Cash prizes ranging from $5,000 to $10,000 per match were secured from corporate sponsors and awarded to tournament winners to generate interest from the student community.

[10][11][12][13][14] Since the end of 2017, Topcoder has continued to offer its enterprise clients the Hybrid Crowd platform, as a way to protect intellectual property in crowdsourcing projects.

It is open and global: anybody, with a few legal restrictions dictated by US laws, and listed in Community Terms, can join and compete, without any financial commitment to Topcoder.

Intellectual property for the winning submissions to commercial challenges is passed to the client, in exchange for monetary prizes paid to the winners.

In both cases, more substantial prizes compared to regular design challenges with the similar goals, are offered in exchange for the shorter timeline.

Short timelines allow Topcoder managers to demonstrate to customers how crowdsourcing works on real cases, during live, and few-days meetings with the clients.

Each year, the most successful participants of each competition track included into TCO are selected and invited for a free one-week trip to on-site finals, where they compete for prizes, and also socialize with each other, helping to build community spirit among the most active members.

[50] Researchers say that Topcoder competitors approached the biology-related big-data challenge, and managed to create a more accurate and 1000 times faster alternative of BLAST algorithm.

From July 2017 to February 2018 it ran the Functional Map of the World challenge to develop deep learning algorithms capable of scanning and identifying in satellite imagery different classes of objects, such as airports, schools, oil wells, shipyards, or ports .

[53][54] In the ongoing Mercury challenge it aims to create AI methods for automated prediction of critical events, involving military action, non-violent civil unrest, and infectious diseases in Middle East.

[59][60] In 2010, NASA asked the Topcoder community to optimize the contents of medical kits for future human space exploration missions.

[66] In another challenge, Topcoder community helped NASA and National Geographic's explorer Albert Lin to develop an algorithm to identify human-built structures in Genghis Khan's homeland.

[69][70][71][72][73][74][75][76] In 2015, the Topcoder Data Science community was challenged by NASA, Quakefinder, Harvard Crowd Innovation Lab, and Amazon Web Services, to come up with an algorithm that finds correlations between ultra-low frequency electromagnetic signals emanating from the earth, and subsequent moderate and large earthquakes.