Why this series exists

To understand AI today, model benchmarks are not enough.
We also need the long arc: why computers were built, what problems they solved, and how each layer evolved.

This series follows the life story of computing, one turning point per week.

Main point first: there was no single "birth date"

Computing was not born in one moment.
It emerged when theory, real-world demand, and hardware breakthroughs converged.

Theory: defining what is computable
Demand: wartime and industrial calculation pressure
Implementation: electronic machines and stored-program architecture

Episode 1 takeaway: the birth moment

Computers did not begin as "fast calculators."
They began as systems that break complex work into repeatable procedures.

1930s-1940s: explosive demand for automated calculation
Turing: formal limits of what can be computed
von Neumann: stored-program architecture as the modern baseline

Modern AI still runs on this foundation.
No matter how strong the model is, execution is constrained by compute, memory, and I/O.

Timeline of the birth era

Year	Event	Why it matters
1936	Turing formalizes a computation model	Theoretical basis for algorithmic execution
1943-44	Colossus used for codebreaking	Proof that large electronic computation is practical
1945	ENIAC announced	Symbolic start of general-purpose electronic computing
1945	Early von Neumann report draft	Direction for stored-program architecture
1948-49	Manchester Baby / EDSAC	Stored-program model becomes real and repeatable

Turing and von Neumann in practical product terms

Turing: "What can be computed?"

Turing gave us a way to describe problems as procedures and state transitions.
That framing still appears in modern LLM pipelines.

define input
define rules
manage intermediate state
define stop conditions

von Neumann: "How should it run?"

The core of von Neumann architecture is storing program and data in memory together.
Modern AI inference systems are still extensions of this principle.

fetch/decode/execute flow
memory bandwidth as a bottleneck
I/O design shaping end-to-end throughput

Why this still matters for AI teams now

The market talks about models, but production bottlenecks still sit in core computing fundamentals.

Memory and bandwidth limits: longer context increases latency and cost
I/O architecture: retrieval, caching, and streaming shape user experience
Execution orchestration: agents/workflows are procedural systems at scale

So, better models help, but better execution architecture wins in production.

12-week publishing roadmap

Week	Theme	Why it matters for AI today
1	Birth of computers	Root of modern AI infrastructure
2	Transistors and ICs	Cost/performance path to AI at scale
3	OS and software engineering	Core discipline behind reliable AI products
4	Internet expansion	Connectivity layer for distributed AI
5	Search engine era	Predecessor mindset for RAG systems
6	Mobile computing	How AI moved into everyday UX
7	Cloud computing	Standardized training/deployment model
8	Big data and recommender systems	Data strategy before foundation models
9	Deep learning revival	GPU + neural nets turning point
10	Transformers and LLMs	Core architecture of generative AI
11	Multimodal and agents	Shift toward workflow automation
12	AI-native era	How products and teams are being redesigned

This week's action points (operator checklist)

In planning, set latency and cost budgets alongside model quality targets.
Draw a simple data flow (collect -> store -> retrieve -> respond) and mark bottlenecks.
Split issues into "prompt-level fixes" vs "infrastructure-level fixes."

Summary

The birth of computing is not just history; it is the base layer of today's AI product decisions.
This first episode connects theory (Turing), architecture (von Neumann), and current operational bottlenecks.

Next episode

Episode 2 covers how transistors and integrated circuits reshaped the economics behind today's AI stack. ai-evolution-chronicle-01-birth-of-computing 2026-02-08 ai_road_f44bb122 evolution_to_f54bb2b5 chronicle_ai_f24badfc 01_01_f34baf8f birth_how_f04baad6 of_computers_f14bac69 computing_were_ee4ba7b0 ai_born_ef4ba943 evolution_road_fc4bbdba chronicle_to_fd4bbf4d

von Neumann Posts

Road to AI 01: How Computers Were Born