What is the prospect of developing artificial general intelligence (AGI)? I
investigate this question by systematically comparing living and algorithmic
systems, with a special focus on the notion of "agency." There are three
fundamental differences to consider: (1) Living systems are autopoietic, that
is, self-manufacturing, and therefore able to set their own intrinsic goals,
while algorithms exist in a computational environment with target functions
that are both provided by an external agent. (2) Living systems are embodied in
the sense that there is no separation between their symbolic and physical
aspects, while algorithms run on computational architectures that maximally
isolate software from hardware. (3) Living systems experience a large world, in
which most problems are ill-defined (and not all definable), while algorithms
exist in a small world, in which all problems are well-defined. These three
differences imply that living and algorithmic systems have very different
capabilities and limitations. In particular, it is extremely unlikely that true
AGI (beyond mere mimicry) can be developed in the current algorithmic framework
of AI research. Consequently, discussions about the proper development and
deployment of algorithmic tools should be shaped around the dangers and
opportunities of current narrow AI, not the extremely unlikely prospect of the
emergence of true agency in artificial systems.

通过系统比较生命和算法系统的不同，着重关注 “代理” 的概念，探讨了发展人工通用智能（AGI）的前景，结果发现与当前的 AI 研究算法框架相比，生命和算法系统存在非常不同的能力和局限性，并特别指出在当前 AI 研究算法框架中极不可能发展真正的 AGI。因此，讨论有关算法工具的正确开发和部署应围绕当前狭窄 AI 的危险和机遇，而不是人工系统中真正产生代理的希望。

人工智能是算法模仿：为什么人工 “智能体” 不是（也永远不会）是合适的代理人

Artificial intelligence is algorithmic mimicry: why artificial "agents"  are not (and won't be) proper agents

Artificial life is a research field studying what processes and properties
define life, based on a multidisciplinary approach spanning the physical,
natural and computational sciences. Artificial life aims to foster a
comprehensive study of life beyond "life as we know it" and towards "life as it
could be", with theoretical, synthetic and empirical models of the fundamental
properties of living systems. While still a relatively young field, artificial
life has flourished as an environment for researchers with different
backgrounds, welcoming ideas and contributions from a wide range of subjects.
Hybrid Life is an attempt to bring attention to some of the most recent
developments within the artificial life community, rooted in more traditional
artificial life studies but looking at new challenges emerging from
interactions with other fields. In particular, Hybrid Life focuses on three
complementary themes: 1) theories of systems and agents, 2) hybrid
augmentation, with augmented architectures combining living and artificial
systems, and 3) hybrid interactions among artificial and biological systems.
After discussing some of the major sources of inspiration for these themes, we
will focus on an overview of the works that appeared in Hybrid Life special
sessions, hosted by the annual Artificial Life Conference between 2018 and
2022.

《Hybrid Life》是一篇关于人工生命研究领域的文章，着重分析了三个主题，分别是系统和代理的理论、生物和人工系统相结合的增强型结构以及生物和人工系统之间的相互作用，同时着重对 2018 年至 2022 年间举办的人工生命会议上出现的文章进行了综述。

混合生命：整合生物、人工和认知系统

Hybrid Life: Integrating Biological, Artificial, and Cognitive Systems

Rubenstein et al. present an interesting system of programmable
self-assembled structure formation using 1000 Kilobot robots. The paper claims
to advance work in artificial swarms similar to capabilities of natural systems
besides being highly robust. However, the system lacks in terms of matching
motility and complex shapes with holes, thereby limiting practical similarity
to self-assembly in living systems.

Rubenstein 等人提出了一种有趣的可编程自组装结构形成的系统，利用 1000 个 Kilobot 机器人。然而，该系统在与具有复杂形状和孔的自然系统相似的运动能力上存在局限性。