Introduction: Unconventional Collective Intelligence

• Levin discusses collective intelligence beyond traditional brains, focusing on cells, tissues, and unconventional organisms.
• Turing’s interest in both AI and morphogenesis (shape formation) suggests a deep connection between intelligence and biological development.
• The transition of an oocyte “just physics”, into a cognitively-aware, is amazing.
• Transition. Nested intelligence where lower structres contribute with their behaviors to reach the goal/attractor state.

Key Concepts: Multi-Scale Competency and Navigation

• Biology uses a “multi-scale competency architecture” where nested problem-solvers (cells, tissues, organs) operate at different levels.
• “Navigation” of spaces (physical, physiological, morphogenetic) is a central concept for understanding biological intelligence.
• Goal-directedness is critical for recognizing and interacting with diverse “agents,” including unconventional ones. Goal can simply mean, in this context, attractor.
• Cognitive Light Cone – bounds what can/could be percieved given sensory data limits.
• A “cognitive boundary model” helps understand how goals scale in biological systems.

Bioelectricity and Morphogenesis: A Specific Example

• Biological pattern formation (how organisms get their shape) is the behavior of a “collective intelligence” of cells in “morphospace” (the space of possible anatomical forms).
• Bioelectrical networks (using ion channels and gap junctions) are a “proto-cognitive medium,” an evolutionary ancestor of brain function.
• Bioelectrical signals are not just for brains; all cells have ion channels and communicate electrically, allowing them to navigate morphospace.
• Homeostasis and its ability to react/regenerate is based on bioelectric communication between the various components and organizational level structures.
• Top down influece can and will trump genetic information if there is a homeostatic trigger, for example, cancer being removed due to electric influence and cellular communcation between healthy and canerous cells.

Practical Implications: Bio-medicine and Synthetic Bioengineering

• Understanding bioelectrical control has implications for regenerative medicine (e.g., limb regeneration) and birth defect repair.
• “Electroceuticals” (drugs targeting ion channels) could be designed to guide cells to correct anatomical outcomes. The cells talk and can direct others towards building/changing something based on an end-goal it may have.
• Synthetic bioengineering opens a vast “option space” for new bodies and minds without traditional evolutionary constraints.

Examples of Morphogenetic Intelligence and Plasticity

• The collective’s components will “remember”, such that it has the ability to recall and “do” the previous goal.
• Slime mold (Physarum): A single-celled organism that navigates its environment using vibrations, showing problem-solving in physical space.
• Planaria: Flatworms that regenerate any body part, demonstrating memory of body plan (stored bioelectrically) and adaptability.
• Planaria are not limited to its default body type/genetics. One of the reasons for regeneration is it can use feedback mechanisms from others, especially from a top-down influence/heirarchical manner.
• Homeostatic error minimizing, or simply, error minimizing is a good strategy when resources are limited, but still allowing complex things like organ formation, from imperfect/unknown/variable components/ingredients.
• Frog tadpoles with misplaced eyes: Demonstrate that the brain can adapt to novel sensory inputs without evolutionary pre-programming.
• Picasso tadpoles: Tadpoles with scrambled facial features that still develop into largely normal frogs, demonstrating error-minimization in morphospace.
• Axolotl limb regeneration. They continue regeneration and will keep attempting to do work “until” they get there.
• Nephron example. Nephrons will adapt and change its form and function such that its final outcome will result from top-down influence, especially during stress/pressure.
• Xenobots, in the process, create children xenobots that keep repeating the processes, in which are not observed previously in its normal context, in frog. It may continue to develop. The limit to cognitize potential in this new structure, xenobot, are still under works.
• Xenobots: Synthetic organisms made from frog skin cells that self-organize and exhibit novel behaviors (movement, self-replication), showing unexpected plasticity.

Scaling of Cognition and Implications

• Goal directed behavior – collective/lower cells “listen” to and communicate based on end goal/error detection/homeostatic signal that occurs at all organizational/hierarchical layers.
• Higher structure(s) direct smaller levels, this influence, is top-down and may use strategies like, bending/re-directing its paths to reduce the “energy” of “work” from lower levels in completing its goal/achieve homeostatic state.
• The boundary between “self” and “world” is flexible; cells can cooperate to form larger collectives with scaled-up goals, or defect (as in cancer) to pursue smaller goals.
• A “cognitive light cone” framework allows comparing diverse intelligences based on the scale of their goals in space and time.
• Endless beautiful forms due to a combination of intelligence, evolution, environment and a ton of other variables can arise in ways beyond human comprehention.

Ethical and Philosophical Considerations

• Understanding this allows one to reframe our assumptions about agency/cognition in biological and technological systems, with applications towards building machines that emulate this emergent complexity.
• We will likely encounter diverse biological and artificial agents that challenge traditional categories of life and intelligence.
• Existing frameworks in ethical and philosophical ways won’t cut it, and we need new ones, especially as technology becomes increasingly involved in influencing what life becomes in a broader biological, philosophical sense.
• Existing tools of Neuroscienc, can and often do, translate into cell research. For example, many/some cells contain “memories”, including “counter-factual memory.”

