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American business publication Fast Company has released its list of the most innovative companies of 2017. The annual list ranks enterprises that “tap both heartstrings and purse strings and use the engine of commerce to make a difference in the world” according to its website.

Amongst the top ten artificial intelligence and machine learning companies are tech giants Google and IBM and startup Iris AI. AI companies also dominated the top 10 global businesses across all sectors with Amazon at number one.

Amazon was selected as the leading company for “offering even more, even fast and even smarter”. The cloud computing giant which is America’s largest e-commerce company is worth $390 billion. Google was a close second due to its array of projects using artificial intelligence that are designed to reflect the search giant’s original mission: organizing the world’s information and making it universally accessible and useful.

 

Uber, Apple, Snap (the company that founded Snapchat), Facebook, Netflix and Twilio were also featured in the list. Meaning that nine out of the top ten most innovative companies are using artificial intelligence or machine learning.

The artificial intelligence top 10 featured companies ranging massively in size from startup Iris AI with 8 employees to IBM with almost 400,000. Here’s the top 10 in order:

01 Google

“When Google CEO Larry Page created a new holding company called Alphabet in 2015, initiatives such as self-driving cars and health tech got divvied up into new companies, and Google became an Alphabet division with a sharper focus on internet services and software. Today’s Google, now led by CEO Sundar Pichai, still dominates web search and online advertising sales. It has the most widely used mobile operating system (Android) and web browser (Chrome). Other venerable offerings, such as YouTube, Gmail, and Google Maps, continue to be the 800-pound gorillas of their respective categories.”

02 IBM

“Over the past decade, IBM has been moving away from its old business of making and selling computer hardware and transforming itself into something a little more modern: a company that offers services like cloud computing and data analytics.

Since Watson became commercially available, the technology has been applied to everything from cancer research, where Watson is used to sort through and decipher millions of medical journals, to retail, where Watson is being used to help shoppers locate exactly what they’re shopping for or similar items. As of 2017, Watson is already available to more than 400 million people and patients.”

 

03 Baidu

“In 2016, Baidu's CEO Robin Li publicly stated that the company is actively integrating artificial intelligence technologies into all of Baidu's major businesses, including the search engine, as well as new businesses such as autonomous driving. In August, Baidu, Stanford, and the University of Washington released an academic study demonstrating that voice input is more accurate and three times faster than human typing on smartphones.”

04 SoundHound

“In 2016 SoundHound launched its Hound virtual assistant, taking on Siri, Amazon’s Alexa, and the Google Assistant, and there are now 20,000 developers on the Houndify platform, with the service having already been integrated into 150 domains. Among those enterprises who have implemented it are Samsung, Nvidia, Sony’s Xperia, Yelp, and Uber.”

05 Zebra Medical Vision

“For using deep learning to predict and prevent disease”

06 Prisma

“For making masterpieces out of snapshots”

07 Iris AI

“For speeding up scientific research by surfacing relevant data”

08 Pinterest

“For serving up a universe of relevant pins to each and every user”

09 TrademarkVision

“For helping startups make their mark without any legal confusion”

10 Descartes Labs

“For preventing food shortages by predicting crop yields”

Source : http://www.access-ai.com/articles/10-most-innovative-companies-ai-and-machine-learning

Categorized in Internet Technology

Anonymity networks offer individuals living under restraining regimes protection from surveillance of their internet use. But citing the recently divulged vulnerabilities in the most popular of these networks - Tor - has urged computer scientists to bring forth more secure anonymity schemes.

An all-new anonymity scheme that offers strong security guarantees, but utilizes bandwidth more efficiently as compared to its predecessors is in the works.

Researchers at MIT's Computer Science and Artificial Intelligence Laboratory in collaboration with the the école Polytechnique Fédérale de Lausanne will present the new scheme during the Privacy Enhancing Technologies Symposium in this month.

 

During experiments, the researchers' system required only one-tenth as much time as current systems to transfer a large file between anonymous users, according to a post on MIT official website.

