这一发现挑战了美国在AI领域的主导地位叙事，暗示全球AI权力格局正在发生根本性转变。这种转变可能对技术标准制定、数据治理和国际AI合作产生深远影响。

这一发现具有地缘政治意义，表明AI领域的权力平衡正在发生重大转变。中美之间的技术竞争从美国单方面领先转变为势均力敌，这可能重塑全球AI治理格局和供应链结构，引发新的国际合作与竞争模式。

这是一个令人警醒的声明，暗示AI技术的控制权已经从公共部门转移到了私人企业手中。作者暗示Anthropic等公司可能已经掌握了具有战略意义的技术，而他们的价值观将直接影响这些技术的使用方向，这挑战了传统的国家主权概念。

全球 AI 算力的 25% 被一家公司独占——这个数字令人震惊。更值得注意的是这个数字的性质：这是「累积持有量」而非「新增采购量」，意味着 Google 多年来的硬件积累已形成近乎垄断性的算力护城河。在 AI 竞赛被描述为「群雄逐鹿」的叙事下，这个数字揭示了真正的权力集中程度。

[[The Means of Production by Maximilian Kasy]] overview in slides by author https://maxkasy.github.io/home/files/slides/meansofprediction_slides_long.pdf

for - progress trap - AI - misuse of power - Palantir?

Intent def is there too though, much of this is entrenching, and much of it is a power grab (esp US tech at the mo), to get from capital/tech concentration to coopting governance structures

AI is a tech where by design it is not lowering a participation threshold, it positions itself as bigger-than-us, like nuclear reactors, not just anyone can run with it. That only after 3 years we see a budding diy / individual agency angle shows as much. It was only designed to create and entrench power (or transform it to another form), other digital techs originate as challenge to power, this one clearly the opposite. The companies involved fight against things that push towards smaller than us ai tech, like local offline first. E.g. DMA/DSA

Which paper or article from Romeo Dean and Dwarkesh patel?

The crime was misleading investors, not anyone else, which is very telling. The hype around "AI" - and actually hiring remote workers to do the job - and misleading customers/users doesn't matter.

Im Standard stellt Martin Auber mit aktuellen Daten belegt dar, warum der bloße Ausbau der Kapazitäten zur Erzeugung erneuerbarer Energien nicht zu einer Dekabonisierung führen wird. Der Energiebedarf wächst wesentlich schneller als die zur Verfügung stehende erneuerbare Energiepunkt. Durch den KI-Boom wird er noch einmal deutlich gesteigert. https://www.derstandard.at/story/3000000255154/wann-kommt-die-energiewende-oder-kommt-sie-gar-nicht

Concentration of power.

https://web.archive.org/web/20231019053547/https://www.careful.industries/a-thousand-cassandras

"Despite being written 18 months ago, it lays out many of the patterns and behaviours that have led to industry capture of "AI Safety"", co-author Rachel Coldicutt ( et Anna Williams, and Mallory Knodel for Open Society Foundations. )

For Open Society Foundations by 'careful industries' which is a research/consultancy, founded 2019, all UK based. Subscribed 2 authors on M, and blog.

A Thousand Cassandras in Zotero.

This is a big lesson. As a field, we still have not thoroughly learned it, as we are continuing to make the same kind of mistakes. To see this, and to effectively resist it, we have to understand the appeal of these mistakes. We have to learn the bitter lesson that building in how we think we think does not work in the long run. The bitter lesson is based on the historical observations that 1) AI researchers have often tried to build knowledge into their agents, 2) this always helps in the short term, and is personally satisfying to the researcher, but 3) in the long run it plateaus and even inhibits further progress, and 4) breakthrough progress eventually arrives by an opposing approach based on scaling computation by search and learning. The eventual success is tinged with bitterness, and often incompletely digested, because it is success over a favored, human-centric approach.