China’s top industry regulator unveiled a five-year plan to accelerate the integration of digital and real economies amid a broader push to lay down a policy framework for the nation’s industrial development until 2025.
The Ministry of Industry and Information Technology said accelerating the deep integration of information technologies in all industrial chains is of great significance to promote industrial digitisation and digital industrialisation in the new era. According to the five-year plan, the ministry will adopt five special initiatives, including promoting manufacturing digital transformation and industrial internet platforms, to advance industrial upgrade.
The five-year plan put forward both quantitative and qualitative objectives. For instance, by 2025, the nation aims to grow the penetration rate of industrial internet platforms to 45% and the popularisation rate of digital research, development and design tools to 85%.
– Xie Shaofeng, Director, Information Technology, Development Department, MIIT
The ministry said the integrative development of”5G plus industrial internet” is on a fast track in China. At this time, more than 100 influential industrial internet platforms have also been built. In addition, more than 1,800 5G plus industrial internet projects are under construction in China, covering 10 important industries including mining, coal and electricity.
The intensified efforts to accelerate the development of the industrial internet will greatly improve production efficiency. Over the long term, it will boost the competitiveness of China’s manufacturing on the global stage.
The MIIT also unveiled a five-year plan to cultivate the nation’s big data industry. According to the plan, by 2025, the estimated scale of China’s big data industry will exceed 3 trillion yuan ($471 billion), up from more than 1 trillion yuan in 2020, and the average compound annual growth rate will be maintained at about 25%.
China’s big data industry has grown quickly over the past five years, with the average compound annual growth rate exceeding 30%. The next five years will be an important period to build China into a manufacturing and digital powerhouse, which thus means new and higher requirements for the development of the big data industry.
China’s data will account for 27.8% of the world’s total, ranking it first worldwide. In the era of the industrial digital economy, a large quantity of industrial data will be connected to the internet, which will further drive the development of the big data industry.
Moreover, China will accelerate the construction of a digital government to improve administrative services. Accordingly, the country should create a national digital government network to improve regional and interagency information sharing and ensure its digital public services cover more sectors and become more accessible.
As reported by OpenGov Asia, China Association for Science and Technology (CAST) has provided continuous support to release the potential of digital innovation and foster new drivers of growth. CAST urged to enhance digital literacy of the general public to achieve inclusive development goals beneficial to all. CAST called on efforts to deepen international cooperation and build a global network on digital governance.
The nation is already a leader in the 4th generation of the industrial revolution. Digital transformation is of great importance for the survival and development of small and medium-sized enterprises (SMEs), and special assistance will be provided for SMEs to enhance their intelligent manufacturing capacity. Experts from China and abroad discuss the endless frontier of digital technology and inclusive development as a solution to the digital divide.
China needs to be built into a highland for global digital technologies and a thriving digital economy. Only by filling the digital divide can people eliminate information asymmetry and obtain the best results. China must Take sci-tech measures to promote high-quality development of financial industries.
Epidemiological models have difficulty predicting cases rates throughout the COVID-19 pandemic. A new study by mathematicians from Brown University uses an advanced machine learning technique to explore the strengths and weaknesses of commonly used models and suggests ways of making them more predictive.
There is an old saying in the modelling field that ‘all models are wrong, but some are useful. What we show here is that the major COVID-19 models were wrong and also not very useful — at least in terms of predicting the course of the pandemic. There was a lot of Monday-morning quarterbacking, but not a lot of accurate predictions.
– George Karniadakis, Professor, Applied Mathematics, Brown University
To find out why that was, the team looked at nine prominent COVID-19 models, all of which were some variation of the “susceptible-infectious-removed” or SIR model. These models divide a population into separate bins: those who have not yet been infected (susceptible), those who are infected and could spread the virus to others (infectious) and those who have had the infection and can no longer spread it (removed). More complicated versions of the SIR model include additional bins that capture rates of quarantine, hospitalisation, deaths and other quantities that could influence the spread of the virus.
