Core Viewpoint - The article discusses the emergence of AI for Science as a transformative direction in scientific research, highlighting the establishment of companies like Xaira Therapeutics and the initiatives by OpenAI and DeepMind in this field. It emphasizes the potential of AI to accelerate scientific discoveries and the journey of Chinese entrepreneurs Zhang Linfeng and Sun Weijie in founding DeepMind Technology, which focuses on applying AI to scientific research and industrial applications [3][4][5]. Company Background - DeepMind Technology was founded in 2018 by Zhang Linfeng and Sun Weijie, with initial funding of 12 million RMB from a disruptive technology innovation competition, rather than venture capital [4][5]. - Zhang Linfeng developed the Deep Potential Molecular Dynamics (DeePMD) method during his PhD at Princeton, which later won the prestigious Gordon Bell Award [4][5]. Technological Innovation - DeePMD integrates AI to optimize the long-standing issue of solving first-principles calculations, expanding the range of quantum mechanical calculations from hundreds of atoms to billions, thus enabling the discovery of new materials and drugs [5][6]. - The method allows for significant computational efficiency, achieving over six orders of magnitude acceleration, enabling complex simulations that were previously only feasible on supercomputers to be run on standard laptops [21][24]. Vision and Goals - The founders aim to create an open-source system that spans scientific research to industrial development, aspiring to contribute to a shared human destiny [9][30]. - The company has set a goal to become a leading technology firm originating from China, with a vision to influence global scientific research [8][30]. Product Development - DeepMind Technology has launched several platforms, including the Hermite drug design platform and various pre-trained scientific models, serving notable clients such as CATL, BYD, and others [8][30]. - The company’s first product, Hermite, was developed in response to the existing market needs in drug discovery, differentiating itself by incorporating machine learning methods [30][31]. Market Positioning - The founders identified a significant opportunity in the pharmaceutical and materials sectors, where understanding atomic interactions can lead to breakthroughs in drug development and material science [31][32]. - The company aims to build a comprehensive platform that can serve multiple research directions and stages, rather than focusing solely on vertical applications [50][51]. Educational Initiatives - DeepMind Technology emphasizes the importance of cultivating a new generation of interdisciplinary talent, integrating knowledge from physics, chemistry, and engineering to address complex scientific challenges [27][34]. - The company has developed a unique educational framework to train young talents, fostering a community that encourages collaborative learning and innovation [36][37]. Future Directions - The article suggests that the next phase for AI in science will involve the development of AI scientists, capable of autonomously conducting research and integrating various scientific tools [42][44]. - The integration of pre-trained models and multi-agent systems is expected to enhance research efficiency and redefine the roles of researchers in the scientific process [47][49].