PRESS COVERAGE
  • Businesses in China and elsewhere should step up efforts to use artificial intelligence-based technologies to drive manufacturing, industry experts and media professionals said in a webinar co-hosted by China Daily. Most businesses are already embracing digital transformation to accelerate development, they said. "We are racing to adopt AI technologies in several functions, but there are difficulties in production processes as well as in resource management," said Masahiro Nakamura, CEO of Lexer Research Inc. Neale G. O'Connor, professor and head of the Department of Accounting of Monash University Malaysia, said a big challenge in some factories is the owner's mindset-many owners do not have a strategic vision to make it conducive for the factory to make top-class products. O'Connor said: "They (factory owners) have gone from product to product, and aren't so focused on developing talent and skills in their organizations. "A lot of factories today are at the continuous improvement stage. We need a lot more effort to move to the next stage of digitalizing so we can start to capitalize on the opportunities that AI brings us." The Tianjin Municipal People's Government Information Office and the Asia News Network were the other co-hosts of the webinar. The online event's theme was "The Future of AI in Manufacturing Industries", and it attracted participation of the likes of Nakamura, O'Connor and other corporate, academic, media and research luminaries. The webinar was held against a backdrop of China's big investments in AI-based technologies in industries like manufacturing, finance and transportation. Tianjin is one of the cities to advance AI-based technologies. In 2018, Tianjin set up a 100 billion yuan ($15.48 billion) fund to invest in AI-based technologies. Another 30 billion yuan was added to the fund subsequently to help build the city into an advanced manufacturing research and development hub. China's 14th Five-Year Plan (2021-25) sets benchmarks for the country's AI sector. The value of core AI-enabled industries is predicted to exceed 1 trillion yuan and make China a global leader in AI innovation by 2030. Industry insiders said AI development in China and elsewhere is expected to transform manufacturing everywhere. Chai Hua, senior reporter of business news at China Daily Asia Pacific, said AI development is primarily focused on talent, especially in the manufacturing sector, so placing emphasis on novel talent training models can help accelerate the cultivation of more AI talent in manufacturing. Umar Saif, chief digital officer of Jang Media Group, said, "Machine-learning can help analyze all the information you need. Companies such as Coca-Cola have a need to get information from data. For every shop, they collect data so they can know what they should produce next month." Ly Ly Cao, a reporter for Viet Nam News, said the past decades have witnessed huge improvements in Vietnam's technology development, as the market is a go-to destination for many investors now. Wang Yu, a research fellow of the College of Intelligence and Computing of Tianjin University, however, said that for long, the manufacturing sector has paid attention to only manufacturing, but that may have been due to the notion that its systems and processes are not compatible with AI. "The new AI models designed by the researchers are now being applied in the manufacturing sector; but for some complex scenes like manufacture of goods, we still have a long way to go. But we have a big market and hopefully it can go further in terms of technology and deep learning," he said.
