The world faces a number of environmental sustainability challenges — from the local weather disaster and water shortage to meals manufacturing and concrete resilience. Overcoming these hurdles affords alternatives for innovation by expertise and synthetic intelligence.
That’s why Cloudera and AMD have partnered to host the Local weather and Sustainability Hackathon. The occasion invitations people or groups of knowledge scientists to develop an end-to-end machine studying challenge centered on fixing one of many many environmental sustainability challenges dealing with the world in the present day.
Contributors can be given entry to Cloudera Machine Studying working on AMD {hardware} to allow swift, highly effective computations and breakthrough improvements — a pairing that can assist information scientists craft local weather and sustainability options. On the completion of this hackathon, each line of code from the successful prototypes can be made public in order that the occasion can contribute to the collective effort to deal with the local weather disaster and different urgent environmental sustainability challenges.
This isn’t your peculiar hackathon — it’s meant to yield actual, actionable local weather options powered by machine studying. Contributors can select from the next classes for his or her prototype:
- Local weather Good Agriculture: With the world’s inhabitants anticipated to hit practically 10 billion by 2050, discovering sustainable methods to feed all of those folks is crucial for addressing world starvation in addition to mitigating the local weather disaster. Local weather-smart agriculture (CSA) is an built-in method to managing landscapes — cropland, livestock, forests and fisheries — that tackle the interlinked challenges of meals safety and local weather change. Machine studying (ML) has the potential to advance climate-smart agriculture by offering precious insights, predictions, and resolution help to farmers, researchers, and policymakers. This consists of local weather modeling and prediction, crop yield prediction, pest and illness detection, irrigation administration, precision agriculture, soil well being evaluation, crop choice and rotation, carbon sequestration, provide chain optimization, resolution help programs, local weather adaptation methods, and data-driven analysis.
- The Water Disaster: Whereas water is one thing many take without any consideration, its shortage is turning into one of the urgent sustainability challenges for companies, governments, communities, and people all over the world. Moreover being basic to sustaining life, water is also integral for agriculture, manufacturing, and industrial processes. The local weather disaster is a water disaster, too. Because the planet warms, this results in elevated evaporation, altering and unpredictable precipitation patterns, rising sea ranges, and melting snow pack and glaciers, amongst different challenges. Addressing water shortage is turning into a crucial problem. Attainable tasks embrace forecasting water consumption primarily based on historic information, climate information, and inhabitants development; utilizing satellite tv for pc imagery to detect adjustments within the atmosphere that may point out underground leaks in massive pipelines; or predicting the quantity of rainwater that may be harvested in particular areas primarily based on climate forecasts and historic information to help in designing efficient rainwater harvesting programs.
- Sustainable Cities: Cities are accountable for 70 p.c of world greenhouse gasoline emissions. That signifies that the local weather disaster can be gained or misplaced in our city environments. Many of those emissions are pushed by industrial and transportation programs reliant on fossil fuels. However machine studying and large information supply promise for creating the sensible cities of tomorrow. By bettering efficiencies and enabling higher decision-making, we are able to tackle the sustainability challenges afflicting cities all over the world. Attainable tasks embrace air high quality prediction and monitoring, Predicting power demand in numerous elements of town to optimize electrical energy distribution, or utilizing imagery to categorise waste sorts for extra environment friendly recycling processes.
For this Hackathon, individuals can be tasked with utilizing publicly obtainable datasets (recommendations for every theme are supplied) to create their very own distinctive Utilized ML Prototype (AMP) centered on fixing or gaining additional perception right into a local weather or sustainability problem. Cloudera’s Utilized Machine Studying Prototypes are absolutely constructed end-to-end information science tasks that may be deployed with a single click on instantly from Cloudera Machine Studying, or accessed and constructed your self through public GitHub repositories..
The local weather disaster gained’t wait — we hope you’ll be a part of us in utilizing the facility of knowledge science and machine studying to assist tackle it as soon as and for all. Be taught extra about how one can take part within the hackathon right here.