Also, "GPU on demand" sounds _a_lot_ easier than "drone-based delivery". Between Seti@Home/Folding@Home/etc, various grid-computing/clustering/orchestration stacks that already exist, etc it seems reasonably doable to implement in a year or so. "drone-based delivery" sounds capital-intensive, sounds like you'll need to spend a lot of time building a professional network of business people who might use the service (so there's a 'cultural friction' between techie founders and business folks, potentially), plus the ever-looming threat of Amazon/etc figuring this out first.
tl;dr: I agree it's weird pivot, and good on the founders for being able to make the change! :)
Turns out, using drones to deliver is also not that competitive either. Delivery vans are very cost-efficient, and for food delivery / on-demand delivery, drones are not able to carry most orders. So it's not even the regulatory pains that make this difficult, which are unbearable in their own right.
It was a lot of fun to work on and we would have definitely stuck with it if there was any interest. There was none, so we had to admit that to ourselves.
This is a hard pivot, but it's been very stimulating to work on.
What would make you better than vast is extremely easy spot leasing and job prioritization.
I want to be able to have one of our training jobs finish, and then have the capacity immediately transition to a lease. With vast, we are renting in week long blocks.
I've used vast.ai (similar "Airbnb for GPUs" pitch) for years to spin up cheap test machines with GPUs you can't really find in the cloud (and especially consumer-grade GPUs like 4090s). Any insight into how this is different/better?
Also, don't know if vast.ai does this, but with us you can have 6 user sessions on your machine if you have six GPUs, so granular utilization is possible.