    2021-06-29
  • Artificial intelligence is key to sustaining the future of the manufacturing industry, with the pandemic showing the need for efficient and automatic production, an AI expert said on Friday at a webinar in Hong Kong. Wang Yu, research fellow at the College of Intelligence and Computing in Tianjin University, said while many businesses suffered because of the pandemic, this “huge public health crisis” has also made them “realize the importance of artificial intelligence and intelligent manufacturing”. These enterprises now “understand that intelligent manufacturing can reduce the need for large numbers of people (to be physically present in factories),” Wang said in his keynote speech at the online forum on “The Future of AI in Manufacturing Industries”. The forum was jointly organized by the Tianjin Municipal People’s Government Information Office, China Daily and the Asia News Network, an alliance of 23 leading media outlets across 20 Asian countries. Wang said that “efficient automated production is the future of the manufacturing industry”. He cited how businesses in Tianjin are keen to implement intelligent manufacturing in their operations. The northern Chinese city of Tianjin is home to some of China’s biggest manufacturing companies. Wang said a survey of 472 enterprises in Tianjin last year revealed that “generally, they’re paying more attention to intelligent manufacturing”. He said that more than 45 percent of respondents have overall planning, and the production planning for intelligent manufacturing. Over 65 percent, meanwhile, are carrying out standard implementation of an integrated management system. “Tianjin considers intelligent manufacturing as a rare opportunity for economic development,” he said. Wang said that AI is being developed in the rest of China, too — and was even before the pandemic. He noted that in 2017, the State Council launched the Next Generation Artificial Intelligence Development Plan. This, he said, has led China to nurture homegrown talent, increased the number of patent applications and papers published on artificial intelligence. Neale G. O’Connor, professor and head of the Department of Accounting at Monash University in Malaysia, said that AI can help solve various problems in manufacturing. But in most companies across Asia, “A big challenge in some factories is the owner’s mindset,” O’Connor told the webinar. “Many owners don’t have a strategic vision for making it possible for the factory to make A-class products. They have gone from product to product very much, not so focused on developing the talent and the skills in their organizations.” He said Asian manufacturers need to “focus on continuous improvement and trying to digitalize different areas where you are collecting data, just like in the assembly line”. These companies can also learn from original equipment manufacturers in developed countries which have put such systems in place, he said. “A lot of factories today (are) at the continuous improvement stage. We need a lot more effort to move to the next stage of digitalizing so we can start to capitalize on the opportunities that AI brings us,” O’Connor said. He said that while AI can benefit many industries, it’s currently the automotive sector that “is actually leading the field in this area”. “Major auto manufacturers around the world and in China are adopting Industry 4.0 and AI already, and they are able to do that because of a large volume and automated systems. (They) save lots and lots of data, which makes it amenable to AI algorithms and machine learning and deep learning,” O’Connor said. Masahiro Nakamura, CEO of Tokyo-based Lexer Research Inc, said most companies are “racing to the AI technologies for much functioning more recently, but there are different difficulties in the production process, production and resource management”. He proposed the use of “deep thinking” as an alternative approach to deep learning, or machine learning. He said deep thinking can be used in factory planning, automation and intelligent logistic design. prime@chinadailyapac.com
    2021-06-26
