Computing

A real-world case study of building a complete astronomical observatory notification system in 8 hours using AI assistance. Explores how GPT-4 and Copilot can dramatically boost software engineering productivity across monitoring, server, iOS, and design tasks.

以远程天文台监控系统为例，分享如何在8小时内用AI完成原本需要团队数天的全栈开发。探讨GPT-4和Copilot如何跨越监控端、服务器端、模型训练和iOS客户端提升软件工程效率。

自适应光学入门：大气抖动原理、Seeing Disc和r0参数、波前传感器、镜面校正，以及光场相机和MetaSensor等衍生应用。

总结AI在NLP和计算机视觉领域的三大突破：通用基础模型、生成式模型、会话式UI大幅降低应用门槛，两个领域呈现相似发展趋势。

第三轮迭代：把GPT语音工具封装成Apple快捷指令，构建"点和线"的灵活执行平台，深度集成到手机工作流中。

Third iteration: wrap GPT voice tools into Apple Shortcuts, creating a flexible "points and lines" execution platform that integrates deeply with mobile workflows.

GPT-4加Copilot把一周的NLP任务压缩到十分钟——用自然语言对话实现文本编辑器，连prompt engineering都可以被AI自动化。

GPT-4 and Copilot reduced a week-long NLP task to 10 minutes—building a natural language text editor with JSON output. Even prompt engineering can be automated by AI.

语音速记工具升级为想法迭代系统：GPT不只是转录，还能提出启发性问题、挑战假设，帮助深化思考后再输出，自动导出到Notion。

Evolving a voice transcription tool into an idea iteration system: GPT not just transcribes but asks insightful questions, challenges assumptions, and helps refine thoughts before output.