This is not financial advice.
During the last two weeks Matrix AI Network illustrated average social activity. The Matrix Enterprise Cloudchain, the Matrix’s enterprise-grade big data cloudchain solution, aims to support the operations and maintenance of several industrial production applications by providing distributed computing resources based on the blockchain, data and an AI model ecosystem. To continue, The Matrix Token Swap begins April 11th, 2019. The Matrix team has prepared a convenient token swap method accessible via Matrix’s own online wallet. Last but not least a roadmap for networked intelligence was released. Professor Deng shares his vision for Smart Cities and Networked Intelligence and ‘smart systems’ is a springboard to a new form of intelligence. Finally, Matrix and bitgrit signed a strategic cooperation agreement covering data sharing, technical support, community development and more. MAN has a good sense of humour and published joke on April, 1. Most people had chasing tinsel.
Development
This article delves deeper into the Matrix’s enterprise-grade dig data cloudchain solution — unofficially dubbed the Matrix Enterprise Cloudchain.
The Birth of a Platform
The Matrix Enterprise Cloudchain aims to support the operations and maintenance of several industrial production applications by providing distributed computing resources based on the blockchain, data and an AI model ecosystem. It relies on two major architectures. The first is a platform that controls the system’s core functionality — essentially a fog computing layer that performs core functions for the platform and enables data storage, enterprise-grade data throughput capacity and enterprise-grade data processing capabilities. The second is a predictive health management (PHM) system to track the status of equipment. The system is supported by the National Natural Science Foundation of China, the CRRC and the China Railway Corporation, amongst others.
The Matrix Enterprise Cloudchain makes full use of Matrix’s AI expertise in supporting industrial data analysis and operations status monitoring applications. It has the ability to troubleshoot equipment and optimize operations and maintenance using deep learning strategies, machine learning strategies and GANs, amongst others. The Matrix Enterprise Cloudchain also integrates ERP systems, production line management and work order systems. It supports real-world business processes with visualizations and other reporting tools. It can also integrate with third-party system interfaces and allows companies to access existing systems in an effort to reduce costs by eliminating unnecessary and repetitive development.
Four Building Blocks
Products and applications built on the Matrix Enterprise Cloudchain rely primarily on four core technologies. The first is symbolic regression, which is used to identify failure states and fit them to models. The second is two-stage GANs that are applied to small data samples for the purpose pattern recognition. The third is deep neural networks for image recognition and object detection for the purposes of monitoring and detecting products, processes and personnel status. The fourth is models that integrate industrial domain knowledge to enable automatic reasoning in various industrial fields.
Present Applications
Presently, this technology is being applied and tested in Kenya’s Mombasa–Nairobi Standard Gauge Railway. Currently, with the help of smart meters and remote data centers, 48 locomotives exported to Kenya by the CRRC Corporation Limited are being monitored to optimize the management, maintenance and operations of the trains.
This technology is also being used in the Matrix Enterprise Cloud’s predictive health management (PHM) system. The PHM system is used to complete design improvement, optimize operations and optimize maintenance of industrial equipment. It can also estimate the remaining lifespan of equipment and components, automatically diagnose faults and issue repairs. The Yangdong Artificial Intelligence Research Institute expects that the PHM will greatly improve operations and maintenance efficiency, reduce maintenance costs and support the sustainable development of the railway industry, amongst other things.
Future Opportunities
China’s Belt and Road Initiative was proposed in 2013. One important component is a network of six land-based economic corridors that are to serve as the basis for inter-regional commerce and trade. High-speed rails are a key part of these corridors. It is estimated that by 2020, the annual value of the rail industry will reach 200 Billion RMB. The operations and maintenance testing market is expected to reach 50 Billion RMB in that time. This emerging market has spawned the rapid development of industrial big data platforms and equipment maintenance technologies. Matrix’s Yangdong Artificial Intelligence Research Institute hopes to optimize the existing operations system and jointly apply for research projects with local governmental bodies and other private research institutions.
Social encounters
Last week, HeCaiJing, a prominent Chinese blockchain media outlet, interviewed Matrix Chief AI Scientist Professor Steve Deng. In the interview, Professor Deng discussed several topics including the recently revealed YangDong Artificial Intelligence Research Institute and Matrix’s Enterprise-Grade Big Data Cloudchain Solution — tentatively the Matrix Enterprise Cloudchain, for short.
