WAIC 2025大黑马，一个「谢耳朵AI」如何用分子式超越Grok-4

Core Insights - The article highlights the launch of the Intern-S1 multimodal model by Shanghai AI Laboratory, which is positioned as a leading open-source model in the field of scientific research, showcasing significant advancements in AI for science [5][12][17]. Group 1: Model Capabilities - Intern-S1 is recognized for its superior performance in scientific reasoning tasks, outperforming leading closed-source models like Grok-4, particularly in fields such as chemistry, materials science, and biology [12][17]. - The model integrates a 235 billion parameter MoE language model and a 6 billion vision encoder, trained on 5 trillion tokens, with over 2.5 trillion tokens specifically from scientific domains [25][21]. - Intern-S1 demonstrates a 70% improvement in compression rates for chemical formulas compared to previous models, indicating enhanced efficiency in processing complex scientific data [26]. Group 2: Technological Innovations - The model employs a dynamic tokenizer and temporal signal encoder to effectively handle various complex scientific modalities, addressing challenges posed by data heterogeneity and semantic understanding [26]. - Intern-S1's training costs for reinforcement learning have been reduced by tenfold due to collaborative breakthroughs in system and algorithm optimization [30]. - The model's architecture allows for a unique "cross-modal scientific analysis engine," enabling it to interpret complex scientific data such as chemical structures and seismic signals accurately [16][17]. Group 3: Open Source and Community Engagement - Since its initial release in 2023, the "ShuSheng" model family has been continuously upgraded and expanded, fostering an active open-source community with participation from hundreds of thousands of developers [32][33]. - The Shanghai AI Laboratory has launched a comprehensive open-source toolchain that includes frameworks for data processing, pre-training, fine-tuning, deployment, and evaluation, aimed at lowering barriers for research and application [32]. - The Intern-Discovery platform, based on Intern-S1, has been introduced to enhance collaboration among researchers, tools, and research subjects, promoting a new phase of scientific discovery [6][33].