WHY CAN'T AI RUN WITHOUT SERIOUS COMPUTING INFRASTRUCTURE?
One request to a modern language model means billions of calculations. A 70-billion-parameter model performs around 10–100 billion operations per response.
Now multiply that by millions of users and thousands of requests per second. This is where infrastructure becomes essential.
Ordinary computers can't handle it efficiently. CPUs are universal, but AI needs massive parallelism. That's why it relies on GPUs, TPUs, and tensor accelerators.
Then come memory, networking, cooling, and energy. Models must move data between chips, while thousands of chips generate enormous heat and consume megawatts.
At scale, you also need load balancing, queues, and distributed systems.
Remove any element — and AI stops.
September 25, 2026 109 1
