Version 2: What Changed, What Was Wrong, and What's Next for TPU v8?
Inside Google’s Ironwood TPU v7 Supply Chain
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We're launching two specialized TPUs for the agentic era.
The eighth generation of Google’s TPU includes two specialized chips that will power the future of AI.
Train a model using TPU v5e | Google Cloud Documentation
With a smaller 256-chip footprint per Pod, TPU v5e is optimized to be a high value product for transformer, text-to-image, and Convolutional Neural Network (CNN) training, fine-tuning, and serving. For more information about using Cloud TPU v5e for serving, see Inference using v5e.
Ironwood: The first Google TPU for the age of inference
We’re introducing Ironwood, our seventh-generation Tensor Processing Unit (TPU) designed to power the age of generative AI inference.
Tachyum Defends TPU® Trademark from Infringement by Google TPU | Tachyum
Tachyum® today announced that it is beginning to take steps to defend the use of its registered TPU® trademark.
TPU architecture | Google Cloud Documentation
Tensor Processing Units (TPUs) are application specific integrated circuits (ASICs) designed by Google to accelerate machine learning workloads. Cloud TPU is a Google Cloud service that makes TPUs available as a scalable resource.
Experimental Display Type
T72T Experimental Display Type by T72T part of Lundqvist & Dallyn Studio
Google no longer developing Material Web Components
Google is "no longer actively staffing" Material Web Components (MWC) and has "reassigned the engineers working" on it...
TPUs vs. GPUs and why Google is positioned to win AI race in the long term | Hacker News
To quote The Next Platform: "An Ironwood cluster linked with Google’s absolutely unique optical circuit switch interconnect can bring to bear 9,216 Ironwood TPUs with a combined 1.77 PB of HBM memory... This makes a rackscale Nvidia system based on 144 “Blackwell” GPU chiplets with an aggregate of 20.7 TB of HBM memory look like a joke."
New Isle Browser(formerly Flux Browser) New MAJOR update
Rohan Paul on Twitter / X
Google is trying to win AI by making compute cheap, not by beating Nvidia on raw speed.Nvidia sells GPUs to clouds with a big 70%+ margin that sits on top of manufacturing and R&D cost and raises cloud prices.Google builds TPUs for itself at near manufacturing cost, adds no… https://t.co/aSgWRf0HY7 pic.twitter.com/T3Fzc6czwg— Rohan Paul (@rohanpaul_ai) November 25, 2025
