Becoming believers one success at a time
Following firsthand experience, 95% of SAS Hackathon participants would recommend SAS® Viya®
Every year, the SAS Hackathon gives dozens of teams globally four weeks to tackle an interesting problem using the most productive AI and analytics platform. From business use cases to helping humanity, below are just a few of the projects that highlight what can happen when curious minds get their hands on SAS in the cloud.
Diagnosing disease with data
Nearly 10 million people worldwide are living with Parkinson’s disease, and as populations age that number is growing. Katalyze Data wanted to see if they could use SAS Viya to help diagnose Parkinson’s earlier so patients could seek care sooner.
Using publicly available data of keyboard movements, their ParkinStrike team was able to quickly operationalize machine learning models for use in an external app in which users can self-test to see if their typing patterns indicate symptoms of the disease.
Tamás Bosznay, a Principal Consultant for Katalyze, says that being able to deploy models in a couple of clicks let them take a “try fast, fail fast” approach to experimenting while also feeling confident that Viya’s built-in explainability would ensure trust in the results, which is critical in health care.
Bosznay also noted that one of the biggest advantages was that Viya’s variety of interfaces allowed different teams and different skill sets to all work together on the project.
“I think that’s what SAS Viya excels with,” he says. “Time to market is much shorter these days, so companies need to be able to do this much more quickly and flexibly.”
Satisfying the need for speed
What better way to get people moving faster through a city than with faster-moving AI and analytics?
The Heidelberg Mobility Insights team was able to quickly deploy models – including using no- and low-code options – based on traffic, weather, events and more to better predict how citizens can best get from point A to point B.
Building sustainability brick by brick
By definition, Internet of Things projects are going to involve massive amounts of complex streaming data. It can be easy to “get lost” in that data, Positive Thinking Company’s Alex Buchwald says, and spend weeks or months fine-tuning it.
In their Hackathon project to optimize energy usage for a leading European brick maker, his team used SAS Viya’s automated AI and reinforcement learning to accelerate their timeline for working with all that data and get a working proof of concept for a more sustainable manufacturing process.
“You can really speed up the development phase by a huge amount of time,” Buchwald says. “We thought it would be great to find an AI-driven approach to help customers in reducing the cost for energy while doing something great for the environment.”
Buchwald adds that a side benefit of the project was the chance to expose newer colleagues to all the different phases of the analytics life cycle and let them get hands-on experience on an end-to-end project to create real-world change.
“You can transform the data with SAS, you can do AI models and you can also connect the open AI world via Python,” he says. “It’s fully integrated in one single platform.”
How do you save a sinking city?
Jakarta, Indonesia’s capital, is home to 11 million people. But it’s sinking due to climate change and epic floods, and without help will be underwater by 2050.
Meet the Hackathon team that set out to save Jakarta by developing a centralized and integrated flood control system, based on an analysis of real-time data from IoT sensors.