National AI model project race heats up as consortia expand new AI partners

Attendees visit Upstage's booth during a presentation for the national artificial intelligence foundation model project at Coex in Seoul, Dec. 30, 2025. Yonhap

The government-led artificial intelligence (AI) foundation model project is intensifying its race as the four consortia in the second-round evaluation bulk up with new specialized partners spanning 3D AI, large language model (LLM) inference chips and high‑end training data.

The Ministry of Science and ICT recently selected a consortium led by Motif Technologies to advance to the project’s second round, filling a vacant slot after only three teams — LG AI Research, SK Telecom and Upstage — moved on from the first round of evaluations in January.

Each consortium is now rushing to bring in partners that boost its technical edge ahead of the next evaluation, evolving a model-building contest into creating a globally competitive sovereign AI stack from models to real-world deployment.

LG AI Research announced on Feb. 25 that AI infrastructure and solutions provider Elice has joined its consortium to help commercialize its model K-EXAONE across public and private sectors.

Elice will leverage its modular data center infrastructure to expose the AI model through stable application programming interfaces (APIs), offering a managed AI platform that lets public agencies and enterprises spin up dedicated environments without operational burden.

The company also plans to deploy the AI model in security‑sensitive sectors such as manufacturing, finance and government, offering cloud‑based services for workflow automation, retrieval-augmented generation (RAG)‑powered search and document-generation tools.

A visitor tries LG AI Research's artificial intelligence (AI) model K-EXAONE during a presentation event for the national AI foundation model project at Coex in Seoul, Dec. 30, 2025. Yonhap

Meanwhile, Upstage is reinforcing its consortium with AI semiconductor startup HyperAccel and physical AI startup RLWRLD.

HyperAccel has been developing an LLM processing unit (LPU) based on its own chip architecture to ease inference bottlenecks, and cut power and operating costs for LLM services. As part of the team, the company plans to further refine LPU design and performance, build inference acceleration optimized for generative AI workloads and roll out a high-availability, full-stack software platform.

"The race in ultralarge AI models is not just about how big they are, but how efficiently you can serve them," HyperAccel CEO Kim Joo-young said. "With LPU-based inference acceleration, we aim to help Korea’s AI infrastructure stand on its own technologically and reach global-level cost competitiveness."

RLWRLD is joining the team to help bridge Upstage’s multimodal AI model, Solar, into real‑world robotics deployment.

The company will define vision‑language model (VLM) requirements for robot control optimization and integration with robotics foundation models and identify commercially viable tasks in hotels, logistics and retail. It will also co‑design detailed validation scenarios and test protocols that translate Solar’s capabilities into robots that can see, understand and act in real‑world settings.

Motif Technologies announced that 3D AI startup N.Light and AI training data platform Crowdworks additionally joined its consortium, which aims to build a 300-billion-parameter LLM and scale it into VLM and vision-language‑action models (VLAs).

N.Light will develop an AI-based 3D data pipeline that turns text or images directly into manufacturable, high-precision 3D computer-aided design models and automatically converts them into formats that simulators can use.

It will also generate large synthetic datasets, collected through simulation, to train VLA models that jointly control vision, language and action, which are essential for physical-AI learning.

Crowdworks is taking the role of core data provider for the team’s AI model to deliver high-quality data. It will focus its core capabilities on building datasets specialized for step‑by‑step reasoning to maximize the model’s capacity for intelligent reasoning.

It will also deploy its proprietary unstructured data preprocessing solution, Alpy Knowledge Compiler, to convert complex documents such as tables and charts into data that AI systems can understand.

Robotics company XYZ also joined the consortium to provide real-world data it has collected through its robots, while also gathering and refining multimodal datasets on human-robot interaction and high-precision manipulation data using its proprietary system.

SK Telecom has not announced any additional members to its consortium since the first round.