Like many C++ devs I hacked around in cmake for years, but not really understanding what I was doing or how to structure cmake projects. This was made worse as newer ways of doing things came into being.
If this sounds like you, do yourself a favor and go through these slides (or watch the talk they came from):
It really clarified things for me, but also avoids going too much into detail. You will definitely need more info as you go along, but you can look those things up in the docs. This presentation does a good job at showing the core essentials that you can build your knowledge on later.
While nobody is surprised, still feels like the beginning of the end of an era. I guess the only question is how long Nadal will hang on. My wife and I joke that Djokovic will still be crushing 20 year olds for years to come, but time catches all of us eventually.
It feels like it's worth mentioning that almost all pro tennis players declare residency in places like Monte Carlo to avoid taxes. This makes sense since they are on the road 90% of the year anyway so why pay super high taxes back home? Federer, however, retained his residency in Switzerland, paying very high taxes on his $130mm (!!) in winnings (not to mention all the other income from sponsorships, etc). In a world where wealthy people hyper-optimize to avoid paying their fair share, playing the "it's all perfectly legal!" card, it is comforting to occasionally see someone who says, hey, I have plenty, maybe I'll pay it forward a bit so the next generation can have the same opportunities I had.
Certainly Federer should be fine financially so its kind of gallant that he stuck with his native country. But I don’t really blame other tax optimizers. Tax regimes seem to me to all be predicated on the idea that everyone has an income that is steady or slightly increasing over time. Yes millionaire earners can afford to give up 50% of 1M year after year and still live well. But Working in a feast or famine niche job I can sympathize with the position of having a big payday and never knowing if one will come again. 50% hurts much more when its your life savings and you don’t know what your next job will be because you are hyper specialized.
In my memory it was Batman Begins (2005) that had if bad and started the trend, but you’re right about the first Bourne movie (2002) being somewhere near the start (as far as tent pole movies go).
At any rate it’s a super lazy crutch for bad choreography. Contrasted with something like the Indiana jones airplane fight scene with its wide shots of the action is like night and day.
Pépin heaps praise on Howard Johnson (the person), and has no kind words for his son, whom he blames for the restaurant’s decline. Mainly lack of adaptability as fast food hit the country, but then also drastically cutting quality in ingredients.
Pépin claims that he would take home frozen restaurant food (as it was shipped to the restaurants), reheat it, and serve it to his NYC “foodie” friends, including renowned French chefs, without them being able to tell. I actually believe this since most of the pre-prepared food were stocks and sauce bases which freeze just fine, and also take the most time to prepare.
Aside: Holy crap, are those french sauces hard to prep at home.
During lock downs I got into french sauces. The mother sauces, specifically the fond brun, are quite time consuming to make. I'm talking 2-3 days worth of time.
I mean, the pay off is amazing. I've had guests literally licking the china. But my lord, is it hard to do.
It's not as good as home made, but it's ~85% the way there, 90% with filtered tap water (in my experience).
Do be careful with a demi glace though, you do need to get their product for that. Just trying to reduce the water by half for the fond brun and calling it demi glace doesn't taste the same, at least to me.
Private jet travel being a particularly big one. Many companies claim their CEOs (even ones you’ve never heard of) need to travel private for security reasons.
Animals as Leaders wakes up my brain like nothing else. I think my brain is vaguely aware that what I am listening to is some sort of complex puzzle, but I don't have the knowledge of music theory to crack it, so instead it's just primed for whatever coding / math tasks I'm working on that I can solve.
I think this posts misses the most important piece, the real secret sauce, which is how do you sift through massive streams of data and separate the signals from the noise? And how do you do so continuously so that as soon as an edge evaporates you don't keep trading it?
I think the key insight they made here is much less sophisticated than many think. The usual guess is that all these math geniuses have some magic statistical models that tell them the answer, but I don't think that's it. There are known, good ways to detect these things, and most (if not all) hedge funds are aware of them.
I think the magic is in the systems engineering they have done. It is a system which is able to evaluate the quality of a signal as it would be traded. Traditionally, quants come up with models that they then backtest to "prove" before doing live trading. A lot of models that look great on paper, or on historic data, fall flat in real-world trading. Hedge funds spend significant time and resources on quality back-testing data and systems, and I think Renaissance has been able to take this to a whole new level.
This is all mainly a guess on my part, but based on the book The Man Who Solved the Market, which alludes to this system without going into details (obviously). It is much less exciting than some super sophisticated ML models or what-not that people imagine is the source of their success.
This post focuses on the leverage, which is great for goosing the returns, but isn't the whole story. Put another way, if you could magically be gifted some part of Ren, which you rather have their special leverage arrangements, or the signal vs. noise oracle?
No I think the magic is in the signal detection. Basically, there is only so much alpha in the market. RenTech gets to the signal first and exploits it before everyone else. Thats what makes this so hard. If they all know the same math to figure out where the current signals are, its about who is willing to take the risk of getting into the position before its clear its really a signal.
