Category Archives: Innovation

R&D Statistics

Source: NST, Jun 2018

In 2013, the Unesco Science Report 2030 reported there were 7.8 million full-time (or equivalent) researchers. That works out to 1,083 per 1 million inhabitants, or about 0.1 per cent of the global population.

The Big Five — the European Union (EU), China, United States, Japan, and Russia — account for 72 per cent of researchers worldwide. The US and China alone account for more than one third.

Incidentally, these countries also produce the most research publications — roughly 34 per cent, 20 per cent, 25 per cent, 6.0 per cent and 2.0 per cent, respectively.

With roughly 2,600 researchers per million people (2013), Malaysia is well behind South Korea (8,329), Singapore (7,247) and Japan (7,019), but well ahead of Vietnam (1,170), and Thailand (769).

Estimated global gross expenditure on research and development (GERD) is US$1.48 trillion (expressed in purchasing power parity).

World shares of GERD for the EU, China, US, Japan, and Russia were about 22 per cent, 19 per cent, 17 per cent, 9.0 per cent and 6.0 per cent, respectively.

High-income economies continue to generate the bulk of global R&D expenditure. In fact, the G20 countries account for 87 per cent of the world’s researchers, 92 per cent of global research expenditure and 94 per cent of the world’s scientific publications.

In contrast, as recently reported in this column, the 47 Least Developed Countries, with a population of close to one billion, contributed less than 0.4 per cent of the world’s total scientific publications in 2016.

Besides GERD, another useful yardstick is the ratio of the level of financial resources devoted to R&D as a share of gross domestic product (GDP).

The 2013-2014 figures show spending on R&D activities by the EU, China, US, Japan and Russian Federation were roughly 2.0 per cent, 2.0 per cent, 3.0 per cent, 4.0 per cent and 1.0 per cent, respectively.

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Scientific Paper –> Dynamic Medium

Source: The Atlantic, Apr 2018

… the basic means of communicating scientific results hasn’t changed for 400 years. Papers may be posted online, but they’re still text and pictures on a page.

The Watts-Strogatz paper described its key findings the way most papers do, with text, pictures, and mathematical symbols. And like most papers, these findings were still hard to swallow, despite the lucid prose. The hardest parts were the ones that described procedures or algorithms, because these required the reader to “play computer” in their head, as Victor put it, that is, to strain to maintain a fragile mental picture of what was happening with each step of the algorithm.

Victor’s redesign interleaved the explanatory text with little interactive diagrams that illustrated each step. In his version, you could see the algorithm at work on an example. You could even control it yourself.

the whole problem of scientific communication in a nutshell: Scientific results today are as often as not found with the help of computers. That’s because the ideas are complex, dynamic, hard to grab ahold of in your mind’s eye. 

… to create an inflection point in the enterprise of science itself. 

In the mid-1600s, Gottfried Leibniz devised a notation for integrals and derivatives (the familiar ∫ and dx/dt) that made difficult ideas in calculus almost mechanical. Leibniz developed the sense that a similar notation applied more broadly could create an “algebra of thought.” Since then, logicians and linguists have lusted after a universal language that would eliminate ambiguity and turn complex problem-solving of all kinds into a kind of calculus.

 As practitioners in those fields become more literate with computation, Wolfram argues, they’ll vastly expand the range of what’s discoverable. The Mathematica notebook could be an accelerant for science because it could spawn a new kind of thinking.

To write a paper in a Mathematica notebook is to reveal your results and methods at the same time; the published paper and the work that begot it. Which shouldn’t just make it easier for readers to understand what you did—it should make it easier for them to replicate it (or not).

With millions of scientists worldwide producing incremental contributions, the only way to have those contributions add up to something significant is if others can reliably build on them. “That’s what having science presented as computational essays can achieve,” Wolfram said.

Pérez admired the way that Mathematica notebooks encouraged an exploratory style. “You would sketch something out—because that’s how you reason about a problem, that’s how you understand a problem.” Computational notebooks, he said, “bring that idea of live narrative out … You can think through the process, and you’re effectively using the computer, if you will, as a computational partner, and as a thinking partner.”

A federated effort, while more chaotic, might also be more robust—and the only way to win the trust of the scientific community.

It’ll be some time before computational notebooks replace PDFs in scientific journals, because that would mean changing the incentive structure of science itself. Until journals require scientists to submit notebooks, and until sharing your work and your data becomes the way to earn prestige, or funding, people will likely just keep doing what they’re doing.

When you improve the praxis of science, the dream is that you’ll improve its products, too. Leibniz’s notation, by making it easier to do calculus, expanded the space of what it was possible to think.

Albert Wenger on IP Rights

 

Standardized Languages can Contribute to Innovation

Source: Oxford University Press, Dec 2016

Why did the countries with the highest literacy rates fail to contribute to the innovations of the Industrial Revolution? Recent empirical research shows that people tend to mistrust those perceived to speak with an accent. Here the hypothesis of a link between language, trust and innovation is tested with a new data set comprising 201 urban regions and 117 important innovations between 1700 and 1850.

