Hong Kong, The University of Hong Kong
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Existing Problem - Lack of Data One major key to build successful AI is the ability to gather data. The lack-of-data obstacle is hindering the R&D of machine learning (ML), and the adoption of the technology in businesses. There are limited existing channels to access and crowdsource data, especially for data which fits specific business needs. Furthermore, traditional solutions are expensive and centralized server-client model is not suitable for data sharing and exchange because of the ambiguity in the ownership of data. Data sharers have to bear middleman risks when using centralized solutions. Our Solution - Datax Ecosystem Datax is a data exchange platform built on blockchain that ensures data ownership and upholds integrity of data and participants’ reputation. It comprises of two functions: Datax Workforce and Datax Marketplace. Datax Workforce is a data crowdsourcing platform which provides a channel for data requesters to gather data. Data requesters design and post tasks onto the platform at a specific price, while incentivized workers complete the work and await payment. Requesters include researchers, consumer product groups, universities, MNCs and small businesses; whereas workers are individuals. Thanks to blockchain technology, data flows directly from workers to requesters, thus middleman risk is eliminated. Also, task submission and acceptance history are tracked by blockchain with integrity, therefore ensuring reputation of participants. Datax Marketplace empowers data owners to commercialize their datasets without risking their ownership of data, and allows academic researchers and companies to source data for R&D with confidence in data quality. With smart contracts, data ownership can be ensured as transactions are settled without a third-party. In addition, blockchain upholds the integrity of reputation of data buyers and sellers. It is believed that lowered risks and assured data ownership encourage data owners to share or sell their data. Datax Workforce & Marketplace Synergy - We encourage data requesters who crowdsource data from Workforce to resell their data on Marketplace. This synergy increases the monetary value of data crowdsourced from Workforce therefore increasing the reward requesters willing to pay workers. This fully utilizes the data resources contributed by workers and speed up the growth of the whole industry by avoiding duplicate efforts, time and resources used in collecting or generating similar data. Business Model For Datax Workforce , we charge a fixed percentage of commission on every task posted on the platform. We also provide some pay on demand tools that helps requester to collect more accurate data. Requesters can reach out to specific groups of the workforce through our filtering tools which limit the task to only relevant and preferred workers. Every filter deployed is charged separately. For Datax Marketplace , we charge a fixed percentage of commission on every transaction made on our platform. We also provide some pay on demand tools that helps requester to promote and boost sales of their dataset, such as search appearance optimization. Marketing and Sales Plan - At the initial stage of the sales plan, Datax will target academic researchers and startups by leveraging our connections with the academia and startup community. Our user base established from earlier stage would facilitate our penetration into the business sector. Datax will look for collaboration in a greater scale by approaching SMEs and big companies. Social and Community Impact Facilitate Cooperation - Cooperative R&D synthesize findings and accelerate research progress, but cooperation is often obstructed by trust issues. Decentralization encourages data sharing because no single party controls the infrastructure that holds the data. Better AI Models Benefit Society - Datax is establishing a global commons for datasets. People can make good use of others’ data while submitting their own. A global commons for datasets will ultimately realize a open data community, bringing AI technology to the next level. In a thorough data sharing and crowdsourcing environment, diversity of data reaches a new scale. Diversity of data results in qualitatively new datasets. Since data are the fundamental of AI, with more qualitatively new data being used in AI training, there will be qualitatively better resultant AI models, such as more accurate cancer diagnosis and more reliable self-driving vehicles.
Our team consists of three HKU students, including CS undergraduates and MSc(CS) postgraduates. The team is experienced in software development, marketing and community management in the blockchain industry. This enables us in rapid development at early stage. We are joined by a GM of FinTech Association of Hong Kong and several HKU professors researching in AI, blockchain and IT entrepreneurship as our advisors. Lung Yue Hin Hinnes Position/Titles: Technical Lead Hinnes is an enthusiast in innovative technologies, especially in machine learning and blockchain. He worked as a data scientist in a FinTech startup and had hands-on experience in price data analysis with deep learning. His extensive experience in mobile and web application development projects and strong technology-related academic background will help the team launching the Datax ecosystem smoothly and realizing our vision. In Datax, Hinnes is responsible for technology research and blockchain application development. He will determine the technology and protocol to be adopted to best fit the project. He will also participate in the decentralized application development, including the implementation of data storage protocol and building smart contracts on the Ethereum blockchain. Pang Chee Hin Marvin Position/Titles Business: QA Engineer and Blockchain Developer Passionate about information technology, Marvin is aspired to realize the true potential of crowdsourcing and blockchain. Previously, he was a summer intern at ICBC, where he contributed in managing information security risk and IT audit. He also gained exposure in AI and machine learning through his participation in a business analytics research lab in HKU. In Datax, Marvin will be responsible for developing the platform as a blockchain developer. He also assures the quality, security and reliability of the final product as a QA engineer. Lo Cheuk Yin, Jason Position/Titles: Blockchain Developer Jason sees high potential in blockchain technology and decided to devote his final year project to the topic. Jason has IT internship in various business sectors, including investment bank, startups and technology firms. Previously at Nomura and EMC, he had hands-on experience and gained exposure in corporate infrastructure development. He is adaptive in learning new technologies fast to perform duties quickly and well. He has also extensive experience in full stack development of web and mobile applications. In Datax, Jason will be responsible for building the platform as a blockchain developer.