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๐Ÿ‡ฐ๐Ÿ‡ท South Korea /Technology

Bdraft and Ourbox sign contract to build logistics-focused LLM and digital twin proof of concept

From Dong-A Ilbo · () Korean

Translated from Korean and summarized by DistantNews. Read the original for the full story.

At a glance

Press release Official statement New plan
  • Bdraft and Ourbox signed a proof-of-concept contract to develop a logistics-focused large language model and a digital twin for the WAVE operations plan.
  • The project will apply their jointly developed Ourbox-31B-JGOS model and Bdraftโ€™s AI optimization technology to logistics operations.
  • Ourbox plans to advance its artificial intelligence transformation strategy under its โ€œTech Firstโ€ initiative.

AI deep-tech company Bdraft and fulfillment provider Ourbox are moving their joint model into logistics operations through a new proof-of-concept project.

The companies said on the 7th that they had signed a contract to introduce a logistics-focused large language model and the โ€œWAVE operations plan digital twin.โ€ They have begun implementing practical functions for the logistics field.

The project expands on the companiesโ€™ jointly developed Ourbox-31B-JGOS model, which ranked highly in the 30B-and-above category of the K-AI leaderboard. Bdraft will apply its AETHER foundation model, model-evolution technology and optimization capabilities demonstrated in a global inference-acceleration competition.

Founded in 2017, Ourbox operates an integrated logistics system called #MATE and handles the full e-commerce fulfillment process through its information network. The company has recently pursued artificial intelligence transformation under its โ€œTech Firstโ€ strategy. The new logistics-focused LLM will support everyday natural-language questions from field staff, along with document-related functions.

About this summary

Originally published by Dong-A Ilbo in Korean. Translated, summarized, and contextualized automatically by DistantNews, with a note on how the source frames the story. Not individually reviewed before publishing. How this works.