Code. Hack. Innovate for Social Good.

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Agenda
9/26 08:00 AM Competition check-in, continental breakfast provided by Intel
09:15 AM Kickoff Speaker: Wei Li
oneAPI AI Kit Workshop and Introduction to AI Reference Kits
09:45 AM Habana Gaudi Demo
10:30 AM Competition Begins (with pre-recorded video and starter notebooks)
12:00 PM Lunch provided by Intel
01:30 PM Model Deployment & Execution Demo with MLflow
07:00 PM Competition Submission Deadline
10:00 PM Winners Notified
9/27 10:00 AM Grand Prize Winner Live Video Interview with Greg Lavender at the Host desk
06:00 PM Category Winners Announcement at Technology Showcase

When: Monday, September 26th from 08:00 AM to 05:00 PM PT

Where: San Jose McEnery Convention Center - 150 W San Carlos St, San Jose, CA 95113

Don’t forget to bring your talents, enthusiasm, coding skills, and your laptop to the event – we will provide the rest, including a complimentary breakfast and lunch, as well as fun prize giveaways throughout the day.

The hackathon will have three tracks:

Machine Learning Challenge Track: Predict the quality of freshwater

Freshwater is one of our most vital and scarce natural resources, making up just 3% of the earth’s total water volume. It touches nearly every aspect of our daily lives, from drinking, swimming, and bathing to generating food, electricity, and the products we use every day. Access to a safe and sanitary water supply is essential not only to human life, but also to the survival of surrounding ecosystems that are experiencing the effects of droughts, pollution, and rising temperatures. In this track of the hackathon, you will have the opportunity to apply the skills you learned in the Machine Learning Workshop to help global water security and environmental sustainability efforts by predicting whether freshwater is safe to drink and use for the ecosystems that rely on it.

Computer Vision Challenge Track: Target and Eliminate weeds to increase crop yields

Weeds are an unwanted intruder in the agricultural business. They steal nutrients, water, land, and other critical resources to grow healthy crops. These intruders can lead to lower yields and inefficient deployment of resources by farmers. One known approach is to use pesticides to remove weeds, but aggressive pesticides create health risks for humans. Computer vision technology can automatically detect the presence of weeds and use targeted remediation techniques to remove them from fields with minimal environmental impact. In this hackathon track, you will be tasked with training and deploying a model into a simulated production environment - where your binary-classification accuracy (F1 score) and inference time will be used to rank you against other teams competing for this track's top spot.

Natural Language Processing Challenge Track: Text classification

Text classification is an important problem to tackle in the field of natural language processing (NLP). In this track of the hackathon, you will get to use some of the latest transformer-based NLP models to train a model to predict the class label of a piece of text. The principles learned in this track are applicable to a much wider array of NLP and classification problems that could be applied to your work. You will get to use some of the most advanced Habana® Gaudi® AI Accelerators in this track to train a model. You will also get to learn some of the essential elements of a production model serving environment, where your model F1 score will be ranked against other teams on an unseen test dataset. We look forward to seeing your solutions!

Do something wonderful.