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8 foundational pieces. Each one is the anchor for the shorter articles in its domain — read the topic first and the rest follows from it.
2 topics
AI, machine learning, deep learning and generative models are nested, not synonymous. Here is what distinguishes each layer, and which one people now mean when they say AI.
Four serious positions on AGI, what each treats as the binding constraint, and — for each — the observation that would refute it. A guide to holding the question rather than picking a side.
3 topics
Nanotechnology is defined by scale rather than substance. Here is what changes between 1 and 100 nanometres, why it changes, and why a nanoparticle of a familiar material can be a genuinely new one.
Why a drug-delivery nanoparticle has a core, a shell, a polymer coat and a targeting ligand — told as the sequence of failures each layer was added to solve.
Discovery, characterisation, pilot line, product. What each stage measures, what kills projects at each one, and why most of the field is permanently in the first two.
1 topic
2 topics
What eight real deep-science roles involve day to day, what qualification each actually needs, and the two axes — bench time and code time — that decide which will suit you.
What machine learning has actually changed in biology, what it has not, and why the loop between a prediction and a measurement is still the part that takes months.
