Why Speed Is Not Always Efficiency
The Speed–Drift Paradox explains why faster AI search can move further from the solution—and why evidence, adaptive compute, and purposeful design matter more than activity alone.
AI, technology, education, and ideas about what comes next.
The Speed–Drift Paradox explains why faster AI search can move further from the solution—and why evidence, adaptive compute, and purposeful design matter more than activity alone.
From mathematical breakthroughs and intellectual entertainment to cancer cures, crop yields and measurable human progress.
Can we make the structure, weight and evolution of knowledge visible through a consistent visual language? Explore NNIG’s proposed visual grammar for weighted knowledge networks, topology and change.
A Live Notebook turns a blog into an evolving record of thought: preserving the reasoning behind ideas, reducing cognitive load, and creating bridges between unfinished investigations and completed essays.
Can recognizable patterns persist while their configurations change? EFNRT explores the possible connections among evolving information, geometry, structure, and chaos—starting with four books on complex systems.
A proposed framework for testing abstract information networks by applying disturbances to nodes with different, changeable resistance profiles—and examining stability, cascading failure and transferability across similar models.
AI can produce extraordinary benefits or harmful outcomes without those outputs alone proving conscious moral intention. Artificial Innocent Intelligence asks us to examine the training, objectives, incentives and human decisions that shape artificial intelligence before calling it a deity or a monster.
Superintelligence may discover extraordinary solutions—and reveal why some problems have no solution under their defining constraints. Explore physical, mathematical and epistemic limits on solvability.
How mathematical patterns, sacred geometry, numerical coincidences and esoteric symbolism can lend authority to claims that go beyond the evidence—and how to test the connections.
AI doom can be real without every AI-doom narrative being reliable. The Cute Tiger Cub Problem examines how satire, music, borrowed authority and visual certainty can blur the line between evidence, interpretation and speculation.
AI & Human Intelligence begins with Book I: The Augmented Mind—a three-part exploration of artificial intelligence, human intelligence, and how AI may change the way we think.
A Nobel economist’s new paper on automation and repression raises a disturbing question about what happens when humans become less economically necessary.
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.