Month: December 2018

18 Dec 2018

New AI system mimics how humans visualize and identify objects

UCLA and Stanford University engineers have demonstrated a computer system that can discover and identify the real-world objects it “sees” based on the same method of visual learning that humans use.

The system is an advance in a type of technology called “computer vision,” which enables computers to read and identify . It could be an important step toward general artificial intelligence systems—computers that learn on their own, are intuitive, make decisions based on reasoning and interact with humans in a much more human-like way. Although current AI  are increasingly powerful and capable, they are task-specific, meaning that their ability to identify what they see is limited by how much they’ve been trained and programmed by humans.

Even today’s best computer vision systems cannot create a full picture of an object after seeing only certain parts of it—and the systems can be fooled by viewing the object in an unfamiliar setting. Engineers are aiming to make computer systems with those abilities—just like humans can understand that they are looking at a dog, even if the animal is hiding behind a chair and only the paws and tail are visible. Humans, of course, can also easily intuit where the dog’s head and the rest of its body are, but that ability still eludes most artificial intelligence systems.

Current computer vision systems are not designed to learn on their own. They must be trained on exactly what to learn, usually by reviewing thousands of images in which the objects they’re trying to identify are labeled for them. Computers, of course, also can’t explain their rationale for determining what the object in a photo represents: AI-based systems don’t build an internal picture or a common-sense model of learned objects the way humans do.

The engineers’ new method, described in the Proceedings of the National Academy of Sciences, shows a way around those shortcomings.


17 Dec 2018


Artificial intelligence systems for health care have the potential to transform the diagnosis and treatment of diseases, which could help ensure that patients get the right treatment at the right time, but opportunities and challenges are ahead.

In a new article in the Journal of the American Medical Association, two AI experts discuss the best uses for AI in health care and outline some of the challenges for implementing the technology in hospitals and clinics.

In health care, artificial intelligence relies on the power of computers to sift through and make sense of reams of electronic data about patients—including ages, medical histories, health status, test results, medical images, DNA sequences, and many other sources of health information.

AI excels at the complex identification of patterns in these reams of data, and can do so at a scale and speed beyond human capacity. The hope is that this technology can be harnessed to help doctors and patients make better health-care decisions.

Here, the authors—Philip Payne, a professor at and director of the Institute for Informatics, and Thomas M. Maddox, a professor of medicine and director of the Health Systems Innovation Lab, both at Washington University in St. Louis—answer questions about AI, including its capabilities and limitations, and how it might change the way doctors practice.


15 Dec 2018

Three Ways Entrepreneurs Can Use AI to Boost Their Business

The scope of artificial intelligence (AI) never ceases to intrigue the human mind. From interactive search assistants and employee management systems to self-learning user segmentation tools and complex ambient intelligence, AI has always remained a progressive technology limitless in its potential.

With recent leaps in technology, AI has forayed to the forefronts of digital marketing, creating innovative solutions to automate, organize and personalize corporate marketing, giving entrepreneurs the opportunity to improve the effectiveness of their business strategies.

In the past few years, AI’s rising demand has served as a key stimulus in its further development, to the extent that countries such as the UAE now have a dedicated ministry for AI.

While the applications of AI are innumerable, modern industry verticals crucially rely on faster, affordable and more accurate modes of marketing. By utilizing AI in digital marketing practices, entrepreneurs can benefit from higher response value from the target audience and ultimately achieve a stronger competitive edge against other online brands and e-commerce websites.

Here’s how AI has affected some of the most common online marketing practices and why entrepreneurs must leverage from them.

Improving relevancy and quality of content

With the latest AI integrations, search engines have become just as responsive in understanding user queries as identifying publisher’s intent when they upload content.

AI integrated search engines are now doing a far better job in serving that searcher intent, using deep learning algorithms to grade relevancy, reader-friendliness, and authenticity before displaying content.

This means publishers will have to generate higher quality content since its rankings predominantly depend on how well it addresses its intent to the target audience.

AI integrated search engines respond to user intent signals more authoritatively against predefined algorithms. At the same time, machine learning capabilities of search engines allow them to gather information and predict, anticipate and influence trends in content marketing. This enables content marketers to use this element and shape their content accordingly to drive desired outcomes.

