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Month: November 2018

28 Nov 2018
Manahel Thabet

How the Geography of Startups and Innovation Is Changing

We’re used to thinking of high-tech innovation and startups as generated and clustered predominantly in fertile U.S. ecosystems, such as Silicon Valley, Seattle, and New York. But as with so many aspects of American economic ingenuity, high-tech startups have now truly gone global. The past decade or so has seen the dramatic growth of startup ecosystems around the world, from Shanghai and Beijing, to Mumbai and Bangalore, to London, Berlin, Stockholm, Toronto and Tel Aviv. A number of U.S. cities continue to dominate the global landscape, including the San Francisco Bay Area, New York, Boston, and Los Angeles, but the rest of the world is gaining ground rapidly.

That was the main takeaway from our recent report, Rise of the Global Startup City, which documents the global state of startups and venture capital. When we analyzed more than 100,000 venture deals across 300-plus global metro areas spanning 60 countries and covering the years 2005 to 2017, we discovered four transformative shifts in startups and venture capital: a Great Expansion (a large increase in the volume of venture deals and capital invested), Globalization (growth in startups and venture capital across the world, especially outside the U.S.), Urbanization (the concentration of startups and venture capital investment in cities — predominantly large, globally connected ones), and a Winner-Take-All Pattern (with the leading cities pulling away from the rest).

These major transformations pose significant implications for entrepreneurs, venture capitalists, workers, and managers, as well as policymakers for nations and cities across the globe. 

The Great Expansion

The first shift is the Great Expansion, as the past decade has witnessed a massive increase in venture capital deployed globally.

Read more: https://hbr.org/2018/11/how-the-geography-of-startups-and-innovation-is-changing

27 Nov 2018
Manahel Thabet

What’s technology got to do with the economy?

When we say technology, what do you think of?

Chances are, you’re probably picturing some sort of whizzy modern gadget; a smartphone, perhaps, or a self-driving car, or a drone or a television or camera or virtual reality goggles or a quantum computer.

But when economists think about technology, they think about anything that helps us produce things faster, better or cheaper. Economists are really nutty about production. Production in economist-speak is how we go about making all the stuff we use (from goods like cars to services like divorce lawyers).

Traditionally, economists have worked on the assumption that the more production we have, the better. When they talk about economic growth, they literally mean that the amount (or value) of stuff an economy produces has increased. And for lots of economists, politicians, and businesspeople, economic growth is seen as a sort of Holy Grail. That’s because for a long time lots of people have assumed that more stuff in an economy = more money in an economy = more stuff and money for all of us.

If economic growth is your only endgame, you’re always going to be a fan of new technology. But what if you’re less concerned about economic growth, and more concerned about things like economic inequality, the environment, or improving everyone’s happiness?

To be clear: lots of people who care about economic inequality, the environment and happiness rave about technology – or certain types of technology – and the benefits it can bring. But their debate tends to be more complicated and nuanced.

Take economic inequality. If you think the top goal of an economy should be to stop poverty and/or unequal access to things like healthcare and education, you might be buzzing about how iPads can help schoolkids with learning disabilities, or how drones can get medicine to remote areas with poor road access.

But you might also worry that as machines can do work tasks better than humans, new technologies might mean employees lose their jobs, and that if these displaced workers can’t find other work that is as well-paid or as enjoyable, they’ll lose out. And you might be particularly worried that the jobs that are easiest to replace are often the low-skilled, low-paid ones – so it’s the people lowest down the socioeconomic ladder who will be hit the hardest.

Or take the environment. Technology often needs a lot of power: electricity for computers, petrol for airplanes etc. A lot of that power comes from non-renewable energy sources which contribute to climate change. But technology can also combat that problem. Think of wind turbines, which are a type of technology that creates renewable energy.

For most environmentalists, the problem isn’t so much the technology as the obsession with using technology to up production. That’s because producing more and more stuff isn’t usually good for the environment. Producing more tables means chopping down more trees. Producing more jewelry means blasting more mines into the ground. And historically, we’ve not been very good at recycling the stuff we make, or disposing of it in an environmentally friendly way. More production has therefore tended to mean more landfills, rubbish and pollution.

What about technology and human happiness? We probably don’t need to tell you that lots of people think tech makes us unhappy: just look at all those newspaper articles on how the internet is supposed to make us feel lonely, or encourage extremist views, or increase bullying and trolling. And lots of people are angry that technology has often come alongside a bigger and bigger invasion of our privacy: through things like facial recognition, location-tracking and keystroke logging.

