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PimEyes is a Polish search engine that’s raising some eyebrows over its privacy implications. Powered by facial recognition technology, the service takes any portrait of a person and finds other photos of that person on the Web.

ClearView AI is a service that has been stirring up controversy by scraping social media photos and making them searchable through facial recognition by law enforcement. PimEyes is similar, except it’s a free service available to the public even without signing up.

Google’s popular reserve image search can find photos similar in appearance to images you provide, but PimEyes specifically uses facial recognition and can accept multiple reference photos to find images of specific individuals.

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What’s even creepier is the fact that you can pay for a premium account — $10 for one alert or $15/month for up to 25 — on the service and get alerts every time a similar face is found.

“PimEyes markets its service as a tool to protect privacy and the misuse of images,” writes OneZero. “But there’s no guarantee that someone will upload their own face, making it equally powerful for anyone trying to stalk someone else.”

[Source: This article was published in petapixel.com By MICHAEL ZHANG - Uploaded by the Association Member: Jason bourne]

Categorized in Search Engine

One of Google Photos’ best features is face recognition for easier grouping, search, and sharing with friends and family. Google is now extending that detection and adding naming support for your cats and dogs.

The picture backup and management service has long been able to recognize animals in general and surface them in search results. However, users would not be able to easily find pictures of just their pet and have to rely on general lookup terms like “dog” or “cat.”

That is changing today, with Google Photos now recognizing specific dogs or cats as long as there is a clear shot of their face. Users are able to label them by name and in turn have them treated as people when looking for pictures.

It appears that there is a new combined “People & Pets” section where animals show up. From there, tapping through to those images should feature the ability to “Add a name.”

Other pet-centric features already available in Google Photos include the ability to search by specific cat or dog breed. Additionally, users can search for animals with emoji.

Today’s new features complement Photos’ existing ability to make movies from images of your pets. Since May, some users have been greeted by clips of their pets, but users can also manually make movies by heading to Assistant. Here, they have control over images and the background soundtrack.

The pet recognition and tagging feature is rolling out in most countries starting today.

 

Source: This article was published 9to5google.com By Abner Li

Categorized in Search Engine

In partnership with academics from the University of Oxford, a London start-up has condensed the power of cloud based visual search technology to the size of a book. The Pholio device, which can safely store or access your media all in one place, allows an incredible level of search and discovery across your photos and home videos. The software in Pholio automatically checks all images in your collections against 20,000 in-built search terms, from ‘birthday’ to ‘christmas’ and ‘house renovation’.  By keying a relevant search term into a browser on a connected TV screen, tablet, phone or laptop at home, families can search for all sorts of things in their own photo collections – from day trips to Bangor to bungee jumps in Niagara. What's more, the technology within the Pholio box will evolve for individuals based on their specific interests and collections - each box will end up understanding different things depending on its owner. The basic Pholio device can store up to 500 gigabytes of data, whilst Pholio Pro offers a storage capacity of 2TB. Prices start at £199.

Pholio Press Release

UK START-UP CHALLENGES GLOBAL CLOUD SERVICES WITH A.I. POWERED PRIVATE PHOTO AND VIDEO BOX

  •          London based start-up takes on the likes of Google Photos with Pholio, a book sized in-home personal photo and video processing box
  •          Pholio provides private control and AI-powered, content-based search across the tens of thousands of digital photos and videos we have scattered across mobile devices, social networks, computers, and cloud backups
  •          Pholio’s built-in deep-learning algorithms can spot and instantly retrieve images which match any of 20,000 built-in descriptions. New content-based descriptors can easily be trained by the user based on example images in their collection or on the Internet 

In partnership with academics from the University of Oxford, a London start-up has condensed the power of cloud based visual search technology to the size of a book.

The Pholio device, which can safely store or access your media all in one place, allows an incredible level of search and discovery across your photos and home videos.

Simon Randall, CEO of Pholio, said: “Thanks to smartphones and mobile devices, we are creating more content than ever before.  The problem is that for every upload to the cloud or (yet another) sub-folder created on the computer, you could well be adding hundreds of files.  The chances are that many of these images and videos will sit for years collecting digital dust.  Searching for special memories and discovering those you thought were lost, is now easier than ever before.”

The software in Pholio automatically checks all images in your collections against 20,000 in-built search terms, from ‘birthday’ to ‘christmas’ and ‘house renovation’.  By keying a relevant search term into a browser on a connected TV screen, tablet, phone or laptop at home, families can search for all sorts of things in their own photo collections – from day trips to Bangor to bungie jumps in Niagara.

