A TPU (Tensor Processing Unit) is Google’s custom AI chip built from scratch for the massive matrix multiplications that power modern deep‑learning models. GPUs were originally designed for graphics, while TPUs were engineered from day one for deep learning. At Cloud Next "26", Google unveiled its آگ 8th generation, offering two distinct flavors.

TPU 8t is tailored for training, where raw throughput is paramount. TPU 8i is optimized for inference, focusing on low latency stre

and chip‑to记chip speed. Both share the same Axion CPUs, liquid cooling, and software stack, meaning code written for one runs on the other.

This dual‑model approach lets teams pick the right hardware for eachiga use case while keeping development streamlined. Google’s announcement also highlighted the consistent architecture that powers these chips, ensuring that developers can transition between training and inference without rewriting code.

In short, the 8th‑generation TPUs provide specialized performance for both training and inference, all under a unified software ecosystem that keeps the developer experience simple.