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Do we really need bigger AI weather forecasting models to improve resolution?
Emma Scharfmann shows that instead of building a bigger AI weather model you can train a small downscaler on top of an existing global one: trained in about an hour, it sharpens AIFS-ENS temperature forecasts over France from ~28 km to 5.5 km and cuts station-measured error by 14% RMSE and 21% CRPS over the first two days.
17 min · 3,914 words
A Visual Intro to Complex Numbers
A visual, intuition-first tutorial on complex numbers: starting from an unsolvable system of equations, it builds up the imaginary unit as a 90-degree rotation, the complex plane, multiplication as rotation and scaling, Euler’s formula, and applications in AC circuits, signals, control and MRI.
16 min · 3,760 words
Functional ultrasound imaging from scratch
Functional ultrasound imaging (fUSI) is a brain imaging modality that is just starting to be demonstrated in human studies. I’m sure many will be familiar with structural ultrasound imaging, which forms static images using ultrasound, as in a sonogram1. Functional ultrasound instead captures movies of brain tissue very rapidly, tracking subtle changes caused by the blood flow that follows neural activity.
11 min · 2,451 words
Standard deviation or standard error? What each one measures, and which one belongs in your paper
Selçuk Korkmaz clarifies SD vs SE with interactive figures: use SD to describe sample spread, and report estimates with confidence intervals rather than bare standard errors.
16 min · 3,717 words
Chemist and science communicator Michelle Wong (Lab Muffin Beauty Science) explains why AI-generated science content is error-prone and lists practical tells for spotting it, from chatbot formatting and voice to hyperprolific output and inhuman errors.
6 min · 1,331 words