France’s RoboCARE bets robots can keep elderly healthy and teach the French to speak better English

RoboCARE wants to put Milo in nursing homes and schools.

TOULOUSE, France — Robots may still be a long away from experiencing emotion, but one French company believes that they can be used to improve connections between humans in areas such as health care and education.

RoboCARE Lab, a company based in Toulouse, France, has launched an ambitious campaign to place robots in nursing homes and schools across the country. The hope is that these robots could help the elderly remain in closer contact with family while stimulating their memories and spirits to improve their long-term health.

In French schools, which have struggled at times to effectively teach English, the robots would provide extra help and motivation for students and teachers. There are also plans to develop a French curriculum for the robots to help autistic children learn social skills and empathy.


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Naturally, in a country like France, which can at times have a contentious relationship with innovative changes, the founders of the company are proceeding with some caution. But in the long run, they believe this new technology could have a big impact on France, and eventually around the world.

“This is something we think can be used to reach older people and younger people as well,” said Faissal Houhou, who co-founded RoboCARE with Dominique Blasco. “And we think France is ready for something like this.”

As the founders have toured recently with their robots to discuss their plans, they’ve certainly generated tremendous attention in the French media.

At the moment, RoboCARE uses two different robots. The first is called “Milo,” and is built by RoboKind, a company based in Texas. Milo has a face that is animated when he speaks, and makes small gestures and motions as he communicates.

Milo is used to lead group games, including memory quizzes, group exercises or singing to keep nursing home residents engaged.

Fred Margolin, chief executive of RoboKind, said his company has been working on Milo for several years now. In the process, they’ve taken a robot that originally cost $35,000 to build and shrunk the cost to under $6,000, making it more affordable for industries that need a widespread deployment.

In the U.S., RoboKind has focused on developing the robots for use with autistic children, in a program called Robots4Autism. He’s hoping the RoboCARE will create a French version of that curriculum, which is massive in the scope of its content and lessons.

RoboKind is also working on finding ways to get Milo into U.S. nursing homes, and says they believe the robot can be effective in helping to delay the early effects of problems like dementia. He’s optimistic RoboCARE in France will pave the toward a broader international market, and has been impresed so far with the company’s progress.

“I seems like RoboCARE has really taken the ball and run with it,” Margolin said.

Starting next year, Milo will also be used in a school in Picardy, France to assist with teaching English. It can be challenging to find teachers, particularly at the elementary school level, who are qualified and capable of effectively teaching English, Houhou said. He hopes educators will embrace Milo as a new teaching tool.

The other robot used by RoboCARE is a telepresence machine from Suitable Technologies. This is also being tested by two Toulouse-area nursing homes.

This robot is a computer monitor on a stand with wheels. Family members who can’t afford to make regular visits can book time online with the robot, and then control it from their own computer.

Houhou said the system provides big advantages over basic Skype video chats or phone calls. The fact that the robot can follow a resident around often leads to longer calls and interactions. And in many cases, residents may not be capable of using a computer or holding a phone for extended periods.

More importantly, whether its Milo or the telepresence robot, Houhou says the robots create a more enhanced feeling that the person is closer.

“The robot is a presence,” Houhou said. “You are not there, but it feels more like a real person.”










Yahoo ex-CIO Mike Kail’s new cyber-security startup Cybric raises $1.3M

security

Six months after departing from Yahoo, Mike Kail has reemerged as the cofounder and CIO of a security startup called Cybric. His new company, cofounded by Ernesto DiGiambattista, Andrew Gilman, and Sean Walter, is launching today with $1.3 million in seed funding behind it.

Kail left Yahoo nearly six months ago after a lawsuit revealed that he may have been receiving kickbacks from vendors while at Netflix. Since then he’s been operating under the radar.

His new venture addresses all aspects of enterprise security at a time when many cyber-security startups are busy building companies around individual security features.


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Cybric’s cloud-based platform simultaneously checks applications, integrations, operating systems, data centers, and other components of an enterprise network for anomalies using a shadow environment. The company employs high performance computing (also know as fabric computing) so it can perform multiple processes at once. This allows Cybric to constantly scan a network for threats and automatically remediate vulnerabilities and attacks.

The company has built its platform to easily integrate with other enterprise security technology. The idea is that through a fabric based platform, Cybric will be able to give enterprises a more holistic understanding of how secure their network is.

In the last several years, lots of new cyber security startups have emerged to capture gobs of venture capital. For evidence look at Code42’s recent $85 million raise, or Zscaler’s $100 million funding announcement from over the summer. It’s not just in Silicon Valley either. A recent report from Forbes notes that in 2015, cyber-security companies have raised $2.3 billion globally.

“There have been tons and tons of companies coming out…and there’s big spending and a lot of confusion and a lot of complexity,” says Cybric chief operating officer Andrew Gilman.