Giving personalized experience to users

By utilizing AI interventions, online marketers are now able to improve engagement, extend retention, personalize user experience and boost sales. One of the most successful yet underrated techniques is search engine optimization (SEO).

Surprisingly, AI integration does not affect SEO from the traffic perspective but instead helps enhance its application on everyday online searchers simply by personalizing their experience when interacting with the brand.

AI in SEO also yields an interesting work impact by efficiently responding to the brand’s key performance indicators (KPIs) while at the same time building it a robust digital footprint in the market.

When practising SEO, data makes the most important ingredient of the AI model, helping it harness the power of user individuality and build persona-based intelligence. Since every customer demands unique treatment, AI utilizes these personas to embody their preferences and design the most fitting solutions for them.

More importantly, SEO practices come with a sound appeal, costing significantly less for longer-lasting impact against traditionally high-dollar practices.

Generating responses through deep learning

With Google’s recent updates this year, paid advertising has undergone significant changes in terms of how well an advertisement is created, optimized and displayed.

AdWords campaigns no longer require humanized optimization and are managed through Google’s own machine learning algorithms. Not only does Google modify the appearance of the campaigns precisely according to geographical, demographical and socioeconomic components, but also integrates the millions of search signals they already have.

Apart from modifying campaign appearance, AI will also serve an imperative role in improving the advertiser-customer relationship by facilitating interaction through deep learning. It works by capturing essential patterns to filter out the most predominant characteristics, which are then used in differentiating users into segments.

For example, when a customer from a particular segment interacts through the landing page, the chatbot will examine the data to generate a response precisely according to his or her preferences. This not only strengthens the advertiser-customer relationship but also grades the quality of the lead.


13 Dec 2018

The AI boom is happening all over the world, and it’s accelerating quickly

The rate of progress in the field of artificial intelligence is one of the most hotly contested aspects of the ongoing boom in teaching computers and robots how to see the world, make sense of it, and eventually perform complex tasks both in the physical realm and the virtual one. And just how fast the industry is moving, and to what end, is typically measured not just by actual product advancements and research milestones, but also by the prognostications and voiced concerns of AI leaders, futurists, academics, economists, and policymakers. AI is going to change the world — but how and when are still open questions.

Today, findings from a group of experts were published in an ongoing effort to help answer those questions. The experts include members of Harvard, MIT, Stanford, the nonprofit OpenAI, and the Partnership on AI industry consortium, among others, and they were put together as part of the second annual AI Index. The goal is to measure the field’s progress using hard data and to try and make sense of that progress as it relates to thorny subjects like workplace automation and the overarching quest for artificial general intelligence, or the type of intelligence that could let a machine perform any task a human could.

The first report, published last December, found that investment and work in AI was accelerated at an unprecedented rate and that, while progress in certain fields like limited game-playing and vision has been extraordinary, AI remains far behind in general intelligence tasks that would result in, say, total automation of more than a limited variety of jobs. Still, the report was lacking in what the authors call a “global perspective,” and this second edition set out to answer many of the same questions with new, more granular data and a more international scope.

“There is no AI story without global perspective. The 2017 report was heavily skewed towards North American activities. This reflected a limited number of global partnerships, not an intrinsic bias,” reads the 2018 report’s introduction. “This year, we begin to close the global gap. We recognize that there is a long journey ahead — one that involves collaboration and outside participation — to make this report truly comprehensive.”

In that spirit of global analysis, the second AI Index report finds that commercial and research work in AI, as well as funding, is exploding pretty much everywhere on the planet. There’s an especially high concentration in Europe and Asia, with China, Japan, and South Korea leading Eastern countries in AI research paper publication, university enrollment, and patent applications. In fact, Europe is the largest publisher of AI papers, with 28 percent of all AI-related publications last year. China is close behind with 25 percent, while North America is responsible for 17 percent.


11 Dec 2018

Artificial Intelligence and the Future of Humans

Experts say the rise of artificial intelligence will make most people better off over the next decade, but many have concerns about how advances in AI will affect what it means to be human, to be productive and to exercise free will.

Digital life is augmenting human capacities and disrupting eons-old human activities. Code-driven systems have spread to more than half of the world’s inhabitants in ambient information and connectivity, offering previously unimagined opportunities and unprecedented threats. As emerging algorithm-driven artificial intelligence (AI) continues to spread, will people be better off than they are today?