But of course technology can make us happy too. It has given us new ways to have fun, made our lives easier and more convenient, and helps us stay connected to the people we love, even when they’re far away. Plus, without technology we wouldn’t get the delight of watching this GIF of a baby panda sneezing. (Don’t tell us that doesn’t make you happy. We won’t believe you.)

Read more: https://www.ecnmy.org/engage/whats-technology-got-economy/

26 Nov 2018
Manahel Thabet

Life Sciences Success Stories in Hungary

The Hungarian Investment Promotion Agency (HIPA) talks to the Budapest Business Journal about recent life sciences success stories in the country.

During the past few decades, life sciences have become one of the growth engines for economies worldwide. The aim of many countries is to move towards a knowledge-based economy, combining natural sciences with experiences in IT-related areas and digitalization. The life sciences sector is considered to be among the most technology-driven and solution orientated sectors of the industry.

One of Hungary’s most traditional economic sectors is life sciences, a field that has seen almost 100 years of innovation, highly specialized technical developments and notable exports to the global market. Academic institutions, Hungarian and global players, innovative small- and medium-sized companies strengthen the ties between science and industry to boost the outcome for the country.

The geographic location of the country, combined with highly skilled staff as well as an excellent technical and scientific background, have positioned Hungary as an ideal location to do business on the European life sciences map.

Based on the location and the business environment, Hungary can provide several advantages to life sciences companies. In Hungary, the life sciences industry is diversified and consists of two sub-segments: biotechnology and pharma on one hand, and medical devices on the other.

Pharma, medical devices and biotechnology produce an important and growing share of the Hungarian economy. Eight out of the global top ten pharma and biotech companies have manufacturing or R&D activities in Hungary. In 2017, more than 48,000 people were employed here by pharma and medical device companies.

Economic Flagship

The pharmaceutical industry has always been one of the flagships of the Hungarian national economy. Pharmaceutical companies contributed 6.8% of the total manufacturing value in 2017. The four largest manufacturing bases (Richter, Teva, Egis, and Sanofi-Aventis) performed 85-90% of the total production and export activities of the industry. Within total Hungarian industrial R&D activity, 40-45% comes from the pharmaceutical industry. In 2017, the total amount of R&D expenditures of the pharma industry reached HUF 67 billion.

The manufacturing of medical devices is another traditional sector of the Hungarian economy where there are some 150 strongly export-driven Hungarian SMEs: the export ratio exceeds 90%. These flagship companies have a special role and characteristics, e.g.: flexibility, innovation, and strong export capability.

Although biotechnology is a relatively young science, its related industries and research fields have longstanding traditions in Hungary, giving companies access to a deep knowledge-base.

The continuous development of life sciences is supported by a network of academic research expertise. Academic institutions provide the sector with well-trained people, representing a strong pillar of Hungary’s educational system. In 2017, the total number of life science students at universities amounted to more than 24,300 and 3,700 students graduated.

The Hungarian labor force is well qualified and cost effective, which increases the country’s international competitiveness. In addition to that, the large number of high quality research institutions is a testament to Hungary’s traditional strengths in science and technology. There are four main centers of R&D which are connected to universities famous for medical and health sciences: Budapest, Debrecen, Szeged and Pécs.

Hungary can offer an attractive environment for investment and R&D activities within the network of scientific centers, enabling cutting-edge technologies and continuously growing business opportunities. Highly educated professionals, a rich tradition in natural, technical and medical sciences, an advantageous geographic setting and a supportive business environment for investment have been the key drivers to make Hungary a favorable location for life science investments.

Source: https://bbj.hu/promotion/life-sciences-success-stories-in-hungary-_157276

25 Nov 2018
Manahel Thabet

What To Expect For AI (Artificial Intelligence) In 2019

AI (Artificial Intelligence) continues to be red hot. Then again, every top tech company is investing heavily in the technology, such as Amazon.com, Facebook, Microsoft and Google.

But AI is more than just about big companies.  Keep in mind that the technology is getting much easier and affordable to use.

“We are seeing the democratization of AI through open source algorithms, affordable computing power and AI specialized hardware,” said Roy Raanani, who is the CEO and founder of Chorus.ai. “Google TensorFlow released open source software to allow anyone to build on Google’s own machine learning algorithms. Also the introduction of AI specialized hardware by Apple, Google, Tesla and NVIDIA is increasing AI performance by tens to hundreds, and enabling that performance in smaller form factors.”

