Harnesses Global Supercomputing for Sustainability


Advances UN Sustainable Development Goals via AI

Research and Education

Promotes Inclusive AI Research and Education


Democratizes Global AI Technology Access


Supercomputers help reduce inequality

Jan 22, 2024

Data Science Africa join international partners to launch the International Computation and AI Network

Jan 19, 2024

World's most powerful supercomputers support UN SDGs and global sustainability

Jan 19, 2024

Rebalancing the global AI landscape: ELLIS becomes a founding member of the Internation Computation and AI Network (ICAIN)

Jan 17, 2024


Managing power imbalances and other problematic effects of AI on society demands smarter, more collaborative use of existing resources and a global response.

The International Computation and AI Network’s (ICAIN) resulting vision is thus to join forces and pooling expert knowledge and the world's foremost supercomputing resources to promote the development of interdisciplinary, innovative research and expertise for large-scale AI models that serve society and the achievement of the Sustainable Development Goals (SDGs) and their development.

Our diverse team, comprising leading scientists, researchers, and educators from renowned institutions worldwide, is dedicated to leveraging AI and computational power for the Good of humanity. ICAIN's inception was inspired by a collective vision to democratize AI technology and foster equitable advancements in AI research and education across all regions of the globe.

The network plans to be fully operational by early 2025. The goals of 2024 are setting up its organization and looking for suitable projects and partners as well as running pilot projects to generate early impact and learnings for the setup.

Founding Members

Our Pilot Projects

1. Improved Weather Prediction for Sustainable Agriculture
In order to improve agricultural production in Africa, it is important to improve the accuracy of weather forecasts available to small scale farmers. Agriculture in Africa is mainly rain fed and accurate rainfall prediction is likely to improve yields by allowing farmers to appropriately time activities such as planting and also help them select appropriate crops to grow.

Goal: In this project we will leverage weather data collected by large networks of sensors to improve weather prediction by linking these data with new artificial intelligence based weather prediction models running on powerful computers. The key goal is to provide accurate medium to long range localised precipitation forecasts.

Partners: This work will bring together Data Science Africa (DSA), the Centre for Data Science and Artificial Intelligence (DSAIL) at Dedan Kimathi University of Technology in Kenya, Amini, a Kenyan climate startup and Communal Shamba Coffee.

2. Early diagnosis of plant diseases through spectroscopy
About 40% of the global crop production is lost to pests. Sub-Saharan Africa is most vulnerable to the increasing risks of pests and diseases spreading in agriculture. The current methods of disease identification and diagnosis involve experts traveling to disparate parts of the country and visually scoring the plants by looking at the disease symptoms manifested on the leaves.

Goal: The research project investigates a 3-D printed smartphone add-on spectrometer that determines the state of disease in plants before it is visibly symptomatic. Portable devices for the early detection of crop diseases are needed to support the farmers and experts working in the field. The output of this tool is integrated into a smartphone in the form of an app, making it accessible for use in the field in real applications.

Partners: This project will be executed by Data Science Africa (DSA), and ETH Zurich.

3. Ethical AI for Humanitarian Action - Developing Tailored LLMs
The International Committee of the Red Cross (ICRC) seeks to leverage Large Language Models (LLMs) to enhance its humanitarian work. Challenges like the bias of existing models, the underrepresentation of humanitarian contexts in commercial AI training sets, and the sensitivity of data related to conflicts limit the adoption of off-the-shelf AI models.

Goal: To address these constraints, the ICRC will investigate the responsible development of LLMs specifically tailored to its mandate on international humanitarian law and in line with its protection work in favor of people affected by armed conflicts. Ethical and accountability considerations will be at the center of this project, with the development of tools to assess if developed models are safe to be used for humanitarian applications.

Partners: This project will be executed by ICRC (DSA), and ETH Zurich.