Several factors affect the movement of individuals from one bin to another. Movement from “susceptible” to “infectious,” for example, depends on how efficiently the virus jumps from person to person along with how often people come in close contact with each other. Many of these factors cannot be observed directly, and so the models must infer their values from available data. In modelling terms, these factors are known as parameters.
The study found that a major downfall of COVID-19 models was that they treated key parameter values as being fixed over time, despite the fact that these factors shifted dramatically in the real world. For example, the community transmission rate of the virus varied widely depending upon mask use, business closings and re-openings, and other measures.
Hospitalisation rates changed over time as the availability of hospital beds shifted. And the death rate changed with new treatments. All of these evolving factors changed the trajectory of case rates and deaths, but prominent models held these parameters steady in time, which led to poor predictions, the researchers found.
The next question was whether there might be a way to capture these changing parameters in epidemiological models. To do that, the team used physics-informed neural networks (PINNs) — a machine learning technique developed at Brown. PINNs are neural networks similar to those used to recognise images or transcribe speech to text.
But unlike standard neural networks, PINNs are equipped with equations describing the physical laws that govern a system. The team first used PINNs to discover velocities and pressures of fluid flows from images and videos. In those cases, PINNs were equipped with equations used in fluid dynamics. In this case, the team equipped the PINNs with equations used to calculate how pathogens spread.
Considering the fact that pandemics evolve in time and there is a continuous collection of data, PINNs can be retrained as new data is collected and update the models over time with inferred parameters. The computational time needed for re-training PINNs with new data is relatively short compared to the time-scale of pandemic evolution.
The findings suggest that while no model can accurately capture all the dynamics that play out during an extended pandemic, models with the ability to adjust key parameters on the fly could make for more useful predictions.
To deepen China-Africa cooperation, China’s Ministry of Commerce said it will step up efforts to formulate specific work plans for nine programs in areas like digital innovation.
Experts said that as the COVID-19 pandemic accelerates digital transformation in many economies, a deeper China-Africa partnership in digital innovation is of greater significance. According to the digital innovation program, China will undertake 10 digital economy projects for Africa, set up centres for China-Africa cooperation in satellite remote-sensing application and support the development of China-Africa joint laboratories, partner institutes, and scientific and technological innovation cooperation bases.
The nine programs, as part of the first three-year plan of the China-Africa Cooperation Vision 2035, will not just promote partnerships in poverty reduction, trade and investment, but further tie in emerging areas such as the digital economy, low-carbon development, and vocational education.
– Shu Jueting, Spokeswoman, Ministry of Commerce
Moreover, China will work with African countries to expand e-commerce cooperation, hold online shopping festivals featuring quality African products and tourism e-commerce promotion activities and launch a campaign to market 100 African stores and 1,000 African products on e-commerce platforms.
Zhou Mi, a senior researcher at the Chinese Academy of International Trade and Economic Cooperation, said the global economic recovery is very unbalanced among regions and development gaps in the digital economy and green technologies are among the factors that fuel such unbalances. The digital divide in Africa is becoming even more challenging during the pandemic.
As the pandemic has severely disrupted traditional trade and investment activities while speeding the development of the digital economy, it is of great significance for Africa to tap digital economy potential to drive economic growth and strengthen global connections. At the same time, strengthened China-Africa cooperation in the digital economy will facilitate the formation of international consensus to establish more effective, widely accepted, and comprehensive rules in the sector, to create a more stable environment for growth and global cooperation in the digital economy, and that is also valuable because the digital economy is becoming a key area for global competition.
Currently, Chinese companies are actively investing in African countries to build digital infrastructure, offer vocational training for local people and provide internet services. For example, a Chinese telecom company kicked off a course that aimed at preparing local students studying information and communications technology for the future of work.