Pholio was trained in the lab by showing it millions of images with a wide range of content.  A custom set of deep learning algorithms has learnt how to create a unique summary of the contents of images so Pholio can recognise and classify faces, objects and scenes that it has never seen before. Pholio has been trained to recognise 20,000 search terms which can be used fully offline.  If Pholio is connected to the internet, owners can search for anything (Pholio can learn new search terms on the fly based on what users search for).

The technology within the Pholio box will evolve for individuals based on their specific interests and collections - each box will end up understanding different things depending on its owner.  It will be a boon for collectors and hobbyists who can train their systems to recognise the things they care about.  From stamps to birds, cars, shoes or handbags, the device allows detailed exploration and sorting based on what it learns about the collections.

Pholio is now taking pre-orders.  The Pholio device, with built-in search capabilities, is available from £199 for early orders.

According to estimates, a staggering 1.2 trillion photographs will be taken this year, double the number taken four years ago.  With many photographers owning a myriad of devices, from tablets to phones to digital cameras, Pholio is a perfect way of condensing and exploring important family archives.  The basic Pholio device will manage collections of up to 140,000 images, the equivalent of 875 standard photo albums [1].

Simon Randall added: “With the growing volume of data coming from imaging and connected devices in the home there is a critical need for local processing and control.  This will save cloud streaming costs, increase response speeds, and provide choices that don't require handing over control of your data.  Pholio is step 1 in our drive to bring data control and ownership back into the home through harnessing developments in deep learning technology that everyone can make use of.”

A short history of our photography collections

1850s                     The earliest photo albums created.  Owners often put the albums on display and they featured ornate illustrations surrounding the images.

1920s                     35mm film invented

1948                       First Polaroid camera launched

1997                       Philippe Kahn instantly shared the first pictures from the maternity ward where his daughter Sophie was born. He wirelessly transmitted his cell phone pictures to more than 2,000 family, friends and associates around the world. Kahn's wireless sharing software and camera integrated into his cell phone signalled the birth of instant visual communications. Kahn's cell phone transmission is the first known publicly shared picture via a mobile phone.

2000                       The first dedicated camera phone sold in Japan

2004                       Launch of Flickr

2005                       Dixons ends 35mm film camera sales

2010                       Launch of Instagram

2017                       An estimated 1.2 trillion digital images taken, scattering our collections worldwide

2017                       Pholio launches, bringing the photo album home

[1] Pholio: 500GB Storage-140k photos | PholioPro: 2TB Storage –560k photos

Estimate assumes Pholio is setup to store optimised photo thumbnails only and is based on physical photo albums which hold 160 photos

Source: This article was published photographyblog.com By Zoltan Arva-Toth

Categorized in Search Engine

The next great Google product offers a window into a company reshaping itself around images, artificial intelligence, and even more of your personal data

Google tends to throw lots of ideas at the wall, and then harvest the data from what sticks. Right now the company is feasting on photos and videos being uploaded through its surprisingly popular app Google Photos. The cloud-storage service, salvaged from the husk of the struggling social network Google+ in 2015, now has 500 million monthly active users adding 1.2 billion photos per day. It’s on a growth trajectory to ascend to the vaunted billion-user club with essential products such as YouTube, Gmail, and Chrome. No one is quite sure what Google plans to do with all of these pictures in the long run, and it’s possible the company hasn’t even figured that out. But in a landscape fast becoming dominated by artificial intelligence, data — in this case, your photos — has become its own reward.

At the company’s annual I/O developers conference, Google touted Photos as a signature platform getting a bevy of valuable updates. Users will soon be able to automatically share all their uploaded photos with a loved one, or filter which specific photos are auto-shared by date or topic. A new Suggested Sharing feature will use facial recognition to prompt users to send photos of their friends directly to them, similar to Facebook’s Moments app. The service already uses machine-learning algorithms to classify the objects in photos and make them searchable, so that users can easily find all their pictures of dogs or beer or sunsets. With all these perks, plus unlimited storage, Google Photos is set to become the most convenient, powerful option available for managing a large media library. No wonder the app’s user base has grown so fast. (Though I have my doubts about how “active” these users are — Photos comes preinstalled on Android devices and automatically collects your photos; I mostly use it to look up a friend’s dad’s HBO password that I screencapped once in 2014.)

But the question remains: Why is Google offering such a feature-rich product that doesn’t appear to be readily monetizable, outside of the few print photo books the company plans to sell? The simplest answer is that the company wants to keep people within its all-encompassing ecosystem. Today’s tech giants now offer to serve as caretakers to our digital lives across a suite of services in exchange for access to our personal information. “Even if Google doesn’t make any money directly from something that it offers, it’s still gathering data,” says Pedro Domingos, a computer science professor at the University of Washington and author of The Master Algorithm. “Increasingly these days, what people perceive at companies is that data is one of your biggest assets.”

