ETRI releases no-code machine learning development tools

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 announced that it has 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 6th, 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.

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.

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.

During the development of TANGO, 24 domestic and international patents are invented, 3 NeurIPS papers and 13 SCI papers are published, 4 technology transfers and KRW 10 billion in commercialization revenue are resulted.

The autonomous maritime navigation solution company, Avenotics, has been selected for the “Public Research Outcome Expansion and Commercialization Project” supported by the Ministry of Science and ICT, which aims to commercialize excellent research results from government-funded research institutes through Tango technology transfer, and received an investment of 1.3 billion won (corporate value of 9.8 billion won) from Korea Science and Technology Holdings (500 million won), Korea Credit Guarantee Fund (500 million won), and Low Partners (300 million won).

Through technology transfer, Avenotics has secured Tango on-device deployment technology and AI performance optimization technology, and is currently commercializing on-device AI that automatically generates contextual information required by navigators.

The research team is focusing on wider adoption by carrying out pilot demonstrations led by its partner research institutions.

The collaborative research institution, Weda Co., Ltd., has developed an artificial intelligence service that can be utilized by on-site employees, targeting two companies in the fields of steel and automotive parts manufacturing. Specifically, the service was developed for vision-based exterior inspection of more complex shapes, such as automotive bumper rolls.

The collaborative research institution, Lablup Inc., collaborated with KT Cloud to launch a deployment optimization service supporting Rebellion’s latest domestic AI acceleration engine, ATOM-Max. They also commercialized a GPU cloud rental service in collaboration with KT.

Seoul National University Hospital is developing artificial intelligence technology that utilizes large-scale chest CT images and diagnostic data to automatically generate diagnostic reports from CT images. The developed technology will be demonstrated in four hospitals, including Seoul National University Hospital (Seoul National University Hospital, Seoul National University Bundang Hospital, Seoul National University Hospital Gangnam Center, and Boramae Hospital), to provide a cardiopulmonary disease prediction service, and will be evaluated and verified through actual clinical data.

In particular, the LLMOps tool, which supports generative AI development, is being developed for immediate commercialization through collaboration with Acryl Inc. The source code for Acryl’s commercial product, Jonathan, is fully open on GitHub, and core algorithms are being added, and a standard operating environment for industry-specific generative AI applications is being established simultaneously.

Kim Tae-ho, Software PM of the Institute of Information & Communications Technology Planning & Evaluation (IITP), stated, “TANGO technology is truly the best open source project in Korea and is contributing greatly to enhancing the competitiveness of the domestic software industry in the field of artificial intelligence development tools.”

Jo Chang Sik, Principal Researcher of ETRI, said, “We plan to expand the existing Tango project, which utilizes vision neural networks, into the field of LLMOps tools that support generative AI. Even in the future, we will share all of our development expertise and provide solutions that can be directly commercialized by the industry through verification.”

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.

1) Machine Learning Operations (MLOps): MLOps is an abbreviation for Machine Learning Operations, and is a technology and tool for managing the life cycle of machine learning, including data preprocessing, model development, deployment, and operation.

2) No-code: A development approach that enables faster and more accurate application development with a user-friendly interface for those with insufficient coding experience

3) GitHub address: https://github.com/ML-TANGO/TANGO

4) TANGO: TANGO (Target Aware No-code neural network Generation and Operation framework)

5) Kubernetes On-Premise Environment: This refers to an environment in which factories, hospitals, etc., operate their own servers or data centers instead of a cloud environment for security reasons. This means deploying and managing Kubernetes on their own physical infrastructure (servers, networks, etc.) without using the infrastructure of an external service provider. Kubernetes is an open-source system for deploying and managing containerized applications.

6) Data Labeling: The process of identifying and annotating data to train a machine learning or artificial intelligence (AI) model, helping the learning model understand and predict the data For example, to train an image recognition model, descriptions (labels) of objects in a photo (e.g., cat, dog, car, etc.) are added.

7) LLMOps: LLMOps is an abbreviation for LLM Operations, and is a technology and tool for managing the life cycle of large language model (LLM) training, including data preparation, training, tuning, deployment, and operation.

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This achievement was developed with support from the Ministry of Science and ICT and the Institute of Information & Communications Technology Planning & Evaluation (IITP) through the “Automatic Generation of Neural Network Applications and Optimization of Execution Environment” and “Generative AI Support System SW Framework” projects.

About Electronics and Telecommunications Research Institute (ETRI)

ETRI is a non-profit government-funded research institute. Since its foundation in 1976, ETRI, a global ICT research institute, has been making its immense effort to provide Korea a remarkable growth in the field of ICT industry. ETRI delivers Korea as one of the top ICT nations in the World, by unceasingly developing world’s first and best technologies.