Then what may we see next year? What are some of the emerging trends?

Here’s a look:

Video and AI will Make Voice the Last Frontier in Business Communications

Santi Subotovsky, General Partner, Emergence:

“We’ve already seen a huge rise in revenue generating applications that combine voice and AI to improve human interactions, sales, and customer service. In 2019, we’ll see new applications that, among other capabilities, will allow enterprise users to employ voice, AI and video to capture and analyze content, interpret non-verbal cues, and quickly respond to queries for data needed in discussions. The increased productivity, efficiency and insights provided by these applications will shift the center of business communications from text to face-to-face meetings, bringing voice and video full circle from the first to the last frontier.”


AI Smart Features Will Improve Meetings

Oded Gal, Head of Products, Zoom Video Communications:

“We believe that in 2019, video meetings will surpass other means of business communications to become the de facto standard. Why? Because video communication has more AI-driven ‘smart’ features than ever and those technologies can dramatically improve meeting productivity and the user’s experience. For example, AI-based features such as voice-to-text transcription can take meeting notes, and soon, virtual personal assistants will record tasks and help set up meetings, and voice recognition will identify meeting participants and provide relevant details on their background. Together, we believe that these features will make many video meetings superior to in-person meetings.

“Additionally, we predict that AI-driven facial recognition will be used in video conference rooms for a variety of purposes. For example, insights into who has used the conference room, when, and for what purpose will also help IT and Facilities staff better plan space allocation and usage.”

Chief Analytics Officer (CAO) or Chief Data Officer (CDO) Roles Will Become More Prevalent

Candace Worley, Chief Technical Strategist, McAfee:

“There are myriad decisions that must be made when a company extends their use of AI. Implications exist for privacy regulation but there are also legal, ethical, and cultural implications that warrant the creation of a specialized role in 2019 with executive oversight of AI usage.

“In some cases, AI has demonstrated unfavorable behavior such as racial profiling, unfairly denying individuals loans, and incorrectly identifying basic information about users. CAOs and CDOs will need to supervise AI training to ensure AI decisions avoid harm. Further, AI must be trained to deal with real human dilemmas and prioritize justice, accountability, responsibility, transparency and well-being while also detecting hacking, exploitation and misuse of data.”

Source: https://www.forbes.com/sites/tomtaulli/2018/11/24/what-to-expect-for-ai-artificial-intelligence-in-2019/#72f7217657b1

24 Nov 2018
Manahel Thabet

Using Artificial Intelligence To Fix Healthcare

The healthcare industry should be using Artificial Intelligence (AI) to a far greater degree than at present, but progress has been painfully slow. The same factors that make the healthcare system so attractive to AI developers – fragmented or non-existent data repositoriesoutdated computer systems and doctor shortages – are the same things that have stopped AI from providing the gains that should be created.

The healthcare sector also presents unique obstacles for AI: data must flow freely through AI systems to achieve real results, but extracting data from handwritten patient files or PDFs is cumbersome for us, and difficult for AI. Despite technical and operational challenges, new research suggests that the arrival of the tech giants into the industry may provide the data and the capital required to digitize this fairly untapped market.

Where AI can help now

Severe fragmentation between different branches of healthcare, and life-threatening miscommunication within institutions (in 2016, ~10% of all US deaths were caused by medical errors), presents an opportunity for AI to ease the burden on doctors in more creative, less intrusive ways. Mabuis a humanoid robot developed by Catalia Health and the American Heart Association that helps patients keep on top of at home treatment for congestive heart failure. Acting as a personal health assistant, Mabu asks patients how they are feeling, makes activity suggestions and provides medication reminders. ‘There are key points we make sure Mabu covers,’ says Catalia Health founder Cory Kidd, ‘but the conversation is adaptive to what is going on with that patient at that moment,’ much like a home nurse’s visits might be scripted to a certain degree while relying on some human intuition.

Mabu is a promising step towards integrating AI into the healthcare system without disturbing doctors within facilities – the data Mabu gathers can be fed into Electronic Medical Records (EMRs) via email or text, and ‘daily conversations’ with the device mean that Catalia Health can collect patient information consensually ‘without depending on access to their medical data.’ The implementation of AI throughout healthcare institutions or an entire country will remain a huge task even for data-rich multi-nationals, but solutions like this may help to improve outpatient care and reduce readmission rates for long-term conditions without setting foot in a hospital.

