Crowdsourcing non profit

Crowdsourcing is only suited for large corporations, to promote the next product launch or to obtain creative ideas at very little cost? These nine successful non-profit projects demonstrate that it can be done differently. And they may inspire you to start your own crowdsourcing project, whether as a profit or non-profit project.

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How long has it been since you last had your smartphone in your hand? 5 minutes, maybe 10? Besides your keys and wallet, your cell phone is probably the most important thing you have with you every day. You use it as an alarm clock, a watch, your most important communication device and even just for amusement. So why not use your Smartphone to earn money as well? Find out in this article which mobile jobs are waiting for you at clickworker.

1. Photos – Shoot and Save

Earn money with your smartphone

Strike a pose, because we pay for your selfies! Our customers are concerned about beauty in only a very few cases though. Instead the photos are usually used to drive the development of artificial intelligence. Your selfies and of course pictures of other subjects (animals, landscapes, etc.) don’t end up on social platforms or in private photo albums, but rather help to make image recognition software more precise, for example.

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B2B Social Media Marketing

Social media marketing can obviously be very successful in B2C business. But what about the B2B sector? Numerous companies wonder what they can achieve on Facebook and co. and assume that they will not find business customers there. But business life has changed.

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NLP

Natural language processing, also known as NLP, describes the machine processing of natural language. NLP is a sub-field of artificial intelligence (AI). Humans are more and more frequently coming into contact with AI in their daily lives – whether with Alexa at home, with OK Google on their smartphone or when making a call to customer support. Today, humans are speaking more often with machines. And the areas of application of NLP are steadily on the rise.

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training data for machine learning

Data are the foundation for training algorithms. The more realistic the data, the better the results. This is because artificial intelligence is based on precise and reliable information for training its algorithms. This is obvious but it is often overlooked. The training data are realistic when they reflect the data that the AI system gathers in real operation. Unrealistic data sets prevent machine learning and lead to expensive false interpretations.

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