The car is the same as last week.
You have to remember that this is a track that verstappen really doesn't like: last year's race at Singapore was also his worst.
Usually verstappen drives ~3 tenths faster than Perez, which, if he did that this week, would also put him up there....
IMO this is less of a case that the car is worse and more that verstappen isn't able to get 100% from his car.
24, always driven manual, EU.
From my experience most people in the EU can or at least could: This is because many (if not all, not sure) countries make a distinction between manual and automatic licenses (see e.g. https://www.learn-automatic.com/qualified/automatic-driving-licence/).
I.e. if you want to drive manual, you have to take the test manual, but if you take the test on manual transmission, you are allowed to drive automatics as well.
No, it's built into the protocol: think of it like as if every http request forces you to attach some tiny additional box containing the solution to a math puzzle.
The twist is that you want the math puzzle to be easy to create and verify, but hard to compute. The harder the puzzle you solve, the more you get prioritized by the service that sent you the puzzle.
If your puzzle is cheaper to create than hosting your service is, then it's much harder to ddos you since attackers get stuck at the puzzle, rather than getting to your expensive service
They are: their car is just a dog in the actual race. From a pure qualifying pace POV they are a lot better, with hulkenberg being able to get the car into q3 quite consistently.
That's also what makes them seem better than they really are: hulk qualifying in p8 (great) and then tumbles down to p16 by the end of the race (usually because they have to stop more often or at least to worse tires since their tire deg is abismal)
Standard lossless compression (without further assumptions) is already very close to being as optimal as it can get: At some point the pure entropy of these huge datasets just is not containable anymore.
The most likely savior in this case would be procedural rendering (i.e. instead of storing textures and meshes, you store a function that deterministically generates the meshes and textures). These already are starting to become popular due to better engine support, but pose a huge challenge from a design POV (the nice e.g. blender-esque interfaces don't really translate well to this kind of process).
No he doesn't?
Don't get me wrong there are many places where the paper can be wrong (eg fig 1 or their magnetism exceptionally looking more similar to diamagnetism than superconductivity) but you are mixing him up with Ranga Dias who has had a history of data fabrication.
Dias has nothing to do with this paper though.
Not really: you have to keep in mind the amount of expertise and ressources that already went into silicon, as well as the geopolitics and sheer availability of silicon. The closest currently available competitor is probably gallium arsenide. That has a couple of disadvantages compared to silicon
Germanium itself is another potential candidate, especially since it can be alloyed with silicon which makes it interesting from an integration point-of-view.
SiGe is very interesting from a logic POV considering its high forward and low reverse gain, which makes it interesting for low-current high-frequency applications. Since you naturally have heterojunctions which allow you to tune the band-gap (on the other hand you get the same problem as in GaAs: it's not a pure element so you need to tune the band-gap).
One problem specifically for mosfets is the fact that you don't get stable silicon-germanium oxides, which means you can't use the established silicon-on-insulator techniques.
Cost is also a limiting factor: before even starting to grow crystals you have the pure material cost, which is roughly $10/kg for silicon, and $800/ kg for germanium.
That's why, despite the fact that the early semiconductors all relied on germanium, germanium based systems never really became practical: It's harder to do mass production, and even if you can start mass production it will be very expensive (that's why if you do see germanium based tech, it's usually in low-production runs for high cost specialised components)
There's some research going on in commercialising these techniques but that's still years away.
Zeiss is German, they also produce substantially more than just the optics https://en.m.wikipedia.org/wiki/Carl_Zeiss_SMT
It's a different paper (e.g. https://www.nature.com/articles/s41586-022-05294-9) from a different researcher (specifically Ranga Dias). This is not connected to the recent non-peer reviewed https://arxiv.org/abs/2307.12008
probably not: Spa is always great for the overtaker due to the long straight into and after eau rouge. McLaren is also running very strong wings which hurts their performance on the straights (but helps during e.g. rainy qualifyings....).
Realistically, if there is any chance of overtaking at all, Verstappen can overtake just due to less drag on the straights.
I hope that heads roll at haas for that disaster. There's one thing making wrong choices in high-stakes scenarios, but they sent out their drivers too late twice within 24h. That's just an unforced, unexplainable blunder. If I were gene haas I'd be furious: spend 100 MILLION dollars to develop a car and they don't even manage to get it around the track once.
This is doubly bad considering that sprints are one of their most reliable places to get points considering that their tire wear doesn't affect them too much over shorter distances.
They might as well pack up and go home now to conserve their parts since at this point there not going to achieve anything anyways.
I think that interest is added, specifically you pay https://www.irs.gov/payments/quarterly-interest-rates based on the quarters you were missing taxes.
Not sure if the numbers quoted here include that already