Read more: https://www.forbes.com/sites/charlestowersclark/2018/11/22/using-artificial-intelligence-to-fix-healthcare/#df75789220cf

19 Nov 2018
Manahel Thabet

How Psychoanalysis Can Help Neuroscience And Neural Networks

We know that neuroscience forms the groundwork for artificial neural networks and in other machine learning applications. Now, this fascinating field surrounding the structure and function of the nervous system and the human mind is playing an important role in improving these applications. Researchers have found out that psychoanalysis — the brainchild of Sigmund Freud — has the potential to bring a fresh face to neuroscience.

The Observable Overlap

If we compare neuroscience with psychoanalysis, certain aspects do match. To break it down, neuroscience deals with the connections or “dialogues” between the brain and the nervous system, while psychoanalysis deals with psychopathology through interactions between a patient and a psychoanalyst. Both fields intersect at the functional level. Instances like thoughts which stem from the nervous system, gaining knowledge through this as a consequence, perception with emotions, etc, share a mutual area when it comes to understanding these two fields.

The above view has garnered strong criticism among neuroscientists because there is no exact evidence establishing a relationship between the two. However, there is a slow uprising in the connection between psychoanalysis and neuroscience. In an article by science journalist Kat McGowan, she details how psychoanalysis could answer problems lingering in neuroscience.

Psychoanalysis has insightful, provocative theories about emotions, unconscious thoughts and the nature of the mind. Neurobiology has the ability to test these ideas with powerful tools and experimental rigour. Together, the two fields might finally answer the most elusive question of them all: How is it that dreams, fantasies, memories and feelings — the subjective self — emerge from a hunk of flesh?  

So, the brain structure is simply a hotbed of cognitive activities. Psychoanalysis specifically delves into this and can uncover more than what lies underneath the network of billions of neural connections.

Exploring The ‘Unconscious’

One of the key elements Freud’s psychoanalysis is the concept of the ‘unconscious state’. What started as a link to unearthing schizophrenia, is now the subject of many studies. In fact, most of them lean toward neuroscience rather than towards psychology, when it comes to deciphering this grey area.

The relationship between neural connections and psychological disorders can explain in detail about why the disorder prevails in the first place. By hinging on this fact, there could be a relation to discovering more on neurons, as these form the basis of subjects such as deep learning. As a matter of fact, one study that looked into the aspect of brain connectivity posits why neuroscience is following the path of psychoanalysis.

In recent years, there has been an increasing interest, in unconscious processes; neuroscientific studies have, in fact, tested subliminal perceptions, implicit cognition, emotion processing and interoceptive perceptions with empirical methods. Though many studies indicate that unconscious processes influence awareness, the cognitive view of the unconscious differs from the psychodynamic notion of the unconscious, which encompasses affect and motivation.

What the study brought out was how psychoanalysis and neuroscience can concur in their approach and lead to an improved scientific temperament.

The Key To Unraveling DL And ML

With psychoanalysis brought into neuroscience, it can answer the mystery behind areas such as machine learning or even deep learning. These areas extensively derive their working based on the human brain. To stress on this point, the key difference between these AI fields and psychoanalysis is the computational factor. While ML or DL is focusing on learning something new, it gradually will follow the footsteps of a computer. This ‘logical’ component misses the ‘biological’ component. Psychoanalysis is where it could help bridge this gap. After all, the essence of mind going into AI is the norm of ‘intelligence’.

As a matter of fact, challenges in these fields could be envisioned in a very different way if emotions and thoughts are brought into the picture. For example, a better model or algorithm could be designed as well as memory requirements are brought down drastically. We see enormous amounts of data going through ML/DL projects. The Freudian field may hold answers ML/DL in the future by evolving into something unknown or unexplored.

Source: https://www.analyticsindiamag.com/how-psychoanalysis-can-help-neuroscience-and-neural-networks/

17 Nov 2018

Playing high school football changes the teenage brain

A single season of high school football may be enough to cause microscopic changes in the structure of the brain, according to a new study by researchers at the University of California, Berkeley, Duke University and the University of North Carolina at Chapel Hill.

The researchers used a new type of magnetic resonance imaging (MRI) to take brain scans of 16 high school players, ages 15 to 17, before and after a season of football. They found significant changes in the structure of the grey matter in the front and rear of the brain, where impacts are most likely to occur, as well as changes to structures deep inside the brain. All participants wore helmets, and none received head impacts severe enough to constitute a concussion.