What more data could Google possibly need? The search giant has effectively achieved its longstanding goal of “organizing the world’s information,” if you consider only the written word. But even cofounder Larry Page has acknowledged that the company’s mission statement is outdated. The internet is fast becoming dominated by visual messaging, benefiting platforms such as Facebook, Instagram, and Snapchat. Google Photos, especially now that it’s been fine-tuned for sharing, is a back door into the social networking and chat functionalities that Google has been trying and failing to pitch to customers for the last decade. While we allow the company to passively track us through platforms like Chrome and Maps, Google Photos may be the first Google product that persuades people to actively share their personal information with the company en masse since Gmail.

 

The data obtained from a photo, though, has the potential to be much more sensitive than what’s contained in an email. Google already has plenty of pictures of objects that it’s indexed across the web with its search engine, but it still doesn’t know that much about what individual people look like. To make the Photo app’s sharing and tagging features work, Google has to analyze a photo subject’s facial structure and create a unique “faceprint” for them. The company is currently fighting a lawsuit in Illinois alleging that this facial-recognition technology violates a state law protecting citizens’ biometric data, and the tech hasn’t been rolled out in many parts of Europe for fear it might run afoul of privacy laws.

The ability to quickly categorize people, places, and things is the entire selling point of Google Photos, of course, and facial recognition helps achieve that aim. But as Google’s AI techniques become more sophisticated, the company is weaving an ever-growing web of relational data about the world. Some of it is user-submitted (you can ID your own face in Photos or tag friends’ faces), but much of it is derived from the unknowable calculations of the company’s powerful algorithms, which are being trained to be able to teach themselves in the same way a human can use current knowledge to interpret new information. When I Google my mother’s name, her picture doesn’t come up in the public search results. But if I search “Mom” in my Google Photos library, there’s a picture of us at a restaurant in October, which I definitely never tagged “Mom.” (I asked Google to explain how this happened. A spokesperson said Google Photos doesn’t analyze facial structure to look for familial similarity and that the result may have occurred because characteristics of the photo matched images labeled “mom” in Google’s public image search database.) Accurately ID’ing my mom is an example of Google’s machine-learning systems getting smarter. It’s also extremely creepy.

“What the companies are doing is they’re continually experimenting to see what they can do,” Domingos says. “Apple has rhetoric that they’re really all about your privacy. Facebook is more cavalier. Google is in the middle. They don’t know what people will be comfortable with or not, so they’re in the process of discovering.”

Right now Google Photos is trained “offline,” which means that users’ uploaded photos are not being fed to Google’s AI systems to help them recognize more objects (the company uses Image Search results for that). But the way Google Photos works now certainly won’t be the same way it functions in the future, and ideas that sound invasive today could be sold as innovative tomorrow. In 2009, one of Google’s annual April Fool’s Day jokes was an AI program that could scan users’ emails and automatically write appropriate responses. In 2015 this far-fetched concept was added to the company’s email app Inbox, and last week it rolled out on Gmail. When Google was first delving into voice recognition, it felt the need to ask users to donate their Google Voice voicemails for research purposes. Today the company saves all voice search queries by default and uses them to train its AI systems. The company tends to argue that these sorts of use cases don’t pose privacy concerns because people’s messages and voices are being screened by a computer, not a human.

The cliché when criticizing free internet platforms has always been “You are the product.” Today a more accurate critique might be “You are the resource.” For a long time we worried that tech giants might sell our private information to the highest bidder. But with Silicon Valley throwing all its efforts into artificial intelligence, data itself has become its own currency. Andrew Ng, the researcher who founded the AI project Google Brain, recently called data a “scarce resource.” The firms that have the most of it can create complex machine-learning systems that power essential consumer tech products. The firms that don’t have enough of it probably never will now that we’re all firmly in the camp of Google, Amazon, Facebook, or Apple. “All those [companies] have a built-in, inherent advantage because they have tons and tons of data, and moreover they don’t have to share it with anybody else,” says Alex Rudnicky, a research professor in Carnegie Mellon University’s computer science department. “In order to get the data, they have to provide something of value to users. And that’s kind of nontrivial to figure that out. They get the data, and then they can turn around and pitch these new products that leverage data for something else.”