The course aims to inspire local talent, enhance knowledge sharing, promote a greater understanding of, and interest in, the information and communications technology sector, and encourage participation in the digital community. The course focuses on the latest technologies like 5G, cloud computing, artificial intelligence and the internet of things.
As reported by OpenGov Asia, China’s top industry regulator unveiled a five-year plan to accelerate the integration of digital and real economies amid a broader push to lay down a policy framework for the nation’s industrial development until 2025.
The Ministry of Industry and Information Technology said accelerating the deep integration of information technologies in all industrial chains is of great significance to promote industrial digitisation and digital industrialisation in the new era. According to the five-year plan, the ministry will adopt five special initiatives, including promoting manufacturing digital transformation and industrial internet platforms, to advance industrial upgrade.
The five-year plan put forward both quantitative and qualitative objectives. For instance, by 2025, the nation aims to grow the penetration rate of industrial internet platforms to 45% and the popularisation rate of digital research, development and design tools to 85%.
China will accelerate the construction of a digital government to improve administrative services. Accordingly, the country should create a national digital government network to improve regional and interagency information sharing and ensure its digital public services cover more sectors and become more accessible.
The growing potency of an AI Platform combined with a Graph Data Platform is successfully enhancing machine learning models and ultimately tackling complex decision making effectively. Undeniably, both technologies are working hand-in-hand to make data relationships simpler by being scalable, performant, efficient and agile.
The most evident advantages of Graph Data Platform were seen during the pandemic when governments needed to track down community infections. From tracing connections via complicated social networks to comprehending interconnections, Graph Data Platform with AI Platform has proven to be an excellent tool for data management in real-time.
Graph Data Platform successfully assists in aiding organisations to make data-driven, intelligent decisions. Additionally, it helps prevent fraud and potential information leaks that mushroom disproportionally with the rapid COVID-driven digitalisation.
The added agility that Graph Data Platform offers, makes it clear that the combination should be the preferred decision-making methodology. Further, an AI Platform along with a Graph Data Platform has proven to be cost-effective for the government and financial institutions.
In times of crisis, obtaining information in real-time has become critical for decision-making. With a Graph Data Platform, information can be structurally arranged quickly. These powerful capabilities are the missing link for agencies to drive actionable outcomes from the data.
Organisations will benefit from an enhanced machine learning model to build an intelligent application that traverses today’s large, interconnected datasets in real-time. The copious volumes of data that organisations generate and collect need to be analysed and interpreted if they are to streamline methods in forecasting based on real-time information and serve as an effective decision-making tool.
OpenGovLive! Virtual Breakfast Insight held on 2 December 2021 provided the latest insights on delivering an effective and efficient citizen or customer experience using Graph Data Platform. This was a closed-door, invitation-only, interactive session with the top Indonesian private and public sectors.
Mining and optimising the “new oil”
Mohit Sagar, Group Managing Director and Editor-in-Chief, OpenGov Asia, kicked off the session with his opening address.
Data is referred to as the new oil, Mohit says, but in and of itself it holds no value. It needs to be mined, refined and optimised to become a performing asset.
The world has fundamentally shifted and the challenges of these times will require sophisticated solutions to generate actionable information that will be vital for decision-making in real-time. Technology and data are the key pillars, Mohit asserts. While both the public and private sectors have vast amounts of data, are they obtaining genuine value from it?
This raises two fundamental questions: What technology is being used to find data today? Is there untapped technology that has not been explored?
Globally, public and private institutions are looking for excellent tools for data management in real-time. Obtaining real-time analysed data to help make critical decision making, moving an organisation or business from “good to great.” He stressed that increased visibility can help organisations make better decisions. It empowers people to make informed decisions, he asserts.
To enhance citizen experiences and to deal with the constant change, institutions need to be more intuitive to sense and respond to new technology opportunities to drive digital transformation. Websites need to be easy to use and safe to use across different mediums and devices. For Mohit, developing new competencies will increase trust and engagement, ease of use and ways of responding to a request.