The study, which is the cover story of the November issue of Neurobiology of Disease, is one of the first to look at how impact sports affect the brains of children at this critical age. This study was made available online in July 2018 ahead of final publication in print this month.

“It is becoming pretty clear that repetitive impacts to the head, even over a short period of time, can cause changes in the brain,” said study senior author Chunlei Liu, a professor of electrical engineering and computer sciences and a member of the Helen Wills Neuroscience Institute at UC Berkeley. “This is the period when the brain is still developing, when it is not mature yet, so there are many critical biological processes going on, and it is unknown how these changes that we observe can affect how the brain matures and develops.”

Concerning trends

One bonk to the head may be nothing to sweat over. But mounting evidence shows that repeated blows to the cranium—such as those racked up while playing sports like hockey or football, or through blast injuries in military combat—may lead to long-term cognitive decline and increased risk of neurological disorders, even when the blows do not cause concussion.

Over the past decade, researchers have found that an alarming number of retired soldiers and college and professional football players show signs of a newly identified neurodegenerative disease called chronic traumatic encephalopathy (CTE), which is characterized by a buildup of pathogenic tau protein in the brain. Though still not well understood, CTE is believed to cause mood disorders, cognitive decline and eventually motor impairment as a patient ages. Definitive diagnosis of CTE can only be made by examining the brain for tau protein during an autopsy.

These findings have raised concern over whether repeated hits to the head can cause brain damage in youth or high school players, and whether it is possible to detect these changes at an early age.

“There is a lot of emerging evidence that just playing impact sports actually changes the brain, and you can see these changes at the molecular level in the accumulations of different pathogenic proteins associated with neurodegenerative diseases like Parkinson’s and dementia,” Liu said. “We wanted to know when this actually happens—how early does this occur?”

A matter of grey and white

The brain is built of white matter, long neural wires that pass messages back and forth between different brain regions, and grey matter, tight nets of neurons that give the brain its characteristic wrinkles. Recent MRI studies have shown that playing a season or two of high school football can weaken white matter, which is mostly found nestled in the interior of the brain. Liu and his team wanted to know if repetitive blows to the head could also affect the brain’s gray matter.

“Grey matter in the cortex area is located on the outside of the brain, so we would expect this area to be more directly connected to the impact itself,” Liu said.

The researchers used a new type of MRI called diffusion kurtosis imaging to examine the intricate neural tangles that make up gray matter. They found that the organization of the gray matter in players’ brains changed after a season of football, and these changes correlated with the number and position of head impacts measured by accelerometers mounted inside players’ helmets.

The changes were concentrated in the front and rear of the cerebral cortex, which is responsible for higher-order functions like memory, attention and cognition, and in the centrally located thalamus and putamen, which relay sensory information and coordinate movement.

“Although our study did not look into the consequences of the observed changes, there is emerging evidence suggesting that such changes would be harmful over the long term,” Liu said.

Tests revealed that students’ cognitive function did not change over the course of the season, and it is yet unclear whether these changes in the brain are permanent, the researchers say.

“The brain microstructure of younger players is still rapidly developing, and that may counteract the alterations caused by repetitive head impacts,” said first author Nan-Ji Gong, a postdoctoral researcher in the Department of Electrical Engineering and Computer Sciences at UC Berkeley.

However, the researchers still urge caution—and frequent cognitive and brain monitoring—for youth and high schoolers engaged in impact sports.

“I think it would be reasonable to debate at what age it would be most critical for the brain to endure these sorts of consequences, especially given the popularity of youth football and other sports that cause impact to the brain,” Liu said.

Source: https://medicalxpress.com/news/2018-11-high-school-football-teenage-brain.html

14 Nov 2018
Manahel Thabet

Brain changes found in self-injuring teen girls

The brains of teenage girls who engage in serious forms of self-harm, including cutting, show features similar to those seen in adults with borderline personality disorder, a severe and hard-to-treat mental illness, a new study has found.

Reduced brain volumes seen in these girls confirms biological – and not just behavioral – changes and should prompt additional efforts to prevent and treat self-inflicted injury, a known risk factor for suicide, said study lead author Theodore Beauchaine, a professor of psychology at The Ohio State University.

This research is the first to highlight physical changes in the brain in teenage girls who harm themselves.

