Tech Trends and Mainstream Biases: Lessons from the AI Bubble

Description (English Version) Title: Tech Trends and Mainstream Biases: Lessons from the AI Bubble and a Legacy of Public Interest Inventions Overview: This document provides a critical analysis of the current AI industry, shifting from the "Golden Age of Software" to a hardware-driven era where advanced computing power serves as a "hard currency". Dr. Hung-Chih Lu explores the unsustainable "negative profit loop" within AI large model development and discusses the profound impact of AI on the global workforce, highlighting the disparity between the few winners and the vast majority of workers. Key Themes: The AI Bubble: An examination of why current AI business models resemble a "game of chicken" and the potential risks of a market correction. Shift in Value: The reversal of roles between hardware and software, and the resilience of hard assets over speculative software valuations. Social Impact: A critique of mainstream economic biases regarding the "spillover effect" and the reality of job displacement. A Legacy of Defensive Disclosure: Since 1999, the author has dedicated his career to creating hundreds of inventions—ranging from early Multi-Chip Integrated Silicon Photonics to modern Pixelated Modular Architectural Systems (PMAS)—strictly for the public good. This submission includes evidence of over 30 patents that were intentionally transitioned into the public domain by ceasing maintenance after grant, a strategy now evolved into direct digital disclosure to establish "Prior Art" and prevent private monopolization of essential technologies. Purpose: Inspired by figures like Copernicus and Tesla, this work seeks to challenge mainstream biases and prioritize scientific truth and public interest over commercial gain. 中文敘述 (Chinese Version) 標題: 技術趨勢與主流偏見:AI 泡沫的啟示與公益發明歷程 內容概述: 本文針對當前 AI 產業進行深入批判,分析技術典範如何從「軟體黃金時代」轉向硬體算力作為「硬通貨」的時代 。盧鴻智博士在文中剖析了 AI 大模型開發中不可持續的「負利潤循環」,並討論 AI 對全球勞動力的深遠影響,特別是那被主流論述忽略的 90% 勞動者 。 核心議題: AI 泡沫化分析: 探討為何目前的 AI 商業模式如同「膽小鬼博弈」,以及面臨市場修正的潛在風險 。 價值位移: 軟硬體角色反轉,以及實體資產相對於投機性軟體估值的穩定性 。 社會影響評估: 批判主流經濟學對於「溢出效應」的偏見,並揭示資本集中化下的勞動力現實 。 防禦性公開與公益實踐: 自 1999 年以來,作者致力於研發涵蓋多晶片整合矽光子架構、分散式 AI 機器人以及圖元模組化建築系統(PMAS)等上百項發明,且始終堅持不以營利為目的 。本文件中包含超過 30 件專利的佐證,詳述了作者早期透過「申請後不維護」的方式將技術轉為公共財的策略,以及現今如何利用數位公開建立「先前技術(Prior Art)」來防止技術被私人壟斷的初衷 。 宗旨: 受哥白尼、特斯拉等前輩啟發,作者旨在挑戰主流價值觀,並在商業利益之外,優先考量科學真理與公眾利益 。