News on China's scientific and technological development.

Aniah

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It's funny how some members in here will use a minority opinion as being the actual truth as in recent a report that China lags behind the US in AI. Would it be surprising that if it were a majority opinion, they would be using that as proof of its validity? Fact is AI needs access to data. In the US Americans are very protective of their personal data being used without their permission. Does that look like a friendly environment for AI? Google was criticized for working with China on AI as if Google were the more important partner. Your AI isn't going to learn without data so where are you going to go to develop your AI when it needs data?
Like they always do, take it by force behind your back.
 

Strangelove

Colonel
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I was surprised seeing this. I thought the project has been dead:


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"BBC, heard you're going to be powered by CCP soon?"

Yeah, aren't they afraid that China General Nuclear will work with Huawei to plant 5G/6G backdoor tech and turn this into Chernobyl anytime?

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gadgetcool5

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The business sector, consisting of around 130,000 industrial companies of scale that report R&D activities,201
is now the leading source of R&D funding (76%) in China. Total business R&D spending jumped 55 times from
30 billion RMB in 1995 to nearly 1.7 trillion RMB in 2019. However, 96 percent of the business sector’s R&D
funding is intramural, directly supporting R&D performance by businesses.202 Furthermore, while contributing
to the vast majority of China’s enormous growth in total R&D expenditures over the years, the proportion of
basic and applied research conducted by the business sector has in fact declined. In 2019, only 0.3 percent of the
business sector’s R&D performance is for basic research, and applied research only accounted for 3.31%.203 In
other words, the business sector in China only devoted 3.61% to scientific research (basic and applied research) in
2019. By contrast, 21% of the R&D performed by the business sector in the United States in 2018 is for scientific research.


While China’s total R&D expenditure has skyrocketed over the past 20 years, the business sector, a
significant contributor to this growth, has been overwhelmingly focused on experimental development at the ex-
pense of scientific research. As Huawei Technologies founder and CEO Ren Zhengfei noted in a 2019 interview,
scientific research is an essential driver to Huawei’s development, and China’s tech giants such as Huawei and
Baidu have the means and resources to operate and sustain their own research academies which employ hundreds
of mathematicians, physicists, chemists, and engineers devoted to scientific research. However, he pointed out
that the large base of small and medium-sized enterprises often lack both in-house scientific research capabilities
as well as communication and cooperation channels with universities


In March 2018, Shi Yigong [施一公], a CAS academician, structural biologist, and dean of the School of Life Sciences at
Tsinghua University, revealed his concerns about the prospects of the Chinese scientific research community in
an interview with the Liberation Daily’s Shanghai Observer [上观新闻].208 As one of the first groups of scientists
who returned to China as part of the Thousand Talents Plan recruitment effort, Shi gave up a position with
Princeton University and renounced his U.S. citizenship in 2011—a move that added to his already considerable
clout and influence.209 According to Shi, rather than making him proud, China’s success in exceeding the United
States in terms of scientific paper counts instead left him more concerned about the state of their competition,
going so far as to say that China had produced too many “garbage papers” [垃圾文章] and was simply publishing
for publishing’s sake. Clearly troubled by the growing popularity of quantitative research assessment metrics, Shi
hinted that they could be easily manipulated: “... These core STI indicators - the number of papers, the number of
citations, the impact factors of journals - can be artificially raised. I think everyone knows what I mean,” adding
that “A country like China could easily raise the values of these indicators.” He cautioned the S&T community

to not conflate publication counts with scientific research capability and called for the improvement of China’s
research assessment system.

Shi has been joined by other voices such as Lu Bai [鲁白], a world-renowned Chinese neuroscientist and
an outspoken figure on China’s national science policy issues,xlvi who shared similar insights in a March 2021
article.210 Lu noted the limitations of indicators such as R&D intensity, workforce size, and S&E publication output
in measuring a nation’s STI capabilities. Lu argued that, as far as scientific research is concerned, to be a global
scientific powerhouse requires a country to meet three key criteria: make transformative scientific discoveries that
change the world; gather a large number of top scientific minds; and exhibit a cultural environment conducive
to stimulating extraordinary scientific discoveries. Lu judged the current state of China’s indicators as far from

meeting these criteria and urged the promotion of measures that could actually advance original, transformative
discoveries.

In 2019, Wang Yiming [王一鸣], deputy director of the Development Research Center of the State Council revealed
that China’s “transfer and conversion rate” of technology born out of research and development funded by the
government [财政资金支持的技术成果转移转化率] is less than 10%, far lower than average of 40% to 50%
in developed nations.212 Wang did not explain how these numbers are calculated, and some Chinese scholars
have pointed to a lack of agreed-upon definition and method for statistical analysis for this indicator. However,
other researchers have drawn similar conclusions based on their own calculations, which employ more precise
definitions and methods of statistical analysis. An analysis performed by Renmin University researcher Shen Jian
[沈健] suggests China’s technology commercialization rate (non-business) is even lower than the official number
(see table 9).213 Additionally, according to a recent report from a Canadian think tank, in the eyes of a Chinese
patent expert, “only 10 percent of China’s patents have market value and that probably 90 percent of them are
‘trash.’”214

What went wrong?


