What happened
Sundar Pichai says Google can innovate quickly for customers by having hardware engineers co-design systems alongside Google DeepMind. He contrasts this approach with waiting years for a traditional semiconductor cycle and notes that four distinct TPU systems were introduced within one generation in one year, attributing that milestone to a quoted post by Amin Vahdat.
Why it matters
Pichai contrasts a traditional semiconductor cycle with Google’s faster co-design approach, offering a concise view of how close collaboration between hardware engineers and DeepMind is framed as a way to speed customer-facing iteration.
Read next
More changes in today’s briefingGoogle DeepMind Introduces Gemini 4 Hydrogen for Fast Agentic WorkflowsFour distinct TPU systems in a single generation in one year! Instead of waiting years for a traditional semiconductor cycle, hardware engineers co-designing systems alongside Google Deepmind means we can keep innovating quickly for customers.
View the quoted post on XThrilled to share a big milestone from our AI & Infrastructure team at @Google.
Today we’re expanding our 8th generation TPU portfolio with:
- TPU 8i Max: Built for massive context windows and the highest compute density per rack
- TPU 8tx: Purpose-built for secure, confidential inference
This marks the first time we’ve introduced four distinct TPU systems in a single generation, in one year.
For developers, hardware is only as good as the software stack. And we want you to be able to build with TPUs as easily and efficiently as we do at Google. You can now:
↳ Run native PyTorch & Hugging Face models via TorchTPU (zero code rewrites)
↳ Cut KV transfer latency >90% with open-source TPU Sync
↳ Eliminate idle compute waste with Agent Compute EngineRead more about our newest TPUs on our blog: bit.ly/3VfETPR
I look forward to connecting with builders, researchers, engineers and organizations pushing the boundaries of AI and computing!