  • As artificial intelligence technology looms as the next big thing to reshape the traditional manufacturing industry, market players, companies and universities should take a good, hard look at its revolutionary power and embrace the game-changing technology with more concerted efforts, experts told the China Daily Asia Leadership Roundtable on Friday. The online event, themed “The Future of AI in Manufacturing Industries”, was jointly organized by the Tianjin Municipal People’s Government Information Office, China Daily, and Asia News Network. “People have doubted that AI could go this far, yet in only five years, AI has entered into all kinds of services such as finance and manufacturing,” said Umar Saif, founder and CEO of SurveyAuto.com, a big data service provider using machine learning and AI technology. He also is the chief digital officer at Jang Media Group. He said that companies could predict market demand, and design the manufacturing process from production capacity to the supply chain through machine learning and big data analysis from the consumption data collected in mom-and-pop stores by distributors. “Capturing data and learning from data could predict what the demand looks like,” Saif said, adding that the lack of real-time customer data has caused the production process to lag in markets where digitalization is still underdeveloped. Neale G. O’Connor, professor and head of the Department of Accounting at Monash University Malaysia, highlighted the major challenge facing manufacturers, most of whom are small- and medium-sized enterprises, to scale up and move into intelligent manufacturing is the hard fact that owners themselves simply don’t want to combine with another factory to make it larger. “There is a legacy mindset,” O’Connor said. “My point is that a factory doesn’t necessarily have to be fully robotized. Instead, it still can be labor-intensive. It’s just a matter of picking strategic parts of the production line to digitalize and collect more data.” To revolutionize the factory, O’Connor said, there is no need for owners to reach out to a leading strategic consultancy like McKinsey & Co and Boston Consulting Group. Instead, he said, this is exactly where millions of undergraduate majors in engineering could come in. “We are talking about 5 million undergraduates in China, a large portion of whom are engineering majors. Do give them an opportunity to come into the factory to do an internship or even to do a collaborative project,” he said. O’Connor also underscored the concept of “cobots” to explain the employment impact of automation and intelligent manufacturing. Cobots, or collaborative robots, are robots that work with people in a shared workspace. Known as people-focused robots, they are created with the goal of helping increase productivity, rather than replace human workers. Citing a projection from the United Nations more than six years ago, O’Connor said there will be 40 million fewer manufacturing workers in China over the next decade. “The actual supply of labor is naturally going down in the country,” he said. “I think a lot of factories are not at a stage where they will replace people with robots. Instead, they’ve got to replace the manual of data on the processes and replace it with a digital copy.” He recalled his visit to a Taiwan-based consumer electronics manufacturer HTC over eight years ago. He remembered the company was automating the testing elements of the smartphone, rather than automating the whole smartphone assembly. “When companies are automating different stages of the assembly line, it’s not like you just replace the whole assembly line with robots. Instead, you automate it strategically,” he concluded. Application of smart tech Wang Yu, research fellow at the College of Intelligence and Computing of Tianjin University, provided several vivid examples of manufacturing companies using AI to upgrade their production. He mentioned an old and well-known Tianjin bicycle manufacturer named Flying Pigeon, which used to need several hours to assemble one bicycle in the 1990s. “That (speed) is not acceptable nowadays; that is too slow. But since about eight years ago, Flying Pigeon has transformed its manufacturing to intelligent manufacturing. What they can do is that they assemble a bicycle in 15 to 17 seconds,” Wang said. Wang also said that adopting AI technology will help the country achieve its targets in reducing carbon emissions and reach carbon neutrality by 2060. He said that with AI, the amount of power needed can be predicted, thus improving the efficiency of generating power and reducing carbon emissions. “Not only in the power generating field, but for many other industries and applications, we can also use such a strategy to reduce carbon emissions, for Tianjin and for any other cities in China,” he said. Wang opined that China’s advantage in developing AI lies in the sheer size of its market, and a massive consumer base that can help test and promote AI research. Despite all