Google Cloud CEO Thomas Kurian addresses compute economics and the cost trajectory of running AI models at enterprise scale.
Opinion
Kurian: Competitors attack Google because their own AI models are terrible
“If you don't have your own model, or you have a model of your own, but it's terrible, naturally you're going to say something like that.”
Opinion
Kurian questions Microsoft's AI contributions beyond supplying OpenAI with GPUs
“Whether that's how much of credit goes to Microsoft outside of providing them a bunch of GPUs, time will tell.”
Insight
Kurian: Long-term AI economics depend primarily on inference cost, not training
“First and foremost, in the long run, if AI really scales, the cost you really want to care about is inference cost, because that's what's integrated into serving, and any company that wants to recover the cost of training has to have a large scale inference fo…”
Prediction Not checkable as stated
Kurian: AI model pre-training will continue to see diminishing returns
“There are gains to be had. I don't think they will be at the same ratio as earlier because just, you know, there's always a lot of diminishing returns at some point. I don't think we are at the point where there are no more gains, but I think we won't see the …”
Assertion Not checkable as stated
Google Cloud sales reps receive no extra pay for selling DeepMind models
“Our field is not compensated any differently. Our partner ecosystem is able to use all the models in the platform, and most importantly, we have very large Anthropic customers running on GCP.”
Assertion Not checkable as stated
Kurian: Google Search, Cloud, and YouTube share the same inference stack
“And one benefit we have at Google is all our services, whether that's search or us or YouTube, this inferencing of the same stack and same model series. So the model learns very quickly from all that reinforcement learning feedback and gets better and better.”