Albert Kwon, the first author on the new paper and a graduate student in electrical engineering and computer science said as the basic use case, the team thought of doing anonymous file-sharing where both, the receiving and the sending ends didn't each other.

This was done keeping in mind that honeypotting and other similar things - in which spies offer services via an anonymity network in a bid to entice its users - are real challenges. "But we also studied applications in microblogging," Kwon said - something like Twitter where a user can opt to anonymously broadcast his/her message to everyone.

The system designed by Kwon in collaboration with his coauthors - Bryan Ford SM '02 PhD '08, an associate professor of computer and communication sciences at the école Polytechnique Fédérale de Lausanne, David Lazar, a graduate student in electrical engineering and computer science, Edwin Sibley Webster Professor of Electrical Engineering and Computer Science at MIT and his adviser Srini Devadas - makes use of an array of existing cryptographic techniques, but combines them in a peculiar manner.

The internet, for a lot of people can seem like a frightening and intimidating place and all they seek is help feeling safer on the internet, especially while performing an array of tasks such as making an online purchase, Anonhq reported.

 

Shell game

 A series of servers known as a 'mixnet,' is the core f the system. Just before passing a received message on to the next server, each server rearranges the order in which it receives messages - for instance - messages from Tom, Bob and Rob reach the first server in the order A, B, C, that server would then forward them to the second server in a completely different order, something like C, B, A. The second server would do the same before sending them to the third and so on.

Even if an attacker somehow manages to track the messages' point of origin, he/she will not be able to decipher which was which by the time they moved out of the last server. The new system is called 'Riffle' citing this reshuffling of the messages.

Public proof

In a bid to curb messages tampering, Riffle makes use of a technique dubbed a verifiable shuffle.

Thanks to the onion encryption, the messages forwarded by each server does not resemble the ones it receives, it has peeled off a layer of encryption. However, the encryption can be done in a way that allows the server to generate mathematical evidence that the messages it sends are indeed credible manipulations of the ones it receives.

In order to verify the proof, it has to be checked against copies of messages received by the server. Basically, with Riffle, users send their primary messages to all the servers in the mixnet at the same time. Servers then independently check for manipulation.

As long as one server in the mixnet continues to be uncompromised by an attacker, Riffle is cryptographically secure.

Author : Vinay Patel

Source : http://www.universityherald.com/articles/34093/20160712/mit-massachusetts-institute-of-technology-researchschool-of-engineering-computer-science-and-artificial-intelligence-laboratory-csail-computer-science-and-technology-cyber-security.htm

Categorized in Online Research

Sundar Pichai says that google are making a big bet on machine learning and artificial intelligence.

Technologies like artificial intelligence and machine learning can make huge difference to everyday life and Google is investing in bringing these to "as many people and as fast as possible", its India-born chief Sundar Pichai on Thursday said.

"We are making a big bet on machine learning and artificial intelligence. Advancement in machine learning will make a big difference in many many fields," Pichai said at his alma mater IIT Kharagpur campus on Thursday, while chatting with students.

 

He pointed out that the ability of computers to do tasks like image recognition, voice recognition or speech recognition, are reaching a tipping point.

"So, we are definitely at a point of inflexion," he said, adding that Google is investing a lot in this space and if the investments are sustained over a few years, it will pave the way for the next wave of computing.

Pointing out to a paper published by Google recently, Pichai said machine learning can be used to detect diabetic retina, which can cause blindness if treatment isn't administered on time.

"This is an early example of the kind of changes that will happen when you apply machine learning to all kinds of fields. Google alone won't do this. What I am excited about is bringing machine learning and AI (artificial intelligence) to as many people and as fast as possible," he said. Pichai said that at Google, the aim is very high and the criterion is building technology that will apply to the lives of billions of people.

 



On India, he praised that the PPP model has been working well and the company is a big supporter of the Digital India campaign.

"To really make Google work in India, you need to make it available in as many languages as possible. English is spoken by only a small segment of the population," Pichai said adding Google has progressed but wants to work more in rural conditions and in the right dialects.

