Before we had ChatGPT writing our boilerplate and Copilot auto-completing our bugs, computer science was forged in the fires of academia.
If you want to truly understand how computers think, you don't need another JavaScript tutorial. You need to read the foundational texts. Here are the papers that didn't just push the boundary—they redrew the map entirely.
1. The Turing Machine (1936)
Alan Turing's "On Computable Numbers, with an Application to the Entscheidungsproblem" is the big bang of computer science. Before hardware existed, Turing invented the concept of software in his head.
"We may compare a man in the process of computing a real number to a machine which is only capable of a finite number of conditions." - Alan Turing
He proved that a simple machine reading and writing 1s and 0s on an infinite tape could compute anything that is computable.
Implementing a Turing Machine in TS
While building an infinite tape in RAM is tough, we can simulate the logic quite easily. Here is what an extremely basic state machine looks like:
type State = 'HALT' | 'READ' | 'WRITE';
interface TuringMachine {
tape: number[];
headPosition: number;
currentState: State;
}
function step(machine: TuringMachine): void {
if (machine.currentState === 'HALT') return;
// Simulating the genius of 1936...
const currentVal = machine.tape[machine.headPosition];
console.log(`Reading: ${currentVal}`);
// Change state, move tape
machine.currentState = 'HALT';
}
This is obviously an oversimplification, but every React component you write, every Docker container you spin up, and every SQL query you run ultimately compiles down to these tape-shifting operations.
2. Attention Is All You Need (2017)
Fast forward 80 years. The Google researchers dropped a paper that completely eliminated Recurrent Neural Networks (RNNs) for natural language processing, introducing the Transformer architecture. This single paper is the reason ChatGPT exists today.
