大多数人认为AI应该追求超越人类认知速度的能力，但作者质疑了这一基本假设。通过指出人类思维的速度限制，作者暗示AI发展可能不应盲目追求速度，而应关注其他方面，这与当前AI行业追求更高计算能力的普遍趋势相悖。

大多数人认为AI应该追求超越人类速度和能力的计算，但这一评论提出了一个颠覆性的问题：我们是否应该重新思考AI的目标？也许真正的人工智能不在于速度，而在于效仿人类思维的本质特征。这与当前追求更快、更强AI的主流观点形成鲜明对比。

大多数人认为'世界模型'是一个明确的概念，但作者认为它从来不是单一的东西，而是不同领域根据各自需求构建的不同投影。这一观点挑战了AI领域对'世界模型'的统一期望，暗示我们需要接受多元而非单一的模型理解。

在AI医疗领域，大多数公司选择与医生合作或复制医生经验，而王小川提出'造医生'而非'复制医生'的理念，强调以患者为中心而非医生权威。这一立场挑战了医疗AI行业普遍的'医生中心'模式，提出了一个与主流医疗AI发展路径不同的非共识观点。

How does the UST's TeachOnline office aligns (or not) with the contents of this encyclical.

In alignment with our Catholic University's mission of goodness, knowledge and discipline; first, we've worked very hard to understand how artificial intelligence works, the best approach for artificial intelligence and, what it can and cannot do. As instructional designers we have an ethical and moral code to do no harm to our students; the creation or purveying of false information would be a moral and intellectual harm; so, to the best of our abilities, we seek to only generate accurate and factual information with artificial intelligence tools. We do this by using existing documents, meeting transcripts, and other human-generated artifacts as part of context engineering for the prompts we are creating.

Additionally, on the topic of goodness, and in alignment with the ethical quandaries of using artificial intelligence tools that can be connected to "long chain of mediation, involving vast networks of natural resources, energy infrastructure, and above all people". That is, tools that are known to be exploitative to the environment and hurt neighboring people, –specially marginalized communities– (xAI/Grok), disregard the subsidiarity of local communities (Meta AI), and known for harming adult and children with its ability to convince them of false and violent informaton (ChatGPT); our chosen tools are Anthropic's Claude Sonnet and Opus models. That isn't to say that Anthropic is guiltless. However, it continues to stand above all other companies as being the most ethical and conscientious artificial intelligence lab – although that is not saying much, Claude has been used as a hacking tool, and it was used in Pentagon for weapon and operation planning; prior to its designation as a national security risk, ironically because they sought to enact a "red line" (that is disarm) on their AI being used on weapon systems and mass surveillance.

As educators and instructional designers, we welcome the challenge to rethink "the organization of schools, physical spaces, evaluation methods and the role of teachers themselves... promote an authentically integral education that addresses every dimension of the person." To do this, we follow our scientific and ethical practices of our profession in the development of courses that have measurable outcomes, accurate, engaging, collaborative, applicable to real life, that hopefully lead to reflection and contemplation. Additionally, our role as educators helps "disarm" AI from its worst possible uses, and we can further assist by beating "swords into ploughshares" by helping our students understand the ethical and moral boundaries of any technological use and implement it in ways that aid humanity. We respect that our faculty engage in the work of Nehemiah, by helping to build the wall of Jerusalem; by engaging in one of the most charitable acts in humanity, that of giving away and imparting their knowledge unto the future generation.

WIP!!!!

大多数人将AI视为需要驯服的工具，但作者将其比作野生的马，暗示AI本质上是一种无法完全控制的自然力量。这种比喻挑战了AI作为完全可控工具的主流认知，暗示我们需要接受其不可预测性。

这一观点挑战了'人工智能'的术语本身，提出'集体智能'可能是更准确的描述。LLM实际上是数百万人的集体知识产物，这一反直觉的视角揭示了AI与人类创造力之间的复杂关系，挑战了AI作为独立实体的传统理解。

大多数人认为大型语言模型通过学习物理世界的知识来理解现实，但作者认为LLMs实际上只是学习了关于现实的文本统计分布，而非对现实本身的直接理解。这一观点挑战了人们对LLM能力本质的认知，暗示当前AI系统存在根本性的理解缺陷。

大多数人认为社交媒体平台会严格限制第三方自动化操作以防止滥用，但作者指出xAI全面开放了MCP协议支持，允许AI Agent直接执行各种操作，这与主流平台的封闭趋势形成鲜明对比。

• The author identifies two primary personality traits: "The Builder" (focused on velocity, utility, and shipping) and "The Thinker" (needing deep, prolonged mental struggle).
• "Thinking hard" is defined as sitting with a difficult problem for days or weeks to find a creative solution without external help.
• In university, the author realized this ability to chew on complex physics problems was their "superpower," providing a level of confidence that they could solve anything given enough time.
• Software engineering was initially gratifying because it balanced both traits, but the rise of AI and "vibe coding" has tilted the scale heavily toward the Builder.
• While AI enables the creation of more complex software faster, the author feels they are no longer growing as an engineer because they are "starving the Thinker."
• The lack of struggle leads to a feeling of being stuck, as the dopamine of a successful deploy cannot replace the satisfaction of deep technical pondering.

Hacker News Discussion

• The loss of the "clayship" process: Commenters compared coding to working with clay; skipping the struggle means missing the intimacy with the material that reveals its limits and potential.
• The "Vending Machine" effect: Receiving a "baked and glazed" artifact from AI removes the human element of discovery and learning.
• Risk of mediocrity: There is concern that AI guides developers toward "average" or conventional solutions, making it harder to push for unique or innovative ideas without significant manual effort.
• The tradeoff of efficiency: While some view the current era as the best time for "Builders" who just want to see results, many veteran developers feel a profound sense of loss regarding the cognitive depth of the craft.
• Clear communication as a new skill: Some argue that interacting with AI requires a different kind of "thinking hard"—specifically, the need to express creative boundaries clearly so the model doesn't "correct" away the uniqueness of the project.

American Philosophical Society. (2020, June 08). Evidence Symposium. YouTube. https://www.youtube.com/playlist?list=PLoKwLGnyZL4Ds5cQo5muFMg8zKXK4KobH

Kant über künstliche Intelligenz