Companies use crowdsourcing to train neural networks for better AI
Implications - Rigorous testing of AI means gathering mass amounts of data that are difficult to accumulate in the lab. Instead, companies have begun to train their machines with crowdsourced online games through which users unwittingly improve the quality of the AI. Gamifying technical aspects of one's brand cleverly redirects the wealth of information embedded in the crowd toward product improvement.
Workshop Question - How could your brand harness the power of the crowd to improve your product?
Trend Themes
1. Crowdsourcing AI Training - Companies are using crowdsourced online games to improve the quality of their AI by training their machines with massive amounts of accumulated data.
2. Prototyping with Pattern Recognition Algorithms - Platforms like MLJAR offer prototyping and development services by using pattern recognition algorithms.
3. User Testing Beta Software Projects - Area 120 has opened a beta-testing signup for users to test new software projects before they hit the public.
Industry Implications
1. Artificial Intelligence - AI companies can turn to crowdsourcing and pattern recognition algorithms for improving their AI technology.
2. Machine Learning - There is a growing trend of machine learning platforms, such as MLJAR, that offer predictive model building services.
3. Software Development - Businesses in software development can utilize beta testing programs for Area 120 projects.
