Winning with 'Data' Not Algorithms… Nota Takes 1st Place Overall at NVIDIA Hackathon - 벤처스퀘어

– 1st place in Track C with synthetic data technology for MoE quantization, overall winner out of 20 teams – Designing datasets with Nemotron-based agents… Presenting a direction for 'data-centric AI optimization' The center of gravity of AI model optimization is shifting from 'algorithms' to 'data'. Nota, a company specializing in AI model lightweighting and optimization technology, announced on the 24th that it took first place in Track C of the NVIDIA Nemotron Hackathon with its synthetic data generation technology specialized in Mixture of Experts (MoE) quantization, and ranked first overall among all participating teams. MoE Quantization Solved Through Data Design This hackathon served as a platform to develop real-world problem-solving AI technologies based on NVIDIA's open-source model 'Nemotron,' and was conducted in three tracks: AI agent development, model enhancement, and synthetic data pipelines. Nota received the highest score in Track C, which deals with dataset construction, and recorded the highest evaluation among all participating teams in the track. Nota's core approach was different from existing ones. While existing quantization technologies have focused on algorithm and formula-centric optimization, Nota minimized performance loss by utilizing a Nemotron 3 Super 120B-based agent to design datasets optimized for the MoE structure. In other words, it amounts to demonstrating a data-centric approach of 'improving performance by changing the data' instead of changing the model. This approach is considered an example demonstrating that the core of AI optimization is expanding from algorithms to data quality and structure design. Based on this achievement, Nota is also expanding its technological collaboration with NVIDIA. It is enhancing real-time anomaly detection and summarization capabilities by integrating NVIDIA's search and summarization tools into its Vision Language Model (VLM)-based image analysis solution, 'NVA (Nota Vision Agent).' Chae Myeong-su, CEO of Nota, stated, “AI optimization is no longer just a matter of algorithms, but rather how to design data that suits the purpose,” adding, “We will advance solutions that can be immediately utilized in actual industrial settings through data-centric AI technology.” You must be logged in to post a comment.