来源：联想创投 近日，联想创投被投企业「深度原理 Deep Principle」完成超亿元人民币A轮融资。本轮由戈壁创投管理的阿里巴巴创业者基金大湾区基金(简称AEF大湾 区基金)与蚂蚁集团共同领投，现有股东联想创投、Taihill Venture 超额加注，BV百度风投继续加注，多家机构参与。 本轮融资将主要用于三大方向：加速 Agentic AI for Materials Discovery 材料发现智能体 Agent Mira™的研发与升级；推进 L4 高通量自主实验室 AI Materials Factory™与其研发管线的建设与布局；深化与国际和国内头部客户的合作，巩固技术落地领先优势。 顶尖团队驱动模型持续突破 联想集团副总裁、联想创投管理合伙人王光熙表示，联想创投本轮加注深度原理，核心是持续看好 AI for Science 引领的产业变革机遇，更认可深度原理 的技术硬实力与商业化闭环能力。团队以扩散模型与大语言模型的前沿突破为根基，将材料研发从"试错式实验"推向"智能化设计"，凭借显著技术领先 性，成立仅一年便斩获超千万订单，展现了团队将顶尖学术成果向产业解决方案转化的超强效率。其提出的 E ...

Core Insights - The emergence of AI for Science (AI4S) is transforming scientific research by enabling autonomous intelligence in chemistry, moving from "artificial design" to "self-evolving" capabilities [1] - Deep Principles, a startup focused on AI for Chemistry and Materials, has recently completed over 100 million RMB in funding, marking Ant Group's first investment in the AI4S sector [2][14] - The founders of Deep Principles, both MIT PhD graduates, aim to revolutionize the research and development process in materials science by integrating AI with quantum chemistry and high-throughput experimental techniques [4][10] Company Overview - Deep Principles was established in 2024 and focuses on accelerating the entire process of materials innovation by combining AI, quantum chemistry, and high-throughput experiments [4][10] - The company has developed a proprietary Reactive AI platform to address challenges in material chemistry simulations, achieving significant improvements in prediction speed and accuracy [6][10] - Within a year of its establishment, Deep Principles has secured over 10 million RMB in commercial orders, indicating strong market demand for its innovative solutions [10] Technology and Innovation - Deep Principles utilizes diffusion generative models to predict reaction pathways and transition states, significantly reducing computation time from days to mere seconds [6][10] - The company has created a comprehensive product system that integrates various research tools, allowing engineers to automate complex experimental processes and enhance productivity [9][10] - The language model LLM-EO enables researchers to generate new molecular candidates based on natural language inputs, streamlining the hypothesis generation and research design phases [9] Market Context - The AI4S paradigm is gaining traction across multiple scientific disciplines, including chemistry, materials science, and life sciences, driven by the need for interdisciplinary collaboration and innovation [3] - The global investment landscape is increasingly recognizing the potential of AI in scientific research, with significant funding rounds for companies like CuspAI and Periodic Labs, indicating a robust market for AI-driven scientific solutions [13][14] - Deep Principles aims to leverage China's manufacturing strength and large market potential to drive scientific discovery and industrial application, positioning itself strategically in the AI4S landscape [14][15]