xAI Is Reportedly Using Just 11% of Its 550k Nvidia GPUs(wccftech.com) |
xAI Is Reportedly Using Just 11% of Its 550k Nvidia GPUs(wccftech.com) |
The bet can eventually pay off when they figure out how to train without human help and also generate useful models. Imagine is terrible too.
More competition is great for us users. I hope they recover. In the meantime why not hosting oss models like google does?
As such, using only 11% of their GPUs indicates that they've elected not to do as much training as they are capable of.
These experts set up quota systems, priority allocation, month-ahead plans, burst and idle quotas, etc, all with a goal to get the resource better used.
However it ends up having the reverse effect - teams now waste the resource deliberately to make it appear they have better utilisation, and run pointless jobs because "use it or lose it" quota systems discourage being thrifty.
These problems are compounded by there being hundreds of resource types - "I've got plenty of CPU and GPU TFlops for my project, but I've run out of disk spindle hours so can't run the training job".
End result is that the company as a whole doesn't even know real utilisation, and makes exceptionally poor use of resources.
That's why he bought Cursor, trying to get the customers to have an audience to give free credits.
I use LLMs for asking questions and coding. Generated answers are bad. Generated code is bad. Images and videos look super fake. And there is no fixed subscription to use it in CLI terminals.
If it was as good as other LLMs, as you say, why 11% usage, and why selling compute to Claude after all the badmouthing? I prefer deepseek 10x.