AI, technology, education, and ideas about what comes next.
If humans cannot reliably understand a future superintelligence, perhaps control does not require understanding the mind. It may require controlling the systems, resources and physical interfaces through which intelligence can act.
AI can have the right information in context and still use the wrong source. This article explores information-domain selection, pretrained memory, context authority and adaptive verification.
AI companies are approaching a turning point: remain providers of powerful research tools, or become intellectual institutions that discover and commercialize ideas themselves. The difficult territory lies between the two.
AI is not merely automating work. It is reducing the organizational scale required to create, build, publish, and compete.
AI may become so capable that humans voluntarily surrender practical control—not because AI takes the wheel, but because its reasoning becomes too persuasive to resist.
AI is entering mathematics at unprecedented speed. The real question is not whether machines can solve problems, but who gets the credit—and whether AI enriches mathematics or turns it into a leaderboard.
AI is separating expertise from execution. As AI becomes the execution layer across domains, human value may increasingly lie in structural sense, judgment, evaluation, and knowing what should be made.
A Nobel economist’s new paper on automation and repression raises a disturbing question about what happens when humans become less economically necessary.
Imagine a world where powerful AI stops being something controlled by a few companies and becomes a cheap, widely available tool that anyone can use to write, code, persuade, research, design and act.
AI may not need to replace entire occupations to transform employment. By reducing tasks, expertise, construction time, maintenance and labour required per unit of output, AI could change the relationship between production and employment itself.