A GPU, a graphics processing unit, performs the same operation on many data values in parallel.
By Tony Yu / tkal · November 8, 2026 · One-minute visual guide
One tutor, or a whole class~
Same math, lots of data ♡
↓
CPUfewer cores, tasks in a linear order
vs
GPUthousands of cores, one operation on many values
A GPU wins when the same step repeats over lots of data.
A simplified picture: the tutor and the class are Mochi’s analogy; the chip details come from AWS and IBM.
Keep this bitA GPU is a graphics processing unit: a chip that performs the same operation on multiple data values in parallel.
Why care?
Because AI leans on that exact trick. AWS says modern GPUs are central to artificial intelligence workloads, and that you can train and deploy AI models on GPUs. When a chatbot answers you, parallel math like this is doing the lifting somewhere in a data center.
Where it came from
Games. Nvidia was the first to market the single-chip GeForce 256 GPUs in 1999. They were aimed at the gaming and CAD markets. A CPU is one patient tutor working through tasks in order; a GPU is a whole class, each kid doing the same sum on a different number at the same time.
CPU
GPU