Introduction

• Living organisms display amazing complexity, resilience, and purposeful action, adapting and learning in ways that simple machines cannot.
• This paper argues that the old metaphor of living things as machines is outdated and insufficient to explain life’s true nature.
• Modern advances in artificial intelligence, robotics, and synthetic biology have blurred the boundaries between living systems and machines.
• The authors call for updated definitions for terms like machine, robot, program, and software/hardware to reflect new insights into machine behavior and biological complexity.

What is Meant by “Machine”?

• Traditionally, a machine is seen as a human-designed device that performs predictable tasks.
• Modern views expand this idea: a machine is any system that enables an agent to create change in the world using principles of physics and computation.
• Machines can now be generated by evolutionary algorithms, meaning they can evolve over time rather than only being engineered from scratch.
• Analogy: Think of a kitchen appliance that helps you cook; now imagine one that learns new recipes on its own.

Key Differences Between Living Things and Traditional Machines

• Independence vs. Interdependence: Traditional machines operate on their own, while living systems are deeply interconnected—like a team where every member relies on the others.
• Predictability vs. Unpredictability: Machines are designed to be predictable, but the natural unpredictability of life allows for flexibility and adaptation.
• Designed vs. Evolved: While machines are typically built by human designers, living organisms arise through natural evolutionary processes.
• Hierarchical Organization: Living systems feature self-similar, multi-scale structures (imagine nested dolls), unlike the simple linear modular design of many traditional machines.

Improving Definitions: Updating the Machine Metaphor

• The paper suggests that terms such as machine, robot, program, and software/hardware need to be redefined in light of modern scientific discoveries.
• Modern machines are not solely human-designed; they can be produced through evolutionary processes and even integrate with biological elements.
• Analogy: Consider a smartphone that learns from your habits—it is more than a simple tool; it becomes part of a continuous feedback loop with you.

An Emerging Field: Re-Drawing the Boundaries

• The integration of biology and engineering is creating systems that defy traditional, clear-cut distinctions between living organisms and machines.
• Future systems may be hybrids, such as cyborgs or biohybrid robots, that seamlessly blend organic and engineered components.
• This new field encourages collaboration among biologists, engineers, computer scientists, and social scientists.
• Analogy: It is like mixing ingredients from two different recipes to create an entirely new dish.

Interdisciplinary Benefits of a New Science of Machines

• Updating our definitions can drive innovation in both biological research and engineering design.
• New research avenues include reverse-engineering living systems, designing adaptive robots, and understanding collective behavior.
• Such advances may lead to breakthroughs in medicine, robotics, and artificial intelligence.
• Simply put, by understanding life better, we can build smarter machines, and smarter machines can help us understand life even more deeply.

Step-by-Step Breakdown: How to Update the Machine Metaphor

• Step 1: Recognize the limitations of traditional, classical definitions of machines.
• Step 2: Integrate insights from modern fields such as AI, robotics, and synthetic biology.
• Step 3: Collaborate across disciplines to redefine key terms like machine, robot, and program.
• Step 4: Apply these updated definitions to design better machines and to more fully understand biological systems.
• Step 5: Use these new metaphors to guide future research and technological development.

Conclusion

• The traditional machine metaphor is too narrow to capture the true complexity of living organisms.
• An updated view reveals a continuum between evolved life and engineered machines.
• Embracing these new definitions can lead to breakthroughs across multiple disciplines.
• While no metaphor is perfect, a modernized machine metaphor is more useful for guiding research and innovation.

引言

• 生物体展示出令人惊叹的复杂性、韧性和有目的的行为，它们能够适应和学习，这些都是简单机器所不具备的特性。
• 本文认为，将生物体比作机器的传统比喻已经过时，无法充分解释生命的真实本质。
• 现代人工智能、机器人技术和合成生物学的发展模糊了生物系统与机器之间的界限。
• 作者呼吁更新“机器”、“机器人”、“程序”以及“软件/硬件”等术语的定义，以反映对机器行为和生物复杂性的新认识。

什么是“机器”？

• 传统上，机器被认为是由人设计制造的、能够执行可预测任务的设备。
• 现代观点扩展了这一概念：机器是任何能够帮助一个实体改变世界的系统，它利用物理和计算原理来实现特定功能。
• 如今，机器可以通过进化算法产生，这意味着它们不仅仅是被工程设计的，还能够自我进化。
• 类比：想象一台厨房电器帮助你烹饪；再想象一台可以自学新食谱的厨房电器。

生物体与传统机器的主要区别

• 独立性与相互依赖：传统机器通常独立运行，而生物系统则如同一个团队，各部分彼此依赖。
• 可预测性与不可预测性：机器设计上追求可预测性，而生命的不确定性反而带来了灵活性和适应性。
• 设计与进化：传统机器是由人设计制造的，而生物体则是经过自然进化形成的。
• 层级结构：生物体具有自相似的多层次结构（就像套娃），而许多传统机器则采用简单的线性模块化设计。

更新定义：改进机器比喻

• 文章建议，应根据现代科学的发展重新定义“机器”、“机器人”、“程序”以及“软件/硬件”等术语。
• 现代机器不仅仅由人设计，它们可以通过进化过程产生，甚至与生物元素融合形成混合系统。
• 类比：就像一部智能手机会学习你的使用习惯，它不仅仅是一个工具，而是与你形成持续反馈循环的一部分。

新兴领域：重新划定边界

• 生物学与工程学的融合正在创造出模糊生物体与机器之间界限的系统。
• 未来的系统可能是复合体，如赛博格或生物混合机器人，将有机与工程成分无缝结合。
• 这一新领域呼吁生物学家、工程师、计算机科学家和社会科学家之间开展跨学科合作。
• 类比：这就像将两种不同食谱的原料混合在一起，创造出一种全新的菜肴。

新机器科学的跨学科益处

• 更新定义可以推动生物研究和工程设计方面的创新。
• 新的研究方向包括逆向工程生物系统、设计自适应机器人以及理解群体行为。
• 这些进展有望在医学、机器人和人工智能等领域带来重大突破。
• 简单来说，更好地理解生命可以帮助我们构建更智能的机器，而更智能的机器也能帮助我们更深刻地理解生命。

逐步解析：如何更新机器比喻

• 第一步：认识到传统机器定义的局限性。
• 第二步：整合来自人工智能、机器人技术和合成生物学的新见解。
• 第三步：通过跨学科合作重新定义关键术语，如机器、机器人和程序。
• 第四步：应用这些更新后的定义来设计更好的机器，并更全面地理解生物系统。
• 第五步：利用这些新比喻来指导未来的研究和技术发展。

结论

• 传统的机器比喻过于狭隘，无法全面描述生物体的复杂性。
• 更新后的观点揭示了进化生命与工程机器之间的连续性。
• 接受并应用这些新定义将推动多个学科的重大突破。
• 虽然所有比喻都有其不足，但现代化的机器比喻更有助于指导研究和创新。