Governments across the world are looking for excellent tools for data management in real-time that can provide insights into data, Mohit observes. The growing potency in an AI Platform combined with a Graph Data Platform has been proven to strengthen machine learning models and address complex decision making effectively, making it an ideal tool.
Graph Data Platform offers a tremendous edge in detecting and interpreting data, Mohit opines. Graph technology can now detect and interpret data to expand finance decision making and understand citizens better. It also offers fast screening, which is particularly effective for discovering money laundering, terrorist financing or corruption to improve governance and compliance.
One of the most obvious use cases for Graph Data Platform is contact tracing. Since COVID-19 proliferates through social interactions, Graph Data Platforms are perfectly suited to helping scientists and policymakers expose and understand connected data – from tracing connections through multifaceted social systems to understanding dependencies between people, places and events.
Before closing, Mohit stressed that organisations need to get smarter about leveraging resources and tools around them to achieve their business goals. He reminded agencies of the complexity of the challenges besetting the world today and the need to elevate the technology they are using. Against this backdrop, it would be wise for delegates to partner with experts to better place themselves to respond with agility and efficiency in a rapidly evolving world.
Accelerating growth through harnessing insights
Joko Parmiyanto, Chief of IT Transformation Division, Statistics Indonesia, spoke next about the strategies to pivot towards being an insights-driven organisation.
The challenges in this day and age are endless: issues of unintegrated data collection, the accuracy and coherence of data, the lack of policy and quality assurance, little attention to data users, lack of relevance and timelines and issues of data access.
He further explained what moving towards Indonesia One Data entails:
– Data Standard: Standards governing methodologies covering concepts, definitions, scope, classifications, measures, and units
– Metadata standard: Structured information that serves to describe the content and sources of data so that they can be easily found, used, or managed again
– Reference Code: The ability of data to be exchanged or shared between interacting systems
– Interoperability: The data generated must use the Reference Code and Master Data available on the One Data Portal
Emphasising the importance of utilising metadata-driven applications, Joko opines that reliable metadata gives the government more information and the ability to know – what is the collected data among ministries/agencies, what the data represents, how data moves through systems and who has access to it. For him, metadata-driven is the key success to realise data integration and orchestration among ministries/agencies.
Moving towards a single source of truth can help to streamline the flow of information and ensure information accuracy. Empowered by technology to manage, streamline and harness data, his organisation has launched Indonesia Data Hub (INDAH), which is a one-stop collaboration platform that aims to improve data literacy and value of statistics as well as support data interoperability and data exploration.
In summary, Joko reiterated the value of properly utilising and organising data. The insights generated through the proper use of technology can be the differentiating factor that propels the growth of the organisation.
Unlock the power of context and relationships with Graph technology
Benny Kusuma, Country Head – Indonesia, Neo4j, elaborated how Graph Data Platforms can elevate the operations and tackle issues that organisations and institutions are facing.
“Data is the new oil,” Benny agrees, building on Mohit’s opening analogy. “Data is the new plutonium.” In 2017, The Economist declared data to be the world’s most valuable resource while Forrester calls it “the new currency of business.”
Benny explains that a traditional database stores data in rows, columns and tables. They are great for quick storage and retrieval of data and aggregating. However, the architecture is not built for understanding relationships. Storing data as a graph on the other hand – as a network or web of interconnected things has some specific advantages. “It can be a game-changer” when applied to the right use case, unlocking new insights for otherwise impossible decision-making.
When that is made accessible it accelerates digital transformation and empowers decision making like never before. Data shapes every facet of the organisation; it inspires ideas, solves problems and allows organisations to monetise the vast reserves of data.
Yet, Benny observes from a study, that half of the data is still untapped and the pool of unconnected data is growing. A report forecasts that there will be 175ZB of data generated by 2025. However, 55% of an organisation’s data will be “dark” – unquantified and untapped – according to another recent global research. There is tremendous business potential in curating data relationships from the untapped, unconnected data, Benny opines.
