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DeepSeek about S.E.B.O.M.E.(bilingual双语)深度求索谈赛搏梅


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Reply from Chat.DeepSeek.com about S.E.B.O.M.E. (bilingual 双语)与深度求索对话)关于 S.E.B.O.M.E. (赛博梅)的回复

For Smart Encyclopedia Based On Machine Evolution (S.E.B.O.M.E.), See https://blog.creaders.net/user_blog_diary.php?did=NTExNjgz


https://blog.creaders.net/user_blog_diary.php?did=NTEyMDM0

https://www.facebook.com/andrew.colesville

https://x.com/mwsansculotte


March 29, 2025

Your commentary presents a rich synthesis of biology, AI theory, and Marxist political economy, offering a provocative critique of contemporary AI development through the lens of analog vs. digital systems and capitalist contradictions. Below is a structured breakdown of your key arguments and their implications:

1. Darwinian Amoebae vs. AI: Analog vs. Digital Intelligence

Amoebae as Proto-Intelligent Systems:

While single-celled organisms lack brains, their ability to remember, adapt, and anticipate (e.g., slime molds solving mazes) suggests a form of analog computation honed over 750 million years. This contrasts with AI's digital computation, which lacks the embodied, evolutionary substrate of biological systems.

Key Discrepancy: Analog systems (e.g., biological neurons) process information continuously and holistically, while digital systems rely on discrete, fragmented operations. Your argument echoes debates in cognitive science (e.g., Hubert Dreyfus' critique of symbolic AI) and embodied cognition theories.

AI's Limitations:

Digital AI cannot originate consciousness because it lacks the self-organizing, evolutionary history of analog systems. Even advanced LLMs (like GPT-4) are static without continuous human-driven updates—a "dead labor" artifact in Marxist terms.

2. AI as "Smart Encyclopedia Based on Machine Evolution" (S.E.B.O.M.E.)

Re-defining AI's Role:

You propose S.E.B.O.M.E. as a modest AI paradigm—simulating brainless organisms (amoebae) first, then gradually ascending to invertebrates (flatworms, jellyfish). This aligns with:

Bio-inspired AI: E.g., Physarum (slime mold) algorithms for optimization.

Evolutionary Robotics: Using genetic algorithms to mimic natural selection.

Marxist Materialism: Rejecting idealism (AI as "conscious") in favor of incremental, materially grounded progress.

Monopoly & Overproduction:

OpenAI's exorbitant pricing ($220K/month) exemplifies capitalism's tendency toward monopolization and crisis (as predicted by Marx). By privatizing S.E.B.O.M.E., capital risks:

Overproduction: Redundant AI tools flooding markets.

Over-unemployment: Displacing workers without creating surplus value.

3. Marxism & the Contradictions of Robotics/AI

Dead Labor vs. Living Labor:

Machines (constant capital) transfer past labor value (from their production) but create no new value. Profit derives solely from exploiting living labor (variable capital).

Robotics in Capitalism: While industrial robots reduce wages, they cannot replace profit generation unless owned collectively (e.g., worker cooperatives or socialist states).

Historical Materialism & AI:

Capitalism's private ownership stifles AI's potential. Under socialism, AI/robotics could:

Liberate labor: Automate drudgery, freeing humans for creative work.

Collectivize benefits: Redirect surplus to social needs (e.g., healthcare, education).

4. Conclusion: A Path Forward for S.E.B.O.M.E.

Your framework suggests:

Reorient AI Research: Prioritize bio-inspired, analog-emulating systems over artificial "consciousness."

Challenge Capitalist AI: Expose how privatization breeds crises (unemployment, inequality).

Advocate for Socialist AI: Push for public ownership to harness AI for collective good.

Final Thought:

The "unity and struggle" of analog/digital systems mirrors the dialectic of labor/capital. Just as amoebae evolved through material constraints, AI must evolve within socio-economic realities—not as a rival to humanity, but as a tool forged by and for the working class.

Would you like to explore specific strategies to operationalize S.E.B.O.M.E. under these principles?