Google’s entire engineering workflow is fast transitioning to this model. All the AI uses mentioned above — recognizing faces, automatically replying to emails, understanding voice commands — are now organized under a broad machine-learning framework known as TensorFlow. The company is staking its future on this system, scaling it down so that it can work on an Android phone that’s not connected to the internet and scaling up to power a new AI chip that will let outside companies leverage Google’s machine-learning advancements via the cloud. Rather than creating a bunch of siloed algorithms that execute discrete tasks, Google wants to devise an overarching AI that can deal with a wide variety of tasks, just like humans do. “Over time, what we discovered is that the same machine-learning techniques and algorithms that solve problems in one area could be used in lots and lots of other product areas and product domains,” Jeff Dean, the current leader of the Google Brain research team, said in a March blog post. “And so what you see is this general explosion of machine-learning usage across Google, across now hundreds of teams and thousands of developers using these machine learning techniques to solve problems in their areas.”

These are powerful breakthroughs that seem likely to accelerate the pace of technological change. But it’s important to remember they are being spearheaded by a company whose primary objective is to sell targeted advertising. Once a Google product has gone through enough iterations vacuuming up enough data to feel like a human necessity, it inevitably must also become a money spigot, whether it’s in the form of promoted destinations clogging up Google Maps or your Google Home playing a Beauty and the Beast commercial unprompted.

Tech leaders are fond of saying we’re in the “early days” of whatever new innovation they’re showcasing. We’re also in the early days of them figuring out how to make money off of it. A photo album used to be a photo album. Now it’s a searchable database that is self-aware enough to infer human relationships. What will it be tomorrow, and who will pay for it? That’s the question to ask whenever Google or one of its peers shows off a new, too-good-to-be-free product. “Sergey Brin says that Google wants to be the third half of your brain,” Domingos says. “But now think about it: Do you really want the third half of your brain to make a living by showing you ads? I don’t.”

This piece was updated after publication with a response from Google about its facial recognition practices.

Source: This article was published theringer.com By Victor Luckerson

Categorized in Search Engine

The charitable arm of Google and the UN have teamed up on a new website aimed at helping people better understand the Syrian refugee crisis through the combination of data from the United Nations High Commissioner for Refugees (UNHCR) along with satellite imagery, 360 degree photos and stills, videos, stories from refugees, and more. The new site, called “Searching for Syria,” presents this information to visitors in an accessible way – by providing simple but visually immersive answers to questions like “What is happening in Syria?” and even, “what is a refugee?”

Google explained that it’s been able to gauge how much worldwide interest there is on the web from people using its search engine for answers to basic questions about the refugee situation in Syria. “What is happening in Syria?” was among the top trending searches in Germany, France and the U.K. last year, for example, and over tens of millions in 2016 searched for information on the Syria.

The company, including its Google.org arm, partnered with the UNHCR to combine the organization’s annual Global Trends report – which contains facts and figures about refugees, asylum-seekers, migrants and others – with Google’s Search trend data. The idea is to offer web searchers better answers to their ongoing questions, but one that taps into more visual imagery to help paint a picture of the human side of the crisis, and the scale of the situation in the country of Syria.

The site begins with a brief introduction, then takes you pages of questions about Syria, like “What was Syria like before the war?,” “What is going on in Syria?” “Where are Syrian refugees going?” and others.

Questions are answered with short text blurbs relying factual answers and statistics, which are combined with full-screen photos, some of which can be turned 360 degrees for a more immersive viewing of a given place or scene.

For example, one section of the website lets you visit half a dozen UNESCO world heritage sites in 360 degrees, including the ancient cities of Aleppo, Bosra, and Damascus, the ancient villages of Northern Syria, Crac des Chevaliers and Qal’at Salah El-Din and the site of Palmyra. After panning through the beautiful imagery, you scroll down to the next slide and learn that the war in Syria has damaged or destroyed them all.

Visualization in the form of charts and graphs are also sometimes present, along with personal stories from refugees and videos from YouTube.

There are only five questions on the site, but scrolling through all their components takes some time. In reading through and watching the material, visitors are meant to understand the true human toll the war has taken on Syrian lives.

The site also encourages visitors to learn how they can help – by signing the UNHCR’s petition to pledge your support that you stand #WithRefugees, making a donation, or just sharing the website to raise awareness.

 

Though largely an educational experience, there’s of course a political undertone to Google’s investment in this resource.

The U.S. and some other countries have pushed back against allowing Syrian refugees to cross their borders. This includes Trump’s hardline stance on Syria in general in which the president has proposed cuts to foreign aid, including the U.N. and agencies helping refugees. He has also tried to stop Syrian refugees from entering the country twice – moves that were blocked by courts. Meanwhile, on Sunday, the U.S. ambassador to the U.N. – seemingly ignoring Trump’s proposed budget – has pledged increased support from the U.S. for the refugees.

This is not Google.org’s first time addressing the crisis – it has already invested more than $20 million in grants supporting solutions to provide over 800,000 refugees with emergency support and access to critical information and education, the company says.

The new site is available here.

Source: This article was published techcrunch.com By Sarah Perez

Categorized in Search Engine

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