Unlike most other lists of top experts, this one is a hand-picked selection, not based on influence or Klout scores, or the number of Twitter followers and re-tweets, or other similar metrics. Each of these experts has his/her own Wikipedia page. Some might not even have a Twitter account. All of them have had a very strong academic and research career in the most prestigious places. Jeffrey Hawkins is the American founder of Palm Computing (where he invented the Palm Pilot) and Handspring (where he invented the Treo).

Since cybersecurity threats have become a topic of nightly newscasts, no longer is anyone shocked by their scope and veracity. What is shocking is the financial damage the attacks are predicted to cause as they reverberate throughout the economy. Cybersecurity Ventures predicts global annual cybercrime costs will grow from $3 trillion in 2015 to $6 trillion annually by 2021, which includes damage and destruction of data, stolen money, lost productivity and theft of intellectual property, personal and financial data, embezzlement and fraud. That doesn't even include post-attack disruption to the normal course of business, forensic investigation, restoration and deletion of hacked data, systems and reputational harm. While traditional security filters like firewalls and reputation lists are good practice, they are no longer enough.

We've been hearing about AI, machine learning, natural language processing, and the like for a while now. Sometimes, even referred to as the same thing. But really, what are those things? How do they affect Google's search results? And why does any of this even matter? In this article, I've put together 5 trends that are revolutionizing search, with a detailed explanation of the mechanisms behind each one, its role in Google's ranking algorithm, and the impact it's likely to have on SEO. But before we get down to the five, here's an important notice: all these five concepts, or "trends", do not exist in isolation and are deeply interconnected in Google's algo. Often, I will be calling a trend something that is in fact only one side of a phenomenon. I'm doing this because that side has its distinct traits and impact on SEO.

The structure-function relationship is fundamental to our understanding of biological systems at all levels, and drives most, if not all, techniques for detecting, diagnosing, and treating a disease. The predominant means of collecting structure/function data in biomedicine is reductionist and has thus led to a proliferation of complex data (for example, gene expression arrays, digital images) that captures only a fraction of the structure/function relationship. Gene sequence and expression data illustrates the structure and activities of individual genes but does not explain how these genes collaborate to control cellular and tissue-scale functions. As a result, despite the abundance of molecular details known about wound healing, for example, it is virtually impossible to accurately predict the final functional state of a healing wound.36 This illustrates a need to build models that represent the structural organization at the organ, tissue, cellular, and molecular levels. Furthermore, such models must capture relationships between these scales and relate them to the underlying functional state. Data-driven network/graph analysis is primed to decipher cellular interactions in the intricate relationship between protein-protein interactions, genetic changes, metabolic pathways, and chemical secretions, which comprise cellular events. When extended to the organ level, the key challenge would be to link the local and global structural properties of tissues to the overall morphology and function of a tissue. Only a systems-level understanding of the various cellular processes encompassing multiple biological levels will take into account the multidimensional complexity of these processes. If the principles governing biological organization on a morphological, spectral, local, and global scale can be deduced, the correlation between structural and molecular signaling within the tissue can be understood and applied to inform and accelerate studies of organ development and tissue regeneration. The cell-graph technique11,12,20 aims to learn structure-function relationship by modeling structural organization of a tissue/organ sample using graph theory. Its main hypothesis is that cells in a tissue/organ organize to perform a specific function.

The dominant public narrative about artificial intelligence is that we are building increasingly intelligent machines that will ultimately surpass human capabilities, steal our jobs, possibly even escape human control and kill us all. This misguided perception, not widely shared by AI researchers, runs a significant risk of delaying or derailing practical applications and influencing public policy in counterproductive ways. A more appropriate framing--better supported by historical progress and current developments--is that AI is simply a natural continuation of longstanding efforts to automate tasks, dating back at least to the start of the industrial revolution. Stripping the field of its gee-whiz apocalyptic gloss makes it easier to evaluate the likely benefits and pitfalls of this important technology, not to mention dampen the self-destructive cycles of hype and disappointment that have plagued the field since its inception. At the core of this problem is the tendency for respected public figures outside the field, and even a few within the field, to tolerate or sanction overblown press reports that herald each advance as startling and unexpected leaps toward general human-level intelligence (or beyond), fanning fears that "the robots" are coming to take over the world.

May 14, 2017, will be the 100th anniversary of the birth of someone you might not have heard of: William Thomas ("Bill") Tutte. During the Second World War he made several crucial contributions to decrypting the Lorenz cipher used to protect the Nazi high command's most crucial radio communications. This work provided the statistical method implemented electronically by Tommy Flowers, a telecommunications engineer, in the Colossus machines, which pioneered many of the electronic engineering techniques later used to build digital computers and network equipment.a The British code-breaking effort of the Second World War, formerly secret, is now one of the most celebrated aspects of modern British history, an inspiring story in which a free society mobilized its intellectual resources against a terrible enemy. That's a powerful source of nostalgic pride for a country whose national identity and relationship with its neighbors are increasingly uncertain. Tutte's centennial gives a chance to consider the broader history of Bletchley Park, where the codebreakers worked, and the way in which it has been remembered. Some kinds of people, and work, have become famous and others have not. Films reach more people than books. So statistically speaking, most of what you know about Bletchley Park probably comes from the Oscar-winning film The Imitation Game. This gives us a starting point: the film is a bad guide to reality but a useful summary of everything that the popular imagination gets wrong about Bletchley Park. One myth is that Alan Turing won the war pretty much by himself.

The Presidential Medal of Freedom, America's highest civilian honor, is usually associated with famous awardees--people like Bruce Springsteen, Stephen Hawking, and Sandra Day O'Connor. So as a computer scientist, I was thrilled to see one of this year's awards go to a lesser-known pioneer: one Margaret Hamilton. You might call Hamilton the founding mother of software engineering. In fact, she coined the very term. She concluded that the way forward was rigorously specified design, an approach that still underpins many modern software engineering techniques--"design by contract" and "statically typed" programming languages, for example.

In the age of AI, how can we live with artificially intelligent machines and robots that may become more intelligent than us? An AI machine can be a computer or smart device; it can also be known as a robot that, with or without appendages, can emulate human life physically. There are still so many unanswered questions. How can we coexist comfortably and conveniently if one day, the machines we have created decide to think for themselves? Do you believe in technological singularity, and is it near?

How would you like it if you some stranger snapped your picture and then used that photo to find out your real name, your address and other information about you? If face recognition technology may not be brand new, anonymity in public could soon be a thing of the past. You may never again be just a face in the crowd. FindFace, a new application launched few months ago, by a Russian start-up has the power to identify total strangers on the street from pictures of their faces. It does so by matching the photos against profile pictures from VK --also known as VKontakte--a Russian social networking website like Facebook.

After introducing virtual butler Jarvis in a Morgan Freeman voice, Facebook founder and CEO Mark Zuckerberg is now seeking suggestions from his Facebook followers to make Jarvis more useful and make it do much more. In a video post, which shows Mark, Priscilla, his child Max and dog Beast, at home in different situations, the co-founder showcases some use cases of Jarvis and wants to do more. Named after the artificial intelligence system designed by Marvel comics' superhero Iron Man or Tony Stark, Jarvis can respond to text and voice commands and it could run music, air conditioning, doors, and other systems. It could recognize visitors, start a toaster and even shoot t-shirts from a cannon in his closet. The video also shows that Jarvis can make decisions like who to tickle next, in this case, it was Max.