I used to work on investing using credit card data (which rentech uses). All the hedge funds can access the daily credit card data at the same time. The question is, where there is a huge amount of noise in some pattern in the data, the risk is still high entering a position on it. The fund that models that risk best and says, "when the unique number of credit card spenders at this company goes up, I buy", they make the most.
I think we are saying the same thing, but I am just elaborating on what "signal detection" means. The usual approaches at worst just don't work, and at best don't scale very well.
I am saying that (I believe) RenTech has taken a very holistic approach to signal detection and maintenance, rather than the very academic approach that used to be the norm. And even if a signal is found, they have to be weaved into the trading system gradually, and eventually removed when they no longer work. This is a very challenging problem and they are very good at it.
From the interview linked in my other comment here, they’re not likely doing anything particularly special. relevant quotes:
> Now we have some of the smartest people around, working in our hedge fund, we have string theorists we recruited from Harvard, and they're doing simple regression.
> the smarter you are the less likely you are to make a stupid mistake. And that's why I think you often need smart people who appear to be doing something technically very easy
> we had 7 Phd's just cleaning data and organizing the databases
I get what you're saying, and I would agree that the power of _most_ politicians is minimal compared to the absolute richest people in the world (so not just mere single-digit billionaires, unless their wealth is built on owning a platform, like Oprah).
However, read the book Charlie Wilson's War. Wilson had no money to speak of, but the book reveals the incredible power that he wielded, largely by sidling up to selective groups (like the Israeli lobby) and getting key committee appointments. And Wilson wasn't even a U.S. Senator! (Generally speaking Representatives have far less power than Senators)
Maybe even more so then now, it was very common for studios to step in and "fix" a movie. I.e., re-edit it. So any footage that existed was fair game to end up in the final movie.
Wilder would famously film the absolute minimum amount, so in his words, "there is only one way it can fit together." Or another line of his, "the only thing that should be left on the cutting room floor are tears and chewing gum."
I am not so confident that even in 8 years the outcome will be clear. Just like today Tesla is selling hot garbage and calling it "self driving", I am sure manufacturers will be selling cars that claim to satisfy the requirements of the bet, and even do so... sometimes. I am not confident they will work as reliably as the bettors here are intending, even if it is marketed as L5.
Edit: What I'm getting at is even though it is a friendly bet, they should define the terms of success / failure a little more clearly. Unless there is some governing body that grants L5 status?
Given that these gentlemen are known to have at least ordinary prudence, even in the face of a $10k loss, an operational definition might take the form
L5 = the person asserting that L5 has been achieved is willing to be driven by the vehicle, without access to the controls, through mixed conditions for X hours.
I feel that is pretty bad. It doesn't require system to actually work too well. It doesn't name anything about effectiveness of system. Just safety. Still, effectiveness might come to abstract things like:
L5 = vehicle can achieve similar travel times and destinations to average human driver in mixed conditions.
What if the car "works" under all conditions, but moves extremely slowly, takes huge detours to avoid tricky roads etc. In fact what is stopping this "technically correct" approach: car calls a human driven tow truck, gets hitched and towed to destination?
I don't really care for the L5 definition. Humans can't drive on all roads in all conditions even if their vehicles are theoretically capable of it. There are certainly weather conditions I don't want to be driving in. And there are certainly some unpaved roads I don't want to be driving on even with high clearance 4WD.
The realistic definition would be that if a human could not reasonably be expected to drive in it (fog/smog with less than 6 inches visibility, hurricane, blizzard, military invasion) then the cars are not required to drive it in. And perhaps the cars can accept a circumstance or two where humans can't drive, in exchange for one or two where humans could, but the cars can't. But it would need to be circumstances that humans can predict/understand. Like if the car won't drive if the countrywide car-to-car comms network is down or something.
Of course. I meant this in response to dharamon above talking about manufacturer's misleading claims. But I see their edit and I think I also misunderstood your point - in the context of this bet the selected criteria are probably good enough.
If the car moves extremely slowly in a major city, it would get banned after a handful of traffic jams, and so wouldn't be commercially available. And anyways no company would risk the bad PR of launching a car that tops out at below the speed limit.
If the car calls itself a tow truck, it has obviously failed to drive itself.
If the car is programmed to avoid tricky roads, it can't "drive everywhere in all conditions" per SAE.
Exactly. "All conditions" means all conditions. Once a self-driving 4WD truck can be relied upon to get me over Echo Summit pass on US-50 during chain control / whiteout blizzard conditions, then maybe, just MAYBE I'll start to take it seriously. "Full" self driving, at least as of 2022, relies too heavily on all cows being spherical.
If a company falsely claims level 5 they can be disproved pretty easily by some posts on twitter. If the stoppages are too rare to even show up there, then it might as well be level 5.
If this sounds like you, do yourself a favor and go through these slides (or watch the talk they came from):
https://github.com/boostcon/cppnow_presentations_2017/blob/m...
It really clarified things for me, but also avoids going too much into detail. You will definitely need more info as you go along, but you can look those things up in the docs. This presentation does a good job at showing the core essentials that you can build your knowledge on later.