On the Matrix AI Network
The Matrix AI Network aims to tackle two big problems slowing the development of AI. Namely, the lack of computing power available for AI research and the relative lack of verified data necessary to produce qualitative improvement in AI models for social good. The Matrix Enterprise Cloudchain is designed not only to promote the further development of the Matrix AI Network ecosystem, but also to promote the integration of both AI and blockchain technology in everyday life to create real economic value.
On Decentralizing AI
Strictly speaking, AI has historically relied on centralized research data. According to Professor Deng, Matrix combines AI with the decentralized and distributed characteristics of blockchain technology to enable several key components on the Matrix Enterprise Cloudchain. First, using the Matrix AI Network, computing power from several distinct sources can be integrated into the Enterprise Cloudchain platform to power applications beyond the scope of standard personal equipment. Second, the Matrix AI Network allows the Enterprise Cloudchain to safely store data due to, amongst other things, Matrix’ IPFS support. Finally, and perhaps most importantly, Matrix’s blockchain technology helps solve issues of data validation.
According to Professor Deng, “many enterprises have a lot of data, but they are not willing to give you access to their data to train AI models because they have fears about data privacy and improper data disclosure. Besides these fears, enterprises also worry that once the data has been used to train the AI model, the AI model might be used to generate revenue. They worry that they won’t get a fair share of this revenue.”
Professor Deng believes that the solution to this problem is found in blockchain technology. Blockchain technology makes it possible to guarantee the rights and interests of everyone involved — be it the data providers, AI-model developers and users. With the kind of protection that blockchain provides, major obstacles slowing the development of AI can be overcome. “Data and AI models are inherently digital, so we aim to take into account the interests of all parties using our enterprise-grade big data cloudchain solution,” reiterates Professor Deng.
On AI and Blockchain
From a technical point of view, although blockchain and artificial intelligence are two distinct technologies, Professor Deng believes that the integration of both is necessary to maximize their potentials. “The integration of AI and blockchain technology brings new possibilities.” He points out that, in the near future, the integration of data and AI models will bring the first of many great achievements made possible due to the provision of computing power for data validation and AI model training over the blockchain. This will form the foundation of an open, credible AI platform for Internet of Things applications.
On Industrial Big Data
Industrial Big Data is at the intersection of big data, the Internet of Things, and industrial equipment. Industrial Big Data is also the central peg of several Chinese national strategic plans including the “Action Plan for the Development of Industrial Internet”, “Made in China 2025” and “Industry 4.0”.
While domestic in nature, these Chinese national strategies have far reaching implications as China is a major player in industrial equipment manufacturing, operations and maintenance industries. For instance, China is responsible for about 80% of the world’s total port equipment, 70% of the world’s high-speed trains, 60% of the world’s excavators, 40% of the world’s marine vessels and 39% of the world’s heavy equipment. However, despite these lofty achievements, inefficiencies abound.
According to recent data, while China created 11.6% of the world’s GDP in 2013, it did so while accounting for 21.3% of the world’s energy consumption. According to Professor Deng, these industries are primed for a revolution. “When only considering the rail industry, a quarter of the world’s transport workload happens in China despite using only 6% of the world’s railway operating mileage,” notes Deng. “This is the highest transport density in the world.”
Unlike traditional internet applications, industrial big data applications tend to have higher and more stringent requirements for real-time processing. As network bandwidth is often limited, it can be difficult to guarantee performance by solely relying on cloud platforms. Similarly, industrial big data has stringent privacy requirements. This means that using existing public cloud solutions is not appropriate. Professor Deng notes that “the cost required for an enterprise to build, operate and maintain a private cloud is prohibitive. It is not a cost-effective or viable option for most enterprises.”
On Equipment Manufacturing, Operations and Maintenance
In this blockchain era, large industrial data platforms like the Matrix Enterprise Cloudchain have the potential to create value across industries and countries. Professor Deng notes that the technology underlying Matrix’s Enterprise Cloudchain is already being used and tested in an overseas locomotive remote monitoring system servicing Kenya’s Mombasa–Nairobi Standard Gauge Railway. The system is monitoring 48 locomotives exported to Kenya by the CRRC Corporation Limited. Professor Deng also indicates that the system is supported by the National Natural Science Foundation of China, the CRRC and the China Railway Corporation, amongst others.
On Medical Treatments
Professor Deng goes on to reiterate that Matrix is engaged with several hospitals to deploy and use Matrix’s cancer diagnosis services. He posits that “the uniqueness of this system is that, first, we pay more attention to the challenging issues based on the obtained diagnostic and therapeutic data and laboratory test results. Second, we are cooperating with leading hospitals in the industry to tack frontier issues. Third, we have high-quality patient data from early screening to CT imaging to biopsy. So far, we have more than 2000 patients’ data — all of which are labeled by top Chinese doctors.” This type of data is invaluable to the development and training of AI models.
