CrowdPrecision
| CrowdPrecision | |
|---|---|
 CrowdPrecision ICO Review | |
| CrowdPrecision ICO | |
| ICO start: | 2018-07-22 13:00:00 |
| ICO end: | 2018-08-19 13:00:00 |
| Price: | 1 ETH = 80,000 CPT |
| Tokens: | 2,400,000,000 |
| Tokentype: | ERC20 |
| Hardcap: | 30,000 ETH |
| Softcap: | 7,500 ETH |
| Platform: | Ethereum |
| Accepting: | ETH |
CrowdPrecision offers higher quality results at lower cost and faster. They decided against a solely decentralized platform. Their experiences show that there are always cases that can not be clarified automatically. Therefore, our platform has a group of experts who serve as a point of arbitration and take into account both, the interests of employees and employers in a neutral way. CrowdPrecision tackles two of the most significant challenges in current Crowdsourcing applications – quality control of the work submitted and fast and cost-effective payment mechanisms.
Contents
Description
With the fast evolution of information and communications technology, the Internet has become available almost anywhere and at any time. Smartphones and similar devices have become increasingly essential in everyday life and various kinds have been made readily available in large numbers. The ease of access to such devices has had an immense impact on the number of people around the globe who are interconnected. These global connections enable people to communicate and collaborate across borders instantaneously and at a low cost. That would have been challenging or even impossible a few years ago. Besides enabling easy and fast transfer of information, the Internet has also generated an incredibly huge potential labor force that is available 24/7, globally distributed, and has a highly diverse set of skills.
One approach to access this labor force consisting of global Internet users is Crowdsourcing. Instead of delegating large tasks to dedicated employees, the work is broken down into smaller jobs that can be accomplished independently and are distributed via marketplaces to a large number of online workers. On the one hand, the parallelization leads to a much faster achievement of the tasks. On the other hand, the approach helps to reduce the overall labor costs due to the inclusion of global workers of different salary expectations. Additionally, it further facilitates the flexible scaling of human crowd resources based on current demands, similar to technical cloud infrastructures.
Besides economic aspects, Crowdsourcing also offers a great opportunity for individuals from developing countries, as it introduces channels for safe and well-paid online labor. With its new possibilities for increasing productivity and redefining ways by which businesses carry out projects, Crowdsourcing is already successfully applied in various fields of traditional work, including text production, logo design, programming, and even research and development tasks. Furthermore, it also makes possible the cost-efficient and timely completion of vast numbers of so-called microtasks, which non-expert crowdworkers can complete within a few minutes and without any prior knowledge but which are impossible to perform using algorithmic means. Micro-tasks exhibiting interesting patterns and worker behaviors, for example labeling or tagging a set of objects, are utilized for machine learning and could be used in deep learning. The current approach to understanding crowdsourced human input is vital for the further development of machine learning models and approaches.
The rapid rise in the use of international platforms like Amazon Mechanical Turk (MTurk), Microworkers, and Crowdflower demonstrate the considerable growth of Crowdsourcing in recent years. Consequently, CrowdPrecision aims at combining the success of these traditional Crowdsourcing platform providers with the benefits of current developments in Blockchain Technology and using cryptocurrencies.
Roadmap
| “ | 2000: Rise of Crowdsourcing 2013: Problems emerge in trust and result quality 2009: Microworkers.com starts international operations 2014: Idea of building trust-based high-quality Crowdsourcing within the Microworkers.com environment Q2 2017: Identification of Blockchain as a promising technology toward trust-based quality Crowdsourcing Q3 2017: Microworkers.com size exceeds 1 million workers CrowdPrecision core team forms Q4 2018: Quality Crowdsourcing concept adjusted Q1 2018: CrowdPrecision Pte Ltd founded Preparation for token sale Q2 2018: ICO White List opens CrowdPrecision Token (CPT) Sale Q3 2018: Listing CPT tokens on first exchanges Q4 2018: Public beta of the CrowdPrecision platform for registered workers Q1 2019: Implementation of Entropy-Based Ranking mechanisms (EBR) Q2 2019: Initial building of Specialized Crowds in CrowdPrecision Expansion of CrowdPrecision to other languages and specialty targets First public version of CrowdPrecision platform Q3 2019: Integration of Microworkers.com as first external Crowdsourcing platform Other worker sources Q4 2019: Expansion of marketing in Asia Pacific 2020: Integration of additional task providers partners Integration of additional Crowdsourcing platforms Optimization of Entropy-Based Ranking Expansion to developing countries, creation of dedicated local micro-tasking workplaces (if Hard Cap is reached)[1] | ” |
Team
| name: | title: | links: | group: | photo: | iss: |
|---|---|---|---|---|---|
| Thomas Tran-Gia | CEO & Co-founder | https://www.linkedin.com/in/thomas-trangia/ |  | 3.6 | |
| Leng Yaw-Owe | Co-founder & Business Manager, Asia-Pacific | https://www.linkedin.com/in/yaw-owe-leng-60036a3/ |  | 3.6 | |
| Phuoc Tran-Gia | Co-founder & Head of Finance | https://www.linkedin.com/in/phuoc-trangia/ |  | 3.6 | |
| Matthias Hirth | CTO | https://www.linkedin.com/in/matthias-hirth/ |  | 3.6 | |
| Andreas Schütz | https://www.linkedin.com/in/andreasschuetz85/ | Advisors |  | 3.6 | |
| Tobias Fertig | https://www.linkedin.com/in/tobiasfertig/ | Advisors |  | 3.6 | |
| Igor Eisenbraun | https://www.linkedin.com/in/igor-eisenbraun/ | Advisors |  | 3.6 | |
| Henry Vu | https://www.linkedin.com/in/vu-henry/ | Advisors |  | 3.6 | |
| Wolfgang Stegmann | https://www.linkedin.com/in/wolfgang-stegmann-39705287/ | Advisors |  | 3.6 | |
| Paul Müller | https://www.linkedin.com/in/paul-mueller-b4458073/ | Advisors |  | 3.6 | |
| Karl Klug | https://www.linkedin.com/in/karlklug/ | Advisors |  | 3.6 | |
| Benedikt Glatzl | https://www.linkedin.com/in/benediktg/ | Advisors |  | 3.6 |
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