To improve access to digital world, he said he would love to see cheaper smartphones hit the market.

"You really need to bring the prices of entry level smartphones down at around $30," he said adding connectivity is also extremely important.

He described India as the most dynamic internet market in the world and the second largest one.

"When we built for India, we built for the world," he said citing the YouTube offline feature which is now available across 80 nations.

In the next 3-4 years, Pichai expects there will be big software companies coming out of India.

When asked by students, he said "You can build for a global market from India."

Pichai said he is convinced that India will become a global player soon.



"I am confident that it will compete with any player in the world. It is growing well as a country and will take few more years," he said when asked to comment on whether India can take on China.

Author : Kharagpur

Source : http://www.business-standard.com/article/pti-stories/google-bets-big-on-artificial-intelligence-117010500764_1.html

Categorized in Search Engine

Rather than leading to the violent downfall of humankind, artificial intelligence is helping people around the world do their jobs, including doctors who diagnose sepsis in patients and scientists who track endangered animals in the wild, experts said Thursday (Oct. 13) at the White House Frontiers Conference in Pittsburgh.

Advancements in the field of artificial intelligence (AI) haven't always been met with enthusiasm. Famed astrophysicist Stephen Hawking warned on several occasions that a fully developed AI could destroy the human race, and Hollywood sci-fi movies are rife with fierce robots battling humans for control. But at yesterday's conference — attended by the country's leading researchers, innovators, entrepreneurs and students — scientists explained how newly developed AI is accelerating research and improving lives.

Wildlife preservation

A herd of Grévy's zebras.
A herd of Grévy's zebras.

Credit: Rich Carey Shutterstock.com

Many researchers want to know how many animals are out there and where they live, but "scientists do not have the capacity to do this, and there are not enough GPS collars or satellite tracks in the world," Tanya Berger-Wolf, a professor of computer science at the University of Illinois at Chicago, said at the conference, which was jointly hosted by the University of Pittsburgh and Carnegie Mellon University and was also streamed live online.

Instead, Berger-Wolf and her colleagues developed Wildbook.org, a site that houses an AI system and algorithms. The system inspects photos uploaded online by experts and the public. It can recognize each animal's unique markings, track its habitat range by using GPS coordinates provided by each photo, estimate the animal's age and reveal whether it is male or female, Berger-Wolf said.

After a massive 2015 photo campaign, Wildbook determined that lions were killing too many babies of the endangered Grévy's zebra in Kenya, prompting local officials to change the lion management program, she said.

"The ability to use images with photo identification is democratizing access to conservation in science," Berger-Wolf said. "We now can use photographs to track and count animals."

Diagnosing sepsis

Sepsis is a complication that is treatable if caught early, but patients can experience organ failure, or even death, if it goes undetected for too long. Now, AI algorithms that scour data on electronic medical records can help doctors diagnose sepsis a full 24 hours earlier, on average, said Suchi Saria, an assistant professor at the Johns Hopkins Whiting School of Engineering. 

Saria shared a story about a 52-year-old woman who came to the hospital because of a mildly infected foot sore. During her stay, the woman developed sepsis — a condition in which a chemical released by the blood to fight infection triggers inflammation. This inflammation can lead to changes in the body, which can cause organ failure or even death, she said.

The woman died, Saria said. But if the doctors had used the AI system, called Targeted Real-Time Early Warning System (TREWScore), they could have diagnosed her 12 hours earlier, and perhaps saved her life, Saria said.

TREWScore also can be used to monitor other conditions, including diabetes and high blood pressure, she noted. "[Diagnoses] may already be in your data," Saria added. "We just need ways to decode them." [A Brief History of Artificial Intelligence]

Search and rescue

Victims of floods, earthquakes or other disasters can be stranded anywhere, but new AI technology is helping first responders locate them before it's too late.

 

Until recently, rescuers would try to find victims by looking at aerial footage of a disaster area. But sifting through photos and video from drones is time-intensive, and it runs the risk of the victim dying before help arrives, said Robin Murphy, a professor of computer science and engineering at Texas A&M University.