Unlike the legacy institutions that came before them, many of these startups are small and based around a single feature. Rather than provide an enterprise with everything, these companies focus on securing one element like protecting web access, data centers, or an internal enterprise network.

Through its new technology, Cybric is hoping to simplify the security space. In the short term, that means the company will focus on making its technology highly compatible with existing enterprise security software. In the future, it could mean acquiring security features to round out its platform.

To gear up for its next phase, Cybric says it will continue to raise funding over the next year.










Opera’s Max Data-Savings App Now Comes Pre-Installed On Phones From 14 OEMs

opera-max-100m Opera today announced that its Opera Max data-management app is now integrated into phones from 14 OEMs. These include previously announced partners like Samsung and Xiaomi, as well as three newly announced partners: Acer, Hisense and TWZ. Thanks to these partnerships, Opera now believes its Max software will be on more than 100 million Android phones by 2017. Opera Max essentially works as… Read More

500 Startups-backed Mobingi wants to automate your company’s cloud, starting with AWS

mobingi

(By Masaru Ikeda, The Bridge) – Mobingi, a Japanese startup based in Tokyo and Silicon Valley, announced on Friday that it has fundraised $125,000 from 500 Startups and is participating in the 15th batch of the 500 Startups acceleration program beginning October 13th. The latest funding follows their previous seed funding from Digital Garage back in January of this year.

Mobingi provides an automated app maintenance platform for users of Amazon Web Services (AWS) and other cloud services. Targeting small and medium-sized enterprises, typically unlikely to arrange engineers specifically for maintaining cloud or server environment, the company wants to enable more systems development focus by them through elimination of DevOps tasks.

According to Mobingi CEO Wayland Zhang, his company plans to make the Mobingi platform compatible with other cloud services like Microsoft Azure, Softlayer and Google Cloud Platform, but first they are focusing on AWS and trying to spread word of the service through AWS user communities. They have acquired outstanding companies as clients such as Yamada Denki (major consumer electronics retailer chain in Japan), Digital Garage, University Press Center of Japan, Digital Cube (providing system integration focused on content management system) and Japanese gaming developer G&D.

ss_dashboard

Graduated from the 9th batch of the Open Network Lab accelerator, Mobingi participated in the Tokyo preliminary event of the Slush pitch competition in October last year, followed by incorporation of Mobingi K.K. and securing of seed funding (2 million yen or about $16,000) from Digital Garage this January. They have been exploring another funding opportunity in Japan for further service development, but they recognized it’s hard for cloud or PaaS (platform as a service) developers to gain funds in Japan and subsequently set up Mobingi Inc. in Silicon Valley to fundraise in the US. While they are participating in the latest 500 Startup incubation batch, many members of the engineering team are working out of Tokyo.

The members of the Mobingi team are a dazzling selection. Graduating from University of Toronto in Canada, CEO Wayland Zhang joined the country’s largest online ad platform Clicksor.com. Subsequently he founded several startups in Beijing as a serial entrepreneur. Yasuhiro Horiuchi, former CTO of Japanese mobile gaming company Gumi (TSE:3903) who is also known as a former AWS evangelist, had been serving Mobingi as an advisor but he joined the board of directors this time around. Shingo Yoshida, formerly evangelist at AWS-focused system integration company Iret, also joined the team as a senior advisor.


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According to the Mobingi engineering team, what differentiates Mobingi most from other similar platforms is the database clustering feature. While load balancing for web apps are relatively easily installed on many cloud services, database clustering typically requires a lot of work as well as time for installment and configuration. By simplifying this process, Mobingi helps engineers secure fault tolerance and performance of service maintenance.

In addition to the Mobingi platform, the company also provides a freemium PaaS (platform as a service) for freelance developers, called moCloud with the intention of marketing services.

The “AWS Japan Mafia”

We’ve recently seen more than a few cases of evangelists and engineers from AWS Japan founding businesses or changing jobs to startups. The diagram below shows you how they are migrating in the Japanese startup scene including Mobingi. Horiuchi said a cloud engineering-ecosystem of startups are being formed in Japan, where they change jobs to cloud-focused startups or move to a cloud-oriented department at a big company.

aws-japan-mafia-nov2015-620x354

Edited by “Tex” Pomeroy










500 Startups-backed Mobingi wants to automate your company’s cloud, starting with AWS

mobingi

(By Masaru Ikeda, The Bridge) – Mobingi, a Japanese startup based in Tokyo and Silicon Valley, announced on Friday that it has fundraised $125,000 from 500 Startups and is participating in the 15th batch of the 500 Startups acceleration program beginning October 13th. The latest funding follows their previous seed funding from Digital Garage back in January of this year.

Mobingi provides an automated app maintenance platform for users of Amazon Web Services (AWS) and other cloud services. Targeting small and medium-sized enterprises, typically unlikely to arrange engineers specifically for maintaining cloud or server environment, the company wants to enable more systems development focus by them through elimination of DevOps tasks.

