ShapeMinds AI:
基于提示工程的汽车造型设计流程优化与应用
ShapeMinds AI:
Automobile Styling Design Process Optimization and Application Based on Prompt Engineering
ShapeMinds 是一款基于 Stable Difusion（文本到图像生 成模型）的 AIGC 汽车造型设计生成平台。ShapeMinds 通 过调研生成式产品的应用痛点，结合 ChatGPT Agent 搭建
ComfyUI 工作流和 InstantMesh， 在设计流程中使用不同精 度的模型和线稿作为生成的引导条件，优化了汽车造型生成流 程的操控性，让设计师成为 AIGC 的主导者；同时引导用户参 与共创，通过组件，快速探索造型。
设计亮点有：
(1) 对于设计师，增强造型生成的可控性，从“抽卡”转变为 保留满意特征的多轮生成；
(2) 组合 InstantMesh、差异扩散（Differential Diffusion）等 技术，实现多视角生成的一致性，利于局部再调整； (3) 以组件化的形式，引导用户参与个性化共创，分析用户喜好。
ShapeMinds is an AIGC automotive styling design generation platform based on stable difusion. By investigating the application pain points of generative products, combined with ChatGPT Agent to build ComfyUI workfow and InstantMesh, models and line drafts of diferent precisions are used as guide conditions for generation in the design process, which optimizes the controllability of the automotive styling generation process and allows designers to become the leaders of AIGC. At the same time, it guides users to participate in cocreation and quickly explore styling through components.
Design highlights include:
(1) For designers, the controllability of styling generation is enhanced, from a “random draw” approach to iterative generation that preserves satisfactory features.
(2) Combining technologies such as InstantMesh and Differential Diffusion to achieve consistency in multiperspective generation, which is conducive to local readjustment.
(3) In the form of components, it guides users to participate in personalized cocreation and analyzes user preferences.
基于 LLM 的企业新人培训工具套件设计
A Design of a Suite of Corporate Newcomer Training Tools Based on a Large Language Model
在现代企业中，新员工的培训有助于员工适应工作环境，熟 悉工作内容，提高劳动生产率，为企业带来利润。然而，目 前部分工作岗位对职业技能要求较高，许多企业新员工的培 训方法还停留在“师徒模式”，这不仅仅影响了新员工的培 训效率，也降低了资深员工的工作效率。随着人工智能技术 的发展，大语言模型在自然语言处理、数据分析和推荐系统 方面的能力也不断提高，这为本项目的实践提供了可能。故 本项目旨在利用大语言来设计实现一个基于大语言模型的企 业新人培训工具套件，通过自动化、标准化的方式培养企业 新人，探索大语言模型在企业新人培训方面的应用潜力。
In modern enterprises, the training of new employees helps employees adapt to the working environment, familiarize themselves with the work content, improve labor productivity, and bring profits for the enterprise. However, at present, some jobs require high vocational skills, and the training method for new employees in many enterprises still stays in the “master and apprentice mode”, which not only affects the training efficiency of new employees, but also reduces the work efficiency of senior employees. With the development of artificial intelligence technology, the ability of Large Language Model in natural language processing, data analysis and recommendation system is also improving, which provides a possibility for the design practice of this project. Therefore, the purpose of this project is to design and implement an enterprise newcomer training tool suite based on Large Language Model using Large Language, to train enterprise newcomers in an automated and standardized way, and to explore the potential of Large Language Model in the application of enterprise newcomer training.
