This is more of a negotiation tactic against pharmaceutical companies that are marketing new wonder drugs that give terminal cancer patients 1% longer life expectancy for 10x more cost.
The drugs company can sell their new wonder drug to the UK for 80k a year, or not at all. That's why these drugs are so much cheaper in the UK than in countries such as the US.
> That's why these drugs are so much cheaper in the UK than in countries such as the US.
Well, sort of. The drugs come to us in the UK after the US customers have paid for the R&D. That's why they're cheaper; they're not being used to fund new drug discoveries.
Drugs dont come to the UK after R&D has been paid. UK/EU approvals times are often close to the US, but anticipated US revenue is what justifies the initial R&D spend.
E.g.
You are deciding if you will spend 1 Billion to develop a drug with a 20% sucess rate. Europe sales are projected at 2 Billion, and US sales at 10 Billion.
It is US sales that make the expected value positive. If the US paid European rates, the product would not be developed.
>The R&D funding came from the previous drug, not the current drug.
In practice, yes that is often the case, but it doesn't matter for the new drug development decision.
If a new drug is unprofitable, it doesnt matter if there are funds from a prior one. A company will invest it elsewhere instead of spending it on a revenue negative drug.
Similarly, If a new drug looks profitable but internal funds are scarce, the Company will secure funding or sell distribution rights to raise the funds.
The Key role that the US is currently playing to making drugs profitable to develop that otherwise would not be.
I have worked on several programs, and the question is always "what is the return on investment" and never "how much do we have in the bank".
I think it is more than just a negotiation tactic. Spending controls drive prioritization within socialized health systems. You cant spend "whatever it takes" for each person.
While there are certainly some areas like the City of London which are almost exclusively commercial/office, most of London, even the central parts, is a mashup of different land uses including residential. Not everyone commutes in from the suburbs.
You can take them on overground trains, though that's kind of restricted at rush hour. I imagine people mostly either cycle from their homes or leave the bike near a station.
This is an awesome view into the implementation details of python. Can anyone recommend other resources that go into the lower level python implementation?
I highly recommend Victor Skvortsov's exhaustive, 12-part series, "Python Behind the Scenes," a deep dive into the implementation details of just about every Python language feature one could possibly take for granted. There isn't a single one I haven't learned something from, but some of my personal favorites include:
The official description of this talk is below, but personally, I'd watch any video with "Raymond Hettinger" in the title.
> Python's dictionaries are stunningly good. Over the years, many great ideas have combined together to produce the modern implementation in Python 3.6. This fun talk is given by Raymond Hettinger, the Python core developer responsible for the set implementation and who designed the compact-and-ordered dict implemented in CPython for Python 3.6 and in PyPy for Python 2.7. He will use pictures and little bits of pure python code to explain all of the key ideas and how they evolved over time. He will also include newer features such as key-sharing, compaction, and versioning. This talk is important because it is the only public discussion of the state of the art as of Python 3.6. Even experienced Python users are unlikely to know the most recent innovations.
You can get a cheaper ticket with an agent than with an airline but this would be a ticket attached to certain conditions (for example, it can only be sold together with a hotel room)
Another possibility is that you do a search and find it per X and then go to an agent and they find it cheaper but because they know how to look around your dates and possibilities you might not know (connection alternatives, etc).
But to be fair, even if it's a little more expensive I prefer the peace of mind of dealing with one vendor instead of two vendors if anything happens.
> You can get a cheaper ticket with an agent than with an airline but this would be a ticket attached to certain conditions (for example, it can only be sold together with a hotel room)
Ticket pricing is unpredictable and really depends on your location and route.
A few times I used Expedia instead of the airline, and it was both cheaper and allowed flexible total unconditional cancellation within a short time after buying.
Quite helpful when you need to arrange multiple bookings, hotels, etc. on short notice with changing availability. Plus there’s that time I literally bought a same day ticket just to enter HKIA and meet arriving friend (a ticket was required due to protests). Returned it as soon as I passed the guards. With that low-cost airline it wouldn’t be possible directly, and even if somehow it was the ordinary refund would’ve taken days. (After I saw their ticket verification procedures I realized a even a well-done fake might have sufficed, but you don’t want to leave stuff like that to chance.)
That said, in some countries I have never seen agents offer better options than airlines.
The problem is that you're not dealing with one vendor though: you're actually dealing with N+1, where the +1 is just an opaque intermediary to the N services it's brokering/reselling.
When there are no issues, this works fine.
If there are issues? Be prepared to do the customer service tango, and hope that the person at check-in understands how $intermediary actually resells their stuff and knows the right knobs to twiddle, because otherwise you're shit outta luck.
> You are trying to use the word that once you get the match result back, it discards the most number of words.
This isn't strictly true either. Two N-sized subsets of words from a common initial set might have completely different difficulty in reducing further, because in the worst case there might not be a valid guess which nicely spreads the remaining words out among the 243 possible outcomes for that guess.
Set-size is a good heuristic, but it's just that - a heuristic.
Yes, as you'll see in the readme that I have numbers for both approaches. The first section is the average number of remaining words after getting the match result back, and the second section is the average number of yellow and green squares.
You might also try maximum instead of average. This is minimax and represents worst case scenarios for each guess.
This is mostly useful for optimal play against an opponent (which is not the case here). Imagine an adversarial version where the opponent doesn't have to commit to a word at the beginning but must reveal one matching all clues if you can't get it in 6 guesses (basically, they can change their word when you guess and you are trying to make that impossible).
The skill is in not leaving yourself with two words that would both fit. If earlier you had tried a word with both an 'm' and a 'g' such as 'image' you would not have been left in a position where you would have to have a lucky guess
It is much easier to work backwards with that logic than forward. It is impossible to both try to guess the word while also trying to eliminate all possible overlaps that may occur with whatever results you get from the previous word. In this specific instance, I would have never played "image" because my first word was "tears" so I immediately knew there was a t, e, and r. There was no reason to try to determine if there was a g or m until I was presented with "ti_er".
I do not. According to the original article, Wordle uses[1] 2,500 common words out of the 12,000 5-letter words in the english language[2]. I use the 5 letter words in the collins scrabble dictionary (which is about 12,000 words).
The assumption you need to make for my analysis to be correct is that the letter patterns in the 2,500 possible answers is statistically similar to the distribution of letter patterns in the original 12,000. There are probably some differences between the distributions, and I'd love to rerun my code with the actual word list Wordle uses, but in the absence of that list, I think that my code does about as good as possible.
[1] uses for the answers; I assume it allows all 12,000 for guesses.
[2] NYTimes does not specify which source they used
