Gould, Head of Emerging Technology at Allectus Capital, said: “Adarga has developed a world-class analytics platform to support real-time critical decisioning by public sector and defence stakeholders. What Rob and the team have built in a short time is a hugely exciting example of the founder-led, disruptive businesses that we like to partner with – especially in an ever-increasing global threat landscape.”

Allectus Capital is based in Sydney, Australia and invests across Asia-Pacific, UK and US. It has previously invested in Cluey Learning (Series A, A$20M), Everproof, Switch Automation and Automio.


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Syte snaps up $21.5M for its smartphone-based visual search engine for e-commerce – gpgmail


Visual search has become a key component for how people discover products when buying online: if a person don’t know the exact name of what he or she wants, or what they want is not available, it can be an indispensable tool for connecting them with things they might want to buy.

Now, one of the companies building technology to do this has raised a round of funding to expand its business further into the US, and not just across digital platforms, but to tap further into the opportunities of bringing visual search into the world of physical commerce, too, by way of smart mirrors and apps for store assistants to better help customers.

Syte, a Tel Aviv startup that works with fashion retailers like Farfetch and River Island as well as those who sell a wider variety of goods like Argos, Sainsbury’s and Kohl’s, has raised $21.5 million in funding. The Series B was led by Viola Ventures, with participation also from Storm Ventures, Commerce Ventures, and Axess Ventures. Syte has now raised $32 million including a previous round in 2017; it’s not disclosing its valuation but is projecting 300 percent revenue growth this year.

The use of visual search — using computer vision to “read” a picture, match it up with its metadata, and then find pictures of products that are similar to it — has become commonplace in e-commerce in recent years.

Among the many other companies that have this kind of tech — including visual search platforms like Pinterest and social media platforms themselves — Syte’s approach is notable in how it engages shoppers in the process of the search. Users can snap pictures of items that they like the look of, which can then be used to on a retailer’s site to find compatible lookalikes. Retailers, meanwhile, can quickly integrate Syte’s technology into their own platforms by way of an API.

Lihi Pinto Fryman, Syte’s CMO who co-founded the company in London with husband Ofer Fryman, Idan Pinto and Dr Helge Voss, said in an interview that the company spent about three years developing its technology — spurred initially by her own surprise, when she was working as an investment banker, at not being able to find a particular dress she spotted in a magazine — and only launched a product about 18 months ago. Since then, she says the company has seen “super hyper” growth because of the gap the company is filling.

The crux of the problem goes something like this: Retailers both online and offline have found that a new generation of shoppers are less interested in visiting their storefronts.

They are instead shopping by browsing social media platforms like Instagram and buying from there, which essentially opens those retailers to whole new set of competitors, and potentially at a great disadvantage, since they are not as well equipped to speak to that audience or anticipate what interests them to trigger sales.

“Young people are on Instagram for hours each day,” Fryman said. Indeed, Instagram is one of the only big social networks that’s seeing usage rise at the moment. “Retailers need to find a way to compete with that and remain in the market, and they can’t just continue what they’ve always done.”

On the other hand, while there are a number of visual search tools out in the market, not all of them are useful enough. “If you are searching for a ruffled floral yellow dress but you get a blouse, it just doesn’t cut it,” she noted. “And if it takes seven seconds to get an answer, that’s also not good, because people will give up after 2 seconds. Millennials and Gen Z shoppers have a very short attention span, so you need to be accurate and fast.”

The idea is that a product like Syte’s addresses both of these issues, and then some. In addition to its camera-based search service, it provides a recommendation engine to retailers, plus tagging services for its back catalog to complete the service.

“Rarely do we find companies that have managed to solve a technological problem that tech giants have been working for years to solve without success,” says Ronen Nir, General Partner at Viola Ventures, in a statement. “The feedback from the market is clear and swift and the rate of adoption of Syte’s solution is unparalleled. We are excited to lead a significant funding round that would be able to take the company to the next level.”

Syte’s more recent foray into physical commerce is an interesting turn as well. Smart mirrors have been more of a wishlist item than something that has seen critical mass adoption so far in changing rooms.

If the idea does catch on, I wonder what kind of a digital divide it might create among retailers, since the cost of refurbishing changing rooms to include these, along with all the backend changes that would need to be made, will likely be only the kind of service that bigger or high-end boutiques will be able to shoulder. More interesting, perhaps, is the idea of app-based tools for assistants, many of whom already carry a smartphone and would likely be grateful for recommendations to help sell better to customers.