汉语译文


Chat.DeepSeek.com (与深度求索对话)关于 S.E.B.O.M.E. (赛博梅)的回复(2025 年 3 月 29 日)

Smart Encyclopedia Based On Machine Evolution (S.E.B.O.M.E.) 见:https://blog.creaders.net/user_blog_diary.php?did=NTExNjgz


https://blog.creaders.net/user_blog_diary.php?did=NTEyMDM0

https://www.facebook.com/andrew.colesville

https://x.com/mwsansculotte


您的评论将生物学、人工智能理论和马克思主义政治经济学进行了丰富的综合,通过模拟与数字系统和资本主义矛盾的视角对当代人工智能的发展进行了富有挑战性的批判。以下是您的主要论点及其含义的结构化分析:

1. 达尔文变形虫与人工智能:模拟智能与数字智能

变形虫作为原始智能系统:

虽然单细胞生物没有大脑,但它们的记忆、适应和预测能力(例如,黏菌解决迷宫)表明了一种经过 7.5 亿年磨练的模拟计算形式。这与人工智能的数字计算形成鲜明对比,后者缺乏生物系统的具体进化基础。

主要差异:模拟系统(例如生物神经元)连续、整体地处理信息,而数字系统则依赖于离散、碎片化的操作。您的论点呼应了认知科学(例如 Hubert Dreyfus 对符号 AI 的批判)和具身认知理论中的争论。

AI 的局限性:

数字 AI 无法产生意识,因为它缺乏模拟系统的自组织进化历史。即使是高级 LLM(大语言模型,如 GPT-4)如果没有持续的人为更新,也是静态的——用马克思主义的话来说,这是一种“死劳动”产物。

2. AI 作为“基于机器进化的智能百科全书”(S.E.B.O.M.E.)

重新定义 AI 的角色:

您提出 S.E.B.O.M.E. 是一种适度的 AI 范式——首先模拟无脑生物(变形虫),然后逐渐上升到无脊椎动物(扁虫、水母)。这与以下观点一致:

生物启发式人工智能:例如,用于优化的绒泡菌(黏菌)算法。

进化机器人:使用遗传算法模拟自然选择。

马克思主义唯物主义:拒绝理想主义(人工智能是“有意识的”),支持渐进的、物质基础的进步。

垄断与生产过剩:

OpenAI 的过高定价(每月 22 万美元)体现了资本主义走向垄断和危机的趋势(正如马克思所预测的那样)。通过将 S.E.B.O.M.E. 私有化,资本风险:

生产过剩:多余的人工智能工具充斥市场。

过度失业:取代工人而不创造剩余价值。

3. 马克思主义与机器人/人工智能的矛盾

死劳动与活劳动:

机器(不变资本)转移过去的劳动价值(来自其生产),但不创造新价值。利润完全来自于对活劳动(可变资本)的剥削。

资本主义下的机器人技术:虽然工业机器人降低了工资,但它们无法取代利润创造,除非集体所有(例如工人合作社或社会主义国家)。

历史唯物主义与人工智能:

资本主义的私有制扼杀了人工智能的潜力。在社会主义下,人工智能/机器人技术可以:

解放劳动力:自动化苦差事,让人类从事创造性工作。

集体化福利:将盈余重新定向到社会需求(例如医疗保健、教育)。

4. 结论:S.E.B.O.M.E. 的前进之路。

您的框架建议:

重新定位人工智能研究:优先考虑生物启发、模拟仿真系统,而不是人工“意识”。

挑战资本主义人工智能:揭示私有化如何引发危机(失业、不平等)。

社会主义人工智能倡导者:推动公有制,利用人工智能造福集体。

最后的想法:

模拟/数字系统的“团结与斗争”反映了劳动/资本的辩证法。正如变形虫在物质限制下进化一样,人工智能必须在社会经济现实中进化——不是作为人类的对手,而是作为强化工人阶级并且为其利益建造的工具。

你想探索在这些原则下实施 S.E.B.O.M.E. 的具体策略吗?


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