Shameless plug of my old dead project: this is great, it reminds me of my Android app "Smozzy" which let you browse the web via SMS/MMS. I apparently posted it on HN exactly 10 years ago tomorrow! https://news.ycombinator.com/item?id=2976764
That was a summer project after my last semester of undergrad, posted at the beginning of my first semester in a PhD program in AI (lucky timing there). Graduated in 2017 and have been working in the field since.
I tried GP's example, and in this particular case both --patience and the default (Myers) work the same, both doing the thing you want them to. Which perplexes me, because I know I've seen the bad case too, but can't seem to find a minimal example of it (I tried a couple variations on the example; they all did the 'right' thing).
You are correct; they both go to the same page. One is a direct link to Doudna's comment, the other to Charpentier's comment on the same page... but since the page is so short, there is nothing to scroll to, so they look like they are the same link.
> According to this Consumer Reports article, “the median car costs more than $9,100 a year to own” over the first five years of ownership driving 12,000 miles a year. That means the median cars costs about 76 cents per mile driven ($9100/12000). I’m just guessing that I’ll average a speed of 30 miles/hour while I’m doing my Lyft job. So my expenses will come to about $22.80 per hour (0.76*30).
Doesn't that $9100 a year median include a bunch of fixed costs (or at least costs that wouldn't grow linearly with the mileage driven)? e.g., the lease/cost of car itself, insurance, etc. I'm not saying this would take the profitability of being a Lyft driver from pretty terrible to great, but it does seem like a pretty significant oversight.
But it's not like his car payment magically disappears when he becomes a Lyft driver. Or magically stop having to carry insurance. It's a good estimate to use for cost, especially considering the author did not even own a car and would have to purchase one.
> But it's not like his car payment magically disappears when he becomes a Lyft driver. Or magically stop having to carry insurance.
Right, my point is that those costs are essentially fixed w.r.t miles driven, not that you wouldn't need those things. If you drive 36000 miles a year as a Lyft driver your car payment is still the same as someone who drives 12000 miles a year, whereas the author's model assumes the payment would be 3x as much. And re insurance, I know insurance companies take mileage into account in determining insurance premium, but it's certainly not the only thing in the formula.
Ah, I misunderstood. Yes, you are correct. I would use the US government's rate per mile, which comes out to about $17 for 30 miles. Unknown what components this is expected to include beyond fuel and wear/tear.
EDIT: Found further clarification. "The TDY mileage rates consider the fixed and variable costs to operate a car (gasoline, insurance, wear and tear, etc.) and are intended to reimburse the average expense of using a POC for the official government travel."
Drive 36k miles a year and the car will quickly have a resell value of 0 and repair costs become more frequent. Insurance is probably the only true fixed cost that benefits from scale
If you were going to approach this in a purely economic-rationalist manner, you'd (probably) discover that buying cars new is wasteful - and that you want to look for late-model full-service-history low-mileage second hand cars in the 2 or 3 year old range. The original owner will have borne the brunt of the capital depreciation, and you can drive higher-than-average-yearly-mileage for a few years while "low mileage" to "slightly high mileage".
(Where I come from, Australia, there are tax breaks that make 3 year old cars fresh off company-car leases pretty commonly available - many people structure their salary package in a way the strongly encourages them to lease a new car every 3 years, and off-load the previous one for often 35% of its original purchase price - and to have those cars get all their required dealer servicing done using pre-tax salary.)
I agree that repair costs and depreciation grow (probably roughly linearly) with miles driven, but those would have been factored into the $9100 median separately from the car payment.
I think what he means is that you cant turn those costs into a "cost per mile rate" since that rate will decline once you excedd 12000 miles assuming a bunch of the costs are fixed costs.
But I don't know, if you're exceeding 12k miles working for Lyft, im sure the cost/benefit analysis takes on a whole new life.
But he calculated his per mile costs using 12000 miles per year. A taxi driver is going to drive far more than that, so the fixed costs will contribute a smaller amount to the per mile cost.
The $9100 number skews the analysis for several reasons. First, it does include fuel, depreciation, interest, insurance, repair, maintenance, and tax - see the linked Consumer Reports article for details.
Second, $9100 is the median number, not the mean or "best price available." The article lists other cars that have numbers closer to $5000-$7000, and all the numbers are lower if you keep the car for longer than 5 years.
Finally, the article says that "Depreciation is the largest cost factor by far," and that it contributes about half of the cost of ownership. Buy a 1-2 year old car, and your cost of ownership will drop considerably.
It's amortizing the cost so it makes sense. The real thing missing is assuming all the miles are lyft miles, and assuming the car provides no value outside of lyft
"Works like a debit card when you swipe it" - I'd probably get this if I wouldn't effectively be paying several hundreds of dollars per year for it in losses of credit card rewards.
> One thing that annoys me about closed ranges (and it's not much talked about) is that it is impossible to express the empty range: in python [i:i] is an empty range, while closed ranges always contain at least one element. That makes closed ranges strictly less expressive than half-open ranges, making often necessary to write special cases for zero-length.
In matlab/octave you can write an empty range as a(i:i-1). Not to say that that's at all elegant or aesthetically appealing, but it does work. But I 100% agree with the sentiment; one of my favorite things about using NumPy rather than matlab in my research code is the vastly superior indexing, in large part due to the fact that it's 0-based. matlab's indexing really is painful and off-by-one-error prone for doing anything other than a(1:n).
> In matlab/octave you can write an empty range as a(i:i-1). Not to say that that's at all elegant or aesthetically appealing, but it does work.
I agree, it feels like an ad-hoc workaround (BTW, I didn't know that).
It kind of makes sense once you mentally reverse-engineer what Matlab is doing underneath, since ultimately the indexes are pointers, but from an abstract point of view there is no mathematical notation where the second endpoint of an interval is smaller than the first. If you go down that road, now you might ask what is (i:i-2) and so on.
Scenario A: The setup is (1) lose $100, gain 1 ticket (current state is -$100, +1 ticket); (2) lose 1 ticket (current state is -$100, 0 tickets). The choices are (a) lose $100, gain 1 ticket (yields state -$200, +1 ticket) or (b) do nothing (yields state -$100, 0 tickets).
Scenario B: The setup is (1) lose $100 (current state is -$100, 0 tickets). The choices are the same as above.
The final 'state' at the end of each setup is the same, and the choices are the same, so the argument is that a rational actor would make the same choice in both situations. Maybe there's an argument that the state should include more than just $ and tickets though?
Often, anticipation is what ruins a movie. All of the best movies I've seen (The Matrix, Fifth Element spring to mind) had such obtuse trailers that I had no idea what was going on before I got in there.
Are all the bot reservations actually made with the intention of a human going to the restaurant? I wouldn't be surprised if some people used these bots just to prevent anyone else from making online reservations and screw with the restaurant/customers.
Based on the bot's code [1], it looks like all they ask for is a phone number and an email address. It might be a good idea to at least require a captcha, if not a credit card deposit of a few bucks.
