Concepts.
The ideas behind the finds — each a primer you can learn from scratch, kept current as the stream catches up, and interlinked with themes and items.
Brain-computer interface
A system that reads neural activity and turns it into control signals — letting a person operate a cursor, type, or draw using decoded intent rather than movement.
GLP-1
A class of drugs (semaglutide and kin) that mimic the GLP-1 hormone to regulate appetite and blood sugar — and increasingly studied for effects well beyond weight and diabetes.
Human–AI collaboration
Designing AI to finish or amplify a human's work rather than replace the human step — keeping judgment with the person and handing the drudgery to the model.
Humanoid robot
A general-purpose robot with a roughly human form, on the bet that a world already built for human bodies is best navigated by one.
Local inference
Running a model on your own hardware rather than calling a hosted API — private, free at the margin, and offline-capable, at the cost of some quality and speed.
Scaling laws
The empirical finding that a model's loss falls predictably as you add compute, data, and parameters — turning "make it bigger" from a hunch into a forecastable curve.
Vision-language model
A model that takes both images and text as input and reasons over them together — describing pictures, answering questions about them, or grounding language in what it sees.
World model
A model that learns an internal, navigable simulation of an environment — predicting how a scene evolves as you act in it, rather than just generating a single frame.