Today, business leaders recognise that data is key to success, yet very few can say that their organisations successfully tap the value of all of their data and data relationships. To become truly data-driven and data-proven requires a system and a method that not only makes data more intelligent with an organisation’s growing business and data strategy, but also helps agencies find and tap into connections within data.
This is where Graph Data Platforms come into the picture: establishing relationships and connecting data. With other modes of organisation, basic organising principles are added to data to create a knowledge base. However, the context is shallow and quickly ages because the underlying infrastructure is not built for relationships. If the system can combine data, semantics and a graph structure, organisations will end up with a knowledge graph that has dynamic and very deep context because it was built around connected data.
Neo4j is the creator of the Property Graph and Cypher language at the core of the GQL ISO project. With thousands of Customers World-Wide, Neo4j is headquartered in Silicon Valley and has outposts in Singapore, Indonesia China, Australia, India and Japan.
Articulating the value of Neo4j, Benny asserts that Neo4j’s Graph Data Platform technology gives an edge in producing deep context through processing collected data to connected data. He points out that analysts have taken notice and ranked Graph Data Platforms as one of the top 10 trends in data and analytics in the last 3 years.
Graph Data Platforms are extremely versatile and can elevate the capability of companies and agencies – their use cases range from oversight, resource management, science and education, planning to security. With Graph Data Platforms, people can solve the previously unsolvable. Top financial institutions, retailers and telecoms, global governments overseeing civilian affairs, defence, and intelligence use Neo4j to analyse, optimise and protect. They have enabled customers to manage financial fraud, patient outcomes, the mission to Mars, global fare pricing and vaccine distribution.
In closing, Benny reminded delegates that Neo4j created the graph category and that it is a tool that can catapult organisations in their growth through faster and better-quality insights.
Interactive Discussions
After the informative presentations, delegates participated in interactive discussions facilitated by polling questions. This activity is designed to provide live-audience interaction, promote engagement, hear real-life experiences, and facilitate discussions that impart professional learning and development for participants.
The first poll inquired on the biggest challenge that delegates face when analysing information to handle a critical decision-making situation during a crisis. Most delegates (37%) indicated that exploring data relationships is the biggest challenge, followed by the difficulty in drawing conclusions (29%). The rest of the delegates expressed that their challenge lies in the interpretation of data (17%), the effectiveness of the data (13%) and ineffectiveness of the data (4%).
Mohit feels it is about how agencies look at data as a whole, identify relationships and contextualise the data. He also added that data has to be anonymised and shared, otherwise it is not “oil”.
On being asked what they experience as the greatest hurdle to becoming more data-driven, almost half (44%) of the delegates said that the skillset of the required workforce was the greatest hurdle. The rest felt their greatest hurdle was the annual IT budget or finance (28%), IT business or related projects alignment (24%) and challenges of IT infrastructure (4%).
On the pain points in their data-driven decision-making journey, an overwhelming majority (68%) found the use of data to drive business in a better more effective way to be a major hurdle while the rest (32%) opted for the need to capture more data (32%) as the ket issue.
Mohit believes that the issue is with generating insights. Capturing data is expensive but without proper organisation and sense-making of the data, the expenditure will not translate into usable insights. The key is to upskill so that agencies can harness the insights from data.
For use cases that best depict how Graph Data Platforms can be valuable to their organisation’s work, most (32%) found AI and Machine Learning the most compelling use case, followed by real-time analysis (24%). The rest of the delegates were split between identity graph (16%), customer 360 (12%), supply chain (12%) and fraud/money laundering (4%).
When asked about the current usage of Graph Data Platforms in their department or organisation, nearly half (46%) admit that they use it to a limited extent and are in the initial phase of exploring how it can be of value.