The findings are especially important given recent increases in self-harm in the U.S., which now affects as many as 20 percent of adolescents and is being seen earlier in childhood, Beauchaine said.

“Girls are initiating self-injury at younger and younger ages, many before age 10,” he said.

Cutting and other forms of self-harm often precede suicide, which increased among 10- to 14-year-old girls by 300 percent from 1999 to 2014, according to data from the Centers for Disease Control and Prevention. During that same time, there was a 53 percent increase in suicide in older teen girls and young women. Self-injury also has been linked to later diagnosis of depression and borderline personality disorder.

In adults with borderline personality disorder, structural and functional abnormalities are well-documented in several areas of the brain that help regulate emotions.

But until this research, nobody had looked at the brains of adolescents who engage in self-harm to see if there are similar changes.

The new study, which appears in the journal Development and Psychopathology, included 20 teenage girls with a history of severe self-injury and 20 girls with no history of self-harm. Each girl underwent magnetic resonance imaging of her brain. When the researchers compared overall brain volumes of the 20 self-injuring girls with those in the control group, they found clear decreases in volume in parts of the brain called the insular cortex and inferior frontal gyrus.

These regions, which are next to one another, are two of several areas where brain volumes are smaller in adults with borderline personality disorder, or BPD, which, like cutting and other forms of self-harm, is more common among females. Brain volume losses are also well-documented in people who’ve undergone abuse, neglect and trauma, Beauchaine said.

The study also found a correlation between brain volume and the girls’ self-reported levels of emotion dysregulation, which were gathered during interviews prior to the brain scans.

Read more: https://news.osu.edu/brain-changes-found-in-self-injuring-teen-girls/

13 Nov 2018
Manahel Thabet

AI should be a global public good

Efforts to develop artificial intelligence (AI) are increasingly being seen as a global race, even a new Great Game. Apart from the race between countries to become more competent and establish a competitive advantage in AI, enterprises are also in a contest to acquire AI talent, leverage data advantages, and offer unique services. In both cases, success would depend on whether AI solutions can be democratized and distributed across sectors.

The global AI race is unlike any other global competition, as the extent to which innovation is being driven by governments, the corporate sector or academia differs substantially from country to country. On average, though, the majority of innovations so far have emerged from academia, with governments contributing through procurement, rather than internal research and development.

While the share of commodities in global trade has fallen, the share of digital services has risen, such that digitalization now underwrites more than 60 percent of all trade. By 2025, half of all economic value is expected to be created in the digital sector. And as governments have searched for ways to claim a position in the value chain of the future, they have homed in on AI.

Accordingly, countries ranging from the United States, France, Finland and New Zealand to China and the United Arab Emirates all now have national AI strategies to boost domestic talent and prepare for the future effects of automation on labor markets and social programs.

Still, the true nature of the AI race remains to be seen. It most likely will not be restricted to any single area, and the most important factor determining outcomes will be how governments choose to regulate and monitor AI applications, both domestically and in an international context. China, the US and other participants not only have competing ideas about data, privacy and national sovereignty, but also divergent visions of what the 21st century world order should look like.

Thus, nationalized AI programs are a hedged bet. Until now, governments have assumed that the country that is first to the finish line will be the one that captures the bulk of AI’s potential value. This seems accurate. And yet the issue is not whether the assumption is true, but whether a nationalized approach is necessary, or even wise.

After all, to frame the matter in strictly national terms is to ignore how AI is developed. Whether data sets are shared internationally could determine whether machine-learning algorithms develop country-specific biases. And whether certain kinds of chips rendered as proprietary technology could determine the extent to which innovation can proceed at the global level. In light of these realities, there is reason to worry that a fragmentation of national strategies could hamper growth in the digital economy.

Moreover, in the current environment, national AI programs are competing for a limited talent pool. And though that pool will expand over time, the competencies needed for increasingly AI-driven economies will change. For example, there will be a greater demand for expertise in cybersecurity.

So far, AI developers working out of key research centers and universities have found a reliable exit strategy, and a large market of eager buyers. With corporations driving up the price for researchers, there is now a widening global talent gap between the top companies and everyone else. And because the major technology companies have access to massive, rich data stores that are unavailable to newcomers and smaller players, the market is already heavily concentrated.

Against this backdrop, it should be obvious that isolationist measures-not least trade and immigration restrictions-will be economically disadvantageous in the long run. As the changing composition of global trade suggests, most of the economic value in the future will come not from goods and services, but from the data attached to them. Thus, the companies and countries with access to global data flows will reap the largest gains.