Some 979 technology pioneers, innovators, developers, business and policy leaders, researchers and activists answered this question in a canvassing of experts conducted in the summer of 2018.

The experts predicted networked artificial intelligence will amplify human effectiveness but also threaten human autonomy, agency and capabilities. They spoke of the wide-ranging possibilities; that computers might match or even exceed human intelligence and capabilities on tasks such as complex decision-making, reasoning and learning, sophisticated analytics and pattern recognition, visual acuity, speech recognition and language translation. They said “smart” systems in communities, in vehicles, in buildings and utilities, on farms and in business processes will save time, money and lives and offer opportunities for individuals to enjoy a more-customized future.

Many focused their optimistic remarks on health care and the many possible applications of AI in diagnosing and treating patients or helping senior citizens live fuller and healthier lives. They were also enthusiastic about AI’s role in contributing to broad public-health programs built around massive amounts of data that may be captured in the coming years about everything from personal genomes to nutrition. Additionally, a number of these experts predicted that AI would abet long-anticipated changes in formal and informal education systems.

Yet, most experts, regardless of whether they are optimistic or not, expressed concerns about the long-term impact of these new tools on the essential elements of being human. All respondents in this non-scientific canvassing were asked to elaborate on why they felt AI would leave people better off or not. Many shared deep worries, and many also suggested pathways toward solutions. The main themes they sounded about threats and remedies are outlined in the accompanying table.


10 Dec 2018
Manahel Thabet

MSPs Must Prepare For These Three Most-Disruptive Technologies

The world’s three most-disruptive technologies are changing the game and creating a multi-billion-dollar opportunity for solution providers that can help customers embrace that change, says futurist Ian Kahn.

The world’s three most-disruptive technologies will “drive the future” and create unprecedented opportunities for managed service providers willing to explore new practices and vendor alliances, said Ian Kahn, a well-known futurist, speaking to attendees of the of the NexGen 2018 Conference & Expo.

Artificial intelligence, blockchain and the Internet of Things—all technologies powered by the cloud—are evolving at a mind-bogglingly rapid pace, disrupting not only industries and markets, but dinner table conversations, Kahn said Sunday at the event hosted by CRN parent The Channel Company in Anaheim, Calif.

“I suggest that you think about the future based on these three technologies,” Khan told the cloud-focused partners in the audience.

The never-before-seen pace of innovation has humanity on a trajectory where, within a few decades, computers will surpass the “thinking power” of all human beings, changing the world in more ways than most of us can imagine.

“As technologists, we have to accept this and help our customers understand that change is happening really, really fast,” he said.

That process might be as basic as convincing those customers it’s time to adopt cloud computing, he said.

“We have to be ready for this era … we are the ones responsible for this era,” he said.

Artificial intelligence, both in augmenting and automating human tasks, is gaining attention for use cases such as self-driving cars and natural-language comprehension.

For MSPs, that technology, still in its early days, can deliver faster customer service, conflict resolution, Service Level Agreement management and other business-enabling capabilities.

But so far, only about 1 to 2 percent of the industry has embraced AI to power its own operations, Khan said.

“All here should be first to raise hands and say ‘we’re experimenting with it,'” he told NexGen attendees. “Before we sell it to our clients, we take the plunge.”

Blockchain, another technology disrupting the world, should allow everyone “to take a deep breath,” Khan said.

“Blockchain is about creating peace of mind,” he said of the technology poised to revolutionize shipping and logistics, infrastructure management, financial services, and food chain safety and reliability.

Blockchain, as opposed to traditional databases, replicates information across its network, enabling trust. The technology that powers cryptocurrencies like Bitcoin delivers a “central thread of truth that binds all different data points together,” he said, “and that was missing in the past.”

Most MSPs, however, aren’t doing anything with blockchain just yet, and rightfully so.

It’s “too new, too disruptive, too complex,” Khan said.

They should be prepared for that to change, however, with many different things happening relevant to services providers, including large vendors introducing blockchain-as-a-service solutions.

“You might see a lot more happening in that space,” Khan told NexGen attendees. “There are still many unknowns that we need to figure out.”

The Internet of Things is another disruptor that poses a multi-billion-dollar opportunity for the channel.

The technology driving a massive flow of data from connected devices is growing to a combined market of $520 billion by 2021—and that involves a $79 billion managed services play.