these impeccable strengths, Wang warned that the world’s second-largest economy should not be so arrogant to believe that it is leading the world in the field of AI. “What this means is that the new algorithms, the new models, designed by the researchers, may be applied to some specific scenarios, but for some complex ones, such as manufacturing, we still have a long way to go,” he said. The application of high technologies, including AI manufacturing, is also taking off in emerging markets, which used to be known for their labor-intensive industries. “Vietnam is now one of the prominent investment markets and it has for a long time been famous for its cheap labor. Many people would come to Vietnam for it, but things are improving as companies are adopting more high technologies,” said Ly Ly Cao, a reporter at Viet Nam News, noting that the government has launched supportive policies for companies adopting high technologies. Cao said that the coronavirus pandemic has accelerated the process as companies turn to technology to make up for the loss in manpower. “Because of COVID-19, the number of workers in factories is lower, and they may not come back to the factories after the pandemic,” she said. However, the application of high technologies is still showing a disparity between big companies and small ones in Vietnam due to the high cost in staff training and the difficulty in accessing high-quality big data for the latter, Cao said. “Only a handful of big companies can apply the high technology while SMEs, which accounts for 97 percent of the total companies, are reluctant to invest in advanced technology,” she added. “(The application of) high tech is improving, but it’ll take a long time (for them) to enter the SMEs.” Grace Chai, a Shenzhen-based senior business reporter of China Daily Asia Pacific, recalled an interview experience with a highly educated AI professional, who at that time was learning how to weld from the workers of a welding factory every single day. In his quest to develop an AI-empowered welding robot, the professional initially planned to find experienced welders with a certain degree of understanding of AI technology but failed. As a result, he had to learn the technique himself and translated the manufacturing jargon as well as workers’ accumulative experiences to codes and algorithms. Shortage of talent Chai highlighted the shortage of AI talent with high academic degrees and a keen willingness to devote themselves into the manufacturing industries. “Meanwhile, technicians from China’s vocational schools usually do not learn much about this advanced technology,” she said. Citing the statistics from market intelligence provider IDC, Chai said the manufacturing industry accounted for only 9.5 percent of China’s total AI market in 2018. The top three are the government, the internet, and finance industries. Chai said she firmly believes that the development of intelligent technology is primarily focused on talent, especially in manufacturing industries. Local governments in China have been implementing innovation-driven development strategies and building “smart cities” and smart factories, she said. To reach the goal, it is imperative to cultivate and attract more AI experts from around world, she added. In particular, Tianjin aims to become a national advanced manufacturing research and development base by the end of the 14th Five-Year Plan period (2021-25) and make every effort to build a national pilot zone of new-generation artificial intelligence innovations. “To provide high-end talent for the mission, local universities have already taken effective actions,” Chai said. “I have learned six higher education institutions in the city have set up dedicated colleges of artificial intelligence.” But as an emerging field, artificial intelligence lacks an education and teaching model that can be copied, Chai said. She has noticed that some colleges innovatively developed a cooperation model linking schools and enterprises, integrating the cooperation into the teaching structure and curriculum design. “I believe they are on the track of providing what the market really needs, and the trend presents a bonanza for research and educational institutions, and companies in Hong Kong, as well as other Asian cities,” Chai said. “They could team up with Tianjin and other mainland cities so that they could tap the market together and achieve a win-win outcome.” Contact the writers at sophia@chinadailyhk.com
    2021-06-26
