Test your skills, have fun and get paid for your winning ideas.
$60,000
Optimization
Build an algorithm that solves for the most profitable solution by sending workers to collect rewards over a map area within a particular time and budget.
Real-world application: Optimize complex schedules for business operations.
$25,000
Generative AI
Fine tune a conditional variational autoencoder to thoroughly explore the possibilities of a simple mathematical function.
Real-world application: Expand solutions in mathematics and geoscience.
$50,000
Partial Differential Equation
Help improve battery efficiency and storage capabilities by exploring the Poisson-Boltzmann partial differential equation to model the electro-chemical processes.
Real-world application: Gain more efficient, green electricity storage.
A grandmaster data scientist, a graduate student researching space junk and a professor of mathematics. This is not the beginning of a joke. These were some of the participants on 233 interdisciplinary teams that competed in this electrified 12-week challenge. The goal: To explore ways to optimize electrolyzers using the Poisson-Boltzmann Equation (PBE) and open source data.
Winning teams demonstrated unique approaches to the problem, including a repurposed self-driving car algorithm, repurposed mass spectrometer processing and a new application of neuro-evolution algorithms.
This challenge was designed with three sequential stages that teams unlocked by submitting correct responses. The winning team was awarded $18,000. Additional prizes were given to the first teams to reach the next stage, and for the top 10 teams overall — a total purse of $50,000.
Oil slicks, whether they’re caused by humans or natural, are, well, kinda slick. The 134 teams that competed in this 12-week challenge learned how the properties that make oil slicks nearly undetectable to the human eye are the same ones that give away their locations on satellite imagery.
The winning teams in this challenge came up with six new and unique algorithms to improve the accuracy of oil slick detection using open source imagery from the European Space Agency. We awarded $30,000 in prize money, with the top team pocketing $15,000.
Using satellite imagery isn’t new for oil slick detection. The solutions developed in this challenge will make the process faster and less expensive, so action can be taken much sooner.
Our Sandbox challenges are a great way to test your skills and find your limits in a safe environment where there are no wrong answers.
Are you looking for some fresh thinking, or a few more brains? We can help you build a challenge that will engage our network of experts so you can get a project unstuck or take it to the next level. Onward Challenges are delivering unique solutions for implementing and optimizing AI, building new models and tools, testing the results of existing algorithms, and scaling dataset ingestion.
Our challenges attract dozens of teams and often produce multiple solutions that represent new ways of looking at a problem. Many solutions have resulted in tangible savings in time, energy and costs. Bring us your challenge, we’ll bring the expertise.