On Remaining Barriers
As Professor Deng points out, “manufacturing industries — especially high-end manufacturing industries — form the foundation of a country. While these industries create value for society and provide employment opportunities, profits themselves are actually quite low.” Matrix aims to help the continued development of these industries by reducing inefficiencies using its Enterprise Cloudchain. Additionally, the Matrix AI Network remains keenly aware of the importance of hardware. “At present, the barrier to the amalgamation of AI and blockchain lies in hardware development.” Professor Deng says that the Matrix AI Network continues to ramp up R&D on its proprietary mining machine chip. “The idea is that these chips are specially designed to efficiently run deep learning algorithms and AI models.” A hardware solution lowers the risk of algorithm and model tampering and reduces the reliance on CPUs and GPUs.
On the Future
Professor Deng shares that, “presently, we hope to increase cooperation with local-level governments to establish research institutes and centers, especially in more developed manufacturing parks.” With the ongoing development of science and technology, artificial intelligence is poised to change our daily lives. Matrix hopes to connect people and business applications around the world to power AI for social good.
See also:
Finance
The Matrix Token Swap begins April 11th, 2019. There is no time limit.
Besides KuCoin, other large exchanges are expected to announce their support in the near future. However, the Matrix community needn’t worry as the Matrix team has prepared a convenient token swap method accessible via Matrix’s own online wallet. Detailed documentation instructions on how to swap your tokens using the Matrix online wallet will be released prior to April 11th.
What about the Matrix Online Wallet
The Matrix team has been quietly updating the Matrix online wallet. Although full functionality won’t be enabled under April 11th, below is a sneak peek! This is the wallet that you can all use to swap tokens starting April 11th.
A more detailed overview will be released alongside the start of the token swap. Details about Matrix’s mobile APP wallet will follow.
What about the mined block rewards
To reiterate, the block rewards received by Matrix’s deployed masternodes will be redistributed in the following ways:
1. Mainnet Airdrop [1,000,000 MAN tokens]
- A total of 1,000,000 MAN tokens will be distributed to every person who has completed their token swap once mining and verification masternodes are open. The amount that each person receives will be random.
2. Early Mining Masternode Incentive [200,000 MAN tokens]
- 200,000 MAN tokens will be distributed to the first 200 people to stake mining masternodes and remain online for 100,000 blocks (cumulative). This equates to 1000 MAN tokens per person.
3. Early Verification Masternode Incentive [200,000 MAN tokens]
- 200,000 MAN tokens will be distributed to the first 100 people to stake verification masternodes and remain online for 100,000 blocks (cumulative). This equates to 2000 MAN tokens per person.
4. Testnet Participation Appreciation [Estimated 300,000 MAN tokens]
- Everyone who applied for test tokens before February 22nd, 2019 will receive 500 MAN tokens each.
5. Token Burn [Estimated 2,000,000 MAN tokens
- For the overall benefit of the ecosystem, the Matrix AI Network will burn an estimated 2,000,000 MAN tokens.
6. The Balance
- The remaining tokens mined during this initial several weeks will be put towards the further development of the Matrix AI Network including but not limited to AI research projects. Once the total number of MAN tokens mined during this initial period is known, the Matrix AI Network will be able to share more specifics about these development activities.
Official dates for token redistribution will be announced once the Matrix AI Network turns off their masternodes and has a final tally of the received block rewards.
One more thing
As some people may feel rushed to complete their token swap as soon as possible, there is the risk of ill-intentioned parties spreading false information. Please only follow instructions shared by official Matrix channels.
Roadmap
The Matrix AI Network’s Chief AI Scientist Professor Deng shares his vision for Smart Cities and Networked Intelligence.
Nearly 25 years ago, Steve Deng, an undergraduate student studying electrical engineering at Tsinghua University, read something that forever changed the way he thought about networks and the nature of intelligence. It was a quote by Nobel Laureate Francis Crick:
You’, your joys and your sorrows, your memories and your ambitions, your sense of personal identity and free will, are in fact no more than the behavior of a vast assembly of nerve cells and their associated molecules.
The insight Crick inspired was that network interactions across distributed systems, even of very simple units, could result in a truly astounding emergent intelligence. This categorical shift in perspective laid the groundwork for a number of breakthroughs in the career of the man who would become the Matrix AI Network’s Chief AI Scientist: from early innovations in parallel computing to leverage global processing capabilities, to pioneering capabilities in Industrial IoT, to creating real-time diagnostic information in high-speed rail systems, to building new forms of actionable intelligence across cities.
