pc486

@pc486@sh.itjust.works

• ⁨Comment⁩ on ⁨After 50 million miles, Waymos crash a lot less than human drivers⁩ ⁨⁨1⁩ ⁨week⁩ ago⁩:

  That’s fair. Comparing regular drivers doing typical city trips to commercial big rigs is a bit apples-and-oranges. I wonder how CDL data would compare when the self-driving semi-trucks start putting on miles. Aurora is about to launch in that exact space.

• ⁨Comment⁩ on ⁨After 50 million miles, Waymos crash a lot less than human drivers⁩ ⁨⁨1⁩ ⁨week⁩ ago⁩:

  Uber had a net income of 9.86 billion dollars and spent 7.14 billion in operations in 2024. That’s a single transportation company. Do you really think Uber or anyone else is going to ignore researching the technology that could significantly reduce their billions in operations costs?

  I’m also not so sure that Europe is 20x safer than the US. A quick search pulled up the International Transport Form’s Road Safety Annual Report 2023 and their data disagrees. The US, even with its really poor showing in the general numbers, is safer than Poland and Czechia (Road fatalities per billion vehicle‑kilometres, 2021). I could see an argument for a 2x gap of Europe outdoing the US, but a 20x? Citation needed.

• ⁨Comment⁩ on ⁨After 50 million miles, Waymos crash a lot less than human drivers⁩ ⁨⁨1⁩ ⁨week⁩ ago⁩:

  Why are we still doing this?

  Because there’s a lot of money in it. 10.3% of the US workforce works in transportation and warehousing. Trucking alone is the #4 spot in that sector (1.2 million jobs in heavy trucks and trailers). Couriers and delivery also ranks highly.

  The self-driving vehicles are targeting whole markets and the value of the industry is hard to underestimate. And yes, even transit is being targeted (and being implemented; see South Korea’s A21 line). There’s a lot of crossover with trucking and buses, not to mention that 42% of transit drivers are 55+ in age. Hiring for metro drivers is insanely hard right now.

• ⁨Comment⁩ on ⁨It’s SSB, But Maybe Not Quite As You Know It⁩ ⁨⁨4⁩ ⁨weeks⁩ ago⁩:

  You’re not off the mark. Honestly not a bad overview to squeeze into a few sentences. Here’s some extra detail for those who remain more curious.

  The circuit complexity reduction happens by changing the math behind the radio signal. Much like how you can describe a vector in cartesian coordinates (a point in x, y) or in polar coordinates (a point in angle and length), choosing how to represent the radio math allows for different techniques to arrive in the same answer. That’s what the author did: he picked a polar modulating scheme over a quadrature modulation scheme. (Note, there are even more mathy ways to modulate a radio signal, but those are what the author is presenting to us.)

  The author’s choice avoids generating unwanted frequencies that must be filtered out before amplifying. That’s components on the board that don’t need to be designed nor exist. A solid win.

  The drawback? Polar modulation is non-linear in frequency space. What that means is certain frequencies are over-represented and others are under-represented. Imagine playing notes on a piano where some keys are very loud and others you could hardly hear them. That’s the unwanted non-linearity.

  Herein lies the trick: what’s bad can be turned into good. Power amplifiers typically need to be linear. Imagine a piano that works fine but the auditorium’s loud speakers make it sound terrible. Those loud speakers would be a non-linear amplifier. The trick is that it’s possible to match the modulator’s non-linear behavior with a power amplifier’s non-linear behavior to end up with a clean signal! A non-linear piano and a non-linear loud-speaker can produce beautiful music! This engineering trick unlocks all kinds of non-linear power amplifier architectures (that’s the “C/E/F” described in the article) which are drastically more energy efficient than linear ones (linear designs max out around 65% efficient).