Announcement • Jun 13
Nota Ai Has Two Moe Quantization Papers Accepted At Icml 2026 Workshop Nota AI announced that two of its papers on MoE-specific quantization algorithms have been accepted to the Resource-Adaptive Foundation Model Inference (AdaptFM) Workshop at ICML 2026. The AdaptFM Workshop focuses on technologies that enable large-scale AI models to run efficiently under limited computing resources. This achievement is significant as it recognizes Nota AI's accumulated technical expertise in optimizing Mixture-of-Experts (MoE) models, an architecture increasingly regarded as a core structure for large language models (LLMs). MoE models improve both performance and efficiency by activating only a subset of expert models as needed. However, their complex structure requires a different approach to quantization, the process of making models smaller and more efficient, compared to conventional model architectures. Nota AI previously won both its track and the overall competition at the NVIDIA Nemotron Hackathon with a data-driven MoE quantization method. With the acceptance of these two papers, Nota AI will once again present research outcomes specifically designed for MoE architectures on a global research stage. The first accepted paper, "DREAM-MoE," proposes a method to reduce changes in a model's decision flow that can occur when large-scale AI models are quantized across multiple segments. The method focuses on the fact that even a small error in an earlier segment can affect expert selection in later segments. DREAM-MoE helps the quantized model select experts in a way that remains closer to the original model. The second paper, "SRA-MoE," proposes a method that identifies and prioritizes important inputs that have a greater impact on the model's final output. Rather than treating all inputs equally, SRA-MoE is designed to prevent expert selection from being significantly disrupted for these key inputs, helping maintain model quality more effectively under limited resources. Both studies demonstrated higher performance compared to the latest MoE-specific quantization methods. This shows that large-scale AI models can be executed with less memory and fewer computing resources while reducing quality degradation. Nota AI has been proactively focusing its R&D efforts on optimizing large AI models that require substantial memory and computing resources. The company is advancing large-scale model optimization, including Solar MoE, as part of the sovereign foundation model project led by the Upstage consortium. It is also expanding its experience in quantizing NVIDIA Nemotron 3 Nano to newer large models such as Nemotron Ultra, further broadening the scope of its optimization technologies. In addition, Nota AI will host "Nota AI - Korea Efficient Days" during ICML 2026 at COEX in Seoul. The event will bring together global researchers, engineers, and business leaders visiting Korea to share research trends and industrial applications of Efficient AI. Through the event, Nota AI plans to introduce its research achievements in large-scale AI model optimization and expand opportunities for technical collaboration and business engagement. New Risk • Jun 06
New major risk - Share price stability The company's share price has been highly volatile over the past 3 months. It is more volatile than 90% of South Korean stocks, typically moving 16% a week. This is considered a major risk. Share price volatility increases the risk of potential losses in the short-term as the stock tends to have larger drops in price more frequently than other stocks. It may also indicate the stock is highly sensitive to market conditions or economic conditions rather than being sensitive to its own business performance, which may also be inconsistent. This is currently the only risk that has been identified for the company. Reported Earnings • May 21
First quarter 2026 earnings released: ₩188 loss per share (vs ₩573 loss in 1Q 2025) First quarter 2026 results: ₩188 loss per share (improved from ₩573 loss in 1Q 2025). Revenue: ₩3.58b (up ₩3.52b from 1Q 2025). Net loss: ₩4.02b (loss narrowed 29% from 1Q 2025). Revenue is forecast to grow 30% p.a. on average during the next 3 years, compared to a 16% growth forecast for the Software industry in South Korea. 
