We have received an overwhelming response to our announcement of free, AI-ready datasets in support of Ukraine. Nearly a hundred AI companies, researchers, developers, and GIS practitioners have offered to support the initiative with Scale – an inspiring global community of AI Developers for good.
Given the high demand, we will provide the datasets in phases starting with requestors with the greatest need, followed by a broader community. At this time, our focus is on providing Structure Damage Assessments in Kyiv, Kharkiv, and Dnipro.
The path forward is now two-pronged – our top priority is the delivery of damage assessments to those with urgent need.
The second prong of our effort is to provide AI-ready training datasets for Damage Assessment to the broader AI community, starting with a structure recognition training dataset.
Today, we are sharing an initial dataset with the broader AI community: link to download dataset.
Note: the corresponding ZIP file's SHA256 Checksum is: 379c394dab6a4d7f1358625d086ebea4b39aaa124548e8c079bee16fb574bc53.
We appreciate your patience as we assess and prioritize requests for data and data development. We look forward to continuing to support Ukraine alongside other AI Developers leveraging critically important open-source and commercially available data for this important work.
Sincerely, Scale AI Team
At Scale, we believe in using AI technology in support of democratic values. That’s why starting today, Scale will be providing a series of AI-Ready datasets that algorithm developers can use to rapidly train and deploy AI in support of Ukrainian operations. By providing these datasets at no cost to national security practitioners, we hope to support a diplomatic solution and swift end to this conflict.
Diplomacy is fueled by insights; foundational to that is quality, trusted data. We have recently created strategic partnerships with commercial satellite imagery providers in order to develop these datasets, which include Aircraft Detections, Structure Damage Assessments, Change Detection, and the JSON and GeoJSON annotations. We encourage AI Developers to contact email@example.com to receive this data free of charge.
To better understand how these datasets can be used, Scale presents a contemporary use case of our partnerships with national security leaders. We deliver an AI-powered change detection solution capable of identifying and tracking military formations across the globe.
The video below demonstrates continuous monitoring and improvements by Scale’s ML engineers and deployment strategists. We provide timely and accurate insights through our AI Data Readiness platform, our Test and Evaluation platform and our continuous ML Ops tooling.
Leveraging Scale's AI/ML ops platform, we continuously develop and hone deep learning models to describe scenes and detect objects across a range of inputs from commercial satellite imagery providers.
We are now delivering insights to U.S. national security customers from this full-stack, multi-intelligence, human-teaming product, including on Russian formations across Europe and Eurasia.
Here, on Russian air and ground order of battle (OOB) data, we successively identified OOB changes across the EUCOM area of responsibility (AOR) over the past several months. We used high-resolution synthetic aperture RADAR(SAR) imagery from Capella Space and high-resolution optical imagery to deliver high-accuracy, time-sensitive insights.
“In these intricate and time-sensitive scenarios, it is critical that we deliver insights from multiple, disparate datasets at the speed of relevance,” said Mark Valentine, Head of Federal at Scale. “We are proud to demonstrate the power of our platform, and our approach to human-machine teaming to support national security leaders and practitioners.”
Monitoring the Russian OOB on the border of Ukraine using commercial satellite imagery, and other non-traditional Intelligence, Surveillance and Reconnaissance (ISR) sources requires adaptation to a variety of challenges in a constantly-evolving field.
The challenges in using AI to analyze OOB changes include: exigent scenarios presented by weather, disparate image varieties and quality, and the inclusion of relatively rare military objects such as transporter erector launchers (TELs), for which there are limited real-world observations.
The depth of ontology can also present complications: the presence of multi-generational aircraft, ground vehicles, RADAR and TELs mean that models need to be trained against tens of thousands of observations in a range of environmental conditions.
If you are an AI Developer who would like to receive this data free of charge, please contact firstname.lastname@example.org.