The fuck are people supposed to do who don’t even own the car?
Their failure on this point is particularly concerning if they want to run a robotaxi service.
The fuck are people supposed to do who don’t even own the car?
Their failure on this point is particularly concerning if they want to run a robotaxi service.
Yikes! That’s a service latch, not an emergency release.
Stargate Atlantis season 1 episode 4 may not be enjoyable for you.
The inner diameter is less than the outer diameter which makes for a small overdrive gearing ratio, translating to fewer steps even under normal operation.
The hamster balls also win for style points but that’s arguably walking with extra steps.
The whole point of captchas is to train bots. Did you think they were all road object and optical character recognition based because those are the categories humans really excel at?
From a product development viewpoint, the gun is an uninteresting part. It’s better to use something that already has a mature production line and has been thoroughly field tested. It’s the vision and control systems they are interested in developing, the gun is just the chosen end effector for this application.
Even when they’re ready to start deploying systems like this, there’s a lot of value in using compenents that the military already has a lot of spare parts for and that personnel know how to maintain. I wouldn’t expect a custom gun until units like this are commonplace.
He was planning to retire 6 months ago, but the market hasn’t been doing great and his brother in law had to borrow some money to deal with gambling debts.
That’s $700 for a digital only edition without a disk drive or vertical stand. It’s $810 to match the features of the PS5.0
Why not? The ps5 is good at pretending to do 4k, but is very much on the anemic side of graphics power for 4k gaming. Why wouldn’t people want a performance bump if it’s available and they can afford to upgrade?
Imagine thinking that PhD’s and postdocs aren’t exploited by capitalism.
I’m not saying normalization is a bad strategy, just that it, like any other processing technique comes with limitations and requires extra attention to avoid incorrect conclusions when interpreting the results.
Because relative to the population density, there were 100 times as many sightings. Or what am I missing.
If you were to attempt to trap and tag bigfoots in both areas, would you end up with 100 times as many angry people in a gorilla suit in the small town? No. You would end up with 1 in both areas. So while the tiny town does technically have 100x the density per capita, each region has only one observable suit wearer.
Assuming the distribution of gorilla suit wearers is uniform, you would expect approximately 99 tiny towns with no big foot sightings for every 1 town with a sighting. So if you were to sample random small towns, because the map says big foots live near small towns, you would actually see fewer hairy beasts than your peer who decided to sample areas with higher population density.
If we could have fractional observations, then all this would be a lot more straightforward, but the discrete nature of the subject matter makes the data imherently noisy. Interpreting data involving discrete events is a whole art and usually involves a lot of filtering.
Simple normalization does amplify signals in low density areas. If a person in a tiny town of 100 reports a bigfoot sighting and another person in an area with 10,000 population also reports a sighting, then with simple normalization the map would show the area with 100 people having 100 times as many big foot sightings per capita as the area with the population of 10k. Someone casually reading the map would erroneously conclude that the tiny town is a bigfoot hotspot and would in general conclude bigfoot clearly prefers rural areas where they can hide in seclusion. When the reality is that the intense signals are artifacts of the sampling/processing methods and both areas have the same number of fursuit wearers.
A bear has time and motivation to keep trying over and over again to get into the garbage. People are generally much less determined to figure it out.
I think someone ran the image through an ai upscaler. The textures on the rails an stuff are too smooth and the edges are overly sharpened.
My samsung phone does this level of overprocessing when taking pictures and I wish I could figure out how to turn that off.
https://old.reddit.com/r/pics/comments/ae83eg/a_girl_and_her_hydrant/
I think the second pinky is actually a white line in the rock.