DBpedia – Linked Data Fragments

Matches in DBpedia 2015-10 for { ?s ?p "Eric Brown, co-author of "The Effective CIO", alluded to the term "Crowdcomputing" in 2009.It is an overarching term which defines the myriad tools that enable idea sharing, non-hierarchical decision making and the full utilization of the world’s massive "cognitive surplus”-the ability of the world’s population to collaborate on large, sometimes global projects. Crowd computing brings together the strengths of crowdsourcing, automation and machine learning.Prof. Rob Miller of MIT further defines crowd computing as “harnessing the power of people out in the web to do tasks that are hard for individual users or computers to do alone. Like cloud computing, crowd computing offers elastic, on-demand human resources that can drive new applications and new ways of thinking about technology.” Crowd computing offers a harmonious amalgamation of both cloud computing and crowdsourcing. It combines human intelligence (the crowd) with artificial intelligence (the cloud) in order to produce quality results at unprecedented speed. Scientists and historians are already utilizing this process to complete time-consuming research, and many businesses are beginning to realize its potential for cutting costs and increasing productivity. Crowd computing very well may be on its way to changing the way humans live and operate in our society by using artificial intelligence in combination with the human mind.Srini Devadas, professor of electrical engineering and computer science at the MIT Computer Science and Artificial Intelligence Laboratory, asserts that “crowd computing will complement the cloud as one of two burgeoning infrastructures that will enable the world to become more ‘collectively intelligent’.”Four key process and technology innovations are the core of crowdcomputing: Microtasking. Work is broken into small components that are easier to complete by the crowd. Automation. Machines complete repetitive work, leaving judgement work to humans Hybrid Crowd: Higher value work and a greater volume of work can be completed when specialists, crowd workers and machines work together. AI: Machine learning creates a cascade of knowledge that enables more and more automation and continuously optimizes cost and quality. ↑ ↑ ↑ ↑ ↑ ↑"@en }

• Crowd_computing abstract "Eric Brown, co-author of "The Effective CIO", alluded to the term "Crowdcomputing" in 2009.It is an overarching term which defines the myriad tools that enable idea sharing, non-hierarchical decision making and the full utilization of the world’s massive "cognitive surplus”-the ability of the world’s population to collaborate on large, sometimes global projects. Crowd computing brings together the strengths of crowdsourcing, automation and machine learning.Prof. Rob Miller of MIT further defines crowd computing as “harnessing the power of people out in the web to do tasks that are hard for individual users or computers to do alone. Like cloud computing, crowd computing offers elastic, on-demand human resources that can drive new applications and new ways of thinking about technology.” Crowd computing offers a harmonious amalgamation of both cloud computing and crowdsourcing. It combines human intelligence (the crowd) with artificial intelligence (the cloud) in order to produce quality results at unprecedented speed. Scientists and historians are already utilizing this process to complete time-consuming research, and many businesses are beginning to realize its potential for cutting costs and increasing productivity. Crowd computing very well may be on its way to changing the way humans live and operate in our society by using artificial intelligence in combination with the human mind.Srini Devadas, professor of electrical engineering and computer science at the MIT Computer Science and Artificial Intelligence Laboratory, asserts that “crowd computing will complement the cloud as one of two burgeoning infrastructures that will enable the world to become more ‘collectively intelligent’.”Four key process and technology innovations are the core of crowdcomputing: Microtasking. Work is broken into small components that are easier to complete by the crowd. Automation. Machines complete repetitive work, leaving judgement work to humans Hybrid Crowd: Higher value work and a greater volume of work can be completed when specialists, crowd workers and machines work together. AI: Machine learning creates a cascade of knowledge that enables more and more automation and continuously optimizes cost and quality. ↑ ↑ ↑ ↑ ↑ ↑".