In the three states that contributed almost all of these innovations (Britain, France and the USA), rising literacy was merely the first step toward the formation of large networks of people speaking standardized languages. Elsewhere, where language standardization was delayed, innovation also came later.

Curiosity Drives Creativity & Innovation

Source: IdeaToValue website, Jun 2017

the world’s greatest innovators are passionately curious and even nosy or annoying.

They approach situations and problems from an open, childlike, mind unconfined by rigidity or preconceived notions.

Fueled by curiosity, they ask crazy questions.

Their expertise grows as they actualize their curiosity by developing a love of learning. Their curiosity impulse and prior knowledge alert them to invisible gaps or details others miss, fueling even more questioning. Their curiosity drives them to become persistent. Their wide interests and curiosity enable them to apply ideas across divergent fields, improving upon the ideas of others,

Their wide interests and curiosity enable them to apply ideas across divergent fields, improving upon the ideas of others, synthesizing ideas, and discovering patterns from disparate fields to generate new ideas. Curiosity reveals new options even at dead ends and inspires a sense of purpose and meaning. Continuously rewarded and renewed curiosity becomes a lifelong passion.

How to nurture the curious attitude?

  1. Find and remove what gets in the way of your curious mind
  2. Never be too shy to ask questions, and ask questions even when you think you know everything you need to know. 
  3. Become more a interesting person and live a more interesting life by reconnecting with your inner child, sense of wonder, and mindset 
  4. Turn away from the familiar, and open your mind to new ideas, interests,experiences, and adventures 
  5. Dig deeper and understand the context, origin, and history of things
  6. Forge deep and quality relationships by showing your sincere and genuine interests in people around you, across all levels
  7. Build your own lab with full of experimental tools as your sandbox to tinker or try out new things; enjoy mistakes and failures 
  8. Finally, work with inquisitive minds, rather than just qualified and experienced people

Declining Productivity

Source: MIT Technology Review, Apr 2016

Between 1920 and 1970, American total factor productivity grew by 1.89 percent a year, according to Gordon. From 1970 to 1994 it crept along at 0.57 percent. Then things get really interesting. From 1994 to 2004 it jumped back to 1.03 percent. This was the great boost from information technology—specifically, computers combined with the Internet—and the ensuing improvements in how we work. But the IT revolution was short-lived, argues Gordon. Today’s smartphones and social media? He is not overly impressed. Indeed, from 2004 to 2014, total factor productivity fell back to 0.4 percent. 

Related Resource: MIT Technology Review, Jun 2016

According to Chad Syverson, an economist at the University of Chicago Booth School of Business, U.S. productivity grew at a mere 1.3 percent per year from 2005 to 2015, far less than the 2.8 percent annual growth rate during the decade earlier. Syverson calculates that had the slowdown not occurred, the gross domestic product would have been $2.7 trillion higher by 2015—about $8,400 for every American.

Michael Mandel, an economist at the Progressive Policy Institute in Washington, D.C., says the productivity slowdown is occurring in what he calls the physical industries, including manufacturing and health care. Such industries, which he estimates make up 80 percent of the national economy, account for only 35 percent of investments in information technology and their productivity reflects that, growing at only 0.9 percent annually. Meanwhile, productivity is growing by 2.8 percent a year in what Mandel calls digital industries, which include finance and business services.

Shenzhen – Innovation Hub

Source: The Economist, Apr 2017

Between 1980 and 2016 Shenzhen’s GDP in real terms grew at an average annual rate of 22% and today stands at 2trn yuan. The city’s Nanshan district, home to about 125 listed firms with a combined market value of nearly $400bn, has a higher income per person than Hong Kong. Unlike Beijing, which has many top-flight universities, Shenzhen has only a handful of lacklustre institutions of higher learning; but so many graduates from all over China flock to the city that they make up a greater share of its population than do graduates in Beijing.

Shenzhen spends over 4% of its GDP on research and development (R&D), double the mainland average; in Nanshan the share is over 6%. Most of the money comes from private firms. Companies in Shenzhen file more international patents (which are mostly high quality, unlike many of the domestic Chinese ones) than those in France or Britain (see chart).

The common perception that China is incapable of innovation needs re-examining. According to a widely quoted study published earlier this decade, the value added on the mainland to Apple’s iPods (nearly all of which are assembled there) represents less than 5% of the total, reinforcing the stereotype of Chinese factories as low-end sweatshops. However, a more recent study by Britain’s University of Sussex and others for the European Commission concludes that the iPod example “is far from representative”. These researchers calculate that the average value China adds to its exports is 76% (the EU’s is 87%). The World Bank reaches similar conclusions.

Shenzhen has done more than any place on the mainland to debunk the outdated myth of “copycat China”, becoming the global hub of innovation in hardware and manufacturing. Its entrepreneurs are coming up with entirely new industries. It has been the driving force behind the upgrading that should help the PRD withstand competition