AI for Social Good Hackathon

Code. Hack. Innovate for Social Good.

Join Intel^® in-person in San Jose, California to innovate for social good on Monday, September 26^th as we kickoff Intel^® Innovation 2022!

Showcase your Machine Learning and Deep Learning skills and compete for a chance to win Intel® NUC Kits, thousands in cash prizes, Gaudi-based Amazon EC2 DL1 Instances, and more! In this hackathon, you’ll also learn how to build a full end-to-end MLOps pipeline, from data ingestion to model deployment and productization using industry-standard frameworks and tools which are performance-optimized by oneAPI for cross-architecture use.

Join us for this in-person event at the San Jose McEnery Convention Center as we kickstart Intel® Innovation. With your attendance at the hackathon, you will qualify for a complimentary pass to Intel® Innovation, where we will share the latest advanced AI technologies, open ecosystem resources, and innovative new computing solutions.

So, register now to reserve your spot!

What to expect:

This two-part event will begin with an AI workshop detailing Intel's portfolio of optimizations for popular industry-standard frameworks (including TensorFlow, PyTorch, Scikit-Learn, XGBoost, and others), open AI software tools, and domain-specific reference kits. This will lead into the Hackathon where you will have the option to compete in one of three tracks: Machine Learning, Computer Vision, or Natural Language Processing.
As a contest participant, you will be provided with access to an Intel® Xeon™ 3^rd Generation Scalable Processor or a Habana® Gaudi® Deep Learning Accelerator to build your solution
Collaborate, network, and compete in teams of up to three while getting the chance to demonstrate your work to thousands of data scientists and industry experts attending Intel® Innovation at our networking reception on the evening of September 27^th!

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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
	09:15 AM	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
9/27	06:00 PM	Category Winners Announcement at Technology Showcase

When: Monday, September 26^th 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!