AI permits computer programmers to write basic algorithms that can examine extensive footage and find missing people in less than 2 hours, Murphy said. The AI can even find piles of debris in flooded areas that may have trapped victims, she added.

In addition, AI algorithms can sift through social media sites, such as Twitter, to learn about missing people and disasters, Murphy said.

Cybersecurity

Finding flaws and attacks on computer code is a manual process, and it's typically a difficult one.

"Attackers can spend months or years developing [hacks]," said Michael Walker, a program manager with the Defense Advanced Research Projects Agency's (DARPA) Information Innovation Office. "Defenders must comprehend that attack and counter it in just minutes."

But AI appears to be up to the challenge. DARPA held its first Cyber Grand Challenge on Aug. 4 in Las Vegas, a competition won by Mayhem, a program created by the Pittsburgh-based startup ForAllSecure.

Walker described how the second-place team Xandra "discovered a new attack in binary code, figured out how it worked, reached out over a network [and] breached the defenses of one of its opponents, a system named Jima. And Jima detected that breach, offered a patch, decided to field it and ended the breach."

 

The entire episode took 15 minutes. "It all happened before any human being knew that flaw existed," Walker said. The attack happened on a small network, but Walker said he was confident that AI could one day patch bugs and respond to attacks online in the real world.

Restoring touch

Researcher Rob Gaunt prepares Nathan Copeland for brain computer interface sensory test.
Researcher Rob Gaunt prepares Nathan Copeland for brain computer interface sensory test.

Credit: UPMC/Pitt Health Sciences Media Relations

In a landmark event announced Thursday, researchers revealed that a paralyzed man's feelings of touch were restored with a mind-controlled robotic arm and brain chip implants. [Bionic Humans: Top 10 Technologies]

A 2004 car accident left the man, Nathan Copeland, with quadriplegia, meaning he couldn't feel or move his legs or lower arms, Live Science reported yesterday. At the Frontiers Conference, Dr. Michael Boninger, a professor in the Department of Physical Medicine and Rehabilitation at the University of Pittsburgh School of Medicine, explained how innovations allowed Copeland to feel sensation in his hand again.

Doctors implanted two small electronic chips into Copeland's brain — one in the sensory cortex, which controls touch, and the other in the motor cortex, which controls movement. During one trial, Copeland was able to control the robotic arm with his thoughts. Even more exciting, Boninger said, was that the man reported feeling the sensation of touch when the researchers touched the robotic hand.

Many challenges remain, including developing a system that has a long battery life and enables full sensation and movement for injured people, he said. "All of this will require AI and machine learning," Boninger said.

Author : Laura Geggel

Source : http://www.livescience.com/56497-artificial-intelligence-intriguing-uses.html

Categorized in Internet Technology

Major advances in artificial intelligence (AI) have opened the door to many new ideas that were just impossible a few years ago

When creating a new AI-based app, there are many generic problems that are already being solved by other companies, for example face and gesture detection.

Unless this is the main business and focus of the company, they will prefer to look for an out-of-the-box AI-as-a-service solution which will save them time, expertise and money.

This type of solutions are called AI platforms and give their users many out-of-the-box services, such as computer vision (feature/face and gesture detection), natural language processing (NLP), speech to text, and translations between different language.

Many companies including Google and Amazon sell this kind of AI services. During 2017, we will continue to see many improvements in those platforms mainly in the ease of use, accuracy and performance.

Businesses whose goals can’t be achieved using AI-as-a-service will create customised modules on top of those platforms or completely start from scratch to create their own image recognition algorithm.

Companies in the medical field such as Zebra medical will continue to improve their AI algorithm, which can now detect under-diagnosed medical conditions in MRI scans.

 

Other companies such as Tesla will use similar technologies to improve their fully autonomous level five self-driving vehicles.

2017 will continue to see many businesses taking advantage of existing platforms and others creating their own customised AI algorithms.

Another major trend that will grow dramatically next year is apps being built on top of existing AI-ecosystems such as Siri by Apple, Alexa by Amazon and Assistant by Google.