“That’s a good amount of business that you can be part of,” Khan said.

As all those changes are happening, MSPs must pick their targets.

“You can’t be on top of all of them,” Khan said, “It’s impossible.”

Instead, the channel must work collaboratively and collectively, Khan said.

“With peers and competition and industry, we have to work together in a way we’ve never done before,” he told NexGen attendees.

Allen Falcon, CEO of Cumulus Global, told CRN that Kahn’s presentation highlighted how “trust is moving from people and organizations to technologies.”

“This creates opportunities but also risk,” Falcon told.

And adoption of those three disruptive technologies has a broader impact than simply business, Falcon said.

“It is societal and will require a renewed focus on ethics,” Falcon said.

Mark Fielding, partners and sales, at Vation Ventures, a Denver-based channel strategy firm that advises enterprise tech vendors and solution providers, said he sees the need for MSPs to find sufficient time to invest in exploring emerging technologies.

MSPs and VARs need to “find ways to take pragmatic steps to innovate for their clients,” he said.

“It’s not an overnight process,” Fielding said. “They need to understand how emerging tech relates to their clients specifically, how it addresses their clients’ needs,” Fielding said.

Nevertheless, with technology evolving so fast, solution providers have to move as quickly as possible, Khan said.

“If you’re doing that, you will be highly successful,” Khan said.


09 Dec 2018
The Five Most Worrying Trends in Artificial Intelligence RigThe Five Most Worrying Trends in Artificial Intelligence Right Nowht Now

The Five Most Worrying Trends in Artificial Intelligence Right Now

Artificial intelligence is already beginning to spiral out of our control, a new report from top researchers warns. Not so much in a Skynet kind of sense, but more in a ‘technology companies and governments are already using AI in ways that amp up surveillance and further marginalize vulnerable populations’ kind of way.

On Thursday, the AI Now Institute, which is affiliated with New York University and is home to top AI researchers with Google and Microsoft, released a report detailing, essentially, the state of AI in 2018, and the raft of disconcerting trends unfolding in the field. What we broadly define as AI—machine learning, automated systems, etc.—is currently being developed faster than our regulatory system is prepared to handle, the report says. And it threatens to consolidate power in the tech companies and oppressive governments that deploy AI while rendering just about everyone else more vulnerable to its biases, capacities for surveillance, and myriad dysfunctions.

The report contains 10 recommendations for policymakers, all of which seem sound, as well as a diagnosis of the most potentially destructive trends. “Governments need to regulate AI,” the first recommendation exhorts, “by expanding the powers of sector-specific agencies to oversee, audit, and monitor these technologies by domain.” One massive Department of AI or such that attempts to regulate the field writ large won’t cut it, researchers warn—the report suggests regulators follow examples like the one set by the Federal Aviation Administration and tackle AI as it manifests field by field.

But it also conveys a the succinct assessment of the key problem areas in AI as they stand in 2018. As detailed by AI Now, they are:

  1. The accountability gap between those who build the AI systems (and profit off of them) and those who stand to be impacted by the systems (you and me) is growing. Don’t like the idea of being subjected to artificially intelligent systems that harvest your personal data or determine various outcomes for you? Too bad! The report finds that the recourse most public citizens have to address the very artificially intelligent systems that may impact them is shrinking, not growing.
  2. AI is being used to amplify surveillance, often in horrifying ways. If you think the surveillance capacities of facial recognition technology are disturbing, wait till you see its even less scrupulous cousin, affect recognition. The Intercept’s Sam Biddle has a good write-up of the report’s treatment of affect recognition, which is basically modernized phrenology, practiced in real time.
  3. The government is embracing autonomous decision software in the name of cost-savings, but these systems are often a disaster for the disadvantaged. From systems that purport to streamline benefits application processes online to those that claim to be able to determine who’s eligible for housing, so-called ADS systems are capable of uploading bias and erroneously rejecting applicants on baseless grounds. As Virginia Eubanks details in her book Automating Inequality, the people these systems fail are those who are least able to muster the time and resources necessary to address them.
  4. AI testing “in the wild” is rampant already. “Silicon Valley is known for its ‘move fast and break things’ mentality,” the report notes, and that is leading to companies testing AI systems in the public sector—or releasing them into the consumer space outright—without substantial oversight. The recent track record of Facebook—the original move fast, break thingser and AI evangelist—alone is example enough of why this strategy can prove disastrous.
  5. Technological fixes to biased or problematic AI systems are proving inadequate. Google made waves when it announced it was tackling the ethics of machine learning, but efforts like these are already proving too narrow and technically oriented. Engineers tend to think they can fix engineering problems with, well, more engineering. But what is really required, the report argues, is a much deeper understanding of the history and social contexts of the datasets AI systems are trained on.