  • A webinar, themed "The Future of AI in Manufacturing Industries", co-organized by China Daily, Tianjin Municipal People's Government Information Office and Asia News Network, was held on June 25, 2021. Industry experts, journalists, academics and researchers from countries along the Belt and Road joined the event online. The development of artificial intelligence in China and elsewhere will have ramifications in the transformation of manufacturers not just in China but in Asia and the rest of the world. There are opportunities and challenges for businesses as they embrace digital transformation. How can China, Asia and the rest of the world work together to achieve a win-win situation? China's policy on AI is included in the 14th Five-Year Plan (2021-25), in which the State Council issued a plan that sets benchmarks for China's AI sector — with the value of core AI industries predicted to exceed 1 trillion yuan ($155 billion) and make the country the global leader in AI innovation by 2030. For example, Tianjin was selected as one of the core cities to advance its AI technology. In 2018, Tianjin set up a 100 billion yuan fund to invest in AI technologies, and the fund was increased by 30 billion yuan to help build the city into an advanced manufacturing research and development hub. Dr Masahiro Nakamura, CEO, Lexer Research Inc.; Dr Neale G. O'Connor, professor and head of the Department of Accounting, Monash University Malaysia; and Dr Wang Yu, research fellow, The College of Intelligence and Computing, Tianjin University, delivered the keynote addresses. Nakamura said we are racing to the AI technologies for much functioning, but there are difficulties in the production process, as well as in production and resource management. O'Connor pointed out a big challenge in some factories is the owner's mindset. Many owners don't have a strategic vision for making it conducive for the factory to make A-class products. They have gone from product to product very much, not so focused on developing the talent and the skills in their organizations. "A lot of factories today are at the continuous improvement stage, we need a lot more effort to move to the next stage of digitalizing so we can start to capitalize on the opportunities that AI brings us," he said. Wang said AI today has fully penetrated people's lives in their work. It is widely used in many fields, including medical treatment or our culture, government operations, entertainment, retail, transportation, finance, and in manufacturing. Moderated by Pana Janviroj, executive director of Asia News Network, and DJ Clark, multimedia director, China Daily Asia Pacific, the panel invited Ly Ly Cao, a reporter for Việt Nam News; Chai Hua, senior reporter, business news, China Daily Asia Pacific; and Dr Umar Saif, chief digital officer, Jang Media Group, to share their insights. O'Connor and Wang also joined the panel discussion. Ly Ly Cao said we can see huge improvements in Vietnam's technology development as the market is prominent for many investors now. "When we mention Vietnam, most people's first impression would be cheap labor market, it's a challenge for some small and medium-sized companies to apply new technology at this moment. There is still a long way to go, but it's a good start to use technology in Vietnam," she said. Chai Hua said the development of intelligent technology is primarily focused on talent, especially in manufacturing industries, and that we should develop novel talent training models and accelerate the cultivation of more AI talent in manufacturing. O'Connor said there are many university students who take related undergraduate majors before coming to the factory while doing internships. There are big possibilities for them to become engineers in AI technology. Saif said AI machine learning can help analyze all the information you need. "Companies such as Coca-Cola need to get the information from data. For every shop, they collect data so they can know what they should produce next month," he said. Wang said that manufacturing sectors have paid attention to manufacturing, but maybe most of them cannot hold intelligence. "The new AI models designed by the researchers are applied but for some complex scenes like manufacturing, we still have a long way to go. But we have a big market and I hope we can go further in terms of technology and deep learning," he said.
    2021-06-25