Joining one or more of these closed AI-ecosystems brings tremendous benefits to the business, including huge ecosystem and distribution channels.

For the developers, it instantly harnesses the great power of AI, without the need to build and understand artificial intelligence.

All this is worth a lot of money, which can be saved by taking advantage of the existing AI-ecosystems.

As an example, let’s take Amazon’s AI-ecosystem with its ‘Alexa’ brain. One of the ways to interact with Alexa is to buy Amazon Echo, a hands-free speaker that you can control with your voice.

Domino’s pizza created an app for the Echo that allows hands-free pizza ordering with voice-control. This type of AI technology combined with a strong community of third-party developers will dramatically change the way we interact with technology around the house, office or on the go.

Similar to Allo, an instant messaging app developed by Google that includes a virtual assistant which provides a ‘smart reply’ function that allows users to reply without typing, we’ll see AI services further weave into everyday interactions in a conversational manner.

 

In terms of customer service, we’re seeing bots becoming a go-to tool. These bots are built into current platforms such as Facebook to allow people to check their account, make reservations or be redirected to the right department.

By not needing to wait for a physical body, customers are able to lessen the time they need to spend finding help, without draining companies resources.

Moreover, texting a bot feels more natural than conversing with one over the phone where they may only understand simple phrases.

Beyond customer servicing, bots on Facebook have been built by news sites to keep users up to date in a conversational manner.

Quartz introduced a conversational style app that updates throughout the day while CNN has built a bot directly for Facebook messenger that can reply with news depending on the input. So if a user wishes to read news about a certain topic, they can send a text message to CNN to request it.

Author:  Ben Rossi

Source:  http://www.information-age.com/2017-hold-digital-economy-123463767

Categorized in Business Research

When I started in TV journalism three decades ago, pictures were still gathered on film. By the time I left the BBC in 2015, smartphones were being used to beam pictures live to the audience. Following the digital revolution and the rise of online giants such as Facebook and Google, we have witnessed what Joseph Schumpeter described as the “creative destruction” of the old order and its replacement by the innovative practices of new media.

There has been a great deal of furious – and often hyperbolic – discussion in the wake of the US election, blaming the “echo-chamber” of the internet – and Facebook in particular – for distorting political discourse and drowning the online public in “fake news”. Antidotes are now sought to ensure that “truth filters” guard the likes of Facebook – and its users – from abuse at the hands of con artists wielding algorithms.

Students in the town of Veles, Macedonia where reports say hundreds of websites are churning out ‘fake news’ designed to appeal to Donald Trump supporters on social media. EPA/Georgi Licovski

Facebook and Google are now the big beasts of the internet when it comes to distributing news – and as they have sought to secure advertising revenue, what has slowly but surely emerged is a kind of “click-mania”. This is how it works: the social media platforms and search engines advertise around news stories, which means that the more clicks a story gets the more eyeballs see the social media sites’ advertising, which generates revenue for them. In this media environment, more clicks mean more revenue – so the content they prioritise is inevitably skewed towards “clickbait” – stories chosen for their probability of getting lots and lots of readers to click on them. Quality and veracity are low on the list of requirements for these stories.

It is difficult to argue that this did not impact on online editorial priorities with hyperbolic headlines becoming ever more tuned to this end. At times, on some platforms, it resulted in what Nick Davies dubbed“churnalism”, whereby stories were not properly fact-checked or researched.

Erosion of trust

Consumption patterns are inevitably affected by all this creative destruction and social media sites have quickly replaced “the press” as leading sources of news. And yet there is the danger that the resulting information overload is eroding trust in information providers.

 

The outgoing US president, Barack Obama, captured the dilemma the public faces on his recent trip to Germany:

If we are not serious about facts and what’s true and what’s not, if we can’t discriminate between serious arguments and propaganda, then we have problems.