Read more:

08 Dec 2018
This neural-net powered AI is way better at chess than anyone

This neural-net powered AI is way better at chess than anyone

AlphaZero is from DeepMind Technologies, a subsidiary under Alphabet, which is Google’s parent company. It can tackle not only chess, but also shogi and Go — two equally difficult, if not even more challenging, games.

AlphaZero comes after many years of research, succeeding AlphaGo Zero from last year, the world’s best Go player. But this time around there wasn’t any human help. AlphaZero taught itself how to play from scratch.

The neural-net AI studied each of the three games, using a process that’s similar to how a brain is structured. (Neural nets are similar in some ways to neurons in our bodies: It’s essentially the way the computer takes info and works through it, sort of like a very complex equation.) AlphaZero trained for 9 hours on chess, 12 hours on shogi, and 13 days on Go. Playing itself, it thought about the same moves over and over again. And it worked.

The sheer hardware of the AlphaZero is intense (think a Mac Pro on steroids). It used 5,000 tensor processing units, or TPUs, in training alone. These processors are for AI and neural net tasks. Google Photos employs them for AI features within the app.

All of this shows how advanced computers are becoming. With neural net AI inside, decision-making abilities aren’t far off.

Read more:

06 Dec 2018

What A.I. Can Teach You About Books That You Didn’t Already Know

With one spouse studying the evolution of artificial and natural intelligenceand the other researching the language, culture, and history of Germany, imagine the discussions at our dinner table. We often experience the stereotypical clash in views between the quantifiable, measurement-based approach of natural science and the more qualitative approach of the humanities, where what matters most is how people feel something, or how they experience or interpret it.

We decided to take a break from that pattern, to see how much each approach could help the other. Specifically, we wanted to see if aspects of artificial intelligence could turn up new ways to interpret a nonfiction graphic novel about the Holocaust. We ended up finding that some A.I. technologies are not yet advanced and robust enough to deliver useful insights — but simpler methods resulted in quantifiable measurements that showed a new opportunity for interpretation.

There is plenty of research available that analyzes large bodies of text, so we chose something more complex for our A.I. analysis: Reinhard Kleist’s The Boxer, a graphic novel based on the true story of how Hertzko “Harry” Haft survived the Nazi death camps. We wanted to identify emotions in the facial expressions of the main character displayed in the book’s illustrations, to find out if that would give us a new lens for understanding the story.

In this black-and-white cartoon, Haft tells his horrific story, in which he and other concentration camp inmates were made to box each other to the death. The story is written from Haft’s perspective; interspersed throughout the narrative are panels of flashbacks depicting Haft’s memories of important personal events.

Read more:

05 Dec 2018
Manahel Thabet

Coats Group investing US$5mln in “disruptive technology” that could revolutionise the thread industry

Twine has developed a proprietary digital thread dyeing system, allowing thread to be produced on demand at any colour and length.

Rajiv Sharma, Coats’ group chief executive, commented: “This is an exciting and innovative strategic move”

Coats Group PLC (LON:COA) is investing US$5mln in a “disruptive technology” that it believes has the potential to revolutionise the thread industry.

The FTSE 250-listed industrial thread manufacturer is paying the money for a 9.5% share in Israeli-based technology start-up Twine Solutions.

It also said it will get a seat on the board of Twine, which has developed a proprietary digital thread dyeing system, allowing thread to be produced on demand in any colour and length.

Rajiv Sharma, Coats’ group chief executive, commented: ‘This is an exciting and innovative strategic move. We are investing in future technology which will improve our industry and its sustainability by directly addressing the key needs of our customers: speed, innovation and sustainability.”

He added: “The disruptive technology has the potential to revolutionise the thread industry and Coats will work closely with Twine to commercialise this opportunity.”

In early afternoon trading, Coats shares were 0.3% lower at 80.70p.