According to Mobingi CEO Wayland Zhang, his company plans to make the Mobingi platform compatible with other cloud services like Microsoft Azure, Softlayer and Google Cloud Platform, but first they are focusing on AWS and trying to spread word of the service through AWS user communities. They have acquired outstanding companies as clients such as Yamada Denki (major consumer electronics retailer chain in Japan), Digital Garage, University Press Center of Japan, Digital Cube (providing system integration focused on content management system) and Japanese gaming developer G&D.

ss_dashboard

Graduated from the 9th batch of the Open Network Lab accelerator, Mobingi participated in the Tokyo preliminary event of the Slush pitch competition in October last year, followed by incorporation of Mobingi K.K. and securing of seed funding (2 million yen or about $16,000) from Digital Garage this January. They have been exploring another funding opportunity in Japan for further service development, but they recognized it’s hard for cloud or PaaS (platform as a service) developers to gain funds in Japan and subsequently set up Mobingi Inc. in Silicon Valley to fundraise in the US. While they are participating in the latest 500 Startup incubation batch, many members of the engineering team are working out of Tokyo.

The members of the Mobingi team are a dazzling selection. Graduating from University of Toronto in Canada, CEO Wayland Zhang joined the country’s largest online ad platform Clicksor.com. Subsequently he founded several startups in Beijing as a serial entrepreneur. Yasuhiro Horiuchi, former CTO of Japanese mobile gaming company Gumi (TSE:3903) who is also known as a former AWS evangelist, had been serving Mobingi as an advisor but he joined the board of directors this time around. Shingo Yoshida, formerly evangelist at AWS-focused system integration company Iret, also joined the team as a senior advisor.


From VentureBeat
How do you get consumers to connect with and engage with your brand flawlessly? This free and interactive web event arms you with the tools you’ll need to get ahead.

According to the Mobingi engineering team, what differentiates Mobingi most from other similar platforms is the database clustering feature. While load balancing for web apps are relatively easily installed on many cloud services, database clustering typically requires a lot of work as well as time for installment and configuration. By simplifying this process, Mobingi helps engineers secure fault tolerance and performance of service maintenance.

In addition to the Mobingi platform, the company also provides a freemium PaaS (platform as a service) for freelance developers, called moCloud with the intention of marketing services.

The “AWS Japan Mafia”

We’ve recently seen more than a few cases of evangelists and engineers from AWS Japan founding businesses or changing jobs to startups. The diagram below shows you how they are migrating in the Japanese startup scene including Mobingi. Horiuchi said a cloud engineering-ecosystem of startups are being formed in Japan, where they change jobs to cloud-focused startups or move to a cloud-oriented department at a big company.

aws-japan-mafia-nov2015-620x354

Edited by “Tex” Pomeroy










Pinterest now lets you find visually similar things inside of pins

visual-search-results-static

Pinterest is enhancing is search engine to help users better discover new and interesting content. The company announced that starting on Monday, it’ll launch a new visual search tool which allows you to take any existing pin, zoom into any part of the associated image, and then get results for visually similar pins. This offering will be available to all of the more than 100 million monthly active users globally across iOS, Android, and the Web.

“Sometimes you spot something you really love on Pinterest, but you don’t know how to find it in real life, or what it’s even called,” Kevin Jing, an engineering manager at Pinterest wrote in a blog post. “There’s that perfect lamp hiding in a Pin of someone’s living room, or maybe a random street style shot with the exact shoes you’re looking for.”

When you spot something in a pin that you’d like to know more about, tap on the search tool that’ll appear in the corner of the image. Then select the specific part of the pin you’re interested in (kind of like cropping the image), and Pinterest’s deep learning algorithm will scan that selection and pull up associated Pins that it thinks match. The company says that you’ll be able to further filter the results by topic.

visual-search-results-blog

This new visual search tool builds upon services that Pinterest has debuted over the past couple of years. Two years ago, the company debuted related Pins, which showed you results based on things that you’ve saved in boards or pins that you’ve liked. That drastically changed earlier this year when Pinterest enhanced it with deep learning and planned to utilize object recognition (!), through its acquisition of VisualGraph, to make its service more efficient.

Another key component of this visual search tool is Guided Search, which launched in 2014. This is a tool that provided you with pins based on what you’ve typed — even if you didn’t know what you’re looking for. Pinterest’s software engineer on its Discovery team Kevin Ma, stated previously: “Since its launch, Guided Search has become an important driver of Pinterest search traffic and Pinner engagements.”


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Personalization gets you in the door. Mobile personalization gets you in their hearts. Find out more in this free interactive web event.

