What it is
Computing rests on two ideas from the 1930s and 1940s: Turing’s abstract machine that can carry out any computable procedure, and Shannon’s measure of information in bits.
Everything since is layers: transistors make chips, chips run operating systems, systems talk over networks, and applications sit on top. Each layer hides the complexity below so the next one can move faster.
The computing stack
Each layer hides the complexity of the one below it.
- ApplicationsWhat people use: this site, maps, chat
- NetworksPackets moving between machines
- Operating systemsShare one machine among many programs
- ChipsBillions of switches doing arithmetic
- Transistors and bitsOn or off: Shannon’s unit of information
Sources: Proceedings of the London Mathematical Society · Bell System Technical Journal
A diagram of ideas, not a measurement.
Ideas to carry
- 1
Abstraction
You can build a website without knowing transistors exist. That is the point.
- 2
Information is measurable
Shannon showed that messages can be counted in bits, whatever they mean.
- 3
Local or cloud
Small open models now run privately on a laptop for some tasks.
Established What we know
- Alan Turing’s paper “On Computable Numbers” (1936) defined the abstract machine at the root of computer science.[1]
- Claude Shannon’s 1948 paper founded information theory and the bit as a unit of information.[2]
- The computation used to train notable AI systems has grown by many orders of magnitude since 2010.[3]
Interpretation The older lens · History of ideas
Ramon Llull’s paper wheels (c. 1305) combined ideas mechanically; Leibniz saw binary in the I Ching’s hexagrams.
Reading
- 1843Notes on the Analytical EngineAda Lovelace
- 1936On Computable NumbersAlan Turing
- 1948A Mathematical Theory of CommunicationClaude Shannon
Apollo guidance computer: lands humans on the Moon
My laptop: 47 tabs and a fan like a jet engine
Connected subjects, projects and writing
- MathematicsSubject · Cosmos
Established Turing’s machine and Shannon’s bit are mathematical ideas before they are machines.
- RelativitySubject · Cosmos
Established GPS software applies relativistic clock corrections every day.
- AI and neural networksSubject · Intelligence
How machines learn from data, from 1980s backpropagation to the transformers behind today’s language models.
- Agents and automationSubject · Intelligence
Software that plans and acts with tools, and where a human should stay in the loop.
- Private AI that runs at homeExperiment · Intelligence
Small open models running entirely on my own machines: an offline chat in the browser, and a home assistant that never leaves the network.
Sources
- On Computable Numbers, with an Application to the Entscheidungsproblem Proceedings of the London Mathematical Society, 1936. Checked 5 Nov 2026.
- A Mathematical Theory of Communication Bell System Technical Journal, 1948. Checked 5 Nov 2026.
- Artificial Intelligence Our World in Data. Checked 5 Nov 2026.