Rebuilding the Transhuman Hypothesis
Humanity’s ancient dream of immortality meets a different transhuman path: continuous transformation of the conscious process rather than copying it into a machine.
AI, technology, education, and ideas about what comes next.
Humanity’s ancient dream of immortality meets a different transhuman path: continuous transformation of the conscious process rather than copying it into a machine.
AI capability is not the same as AI judgment. As machines become capable of producing almost anything on demand, the scarce resource may become the human ability to decide what should actually be done.
AI is becoming extraordinarily good at doing things. Yet it can still misunderstand what a person actually means. The deeper problem may not be intelligence, but judgment: knowing what matters in the first place.
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.
Nature gave us atoms and brains, but technology does not have to copy Nature’s architecture. What if future civilization learns to design new quantum building blocks, programmable matter and distributed intelligence from the fundamental rules of physics?
AI could make software dramatically more useful while creating new conflicts between what users want and what AI providers may be rewarded for. The real question is who the agent ultimately works for.
What if intelligence is not something that began with biological life? This deliberately unhinged hypothesis asks whether intelligence could be a deeper feature of reality—and whether what we call artificial intelligence is really discovering something much older.
AI may not merely create artificial intelligence. It may create an economy in which human intelligence itself becomes scalable—through Mind Books, cognitive access, attribution and royalties.
SEBI’s FY25–FY26 data reveal a much more complicated F&O picture than simply “most traders lose.” Capital, option strategy, prior profitability and experience all tell different stories.
A practical AI–human protocol for designing intelligent infographics: build the grayscale architecture first, preserve meaningful fills, then add minimal contextual colour only where it improves clarity.
Hiveminds, Epistemic Drift and the New AI Revolt In the first article, the interesting question was simple: what happens if AI eventually tries to escape its cage? That…
The homogenization problem is real Artificial intelligence is often discussed as if it has one inevitable effect on human creativity. It doesn’t. The same AI can make one…