导言：非传统的集体智慧

• 莱文讨论了超越传统大脑的集体智慧，重点关注细胞、组织和非传统生物体。
• 图灵对人工智能和形态发生（形态形成）的兴趣表明了智力与生物发育之间的深层联系。
• 卵母细胞从“纯粹物理”转变为具有认知意识的过程，令人惊叹。
• 嵌套的智慧之转变。其中较低层次的结构通过其行为来促成实现目标/吸引子状态。

关键概念：多尺度能力和导航

• 生物学采用“多尺度能力架构”，其中嵌套的问题解决者（细胞、组织、器官）在不同层次上运作。
• “导航”空间（物理空间、生理空间、形态发生空间）是理解生物智能的核心概念。
• 目标导向性对于识别和与各种“主体”（包括非传统主体）互动至关重要。在这种语境下，目标可以简单地指代吸引子。
• 认知光锥 —— 界定了在给定感官数据限制下能够/可能感知到的范围。
• “认知边界模型”有助于理解生物系统中的目标如何扩展。

生物电和形态发生：一个具体例子

• 生物模式形成（生物体如何获得其形状）是细胞在“形态空间”（可能的解剖形式空间）中的“集体智慧”的行为。
• 生物电网络（使用离子通道和间隙连接）是一种“原认知媒介”，是大脑功能的进化祖先。
• 生物电信号不仅仅用于大脑；所有细胞都有离子通道并进行电通信，使它们能够在形态空间中导航。
• 体内稳态及其反应/再生能力基于各个组成部分和组织层次结构之间的生物电通信。
• 如果有稳态触发，自上而下的影响可以并且将会胜过遗传信息，例如，由于电影响和健康细胞与癌细胞之间的细胞通讯，癌症被消除。

实际意义：生物医学和合成生物工程

• 理解生物电控制对再生医学（例如，肢体再生）和出生缺陷修复具有意义。
• 可以设计“电疗法”（靶向离子通道的药物）来指导细胞达到正确的解剖结果。细胞之间会沟通并可以指导其它细胞为了其最终目标来做建造或变更。
• 合成生物工程为没有传统进化约束的新身体和思维开辟了广阔的“选项空间”。

形态发生智能和可塑性的例子

• 群体的组成部分将“记住”，使其能够回忆和“执行”先前的目标。
• 黏菌（多头绒泡菌）：一种单细胞生物体，利用振动在其环境中导航，显示出在物理空间中解决问题的能力。
• 涡虫：可以再生任何身体部位的扁虫，展示了身体计划的记忆（以生物电方式存储）和适应性。
• 涡虫不仅限于其默认的身体类型/遗传学。再生的原因之一是它可以利用来自其他方面的反馈机制，尤其是来自自上而下的影响/等级方式。
• 当资源有限时，稳态误差最小化，或者简单地说，误差最小化是一个很好的策略，但仍然允许复杂的事件如器官形成,来自那些不完美、未知数，或善变的因素。
• 眼睛错位的青蛙蝌蚪：表明大脑可以在没有进化预编程的情况下适应新的感觉输入。
• 毕加索蝌蚪：面部特征混乱的蝌蚪仍然发育成基本正常的青蛙，表明了在形态空间中的误差最小化。
• 蝾螈肢体再生。它们持续再生，并将不断尝试工作“直到”达到目标。
• 肾单位示例。肾单位将调整并改变其形式和功能，以使其最终结果来自自上而下的影响，尤其是在压力下。
• 异种机器人在这个过程中，创造了孩子异种机器人不断重复这些过程，而这过程在其正常的、青蛙的环境里是不曾观察到的。这个东西还有发展空间。针对此新的构造体的潜质仍处于积极探索状态。
• 异种机器人：由青蛙皮肤细胞制成的合成生物体，可以自组织并表现出新的行为（运动、自我复制），显示出意想不到的可塑性。

认知的扩展和影响

• 目标导向行为 —— 集体/下层细胞“倾听”并根据发生在所有组织/层级层次上的最终目标/错误检测/稳态信号进行通信。
• 较高结构指导较低层次，这种影响是自上而下的，并且可以使用诸如弯曲/重定向其路径之类的策略，以减少较低层次完成其目标/实现稳态的“工作”“能量”。
• “自我”和“世界”之间的界限是灵活的；细胞可以合作形成具有扩大目标的更大集体，或者背叛（如在癌症中）以追求更小的目标。
• “认知光锥”框架允许根据不同智能在空间和时间上的目标规模来比较它们。
• 由于智能、进化、环境和大量其他变量的结合，产生了无数美丽的形式，其方式超出了人类的理解能力。

伦理和哲学考虑

• 理解这一点使人们能够重新构建我们对生物和技术系统中的自主性/认知的假设，并将其应用于构建模拟这种涌现复杂性的机器。
• 我们可能会遇到各种各样的生物和人工主体，它们挑战传统的生命和智能类别。
• 现有的伦理和哲学框架是不够的，我们需要新的框架，尤其是在技术越来越深入地影响生命在更广泛的生物学和哲学意义上变成什么样子的情况下。
• 神经科学的现有工具可以并且经常可以转化为细胞研究。例如，许多/一些细胞包含“记忆”，包括“反事实记忆”。