人工智能时代，人们终将面对一个"意义感"的问题。 我看马斯克已经多次强调过这点了，他认为随着AI+机器人的普及，人类的大多数工作都会被接管，如此一来"工作"就不再是生存的必需，而是个人兴趣的 选择。人类的价值将转向创造性和意义感，而非重复性劳动。 所以，人活着究竟是为了什么？ 我认为这个问题很重要，如果你把它考虑清楚了，那现在很多事大概就不会去做了。要知道人是会死的，在死之前只有短短的几十年时间，从整体来说，有 的事是好的，有的事是坏的，有的事有意义，有的事毫无意义。 比如现在很多人忙于搬运面包屑，为了一点点钱就不择手段，乃至坑蒙拐骗，自欺欺人。还有很多人沉湎于爱恨情仇、是是非非。想一想，百年随手过，万 事转头空。"生命太短暂——它无法承受无休止的恩恩怨怨。"把时间耗费在这些事情上有什么价值呢？ 举个例子，有个人从小被自己长辈贬低，他后来远走他乡，想着有一天衣锦还乡，出一口气，而等他终于回到家乡的时候才发现那个长辈早已是黄土一杯 了。人生百年，众生同归。他心里空落落好难受，看自己一头白发，恍然意识到岁月蹉跎，人生虚度。 大多数人一辈子要么是为了自己的欲望享受，要么是沉迷于儿女情长，或者名利权情，或者望子成龙， ...

Core Viewpoint - The article discusses the insights of Matthew Cobb, a neuroscientist, on the understanding of the brain, the limitations of artificial intelligence, and the implications of relying on AI in decision-making processes [2][4][6]. Summary by Sections Writing "The Idea of the Brain" - Cobb reflects on the initial invitation to write a history of neuroscience, which he found uninspiring until he recognized that the history of the brain is a "history of metaphor evolution" [5]. - He illustrates how perceptions of the brain have changed with technological advancements, from Descartes' hydraulic model to the computer analogy, emphasizing that these metaphors shape scientific understanding [5]. Understanding the Brain - Cobb asserts that humanity fundamentally does not understand how the brain operates, which is a central message of his book [6][7]. - He highlights the complexity of even simple neural systems, such as those in fruit flies, and the lack of understanding regarding human consciousness and the specific neurons involved [8]. Artificial Intelligence Perspective - Cobb identifies himself as part of the "AI skeptics," arguing that while AI is a powerful tool, it does not replicate human consciousness [9]. - He critiques the belief that expanding AI models will lead to human-like intelligence, stating that consciousness cannot emerge from computational systems [9][10]. Decision-Making and AI - The article discusses the potential dangers of relying on AI for decision-making, particularly in contexts where clear rules are absent, such as in general models like ChatGPT [10][11]. - Cobb warns against blind trust in AI-generated content, citing examples of fabricated references and the risks of automated systems leading to significant errors in critical areas like law and finance [12].