Google broadens its AI hardware portfolio with two new specialized chips

Google's new tensor processing units (TPUs) broaden its chip portfolio to more use cases: confidential model training and more memory capacity. Google is notching up its chipmaking game as the company seeks to reduce its dependence on chips made by other companies for its cloud computing business. Google on Monday unveiled two new variants of its tensor processing units (TPUs), in-house-developed chips meant for AI workloads, that broaden its chip portfolio to additional use cases: confidential inference and more memory capacity for large workloads. The new units, TPU 8tx and TPU 8i Max, are part of the company’s eighth generation of chips introduced in April this year, and build on what those chips offered, which was more inference capacity and support for large training requirements.

TPU 8tx, designed with AMD, is based on the TPU 8t chip, and is geared specifically for confidentially training and running AI models, Google said in a blog post. The chip “builds security directly into the hardware layer, keeping sensitive data and model weights protected and isolated even while in active use,” the company wrote. The chip also has a custom inferencing network that lets it run reasoning alongside training, so it can be used to distill and train small models on the fly. That ability, according to Google, could prove useful for cases where