There is a renewed recognition that the traditional “gatekeepers” – journalists working in newsrooms – do provide a useful filter mechanism for the overabundance of information that confronts the consumer. But their once-steady advertising revenues are fast being rerouted to Facebook and Google. As a result, traditional news companies are bleeding to death – and the currently popular strategy of introducing paywalls and subscriptions are not making up the losses. Worse still, many newspapers continue to suffer double-digit falls in circulation, so the gatekeepers are “rationalised” and the public is the poorer for it.

Rise of the algorithm

One of the answers lies in repurposing modern newsrooms, which is what the likes of the Washington Post are doing under its new owner Jeff Bezos. Certainly, journalists have to find ways of encouraging people to rely less on, or become more sceptical of, using social media as their primary source for news. Even Facebook has recognised it needs to do more to avoid fakery being laundered and normalised on its platform.

So how to avoid falling for fakery? One option involves the use of intelligent machines. We live in a media age of algorithms and there is the potential to use Artificial Intelligence as a fundamental complement to the journalistic process – rather than simply as a tool to better direct advertising or to deliver personalised editorial priorities to readers.

 

Software engineers already know how to build a digital architecture with natural language programming techniques to recognise basic storylines. What is to stop them sampling a range of versions of a story from various validated sources to create a data set and then use algorithms to strip out bias and reconstruct the core, corroborated facts of any given event.

Aggregation and summation techniques are beginning to deliver results. I know of at least one British tech start-up that, although in the research and development phase, has built an engine that uses a natural language processing approach to digest data from multiple sources, identify a storyline and provide an artificially intelligent summary that is credible. It’s a question of interpretation. It is, if you will, a prototype “bullshit detector” – where an algorithmic solution mimics the old-fashioned journalistic value of searching for the truth.

If we look at the mess our democracies have fallen into because of the new age of free-for-all information, it is clear that we need to urgently harness artificial intelligence to protect open debate – not stifle it. This is one anchor of our democracies that we cannot afford to abandon.

Source : http://theconversation.com

Author : Kurt Barling

Categorized in Social

YOU KNOW YOU shouldn’t click on that article. There’s no way the headline is going to live up to the promise. But the draw of finding out what happens next—crossing that curiosity gap—is just too much to resist. So you take the bait. And, sure enough, you’re disappointed.

Facebook wants to stop this from happening, and it’s turning to artificial intelligence to help. Earlier this month the company announced that it was tweaking its algorithms to cut down on “clickbait”—the ubiquitous plague of Internet content that over-promises and under-delivers. But it’s a big Internet out there, and plenty of other companies and sites that could benefit from tools that can separate quality news stories from fluff. Now Facebook is open sourcing software to help filter out all that Internet noise.

Facebook’s AI-driven text classification system, bag-of-tricks” approach that helps machines efficiently glean information from the order in which words appear. Another FastText tactic breaks down words into “subwords“—such as prefixes, suffixes and root words—to help computers more easily learn their meanings.

Beyond clickbait, Facebook suggests software developers could use FastText to help filter out spam. It could power search engines and autocomplete fields. Recommendation engines like the ones used by the likes of Amazon or Netflix could also benefit from a little artificial smarts that can get a better read on what you’re writing.

 

FastText is just the latest of several open source AI projects to come out of Facebook in recent years. The company has released AI algorithms, a tool for spotting bugs (in code), and designs for AI-optimized hardware. And it’s not the only tech giant doing this. Google released its AI framework TensorFlow, and companies from Microsoft and Baidu to Amazon and Yahoo have all given away the code for some of their own AI tech.

That may seem like an odd trend, given that each of these companies hopes to best the other with better tech, including AI. But artificial intelligence is still a budding field. The researchers creating these technologies within companies like Facebook and Google benefit from having their counterparts on the outside review their work and suggest changes. In a sense, open sourcing code offers the same potential benefit that publishing research in peer-reviewed journals does for scientists. In other words, Facebook is betting that giving away its AI tech will make for better software, because it too can benefit from the new ways others use it. And besides, more developers and researchers learning to use the software means more coders better prepared to work for Facebook in the future.

Source : http://www.wired.com/2016/08/wont-believe-facebook-giving-away-free-now/ 

Categorized in Social
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