“We have a vision to transform product discovery, and thus the eCommerce experience, for both retailers and consumers.” said Ofer Fryman in a statement. “That vision is what has led us since we founded Syte, and it is what continues to lead us as we enter this stage.”


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Drivetime nabs $11M from Makers Fund, Amazon and Google to build voice-based games for drivers – gpgmail


Fully autonomous cars may (or may not) be just around the corner, but in the meantime, a startup that’s building in-car apps to help human drivers pass the time when behind the wheel has raised a round of funding.

Drivetime — which makes voice-based trivia quizzes, games and interactive stories that people can play while driving — has raised $11 million in funding led by Makers Fund (a prolific investor in gaming startups), with participation also from Amazon (via the Alexa Fund) and Google (via its Assistant investment program).

The startup today has eight “channels” on its platform consisting of games and stories that you can access either within a limited free-to-play tier or via a paid subscription ($9.99 a month or $99.99 a year). The plan is to use the funding to continue expanding that catalog, as well as investing in deeper integrations with its new big-name strategic investors, who themselves have longstanding and deep interests in bringing more voice services and content to the in-car experience.

Co-founder and CEO Niko Vuori told gpgmail that his ultimate ambition is for Drivetime to become “the Sirius XM of interactive content” for cars, with hundreds of different channels of content.

In keeping with those plans, along with the funding, Drivetime is today announcing a key content deal.

It has teamed up with the long-running, popular gameshow Jeopardy to build a trivia channel for the platform, which lets drivers test their own skills and also play against other drivers and people they know. The Jeopardy channel will source content from the TV show’s trove of IP and come with another familiar detail: it will be narrated by Alex Trebek, with a new quiz getting published every weekday for premium users.

That social element of the Jeopardy game is not a coincidence. The San Francisco-based startup is founded by Zynga alums, with Vuori and his co-founders Justin Cooper and Cory Johnson also working together at another startup called Rocket Games since leaving the social games giant and exiting that as well, to gaming giant Penn National, for up to $170 million. That track record goes some way to explaining the strong list of investors in the new startup.

“Social and interactive formats are the next frontier in audio entertainment,” said Makers Fund Founding Partner Jay Chi, in a statement. “Niko, Justin Cooper and Cory Johnson, with a decade-long history of working together and a proven track record in building new platforms, is the best team to bring this idea to life.”

“Gaming and entertainment are among customers’ favorite use cases for Alexa, and we think those categories will only grow in popularity as Alexa is integrated into more vehicles,” said Paul Bernard, director of the Alexa Fund at Amazon, in a separate statement. “Drivetime stands out for its focus on voice-first games in the car, and we’re excited to work with them to broaden the Alexa Auto experience and help customers make the most of their time behind the wheel.”

In addition to the three investors in this latest round, prior to this Drivetime had raised about $4 million from backers that include Felicis Ventures, Fuel Capital, Webb Investment Network (Maynard Webb’s fund) and Access Ventures.

Vuori declined to say how many installs or active users the app has today — although from the looks of it on AppAnnie, it’s seeing decent if not blockbuster success on iOS and Android so far.

Instead, the company prefers to focus on another stat, its addressable market, which it says is 110 million drivers in North America alone.

Meanwhile, adding a Jeopardy channel is building on what has worked best so far. The most popular category at the moment is trivia, with Tunetime (a “name that tune” game) coming in second with storytelling a third.

Drivetime’s premise is an interesting one. Drivers are a captive audience, but one that has up to now had a relatively limited amount of entertainment created for it, focusing mainly on music and spoken word.

However, the rise of voice-based interfaces and interactivity using natural language — spurred by the rise of personal assistant apps and in-home hubs like Amazon’s Echo — have opened a new opportunity, developing interactive, voice-based content for drivers to engage with more proactively.

You might think that this sounds like a recipe for a car accident. Won’t a driver get too distracted trying to remember the fourth President of the United States, or who was known as the Father of the Constitution? (Hint: it’s the same guy.)

Vuori claims it’s actually the reverse: having an interactive game that requires the driver to speak out loud can focus him or her and keep the driver more alert.

“We are double-dipping in safety,” he said. “On the one hand, we embody the safety aspects of Alertness Maintaining Tasks (AMTs). But we also act as a preventative, meaning that while players engage with Drivetime, they are not engaging with anything else.”

