The latency point matters more than it looks imo like the GPU work isn't just async CPU work at a different speed, the cost model is completely different. In LLM inference, the hard scheduling problem is batching non-uniform requests where prompt lengths and generation lengths vary, and treating that like normal thread scheduling leads to terrible utilization. Would be curious if Eyot has anything to say about non-uniform work units.
Not right now, it is far too early days. I'm currently working through bugs, and missing stdlib, to get a simple backpropagation network efficient. Once I'm happy with that I'd like to move onto more complex models.
What is the new language doing that can't be done with an already established language that is worth sacrificing an entire standard library?