About three years ago JD Long said
I like the term “Data Scientist” for now. I expect that term will be meaningless in 5 years.
Sounds about right.
John Tukey said that the best thing about being a statistician is that you get to play in everyone’s backyard. This morning I got to play in IsoTherapeutics‘ backyard. The most photogenic thing on the tour they gave me was their box for working with highly radioactive material with robotic arms. (There was nothing hot inside at the time.)
When I was in Amsterdam earlier this year, Daan van Berkel interviewed me for the Devnology podcast. We talked about my winding career path, the overlap of math and computing, bringing math and computing closer together, formal methods, etc.
The podcast was posted this afternoon here.
Related post: Looking like you know what you’re doing
Starting next week, @MedVocab will post two tweets a day, once in the morning and once in the afternoon (CDT).
I’ve stopped posting to @DailySymbol. It was a fun experiment, but it was time to wrap it up.
My most popular account, @CompSciFact, now has over 100,000 followers. It’s interesting how some Twitter accounts take off and some don’t. CompSciFact has done quite well but I’ve shut down several other accounts that never gained much of a following.
You can find a list of my accounts here with a very brief description of each. Some of the accounts are a little broader than the name implies.
This weekend my family went to Schlitterbahn, a waterpark in New Braunfels, Texas. (The German-sounding name of the park and the city are evidence of the large number of Germans that settled in this part of Texas.) I thought about several engineering questions while we were there.
Most of the rides involve sitting in an inner tube and floating down a course with rapids, waterfalls, swells, etc. At many points there are back currents. You could be headed toward a fall but then find yourself reversing direction. It’s surprising to have to work to make yourself go downhill. At most if not all these points there are employees standing in the water to grab hold of rafts and pull people in the right direction who need a little help.
One question I had is what causes the back currents. Ultimately you could solve Navier-Stokes equations, but it would be nice to understand at a more rule-of-thumb level how these currents work. It would also be interesting to see whether a park could reduce the number of guides while keeping the rides as fun. The guides also serve as lifeguards, so the park may need to position people in all the same spots even if they didn’t need as many guides.
The slowest person in the family was consistently yours truly. I’d start out in front and inevitably end up bringing up the rear. I was curious how I could be so inept at a mostly passive activity.
I was also curious how they designed the rapids to be so safe. You’re repeatedly tossed straight toward rocks — perfectly smooth artificial rocks, but still not not things you want to hit your head on — at a fairly high speed, and yet you never hit one. It has something to do with how they position jets to push you away from the rocks, but that would be interesting to understand in more detail.
Another thing I was curious about is what the park does with its water in the off-season. Schlitterbahn in New Braunfels is actually two parks, an older park that uses untreated water from the Comal river, and a newer park that uses treated water. When the parks close for the season, the older park must just let its water return to the river. (At least one of the rides ends in the river, so they’re already returning water to the river.)
The question of what to do with the treated water in the new park is more interesting. I assume they cannot just dump a huge volume of chlorinated water into the river. Aside from ecological consequences, I wonder whether they’d even want to dump the water. Is it economical to store the water somewhere when the park closes for the year? If not, do they store it anyway because they have no way to dispose of it, or do they treat it so that they can dispose it? I suppose they could circulate the water occasionally while the park is closed, though that seems expensive. I wonder whether different waterparks solve this problem different ways.
If I could propose a new ride for Schiltterbahn, it would be a video presentation about how the park was designed followed by Q&A with a couple engineers. This would be a terrible business decision, but a few visitors would love it.
Michael Keith rewrote Edgar Allen Poe’s poem The Raven to turn it into a mnemonic for pi. Keith’s version follows the original quite well considering his severe constraints. The full poem has 18 stanzas. Here I include only the first and last. The full version can be found here.
Near a Raven
Midnights so dreary, tired and weary,
Silently pondering volumes extolling all by-now obsolete lore,
During my rather long nap — the weirdest tap!
An ominous vibrating sound disturbing my chamber’s antedoor.
“This,” I whispered quietly, “I ignore.”
So he sitteth, observing always, perching ominously on these doorways.
Squatting on the stony bust so untroubled, O therefore.
Suffering stark raven’s conversings, I am so condemned, subserving,
To a nightmare cursed, containing miseries galore.
Thus henceforth, I’ll rise (from a darkness, a grave) — nevermore!