The first issue concerns China’s proportionally low spending on scientific research for the past two decades. The second issue centers on the incentive structure where simple quantitative metrics play outsized roles in the assessment of individual
researchers and institutions, which has led to unintended consequences with serious implications for China’s STI
development

They argue that this may be attributed to the fact that China’s innovation policy overemphasizes development and high-tech industries at the expense of scientific research.Applied research, they note, serves as a critical link in the R&D process, the decline of which would adversely impact China’s ambition to become an innovative country. Since the publication of their article in 2014 the trends they identified have continued. As shown in fig.13, between 1995 and 2018, the majority
of R&D expenditures were channeled toward experimental development, with China’s basic research
funding consistently accounting for merely 5% of the total R&D funding, and only tipped up to 6% in 2019.
Applied research funding meanwhile fell from 26% to 11%.

C
omparing data from 2018 (the latest year for which data from both countries are available), scientific
research (basic and applied science) accounted for 36% of the total U.S. R&D expenditure in 2018, whereas the
latest number in China from 2019 was at 17% (see fig.14 and fig.15).xlvii In nominal terms, total estimated U.S.
basic and applied research expenditures in 2018 were $211.5 billion. Total Chinese basic and applied research
expenditures in 2018 were 328.13 billion RMB (roughly $51 billion), meaning that the United States outspent China on basic and applied science by roughly four to one in 2018. According to OECD data, basic research expenditure accounted for 0.49 percent of total U.S. GDP ($21.43 trillion) in 2018, whereas Chinese basic research expenditure accounted for 0.12 percent of China’s GDP ($13.89 trillion) from the same year.21

Wen Zhenhai, a CAS chemist, told Nature reporter Sarah O’Meara that “Junior researchers must survive
the intense competition for funding, so we have to pursue hot topics of research, even though that means our
work might not be innovative and [might] overlap with others’.”
243 This statement is corroborated by numerous
responses regarding the state of the field given by Chinese scientists on various internet forums.244 For example,
in the field of materials science,liv there is a tacit understanding that the following fields are to be pursued if one
wants to get published: nanomaterials, two-dimensional materials such as graphene, and energy storage materials
such as perovskite, among others. These research areas are so popular as to attract many researchers outside the
field of chemistry, chemical engineering, and materials science to pivot their research focus. However, many
of these clusters die out because those ideas are neither original nor plausible. At the same time, research on
advanced traditional materials and core strategic materials, as outlined in Made in China 2025 plan, has failed to
receive enough research and development efforts from Chinese scientists because researchers knew that it is much
harder to publish in those “more traditional” areas.

Posts on forums suggest that some members of the research community have successfully cracked the
publication “code” and developed a readily applicable routine: 1) identify a trending topic area published in
Science or Nature; 2) read the original text and citations; 3) tweak the chemical composition and characterization
properties; 4) purchase equipment, or sometimes, equipment and lab experiments are not necessary as there are
pieces of software that could conveniently change parameters and conduct simulations; 5) publish “while [the
topic] is still hot.”245 This practice is known as “water dumping [灌水],” 246 which literally means pouring water
into a container, an internet term that was originally used to describe the behavior of posting inundating a BBS
forum with a large amount of useless or meaningless information. Researchers now use this term to describe the
act of publishing for publishing’s sake, an act that dilutes the quality of the publications.
 

tokenanalyst

Brigadier
Registered Member
in measuring a nation’s STI capabilities. Lu argued that, as far as scientific research is concerned, to be a global
scientific powerhouse requires a country to meet three key criteria: make transformative scientific discoveries that
change the world; gather a large number of top scientific minds; and exhibit a cultural environment conducive
to stimulating extraordinary scientific discoveries. Lu judged the current state of China’s indicators as far from
LOL, I love Chinese humility, I love how the guy talks as if China is a third-rate country even though China is literally a superpower in science, along with the United States and the entire European Union. Anyone old enough on this forum can remember that China was not even 10th in any science category 15 years ago, most countries is this world will be more than proud, but not no the Chinese they are never good enough. That's good, that means the job is never done and they never rest on their laurels. Perhaps it may be my own biases in evaluating a culture of high achievers.
 

FairAndUnbiased

Brigadier
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It's funny how some members in here will use a minority opinion as being the actual truth as in recent a report that China lags behind the US in AI. Would it be surprising that if it were a majority opinion, they would be using that as proof of its validity? Fact is AI needs access to data. In the US Americans are very protective of their personal data being used without their permission. Does that look like a friendly environment for AI? Google was criticized for working with China on AI as if Google were the more important partner. Your AI isn't going to learn without data so where are you going to go to develop your AI when it needs data?

lmao teaching data science in schools? talk about putting the cart before the horse. how about teaching basic literacy and numeracy to those schools in South Chicago, East LA, etc?
 
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