AI Basics: Processing Unit

Recently, Google released a new computer chip, called Ironwood.

About Ironwood

Ironwood is Google’s seventh-generation TPU, or tensor processing unit, which has been designed to run artificial intelligence (AI) models.

What Are Processing Units?

Processing units are the core hardware components that perform computing tasks.
They act like the brain of a computer, handling operations such as calculations, image processing, and command execution.
For Example:
- GPU (Graphics Processing Unit), TPU (Tensor Processing Unit), Central Processing Unit.

CPU vs GPU vs TPU

Feature	CPU	GPU	TPU
Purpose	General-purpose processing	Parallel processing for graphics & AI	TPUs are custom-built processors developed by Google for AI and machine learning.
Core Count	2–16 cores	Thousands of smaller cores	Fewer, highly optimized cores
Processing Style	Sequential	Parallel	Parallel, tensor-optimized
Use Case	Operating systems, general tasks	Gaming, video editing, AI workloads	Deep learning, neural network training
Speed (AI Tasks)	Slowest	Faster	Fastest (high throughput AI performance)
Flexibility	Highly flexible	Moderate flexibility	Highly specialized

Conclusion

While CPUs remain essential for general computing, GPUs offer strong performance for parallel tasks, and TPUs take specialization further by accelerating AI and machine learning tasks with unmatched efficiency.

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