The number of letters in most words encodes a digit of pi. Words with 10 letters encode a zero. Words with more than 10 letters encode two consecutive digits of pi. The poem encodes the first 740 digits of pi.
When I did an independent study course with Ted Odell, he told me to get a copy of De Vito’s Functional Analysis and work every exercise. I don’t recall whether I actually worked every problem, though I believe I at least did most of them. I heard of someone who learned algebraic geometry by working every problem in Hartshorne.
Doing all the exercises in a book isn’t a bad way to learn something, though it depends on the book, what you’re trying to accomplish, and on the quality and quantity of the exercises.
Have you ever gone through a book working every exercise? If so, what book? How was your experience?
From the dedication of C. S. Lewis’ A Preface to Paradise Lost:
Apparently the door of the prison was really unlocked all the time; but it was only you who thought of trying the handle.
In context he was saying that Charles Williams had recovered a clear understanding of Milton that had been obfuscated for over a century.
That line made me think of a quote from Alexander Grothendieck (that I haven’t been able to find this morning) to the effect that progress in mathematics has often waited for someone to be bold enough to ask a simple question or introduce a simple concept.
Update: Thanks to Roland Elliot for providing the quote I was missing. Ronald Brown says that Grothendieck said in a letter to him in 1982:
The introduction of the cipher 0 or the group concept was general nonsense too, and mathematics was more or less stagnating for thousands of years because nobody was around to take such childish steps …
I’ve changed the appearance of this blog. If you find anything that’s broken, or if you have suggestions for improvement, please let me know. As far as I can tell, it seems to work OK on multiple platforms.
I’m more likely to implement suggestions that come with specific details. For example, if you say “I don’t like your theme” then there’s not much I can do unless you suggest an alternative. But if you say something like “I’d suggest changing this line of CSS because …” I can at least try it out.
Technology is all about trade-offs.
I find it more plausible when someone says a new technology has new trade-offs than when someone says a new technology is “better.” Rarely does one thing improve on another by all criteria, but often one thing is an improvement on another by the criteria you value most.
If you want to persuade me to adopt something new, you’ll gain credibility by being candid about its drawbacks. Explain by what criteria you think the new thing is better, by what criteria it is worse, and why the former should matter more to me in my circumstances.
Haskell uses a lot of ideas from category theory, but the correspondence between Haskell and category theory can be a little hard to see at times.
One difficulty is that although Haskell articles use terms like functor and monad from category theory, they seldom actually talk about categories per se. If we’ve got functors, where are the categories? (This reminds me of Darth Vader asking “If this is a consular ship, where is the ambassador?”)
In Haskell literature, everything implicitly lives Hask, the category of Haskell types, or in some subcategory of Hask. This means that the category itself is not the focus of attention. In category theory, functors often operate between very different classes of objects, such as topological spaces and their fundamental groups, and so it’s more important to state what category something lives in.
Another potential stumbling block is to think of Haskell types as categories and values as objects. That would be reasonable, since in computer science an “object” is an instance of a type. But the right correspondence is to think of Haskell types as categorical objects. Instances of types are below the level of abstraction we’re working at. This is analogous to how category theory treats objects as black boxes with no way to talk about what’s inside.
Finally, Haskell monads look a little different from categorical monads. Haskell’s
return corresponds directly to unit, usually written as η, in category theory. But Haskell monads have a bind operator
>>= while mathematical monads have a join operator μ. These are not equivalent, though you can implement each in terms of the other:
join :: Monad m => m (m a) -> m a join x = x >>= id (>>=) :: Monad m => m a -> (a -> m b) -> m b x >>= f = join (fmap f x)
To read more along these lines, see the Wikibooks article on Haskell and Category theory.
Update: Stephen Diehl suggested I mention the differences between the idealized category Hask and the implementation of the Haskell language. These are discussed here.
I’ve put down St. Augustine grass numerous times and it never did well until this year. I’d water it regularly all summer and yet most of it would die.
When I ordered a pallet of grass a few weeks ago, the farmer who grew the grass delivered it. He told me the trick was to water it heavily every day for one week, then water whenever you’d water the rest of your grass. For the first week, you want to water it so much that when you step on it you see muddy water bubble up. This breaks down the sticky clay soil that the grass comes in so that it will put roots down into the soil beneath. So far it looks like his advice worked.