One current area of focus for the Yangdong Artificial Intelligence Institute includes expanding the Matrix AI Network architecture for applications in smart cities by partnering with established industry players specializing in equipment like smart edge devices. The baseline for designing smart cities systems starts from conducting needs analysis with civic departments working on the frontlines to understand what disbursed data could be monitored more efficiently. Smart city networks can provide a real-time centralized view of resource flow across cities, regions, or even nations. This has the potential to create dynamic data-driven intelligence for public safety diagnostics, risk management, faster optimization of resource allocation, and forecasting.
Networked systems tied to operational metrics clearly constitute “smart systems” whose capabilities and efficiency already greatly eclipse gains from multiplying human efforts. According to Deng’s roadmap, this is a springboard to a new form of intelligence. “A higher order of value isn’t created until the networked system doesn’t simply lower costs and enable better coverage; it must create new forms of operational intelligence that weren’t possible before,” says Deng.
The roadmap for realizing new kinds of city-wide networked intelligence requires a secure, interoperable and high-performance digital infrastructure. The Matrix AI Network is emerging as a new class of technology provider in this multi-participant tri-sector landscape. The Matrix team is systematically building a robust public/permissioned distributed computing infrastructure that can match or outperform existing enterprise systems. City-wide networked intelligence also requires a more ambitious scope for big data; it requires collecting the richest possible repository of multi-dimensional data. Deng explains, “higher-order executive functions in the brain like visuospatial processing, language, working memory, and planning only become possible by orchestrating different subprocesses across multiple specialized regions of the brain. My team and I have experience designing custom hardware/software solutions, including field-specific sensors and equipment for data gathering and optimized AI models for advanced processing. We could view these like specialized system, roughly analogous to a brain region. The greater vision for AI-powered networks capable of truly transformative intelligence is to orchestrate data across multiple smart systems into something greater than the sum of its parts.”
Shaping and mastering powerful system-level intelligence will present demands for new kinds of systems creativity that are currently hard to fathom. “Discovery and design of city-wide, economy-wide, or even global intelligences could become a very exciting area for collaboration between researchers and new AI models. The Matrix AI Network is focused on expanding and enhancing the building blocks to power this networked intelligence across digital and traditional infrastructure.” says Deng.
What’s next?
- opening masternodes to the public in April
- GPU mining will be available in the summer of 2019.
- FPGA mining will be available by the end of 2019.
- This April, Matrix will have the 1st generation smart contract verification toolkit online. A more comprehensive version will be ready in the latter half of 2019. As for natural language intelligent contracts, Matrix team plans to release a template-based version in the latter half of 2019.
Partnerships and team members
Bitgrit is a Japanese company that believes in the decentralization and democratization of AI. They have a strong, established community of data scientists, coders and data providers. They operate a platform that makes advanced AI algorithms accessible to those who have a need; without necessarily the means to develop AI algorithm in-house. The proceeds generated are redistributed to those who have contributed to the code and to those who have contributed data in a fair and transparent manner. bitgrit has been operating in India, the Philippines and Japan since 2017. They have regularly held and attended forums and hackathons around the world.
Matrix and bitgrit signed a strategic cooperation agreement covering data sharing, technical support, community development and more. bitgrit’s large existing database and high-quality data scientist community will promote Matrix AI Network applications and aid in the training of Matrix’s AI algorithms. In turn, Matrix’s AI algorithms will increase the breadth and depth of bitgrit’s platform. In terms of community development, Matrix and bitgrit will focus on building shared communities in China, Japan and Southeast Asia. Both Matrix and bitgrit believe that through mutual effort, a future of practical, fair and transparent applications leveraging big data, AI and blockchain technology is within reach.
Social media metrics
The chart above illustrates a slight decline in the number of Telegram followers. In general, Matrix AI Network experiences average level of social activity.
- Twitter (Matrix AI Network) — official announcement channel. Recent publications — about the Matrix Mainnet and new partnerships (100–400 likes per publication).
- Facebook — official announcement channel — duplicates news from Twitter (10–20 likes per publication).
- Reddit — news about projects and blockchain, links to interviews, podcasts, upcoming events.
The graph above shows the dynamics of changes in the number of Matrix AI Network Reddit subscribers, Twitter followers and Facebook likes. The information is taken from Coingecko.com