Pinterest says that it took four engineers a few months to develop the core functionality of this visual search system: how images were represented. The company collaborated with the Berkeley Vision and Learning Center to apply deep learning to analyze images across its “annotated dataset of billions of pins”. As a result of this project, the team built a distributed index and search system with open source tools to enable Pinterest’s back end to scan the massive amounts of images that are within Pinterest’s database.

As deep learning is being applied, you can expect some errors in the beginning, but Pinterest says that the more you post to the site, the better the technology will be and adapt to make visual discovery that much better.

This visual search capability will likely mesh well with Pinterest for both users and brand advertisers. With the former, it’ll make it easier to find what they’re looking for by just pointing and clicking (in a manner of speaking). How often have you seen an image, wanted to find what a specific object was, but couldn’t come up with words to describe it?

In the latter situation, brands may see an opportunity to apply a Promoted Pin so that if you’re looking for a dining room table that’s from IKEA or Crate & Barrel, or perhaps a suit from Tom Hardy, or even that Omega watch from the new James Bond movie “Spectre”, brands could have their pins show up in a user’s feed as being related. Pinterest hasn’t disclosed how this’ll work right now, but it’s probably not that far-fetched to think that this scenario could happen.

Pinterest certainly isn’t the only one deploying image recognition to help people search — Google, Facebook, and Snapchat to name a few — but it’s significant for the company. Billing itself as a visual search and discovery engine, it’s the new Google where people can just browse and click to find what they’re interested in. And if a picture is worth a thousand words, that definitely says a lot.

More information:

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Pinterest now lets you find visually similar things inside of pins

visual-search-results-static

Pinterest is enhancing is search engine to help users better discover new and interesting content. The company announced that starting on Monday, it’ll launch a new visual search tool which allows you to take any existing pin, zoom into any part of the associated image, and then get results for visually similar pins. This offering will be available to all of the more than 100 million monthly active users globally across iOS, Android, and the Web.

“Sometimes you spot something you really love on Pinterest, but you don’t know how to find it in real life, or what it’s even called,” Kevin Jing, an engineering manager at Pinterest wrote in a blog post. “There’s that perfect lamp hiding in a Pin of someone’s living room, or maybe a random street style shot with the exact shoes you’re looking for.”

When you spot something in a pin that you’d like to know more about, tap on the search tool that’ll appear in the corner of the image. Then select the specific part of the pin you’re interested in (kind of like cropping the image), and Pinterest’s deep learning algorithm will scan that selection and pull up associated Pins that it thinks match. The company says that you’ll be able to further filter the results by topic.

visual-search-results-blog

This new visual search tool builds upon services that Pinterest has debuted over the past couple of years. Two years ago, the company debuted related Pins, which showed you results based on things that you’ve saved in boards or pins that you’ve liked. That drastically changed earlier this year when Pinterest enhanced it with deep learning and planned to utilize object recognition (!), through its acquisition of VisualGraph, to make its service more efficient.

Another key component of this visual search tool is Guided Search, which launched in 2014. This is a tool that provided you with pins based on what you’ve typed — even if you didn’t know what you’re looking for. Pinterest’s software engineer on its Discovery team Kevin Ma, stated previously: “Since its launch, Guided Search has become an important driver of Pinterest search traffic and Pinner engagements.”


From VentureBeat
Personalization gets you in the door. Mobile personalization gets you in their hearts. Find out more in this free interactive web event.

Pinterest says that it took four engineers a few months to develop the core functionality of this visual search system: how images were represented. The company collaborated with the Berkeley Vision and Learning Center to apply deep learning to analyze images across its “annotated dataset of billions of pins”. As a result of this project, the team built a distributed index and search system with open source tools to enable Pinterest’s back end to scan the massive amounts of images that are within Pinterest’s database.

As deep learning is being applied, you can expect some errors in the beginning, but Pinterest says that the more you post to the site, the better the technology will be and adapt to make visual discovery that much better.

This visual search capability will likely mesh well with Pinterest for both users and brand advertisers. With the former, it’ll make it easier to find what they’re looking for by just pointing and clicking (in a manner of speaking). How often have you seen an image, wanted to find what a specific object was, but couldn’t come up with words to describe it?

In the latter situation, brands may see an opportunity to apply a Promoted Pin so that if you’re looking for a dining room table that’s from IKEA or Crate & Barrel, or perhaps a suit from Tom Hardy, or even that Omega watch from the new James Bond movie “Spectre”, brands could have their pins show up in a user’s feed as being related. Pinterest hasn’t disclosed how this’ll work right now, but it’s probably not that far-fetched to think that this scenario could happen.

Pinterest certainly isn’t the only one deploying image recognition to help people search — Google, Facebook, and Snapchat to name a few — but it’s significant for the company. Billing itself as a visual search and discovery engine, it’s the new Google where people can just browse and click to find what they’re interested in. And if a picture is worth a thousand words, that definitely says a lot.

More information:

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