Medical publishing is the process of distributing the information and data of medical research in an effective and transparent way. Healthcare providers make use of that information to provide enhanced treatment and care to patients. Medical publishing enhances medical knowledge by filling the gap between research and practice. Publishing the results of medical studies in a medium provides easy access to practitioners. Research scholars and practitioners use these publications to stay connected with both the research community and the industry to maintain a productive and informed cycle of research and development (R and D).

A medical document management system tracks, manages, and stores documents and aids related to medical information leading to the reduction of paper usage. It assists in streamlining the billing process and coordinating the flow of information between laboratories and other departments. It enhances productivity by providing fast access to documents and allowing quick processing with minimum errors.

Scaling Law：实验科学的产物。Scaling Law 指的是大语言模型（LLM） 的最终性能主要与计算量、模型参数量和训练数据量的规模相关，而与模型的具体结构（如层数、深度或宽度）基本无关。随着模型规模、数据量和计算资源的增加，模型的性能会相应提升，并且这种提升呈幂律关系。Scaling Law 是实验科学的产物。2022 年 11 月，ChatGPT 的亮相震惊了业界，标志着大模型的重大突破，Scaling Law 并成为进一步扩展模型规模的核心指导思想。业界普遍认为，只要能够提供更大规模的参数、更多的数据和更强大的计算能力，模型的能力将持续提升，最终可能接近或实现通用人工智能（AGI）。

主流三种私有化部署AI方案：本地部署如裸金属、超融合以及线上部署专属云。对于数据敏感行业（如政府、国企、金融、医疗行业），考虑数据安全高要求，本地部署能规避数据安全风险。专属云泛用性更高，是一种介于公有云和私有云之间的云服务模式。根据测算，私有云AI硬件+软件总市场空间近2000亿元。

2025 年 2 月 18 日，DeepSeek 联手两大机构发布最新论文，研究由 DeepSeek 创始人梁文锋亲自领导，旨在优化 Transformer 注意力机制。论文提出了革命性注意力机制 NSA，NSA 是一种面向硬件且支持原生训练的稀疏注意力机制，专为超快长上下文训练与推理设计。它包含动态分层稀疏策略、粗粒度的 token 压缩和细粒度的 token 选择等核心组成部分，在通用、长文本、思维链推理基准测试中，刷新 SOTA，碾压全注意力。NSA 是对 Transformer 注意力机制的重大优化。

Medical automation refers to the use of technology and machines to perform tasks in the healthcare industry that would traditionally be done manually by healthcare professionals. This technology can streamline processes, increase efficiency, and reduce human error in various aspects of medical care, including diagnosis, treatment, administration, and management. Medical automation can involve a wide range of technologies, from robotic systems to software solutions, and can be applied in hospitals, clinics, and laboratories.

The managed network services market was valued at USD 79.68 billion in 2022, and it is expected to reach USD 149.28 billion by 2028, registering a CAGR of 12.19% during the forecast period (2023-2028). Increasing business process efficiency by cost optimization and high penetration of mobility, cloud computing, and big data technology are some of the major factors driving the market growth.

Machine vision refers to the use of computer-based systems that enable machines to interpret and process visual information, such as images or videos, to perform tasks such as inspection, measurement, and identification. Vision guided robotics (VGR) integrates machine vision with robotic systems, allowing robots to see and respond to their environment in real-time for tasks such as assembly, sorting, and material handling. These technologies are widely used in manufacturing, automation, quality control, and logistics to enhance precision, efficiency, and flexibility.

Location analytics tools analyze the locations or geography components from an enterprises data to generate insights. Enterprises generate data such as transactional data, customer data, and operational data, which contain locations or geographical components. The generated data are visualized using a geographical information system (GIS) system, which provides new dimensions of visual analysis and insights.

The products and services used to assess students' knowledge, skills, and abilities in kindergarten through grade 12 education are included in the global market for K-12 testing and assessment. Standardized testing, formative, adaptive, and diagnostic assessments are all included in this. Demands for accountability, initiatives for personalized learning, and the uptake of technology are some of the factors driving the market.