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What You Missed from Genpact’s Record-Breaking ‘Dare In Reality’ Hackathon

Within two weeks, the hackathon received more than 5,200 participants and 10,000+ submissions.

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What You Missed from Genpact’s Record-Breaking ‘Dare In Reality’ Hackathon

Illustration by What You Missed from Genpact’s Record-Breaking ‘Dare In Reality’ Hackathon

The Dare in Reality Hackathon 2021, powered by Genpact in partnership with Envision Racing and MachineHack, challenged participants to develop machine learning models that predict lap times in a Formula E qualifying race. The contest  closed on 22 November having received a record number of entries.

Within two weeks, the hackathon received more than 5,200 participants and 10,000+ submissions. Currently, a panel of judges are selecting the winners. Interestingly, the level of competitiveness in the final score is also marginally high (i.e. close to 0.01 to 0.001 difference) in the leaderboard ranking.

Also, the hackathon had one of the highest prize amounts compared to any other hackathons hosted previously. The ‘Dare In Reality’ was indeed a first-of-its-kind hackathon ever hosted globally. 

Moreover, hackathon entrants showcased their advanced data analytics and AI skills, creating machine learning models to help the Formula E team predict lap times in the important qualifying sessions that determine where on the grid each driver starts a race. 

The hackathon winners will receive a range of cash and tech prizes, including: 

  • First prize: $7,000 
  • Second prize: $5,000 
  • Third prize: $3,000 
  • Fourth prize: iPad Air 128 GB 
  • Fifth prize: Apple AirPods

What Did You Miss? 

Touted as the largest machine learning hackathon globally, ‘Dare In Reality’ gave participants a unique opportunity to work on one of the most complex datasets out there, curated by Envision Racing and Genpact. 

The hackathon was the first time Genpact and Envision Racing gave people outside the partnership the opportunity to help the team make even better use of its data and analytics. 

The hackathon welcomed participants from all across the globe, including the US, China, Russia, Germany, Vietnam, India and South Korea. The entrants also got to compete with experienced professionals. Some of them were leaders in the data science industry with titles like the head of analytics, CTO, and senior data analysts. 

Besides experienced professionals, the hackathon also saw participation from various premium institutions like IITs, IIMs, NITs and others. 

Formula E is the world’s first all-electric international single-seater championship. The race consists of 12 teams and 24 drivers. In every race, drivers and their engineers need to make rapid decisions on how to use their energy, overtake or defend, respond to competitors, and more. To help Envision Racing make the right decisions on the racetrack and beyond, Genpact’s data science and machine learning experts use sophisticated algorithms to provide the team’s drivers and engineers with invaluable insights they need to improve their competitive edge

The hackathon presented participants with the challenge of predicting what drivers’ lap times would be in the all-important qualifying sessions. Ahead of every race, drivers compete to establish their place on the starting grid. Being able to anticipate the lap times for each driver based on the conditions of the track, weather, driver’s experience and other critical and evolving factors offers an invaluable advantage. Our hackathon entrants put data and analytics to work to address this challenge. 

We will announce the names of all the winners of the Dare In Reality Hackathon 2021 shortly, alongside details of the winning approach and solutions.  

If you missed this hackathon, don’t worry. We’ll have more that you can sign up for next year.

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Amit Raja Naik

Amit Raja Naik is a seasoned technology journalist who covers everything from data science to machine learning and artificial intelligence for Analytics India Magazine, where he examines the trends, challenges, ideas, and transformations across the industry.
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