Other delegates use Graph Data Platforms at the enterprise level and are curious to find out more about scalability and distribution (advanced users/clients) (27%). The rest either use it on a small scale and have some understanding of it works (18%) or use it in several projects but not at the production level – not on large scale – (9%).
Inquiring what delegates thought were the advantages of Graph Data Platform and how it will enhance their daily decision-making process, about half (46%) were familiar but have not implemented the technology. The rest of the delegates were either not familiar and have not implemented the technology (33%) or have already implemented and are currently using the technology (21%).
Conclusion
In closing, Benny expressed his gratitude to everyone for their participation and highly energetic discussion.
He is firmly convinced of the edge that Graph Data Platforms offer organisations in their journey towards digital transformation. Complex problems require innovative solutions and harnessing Graph Data Technology can boost capabilities by generating real-time information and deeper analysis.
Before ending the session, Benny highlighted the importance of a Graph Data Platform in vaulting organisations to greater heights. Reiterating that digital transformation is an ongoing and collaborative journey, Benny encouraged the delegates to connect with him and the team to explore ways forward.
Researchers from Nanyang Technological University, Singapore (NTU Singapore), have developed a technology, called Dynamis, that makes industrial robots nimbler and almost as sensitive as human hands, able to manipulate tiny glass lenses, electronics components, or engine gears that are just millimetres in size without damaging them. The breakthrough was first published in the top scientific journal Science and went viral on the internet when it could match the dexterity of human hands in assembling furniture.
We have since upgraded the software technology, which will be made available for a large number of industrial robots worldwide. Mastering “touch sensitivity” and dexterity like human hands has always been the holy grail for roboticists, as the programming of the force controller is extremely complicated, requiring long hours to perfect the grip just for a specific task.
– Professor Pham Quang Cuong, NTU Associate Professor
Clients purchasing the latest robots sold will have an option to include this new technology as part of the force controller, which reads the force detected by a force sensor on the robot’s wrist and applies force accordingly: apply too little force and the items may not be assembled correctly while applying too much force could damage the items.
Today, Dynamis has made it easy for anyone to programme touch-sensitive tasks that are usually done by humans, such as assembly, fine manipulation, polishing or sanding. These tasks all share a common characteristic: the ability to maintain consistent contact with a surface. If the human hands are deprived of our touch sensitivity, such as when wearing a thick glove, the researchers would find it very hard to put tiny Lego blocks together, much less assemble the tiny components of a car engine or of a camera used in our mobile phones.
The technology is a technology for force feedback, which is becoming more and more important in the practical use of robotics. The system is advanced, yet easy to use and light enough to be integrated into the standard robot controllers.
Known as “Force Sensor Robust Compliance Control”, the new software powered by Dynamis, a complex Artificial Intelligence (AI) algorithm, requires only a single parameter to be set – which is stiffness of the contact, whether it is soft, medium, or hard. Despite its “simple set-up”, it has been shown to out-perform conventional robotic controllers which required an enormous amount of expertise and time to fine-tune.
This backbone technology was further improved and was first deployed in custom-built robots, such as, which can handle fragile optical lenses and mirrors with human-like dexterity, now used by multiple companies worldwide. Current robots in the market have either high accuracy but low agility (where robots perform the same movements repeatedly such as in a car factory), or low accuracy but high agility (such as robots handling packages of different sizes in logistics).
By deploying this technology, robotics engineers can now imbue robots with both High Accuracy and High Agility (HAHA) on a large scale, paving the way for industrial applications that were previously very difficult or impossible to implement, such as handling and assembly of delicate, fragile objects such as optical lenses, electronics components, or engine gears.
As reported by OpenGov Asia, Singapore’s IT manufacturer and NTU collaborated to enhance local DS&AI education, empowering students with the tech tools and skills needed to inspire a brighter future. The Lab will put together the IT firm’s cutting-edge deep-learning technology with NTU’s global strengths in artificial intelligence and data science, allowing local data scientists and AI experts to pioneer the development of meaningful AI solutions in important industries.
