By skyforbes 
From zero to chat agent — the jaw-dropping leap in accessibility
Imagine telling a room full of PhD researchers in 2020 that, five years later, anyone — yes, anyone — could build a working ChatGPT-style AI for less than the price of a Netflix subscription and faster than a cricket match. They’d laugh, pat you on the shoulder, and tell you to get some sleep. But then came Andrej Karpathy.
A few weeks ago, the legendary AI researcher and former Tesla AI director dropped Nanochat — a tiny, self-contained, end-to-end ChatGPT clone that costs roughly $100 and four hours to train. No secret servers. No corporate APIs. No billion-dollar data centers. Just your code, your data, your rules.
And that changed everything.
The AI Gold Rush Had a Gatekeeper Problem
Until now, building your own large language model was like trying to open a bank vault without a key. You could use OpenAI’s API, sure, but that meant paying rent in someone else’s house. You could fine-tune open-source models, but the infrastructure was dense, scattered, and fragile.
Then Karpathy, in his classic zero-to-hero spirit, released Nanochat — 8,000 lines of clean…