Deep Block will be attending the next edition of Korea Digital Future Innovation Exhibition that will take place from September 25th to 27th, 2023, at booth Booth #A02, COEX, Hall A, in Seoul, South Korea. Come visit us to understand the latest trends in computer vision and geospatial analysis.
In today's swiftly evolving tech landscape, what we once deemed as innovative — like AI, data, and cloud tech — are now imperative in the present, not just the future. The convergence of digital industries continues to fuel ongoing technological revolutions. The Korea Digital Future Innovation Exhibition 2023 is set to unveil the latest technologies, services, and a plethora of innovation narratives. It will bring together top institutions and companies, both domestic and international, poised to shape the future.
Why Deep Block?Every day,commercial imaging companies collect petabytes of Earth Observation data. The challenge is that there aren't enough people on earth, not even experts, to go through this wealth of information tomonitor key areas, detect changes over time, or anticipate potential threats.
Recent advancements in AI and deep learning have made it possible toautomate 80% of geospatial analysis tasks, allowing analysts to focus on what really requires their expertise and reducing decision-making time.
However,only 53% of AI projects make it from prototypes to productiondue to the difficulties in scaling AI projects. CIOs and IT leaders face many obstacles in creating and managing a production-grade AI pipeline. Building in-house AI capabilities requires substantial investment and expertise, and developing and testing AI models takes considerable time before final deployment. Additionally, finding AI engineers, data analysts, and computer vision experts can be a challenge. Even if the team and infrastructure are in place, training high-performing AI models can be difficult due to the large amount of data labeling required, particularly for edge cases.
Deep Block delivers aproduction-grade AI pipeline that facilitates the deployment of high-performing Machine Learning models (MLOps) in days instead of months. On top of a library of pre-trained models, AI experts and amateurs alike can train and use their own computer vision algorithms, without any coding knowledge required.