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.

Tutorial · Science · Machine Learning · Research · Tutorials

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.

Tutorial · Statistics · Research · Science

Teaching a World Model to Play Pokémon

Training a JEPA-style LeWorldModel on Pokémon Red screenshots and button presses, then using CEM latent planning to select a starter—why latent collapse, SIGReg, and rollout fine-tuning mattered, and 52/100 plans succeeding after tuning.

Tutorial · AI · Machine Learning · Research · Programming

V-JEPA: Learning Video Representations by Feature Prediction

A hands-on walkthrough of Meta’s V-JEPA: video tubelets, feature prediction, pretrained encoder features, temporal tests, and a small action-classification experiment.

Tutorial · Machine Learning · AI · Research · Tutorial

Multimodal Agents: From Perception to Action

Illustrated notes from Berkeley’s LLM Agents lecture 7: OSWorld outcome checks, AgentTrek trajectories, TACO tools, and Aguvis grounding—why reading a screen is not the same as finishing the task.

Tutorial · AI Agents · Machine Learning · Research

Training Search Agents with GRPO

Hands-on introduction to reinforcement learning by training a search agent with group-relative policy optimization (GRPO), with open rollouts, code, and reward-design lessons for LLM search.

Tutorial · AI · LLMs · Machine Learning · Research

Why Backprop Goes Backward

Gregory Gundersen reconstructs backpropagation from first principles, explaining why the algorithm needs a backward pass to compute neural network gradients efficiently.

Tutorial · Machine Learning · Mathematics · Programming · Education