While the content today may serve as a way of keeping drivers from doing things they shouldn’t be doing while in a car, there is another obvious opportunity that might come as drivers become less necessary and themselves will need other things to occupy themselves.

Longer term, the Jeopardy deal could usher in other channels based on popular gameshows. Sony Pictures Television Games, which owns the rights to it, also owns Wheel of Fortune, and Who Wants To Be a Millionaire.

“We are thrilled to work with Sony Pictures Television Games to bring Jeopardy, the greatest game show on the planet, to an underserved audience that desperately needs interactive entertainment the most – the 110 million commuters in North America driving to and from work by themselves every day,” said Vuori said in a statement.

Interestingly, despite the growth of “skills” for Alexa or apps for Google Home and other home hubs, and the overall popularity of these as a way of interacting with apps and sourcing information, Vuori says that he hasn’t seen any competition emerge yet from other app developers to build voice-based entertainment for drivers in the way that Drivetime has.

That gives the company ample opportunity to continue picking up new users — and more details with publishers and content companies looking for more mileage (sorry) for their legacy IP and new business.

“Drivetime is one of the early pioneers in creating safe, stimulating entertainment for drivers in the car,” Ilya Gelfenbeyn, founding lead of the Google Assistant Investments Program, noted in a statement. “More and more people are using their voice to stay productive on the road, asking the Google Assistant on Android and iOS phones to help send text messages, make calls and access entertainment hands free. We share Drivetime’s vision, and look forward to working with their team to make the daily commute more enjoyable.”


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Top VCs on the changing landscape for enterprise startups – gpgmail


Yesterday at gpgmail’s Enterprise event in San Francisco, we sat down with three venture capitalists who spend a lot of their time thinking about enterprise startups. We wanted to ask what trends they are seeing, what concerns they might have about the state of the market, and of course, how startups might persuade them to write out a check.

We covered a lot of ground with the investors — Jason Green of Emergence Capital, Rebecca Lynn of Canvas Ventures, and Maha Ibrahim of Canaan Partners — who told us, among other things, that startups shouldn’t expect a big M&A event right now, that there’s no first-mover advantage in the enterprise realm, and why grit may be the quality that ends up keeping a startup afloat.

On the growth of enterprise startups:

Jason Green: When we started Emergence 15 years ago, we saw maybe a few hundred startups a year, and we funded about five or six. Today, we see over 1,000 a year; we probably do deep diligence on 25.


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Battlefield winner Forethought adds tool to automate support ticket routing – gpgmail


Last year at this time, Forethought won the gpgmail Disrupt Battlefield competition. A  $9 million Series A investment followed last December. Today at gpgmail Sessions: Enterprise in San Francisco, the company introduced the latest addition to its platform called Agatha Predictions.

Forethought CEO and co-founder, Deon Nicholas, said that after launching its original product, Agatha Answers to provide suggested answers to customer queries, customers were asking for help with the routing part of the process, as well. “We learned that there’s a there’s a whole front end of that problem before the ticket even gets to the agent,” he said. Forethought developed Agatha Predictions to help sort the tickets and get them to the most qualified agent to solve the problem.

“It’s effectively an entire tool that helps triage and route tickets. So when a ticket is coming in, it can predict whether it’s a high priority or low priority ticket and which agent is best qualified to handle this question. And this all happens before the agent even touches the ticket. This really helps drive efficiencies across the organization by helping to reduce triage time,” Nicholas explained.

The original product Agatha Answers is designed to help agents get answers more quickly and reduce the amount of time it takes to resolve an issue. “It’s a tool that integrates into your Help Desk software, indexes your past support tickets, knowledge base articles and other [related content]. Then we give agents suggested answers to help them close questions with reduced handle time,” Nicholas said.

He says that Agatha Predictions is based on the same underlying AI engine as Agatha Answers. Both use Natural Language Understanding (NLU) developed by the company. “We’ve been building out our product, and the Natural Language Understanding engine, the engine behind the system, works in a very similar manner [across our products]. So as a ticket comes in the AI reads it, understands what the customer is asking about, and understands the semantics, the words being used,” he explained. This enables them to automate the routing and supply a likely answer for the issue involved.

Nicholas maintains that winning Battlefield gave his company a jump start and a certain legitimacy it lacked as an early-stage startup. Lots of customers came knocking after the event, as did investors. The company has grown from 5 employees when it launched last year at gpgmail Disrupt to 20 today.


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