Scientific Principle
The quantifiable property of a signal or message that can be encoded, transmitted, and decoded. Shannon entropy provides the mathematical foundation. DNA, neural signals, and digital communication are all physical implementations of information processing.
Other principles
Strip away the cryptocurrency layer and blockchain is a database with one specific property: many computers must agree before anything is written. Rasmus Risager Lindegaard explains how consensus mechanisms work, where the technology actually matters, and why the crime narrative is statistically backwards.
Black holes are among the best-supported objects in physics — and among the strangest. Ole Eggers Bjælde explains what they actually are, how time behaves near one, and what the next generation of research will require to resolve what remains unknown.
In 2019, we photographed one black hole. We know millions more exist in the Milky Way alone. That gap is not a problem of knowledge — it is a gap in detection technology, and indirect evidence is not a lesser form of evidence.
The search for extraterrestrial life starts with Earth — not because scientists lack imagination, but because Earth is the only confirmed example of life that exists. Kai Finster explains why using Earth's biochemistry as a template is not anthropocentric bias. It is the only scientifically defensible starting point.
Blockchain crime accounts for less than 1% of transactions. Traditional fiat currency runs at 2–5%. The fear of crypto reveals something other than rational risk assessment — and the permanent public ledger makes it more traceable than cash, not less.
A model trained to detect skin cancer learned to look for rulers instead. The explainability problem is not a glitch. It is Goodhart's Law running at machine speed — and the gap between what AI systems can do and what we understand about how they do it is where the most consequential work in the field is now happening.
In 2012, a neural network cracked image recognition in a way that reshaped the entire AI field. Andreas Møgelmose traces what neural networks actually are, how convolutional architectures build understanding in layers, and why a cancer-detection model that learned to spot rulers instead tells us something important about where the field still cannot go.
The classroom poster shows eight planets and a clean edge at Neptune. The solar system extends halfway to the nearest star. Mads Fredslund Andersen explains what is actually out there, how it formed, and why the boundary question matters for exploration.
The classroom solar system poster implies a closed system ending at Neptune. That implication shapes how people understand science, exploration, and discovery. It is worth correcting.
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