Announcing the Winners of the 2018 AWS AI Hackathon
We’re excited to announce the winners of the 2018 AWS AI Hackathon. Horacio Canales has won first place with his “Second Alert” project. This project enables users from around the world to identify missing persons, including human trafficking victims, children too young to remember their family members’ names, and mentally handicapped individuals. Horacio built the solution using image analysis, text analysis, and conversational agents with Amazon Rekognition, Amazon Comprehend, and Amazon Lex. In recognition for his contribution, Horacio will receive $5,000 USD and $2,500 in AWS Credits.
We want to thank all of the participating developers from around the world for their time and creativity during the 2018 AWS AI Hackathon. In this hackathon, we challenged developers to build intelligent applications using pre-trained machine learning computer vision, natural language processing, speech recognition, text-to-speech, and machine translation API services. Last week our judges determined three winners from more than 900 submissions.
Developers submitted projects aimed at applying artificial intelligence to solve problems in ecommerce, health, entertainment, and much more. Our judges reviewed submissions based on the quality, creativity, and originality of the idea; implementation of the idea, including how well AWS machine learning services were leveraged by the developer; and the potential impact of the idea, such as how the solution can be widely useful. Our panel of judges included machine learning and open source experts from across AWS:
- Adrian Cockcroft, VP Cloud Architecture Strategy at AWS
- Randall Hunt, Senior Technical Evangelist at AWS
- Nino Bice, Senior Product Manager at AWS
- Humphrey Chen, Sr. Manager PMT Amazon Rekognition
- Vikram Anbazhagan, Head of PM – Language technologies – AWS
Congratulations to our winners!
1st Place | $5,000 USD and $2,500 in AWS Credits: Second Alert, by Horacio Canales. Horacio was motivated to help identify missing persons using facial recognition. AWS services used include Amazon Rekognition, Amazon Comprehend, Amazon Lex, and AWS Lambda.
2nd Place | $3,000 USD and $1,500 in AWS Credits: Mobu, by Yosun Chang and Luannie Dang. Yosun built an “empathy-powered movie buddy robot” that recommends movies using chat, image recognition, and a person’s mood—by determining user happiness through facial analysis. AWS services used include Amazon Rekognition, Amazon Lex, and AWS Lambda.
3rd Place | $2,000 USD and $1,000 in AWS Credits: Lab monitor, by Kitson Cheung, Cyrus Wong Chun Yin, Kwok Tung Chan, Chun Long Kwan, Mei Ching Law, Fung Lam Jacqueline Wu, Mike Ng, and Man Ting Ma. This team built an application that helps students stay focused during technical lab classes. AWS services used include Amazon Rekognition, Amazon Polly, Amazon Lex and AWS Lambda.
We also recognize these four submissions in no particular order, with $300 in AWS Credits:
Serverless Hands-free Allergy Checker, by Ceyhun Ozgun. AWS services used include Amazon Rekognition, Amazon Lex, Amazon Polly, and AWS Lambda.
The Healing Power of Telling Your Story, by Mohamed Hassan Abdulrahman. AWS services used include Amazon Translate, Amazon Comprehend, and AWS Lambda.
QuickSeek, by Harry Banda. AWS services used include Amazon Transcribe, Amazon Comprehend, and AWS Lambda.
Galudy, by Emmanuel Adigun, Olalekan Elesin, and Samuel James. AWS services used include Amazon Rekognition, Amazon Comprehend, Amazon Translate, and AWS Lambda.
About the Author
Cameron Peron is Sr. Developer Marketing Manager for Artificial Intelligence at Amazon Web Services.