  • 新聞稿 即時發佈 中國日報網上論壇探討中國製造業人工智能化 2021年6月25日香港 電:中國日報今日與天津市人民政府新聞辦公室、亞洲新聞聯盟合辦題為「從中國製造到中國『智』造」的在線研討會,吸引業界領袖、傳媒代表、學者及研究員在線參會。 《十四五發展規劃綱要》提出,要加強人工智能等科技資訊領域的發展,相關政策将為智能科技產業發展帶來重大機遇。預計到2030年,中國人工智能產業規模將超過1萬億元人民幣 (1410 億美元) ,並在該領域成為全球領導者。 2019年,天津獲批建設國家新一代人工智能創新發展試驗區,設立總規模達1, 000億元人民幣的基金群,及設立總規模達300億元的子基金群,投向智能製造終端產品和傳統產業智能化改造。 本次研討會邀請日本雷克薩研究公司首席執行官中村正博、蒙納士大學馬來西亞校區會計系教授兼系主任尼爾•奧康納和天津大學智慧與計算學部助理研究員王煜作主旨演講。三位主旨演講嘉賓都對人工智能技術表示肯定,認為人工智能將為人們的生活和工作帶來轉機。 中村正博表示,盡管最近業界都在競相採用人工智能技術來實現許多功能,但在生產過程、生產和資源管理方面仍然存在著不同的困難。 尼爾•奧康納認為,如今很多工廠仍在持續改進階段,他們需要付出更多努力、利用好人工智能帶來的機會,才能進入數字化的下一個發展階段。 王煜表示,如今人工智能已經完全滲透到人們的生活工作中,它在很多領域都有非常廣泛的應用,包括醫療、文化、政府運作、娛樂、零售、運輸、金融和製造業。 在專題研討會環節,越南新聞記者曹麗麗、中國日報亞太分社資深財經記者柴華、巴基斯坦Jang媒體集團首席數碼總監奧馬爾•賽義夫與尼爾•奧康納和王煜亦參與討論,由亞洲新聞聯盟秘書長帕納•簡沃熱及中國日報亞太分社多媒體總監大衛•克拉克擔任主持。 曹麗麗指出,越南給大多數人的第一印象還是廉價的勞動力市場,對於一些越南中小企業來說,應用新的人工智能技術是一個挑戰,也是一個很好的開始。 柴華認為,人工智能技術的發展主要集中在人才方面,創新人才培養模式,才能加快培育出更多製造業領域的人工智能人才。 尼爾•奧康納指出,人工智能可以幫助公司分析所需要的數據信息,以便安排未來的生產計劃。 奧馬爾•賽義夫表示,那些攻讀人工智能專業的大學生們,成為人工智能技術工程師的可能性很大。 王煜說:「大多數製造業部門目前可能還無法駕馭人工智能技術,但我們有很大的市場。我希望我們能在技術和深度學習方面走得更遠。」 人工智能,作為新一輪科技革命和產業變革的核心力量,正在推動傳統產業升級換代,並在中國及世界各國迅速發展。但在數字轉型過程中,企業除了收獲機遇,也面臨著困難和挑戰。國際間如何攜手應對各種挑戰,實現互利共贏、共同發展,成為當下值得深思的問題。 有關中國日報 中國日報是中國國家英文日報,全媒體用戶總數超過3.5億,是我國唯一下載量過千萬的英文新聞客戶端,目前全球下載用戶超過3,500萬;微博粉絲數超過5,900萬;微信訂閱人數達1,100萬;臉譜賬號粉絲數超過1億,位居全球媒體賬號粉絲數第二位;推特賬號粉絲數約435萬。 有關中國日報亞洲領袖圓桌論壇 中國日報亞洲領袖圓桌論壇(www.cdroundtable.com),創建於2010年,旨在搭建一個由亞洲國家和地區的政、商、學界領袖和社會精英參與的高端對話和交流平臺,圍繞亞洲地區經濟、商業、產業和社會發展等具有戰略影響的重要議題展開討論和分享見解,以增進中國與亞洲國家和西方國家的交流和理解。迄今,在港澳和亞太多個國家和地區舉辦超過90屆,逾5萬名決策精英參加。
    2021-06-25
  • HONG KONG - The COVID-19 pandemic has raised the awareness of impact investing globally, and a more-standardized, measurable practice of impact investing will help reshape the post-pandemic investment world, an expert said on Monday at a China Daily Asia Leadership Roundtable webinar. Standards are very important to help define and bring discipline to markets, said Diane Damskey, head of the Secretariat, Operating Principles for Impact Management, during the panel discussion themed “Impact Investing and ESG in Post-COVID Economic Recovery”. The Operating Principles for Impact Management was created in 2019 to provide a standard for investors to ensure they incorporate impact throughout the life of an investment. The principles were intended to be “a framework for investors for the design and implementation of their impact management systems,” its website said. Damskey said she is frequently asked about the difference between impact investing and sustainable investing. Impact investing is a subset of sustainable investing, and impact is a subset of environmental, social and corporate governance alignment, she said. ESG is the foundation and impact is a level of rigor above that, because it requires intentionality — you must target an intentional impact at the outset of an investment contribution. You must be able to articulate why your capital makes a difference to the impact achieved. And finally, you must be able to measure the impact, Damskey said. She pointed out that impact investing is critical to post-COVID-19 recovery as impact investors are “patient capital” — capital dedicated to meet long-term goals to achieve a positive, social or environmental impact alongside financial returns. “Impact is sticky capital. It’s not looking for short-term gains. It’s willing to stay with an invested company through challenging times. And I think it’s safe to say that we’re in one of these very challenging times.” Independent verification For long-standing impact, investors have historically targeted the sectors and regions that have been most affected by the pandemic. They have stuck to their commitments over the past one and a half years and are dedicating more capital when they can, she added. But Damskey said that people cannot just say they’re an impact investor. This principle requirement means that impact investment needs to be verified by an independent party. Signatories consistently say that the impact principles have helped them manage through the pandemic. The discipline required in preparing the disclosure statement helps them clarify and better articulate their impact management systems and processes. Many of them are long-standing impact investors, she said. In the past year, their investment teams are better supported and better able to address the challenges they faced, Damskey explained, adding that there’s also an effort to bring some standardization to impact assessment and reporting. “We expect to see greater regulation around sustainable investing. We want to ensure that our working impact is an alliance of what is occurring in the other areas. So it’s an extremely exciting time to be an impact of that thing and be able to help shape the future of this market.”
    2021-06-08
SPEAKERS
VIDEO
Sponsors & Partners