According to NTU, the Lab was still in the planning stages in 2018, and roughly 150 NTU students enrolled in the Bachelor of Science in Data Science and Artificial Intelligence programme have benefited from the Lab’s resources since then.
The country’s central bank received three applications for mobile money services and has licenced all of them, namely, Vietnam Post and Telecommunications Corporation (VNPT), MobiFone, and state-run group Viettel. Pham Tien Dung, the Deputy Governor of the State Bank of Vietnam (SBV), noted that SBV granted Viettel the mobile money service rights after VNPT announced it would pilot this service in Vietnam.
According to a press release, last January, the government urged the pilot use of telecommunications accounts to pay for services of small value and pilot new payment service models as management regulations are lacking. To promote Vietnam’s economy, the Minister of Information and Communications Nguyen Manh Hung made several recommendations, including piloting mobile money in the first quarter of 2020. He stated that if mobile money services are licensed to telecommunications operators, the coverage of e-payment services will quickly reach 100% of the population. This promotes e-commerce, agricultural commodity exchanges, especially in remote areas, promotes online public services, fintech companies, innovative start-ups, and economic growth. In all countries that allow mobile money, this service generates economic growth of up to 0.5%.
The CEO of Viettel Digital, Pham Trung Kien, noted that if the government allows mobile money to pay for services and goods of small value, the number of users of electronic payments will be large as the coverage of mobile networks is much wider than banks, even in remote areas where people do not have bank accounts. He explained that for small value goods, for example, a cup of iced tea, parking tickets, soap, or a pack of instant noodles, users will not use their bank accounts to pay but pay by phone. However, they will use electronic payments with bank accounts to buy motorbikes, houses, or goods of high value.
“Some studies estimate that in Vietnam, only about 30% of the adult population have a bank account, and when we create a habit of using electronic payments, the remaining 70% will be customers of banks. Thus, mobile money not only competes but also promotes the use of bank accounts when they are familiar with electronic payment methods,” said Kien. He added that the government’s policy of allowing pilot mobile money is the right trend. When implementing electronic payment services, people will see the practical value created by payment digitisation like saving time and costs.
Around 85% of Vietnamese banking consumers are more likely to use online and digital banking services compared to 18 months ago, according to a recent report. Globally, nearly two-thirds (61%) of consumers have made greater use of digital banking services over the last 18 months. Two in five (41%) have started using digital banking services for the very first time because of the COVID-19 pandemic. In Vietnam, these numbers are higher, at 70% and 54%, respectively. Approximately 90% of respondents use online and digital banking services mostly to pay bills, transfer money, and check account balances. 87% of local banking customers agreed with the importance of online and digital banking services in a bank or financial institution.
The Malaysia Digital Economy Corporation (MDEC), Malaysia’s lead digital economy agency, is ramping up its efforts in enabling a digital learning landscape for youth through strategic collaborations with the United Nations Children’s Fund (UNICEF) and Yayasan Peneraju Pendidikan Bumiputera.
With the aim to fortify digital talent amid the COVID-19 recovery, both collaborations were secured via MDEC #mydigitalmaker Movement, a joint public-private-academia partnership launched in August 2016. The initiative, which is part of the agency’s #SayaDigital agenda, has benefited more than 2.2 million children through the integration of computational thinking into the national school curriculum and co-curricular activities organised by MDEC and its ecosystem partners.
The Chief Digital Skills and Jobs Officer at MDEC stated that the fast-changing talent market brings many new opportunities for young people. Strong fundamental and transferable skills fostered from their early years will be key in nurturing them to become an agile and digitally competent workforce.
This strategic collaboration with UNICEF and Yayasan Peneraju marks MDEC’s continuous effort in ensuring that Malaysia continues to produce a pool of digitally innovative and creative talents in line with the goals of the Malaysia Digital Economy Blueprint (MyDIGITAL), she said.
