I was hoping there'd be more discussion about the model itself. I find the last couple of generations of Pro models fascinating.

Personally, I've been applying them to hard OCR problems. Many varied languages concurrently, wildly varying page structure, and poor scan quality; my dataset has all of these things. The models take 30 minutes a page, but the accuracy is basically 100% (it'll still striggle with perfectly-placed bits of mold). The next best model (Google's flagship) rests closer to 80%.

I'll be VERY intrigued to see what the next 2, 5, 10 years does to the price of this level of model.

We're eventually going to get it at cerebras inference latency. It's going to be wild.