AFAIK Google is in the middle of massive infrastructure investment in hardware which is of similar performance to Nvidia, but they will own the whole stack. They will also be able to deploy an order of magnitude more compute than openAI to LLMs in 2024/25.<p>LLM tech also seems to be easily swapped between providers. So my view is that the value proposition is in the hardware designers and manufacturers (Nvidia, tsmc, Google).<p>Why are more people not excited by what is happening at Google? What am I missing?
Fantastic blog! In your post, you highlighted the use of Cloud TPU v5e with GKE for AI inference. How does this setup maintain high performance while managing costs, especially in high-demand scenarios like real-time data processing or live interactions?
The demo is really compelling. Using GKE or k8s sounds like a good idea for hosting LLMs, making them perform better and less costly overall. Not bad at all.
AI is a big deal this year. Google is one of the biggest tech companies.<p>Yet a post about AI at Google gets... No comments at all.<p>Back in 2005, this would have been the most talked about news of the day. Now, nobody cares what Googles up to. They lost their way.