Much of Google's AI software doesn't run on industry-standard Nvidia chips, but instead on its own tensor processing units.

Key market opportunities lie in region-specific deployment of Google's semiconductor ASICs, focusing on TPUs, Axion CPUs, and QPUs. Each geographic area offers potential based on its adoption rate of ...

Celestica Inc. took a hit on Thursday, with shares sliding nearly 8% after a report raised fresh doubts about its role in ...

Google's latest earnings showed not only solid operating momentum but also an unprecedented surge in capital spending, with capex set to more than double from US$91.45 billion in 2025 to US$175-185 ...

At the Google Cloud Next '25 conference, the company introduced the seventh-generation Tensor Processing Unit (TPU), Ironwood, designed for AI inference. This chip highlights Google's progress toward ...

Google Cloud today announced the imminent launch of its most powerful and energy-efficient tensor processing unit to date, the Trillium TPU. Google’s TPUs are similar to Nvidia Corp.’s graphics ...

In recent days, reports that Google is shifting some tensor processing unit (TPU) server assembly work from Celestica to ...

Google’s custom TPU chips are emerging as a serious challenger to NVIDIA’s GPUs, driven by potentially lower total cost of ownership through cheaper pricing and higher energy efficiency. Investor ...

The AI sphere is abuzz lately with news and rumors that the latest Google TPU, Ironwood, is powering the Gemini3 model, outpacing OpenAI on many metrics including intelligence and performance. Now, ...

The Maia 200 AI chip is described as an inference powerhouse — meaning it could lead AI models to apply their knowledge to ...