tim-fan

I feel that would be handy in all sorts of situations when networks are down.

Also in comparison the cases of disruption/blocking intersections/emergency-services do seem significant - seems plausible in the right circumstances you could lose lives.

Seems they need to 10x their miles before they can start making confident claims about lives saved.

Maybe that's too much of a statistical stretch.

But would be a good to-the-point number to have on hand for some waymo debates.

"yes they caused some disruption in an intersection in so-and-so scenario, but on the other hand they saved X number of human lives last year"

Bags are stored in numerical order for quick storage and retrieval.

With this you do your decluttering from the web interface: search for items that haven't moved in years, flag for removal.

For frequently used items the system doesn't make sense - the storage and retrieval overheads are too high. But it pays off for any item you might forget the location of, or forget if you have it at all.

I feel we're overdue to have these types of digital front ends over our household item storage.

Then the one I'm more interested / excited for: optimizing the fleet for the cargo. If most trips involve single passengers, then most cars can be small electric single seaters. This can further reduce insurance costs as well as fuel, maintenance and depreciation.

I'd hope that's enough to offset the price of the sensors, compute hardware, and engineers to maintain the system.

But yes paying back investors; not sure how long that would lead to elevated costs for riders.

For one a self driving taxi fleet could take up vastly less space - you'd no longer need one car per person, you'd need far fewer parking spots, most cars could be single or double seaters again taking less space and running more efficiently.

The space savings could be used to boost rail-based public transit options, which would see more adoption as self driving taxis make last-mile transport cheaper and easier. A bunch of positive feedback loops driving public transit adoption and improvements.

Result is cleaner and more efficient transport for all, and vast amounts of space returned from serving cars to serving people.

At least that's the dream!

I don't know much about telescopes :p

Have you looked at producing 3D reconstructions over the thrown trajectory? And/or something like a gaussian splat-based representation for viewing the whole trajectory at once?

Would be good to be able to iterate on images (keep this, change that etc).

The use of the seed looks useful but I'm guessing it has its own limitations.