At a fundamental level, the new global competition is for applications that can compile alternate choices and make optimal decisions. Eventually, the burden of adjusting to such technologies will fall on citizens. But before that moment arrives, it is crucial that key AI developers and governments coordinate to ensure that this technology is used safely and responsibly.

Back in the days when the countries with the best sailing and navigation technologies ruled the world, the mechanical clock was a technology available only to the few. This time is different. If we are to have super intelligence, then it should be a global public good.

Source: http://usa.chinadaily.com.cn/a/201811/13/WS5bea07bca310eff303288360.html

12 Nov 2018

Einstein letter showed he was fearful before Nazis came to power

JERUSALEM (AP) — More than a decade before the Nazis seized power in Germany, Albert Einstein was on the run and already fearful for his country’s future, according to a newly revealed handwritten letter.

His longtime friend and fellow Jew, German Foreign Minister Walther Rathenau, had just been assassinated by right-wing extremists and police had warned the noted physicist that his life could be in danger too.

So Einstein fled Berlin and went into hiding in northern Germany. It was during this hiatus that he penned a handwritten letter to his beloved younger sister, Maja, warning of the dangers of growing nationalism and anti-Semitism years before the Nazis ultimately rose to power, forcing Einstein to flee his native Germany for good.

“Out here, nobody knows where I am, and I’m believed to be away on a trip,” he wrote in August 1922. “Here are brewing economically and politically dark times, so I’m happy to be able to get away from everything.”

The previously unknown letter, brought forward by an anonymous collector, is set to go on auction next week in Jerusalem with an opening asking price of $12,000.

As the most influential scientist of the 20th century, Einstein’s life and writings have been thoroughly researched. The Hebrew University in Jerusalem, of which Einstein was a founder, houses the world’s largest collection of Einstein material. Together with the California Institute of Technology it runs the Einstein Papers Project. Individual auctions of his personal letters have brought in substantial sums in recent years.

The 1922 letter shows he was concerned about Germany’s future a full year before the Nazis even attempted their first coup — the failed Munich Beer Hall Putsch to seize power in Bavaria.

“This letter reveals to us the thoughts that were running through Einstein’s mind and heart at a very preliminary stage of Nazi terror,” said Meron Eren, co-owner of the Kedem Auction House in Jerusalem, which obtained the letter and offered The Associated Press a glimpse before the public sale. “The relationship between Albert and Maja was very special and close, which adds another dimension to Einstein the man and greater authenticity to his writings.”

The letter, which bears no return address, is presumed to have been written while he was staying in the port city of Kiel before embarking on a lengthy speaking tour across Asia.

“I’m doing pretty well, despite all the anti-Semites among the German colleagues. I’m very reclusive here, without noise and without unpleasant feelings, and am earning my money mainly independent of the state, so that I’m really a free man,” he wrote. “You see, I am about to become some kind of itinerant preacher. That is, firstly, pleasant and, secondly, necessary.”

Addressing his sister’s concerns, Einstein writes: “Don’t worry about me, I myself don’t worry either, even if it’s not quite kosher, people are very upset. In Italy, it seems to be at least as bad.”

Later in 1922, Einstein was awarded the Nobel Prize in physics.

Ze’ev Rosenkranz, the assistant director of the Einstein Papers Project at Caltech, said the letter wasn’t the first time Einstein warned about German anti-Semitism, but it captured his state of mind at this important junction after Rathenau’s killing and the “internal exile” he imposed on himself shortly after it.

“Einstein’s initial reaction was one of panic and a desire to leave Germany for good. Within a week, he had changed his mind,” he said. “The letter reveals a mindset rather typical of Einstein in which he claims to be impervious to external pressures. One reason may be to assuage his sister’s concerns. Another is that he didn’t like to admit that he was stressed about external factors.”

When the Nazis came to power and began enacting legislation against Jews, they also aimed to purge Jewish scientists. The Nazis dismissed Einstein’s groundbreaking work, including his Law of Relativity, as “Jewish Physics.”

Einstein renounced his German citizenship in 1933 after Hitler became chancellor. The physicist settled in the United States, where he would remain until his death in 1955.

Einstein declined an invitation to serve as the first president of the newly established state of Israel but left behind his literary estate and personal papers to the Hebrew University.

Source: https://www.foxnews.com/science/einstein-letter-showed-he-was-fearful-before-nazis-came-to-power