January 2, 2026 by National Research Council of Science and Technology
Collected at: https://techxplore.com/news/2026-01-code-machine-tools.html
Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited AI expertise in industrial fields such as factories, medical, and shipbuilding, providing them with a significant boost.
ETRI has now released the core technology of MLOps tool, which automatically generates neural networks based on no-code and automates the deployment process, as open source on GitHub.
On November 6, 2025, the research team held the 4th public seminar to expand the TANGO GitHub community at the Science and Technology Center in Gangnam-gu, Seoul. The TANGO framework is a technology that automatically develops application software (SW) in which artificial intelligence is applied and optimally deploys it to various target hardware (HW) environments, such as cloud, Kubernetes on-premise environments, and on-device.
Challenges in applying AI to industry
For example, while it’s easy to determine whether steel data is defective during quality inspections at a steel mill, applying AI was not easy. In a hospital, it is easy for doctors to diagnose tuberculosis just by looking at an X-ray image, but it has been difficult to utilize an AI-based automatic prediction model.
The TANGO framework developed by ETRI is well suited to neural network processing tasks for domain experts who lack extensive neural network knowledge. It is also easy to use, so it is automatically installed with a simple installation command and can be run immediately through web interface.
Addressing the shortage of AI specialists
In the existing method of developing AI application software, domain experts were responsible for data labeling, while software developers handled the development and learning of artificial intelligence models and the installation and execution of application SW.
However, with the expansion of artificial intelligence (AI) technology, the demand for software (SW) in all industries is increasing. On the other hand, there is a shortage of AI and SW specialists to meet this demand.
To address such issues, ETRI has developed the neural network automation algorithm optimized for object recognition, reflecting the demands of domestic industrial sites, and has officially unveiled it. ETRI also released LLMOps tools that support the development of generative AI.
The research team stated that they will continue to release new versions of the source code on GitHub every six months. They also plan to hold a public seminar once a year in the second half of the year to share not only the technology development source code but also practical expertise. Meanwhile, a total of 944 people from 552 institutions participated in the Tango public seminar over four sessions, sharing insights into AI technology.
More information: On GitHub: github.com/ML-TANGO/TANGO
Leave a Reply