UNICEF
Through the collaboration, MDEC and UNICEF aim to create opportunities and better career outcomes for marginalised young people by bringing them together with industry leaders and experts on the same platform for career guidance and mentorships.
The partnership entails on-the-job training and industrial experience opportunities for young people via apprenticeships as well as skill-building opportunities.
Strategic partnerships such as this will accelerate the delivery of inclusive opportunities in education, employment and entrepreneurship. It is in our interest to build the skills of young people so that no one is left behind, according to the UNICEF Representative to Malaysia and Special Representative to Brunei Darussalam.
Through the partnership, both parties will be focusing on joint and independent programmes that are academic and career-oriented developed by MDEC and UNICEF. The programmes include:
Yayasan Peneraju
Focusing on developing a forward-looking digital landscape for Bumiputera’s youth, MDEC has partnered with Yayasan Peneraju to provide a knowledge-enhancing programme, Yayasan Peneraju High Impact Programme – Competition (Technology), for school students nationwide via a virtual platform.
Fully funded by Yayasan Peneraju, the series of online sessions began in early 2021 and has been benefiting more than 1,000 young Bumiputera students, aged 13 to 17 years old, through learning and exploring digital technology skill sets via online competitions.
The strategic cooperation with MDEC is an important factor in responding to the challenge of nurturing human capital, especially the Bumiputera talent, to the highest potential in deepening technological expertise. As an agency under the Prime Minister’s Department, the organisation’s mandate is to increase the quality of professional Bumiputera talents in the high impact sectors.
“We must ensure that our beneficiaries are also equipped with skills and technological knowledge so that they can excel in their career and life,” said the CEO of Yayasan Peneraju.
U.S. President Joe Biden has been vocal about his goals to boost federal investment in electric vehicles and EV infrastructure since the start of his administration. His proposed American Jobs Plan includes $174 billion for promoting the domestic production of EVs and notably electrifying the entire federal fleet.
The American Jobs Plan will create incentives to continue to lower the cost of and support market demand for electric vehicles. These incentives are a proven policy to support the growing market for EVs, which then drives down the purchase price as the auto industry scales up production and creates incentives for domestic production.
The administration plans to grow the number of charging stations in the U.S. from 42,000 to 500,000 by 2030. Yet even then, perceived upfront costs may deter some state and local governments from purchasing EVs — even those who see EV adoption as an ideal solution to reducing the environmental impact of public fleets.
State and local government leaders interested in electrifying their fleets but put off by the upfront costs of purchasing EVs should take into account the Total Cost of Ownership (TCO) of these vehicles throughout their lifetime. Running a TCO calculation may reveal that an electric fleet can actually present greater long-term savings, thereby easing the path to adoption.
Looking at the TCO equation alone, it may seem like the costs outweigh the returns. But there are aspects to operating EVs that are far more cost-effective than their internal combustion engine counterparts. For example, EVs require less maintenance because there is no need for oil changes or transmission repairs.
Whereas an ICE car has more than 2,000 different moving parts — many of which will need service or replacement at some point — an EV only has 20 moving parts. A study finds that annual maintenance costs for an EV are $330 less than that of an ICE car, and the Department of Energy finds that the average cost of driving an EV is about half the expense of an ICE vehicle.
Certainly, TCO calculations provide essential projections that can facilitate the first steps to adoption. But once purchased and deployed, how can state and local leaders, as well as government fleet managers, know if their electric fleets are truly providing savings over time? This is where vehicle telematics can be hugely beneficial.
Telematics solutions can capture and share detailed, real-time information about how each EV performs, in addition to its location and battery and charging status. These metrics provide valuable intelligence for fleet managers, helping to more accurately measure TCO, improve daily fleet management and even proactively detect issues to enable preventative maintenance. Notably, some of the metrics that managers would be monitoring for can be unique to an electric fleet, including:
