If anything - my opinion at this point is that cars were a mistake in vehicle sizing caused by internal combustion engines.
For the vast, vast majority of ubran transit, something akin to a bike in size seems to make more sense.
We see this already in urban regions in India/Asia where scooters are the predominate transportation method, and I think even traditional scooters are heavy enough to be problematic.
But a class 2 ebike (so throttle with no need to pedal) can weigh as little as 40lbs (20kg), and go 30 miles at 20mph.
It's insane that we're not designing urban transit for bikes at this point. Much better density, much safer, much easier to store and park, much cheaper to operate and license.
Conversely, if this is indeed true motivation and management has accepted it, kudos to them. It sounds like the engineers said that the situation is untenable and this is the cover we need to fix it, and they got what they asked for.
I don't know, it just doesn't feel very scheduled to me.
> I'm about to loose thousands of dollars by the end of Monday 20th because of the automatic shipping deadline on Tindie and it currently being down. I've tried contacting support multiple times but they are not helping. Please respond before my business fails!
You cannot build a physical store in parallel to the current one and swap them in place once done. Here the issue is not that it's down for several days, it's that there is no reason given for something so unusual
I think LLMs are really bad at writing tests. In the good old days you invested in your test code to be structured and understandable. Now we all just say "test this thing you just generated".
I shipped a really embarrassing off-by-one error recently because some polygon representations repeat their last vertex as a sentinel (WKT, KML do this). When I checked the "tests", there was a generated test that asserted that a square has 5 vertices.
But LLMs let you skip all the boring parts - setting up harness, writing some initial inputs, adding asserts for every output. And then _you_ get to do actually important stuff, like ensuring square has 4 vertices.
I suppose that my generalization was too broad and that LLMs can be either good or bad at writing tests depending on your workflow and expectations.
I'm closely supervising the LLM, giving it fine-grained instructions — I generally understand the full interface design and most times the whole implementation (though sometimes I skim). When I have the LLM write unit tests for me, it writes essentially what I would have written a couple years ago, except that it tends to be more thorough and add a few more tests I wouldn't have had the patience to write. That saves me quite a bit of time, and the LLM-generated unit tests are probably somewhat better than what I would have written myself.
I won't say that I never see brain-dead mistakes of the "5-vertex square" variety (haha) — by their nature, LLMs tend towards consistency rather than understanding after all. But I've been using Claude Opus exclusively for while and it doesn't tend to make those mistakes nearly as often as I used to see with lower-powered LLMs.
> AI statement: I didn't use AI to write this article (details).
Meta, but thank you for including this and suggest even putting it at the top of your articles. I'm now off to bother to read something that someone bothered to write :)
I work on the mapping team at Zoox (self driving) and we have c++ roles at the entry and mid levels. Requires onsite in the Bay Area though. Charles, if you're reading and would like to chat, I (Carl Chatfield) have sent you a linkedin request.
Thank you for your work on Wesnoth, I spent many hours playing back in the day. There's also a good android port.
The MacOS window manager is so bad that I've resorted to three monitors plus the built in screen. Two monitors have fullscreen terminal emulators and the last has the browser. The built-in screen handles all the distracting stuff whenever I can be bothered to look down at it.
With Xmonad I had 10 spaces on a single laptop screen (actually however many I wanted) with the flick of a button. And yes, I know about hacks like aerospace and the others that require disabling system integrity
If you were using a maximised app per workspace, I recommend setting up Hammerspoon for quick app switching. I have hyper + J for terminal, hyper + K for browser and so on. No space switching, but since each app occupies the full screen, it doesn't matter.
I learned sed back in the day to show off. I wish I'd invested that effort in learning perl oneliners instead. For whatever reason I picked up enough awk along the way, and now that's what I tend to use if I ever need something beyond a simple substitution.
Yes, S2 is a congruent DGGS. Unfortunately, it kind of straddles the analytics and visualization property space, being not particularly good at either. It made some design choices, like being projective, that limit its generality as an analytic DGGS. In fairness, its objectives were considerably more limited when it was created. The potential use cases have changed since then.
None that are well-documented publicly. There are a multitude of DGGS, often obscure, and they are often designed to satisfy specific applications. Most don’t have a public specification but they are easy to design.
If the objective is to overfit for high-performance scalable analytics, including congruency, the most capable DGGS designs are constructed by embedding a 2-spheroid in a synthetic Euclidean 3-space. The metric for the synthetic 3-space is usually defined to be both binary and as a whole multiple of meters. The main objection is that it is not an “equal area” DGGS, so not good for a pretty graphic, but it is trivially projected into it as needed so it doesn’t matter that much. The main knobs you might care about is the spatial resolution and how far the 3-space extends e.g. it is common to include low-earth orbit in the addressable space.
I was working with a few countries on standardizing one such design but we never got it over the line. There is quite a bit of literature on this, but few people read it and most of it is focused on visualization rather than analytic applications.
He always comments like this. Never commenting a concrete answer. Just look at his history. Hes been doing this for years. Probably as advertisment for himself or to just feel/show superior.
Yep, and won't activate until any morning dew is off the sensors.. or when it rains too hard.. or if it's blinded by a shiny building/window/vehicle.
I will never trust 2d camera-only, it can be covered or blocked physically and when it happens FSD fails.
As cheap as LIDAR has gotten, adding it to every new tesla seems to be the best way out of this idiotic position. Sadly I think Elon got bored with cars and moved on.
If the camera is covered or blocked, you can't drive plain and simple, as you can't drive a car (at least on Earth) with just Lidar. The roads are made for eyes. Maybe on Rocky's homeworld you can have a Lidar only system for traveling.
I'm an engineer on the HD Mapping Team at Zoox (autonomous vehicles) and we are looking for a mid-career full stack engineer with a flair for automation and dev tooling. The role is about helping us scale our map production and management systems. Geospatial data and 3D visualization (deck.gl) experience are nice to haves but by no means required.
If the role sounds like a good fit and you would like to talk to someone directly you can email me at carl chatfield gmail. (Please fill in the gaps).
Usual perks apply, but please read the linked job description for details.
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