jonp

The URL of the equation image contains the equation in TeX.

The page http://www.benjoffe.com/holdem_files/heuristic.html is running the two-player case. It seems to be using a Javascript hill-climbing algorithm: pick a scoring function which measures how good the solution is, then start from a random deck and try small changes, keeping them only if the score improves.

He's actually talking about 24! not 25!. (Maybe because the free square is in a fixed position?)

24! = 6.20e23; and Avogadro = 6.02e23.

I thought the OP was alluding to the slight ambiguity because 1 appears twice in the Fibonacci sequence. You could interpret the approach two ways and do either 21 + 8 + 2 = 31 km or 21 + 8 + 1 = 30 km. Happily these span the correct answer of 30.55km.

Also, Rot13 contains the longest pair.

Here's a list of all words (in sowpods.txt) of six or more letters which translate in rot-N for some N:

   1   anteed   bouffe
   1   azlons   bampot
   4   ganjah   kernel
   4   lallan   pepper
   6   fusion   layout
   6   alohas   grungy
   6   jigjig   pompom
   6   bombyx   hushed
   6   mulmul   sarsar
   7   inkier   purply
   7   manful   thumbs
  10   muumuu   weewee
  13   cravat   pening
  13   harira   uneven
  13  abjurer  nowhere

(sowpods.txt is at http://code.google.com/p/scrabblehelper/source/browse/trunk/...)

The relevant numbers from the paper:

  1230186684530117755130494958384962720772853569595334792197322452151726400507263657518745202199786469389956474942774063845925192557326303453731548268507917026122142913461670429214311602221240479274737794080665351419597459856902143413
  =
  33478071698956898786044169848212690817704794983713768568912431388982883793878002287614711652531743087737814467999489
  *
  36746043666799590428244633799627952632279158164343087642676032283815739666511279233373417143396810270092798736308917

Apparently placebos are effective, even when you know it's a placebo. See http://www.placebo.com.au/node/31 for a reference to research on this (on the site of a company that sells placebos...)

See "The pie fallacy" in http://www.paulgraham.com/wealth.html.

It's good. I would have found this helpful a few years ago.

How about putting the tables into normal form? ie where you currently have the company name as a string in the Person table, instead have an ID which references the Company table. It's not necessary for understanding the example shown, but it can't hurt to start off with good practice.

Yes please: http://mailhide.recaptcha.net/d?k=01Pk6P0EgEIu1GnKZfGDGi1w==...

Thanks. For some reason I was thinking of old-fashioned wooden wheels rather than modern car wheels. I guess someone figured out the physics at some point and there was no looking back.

Another book of his on a different topic but with same great clarity of explanation is "Information Theory, Inference, and Learning Algorithms". The PDF is on his site at http://www.inference.phy.cam.ac.uk/mackay/itila/book.html.

I wonder why they chose a wheel with seven spokes. I don't recall ever seeing one with an odd number.

I guess it's hard to give an answer to an ambiguous input that will please everyone. Personally I would have expected the 1st of the month.

It seems unusual that "next June" and "last June" both pick the 4th of the month (today's date); but just "June" gives the 1st of the month.

Also "next June" gives "Friday, June 04, 2010 12:00:00 AM" so it picks the day of the month based on today; but the time of day doesn't depend on the time now.

Of the top ten entries eight used C++ and two used Java. I used Python.

Zookeeper.

Wolfram Alpha lets you get the position. eg http://wolframalpha.com/input/?i=sun+at+9am+in+London

The part about thinking hard then stepping away from a problem before the eureka moment reminds me of "A Technique for Producing Ideas".

http://books.google.com/books?id=a8EqjMJXXEMC&dq=a%2Btec...

The original quote in context on HN: http://news.ycombinator.com/item?id=179639

A small proportion in cash (enough to survive for a year or two if I want to stop being employed). The rest in equity index funds, spread between UK, US, Europe, Japan/Pacific. Some of those equities are in retirement funds for the tax advantages, and for the discipline of not being able to spend them any time soon.

That seems reasonable for me now, as someone who's young and employed. My future earnings ("human capital") are likely to be bigger than my current financial assets (because I'm young) and fairly steady and bond-like. As I get older, or if I become self-employed, I would move more of my financial wealth into safer assets (eg long-dated index-linked bonds).

If you can do medium-term (over the next year) then consider trading weather derivatives. Such contracts pay out on eg the number of warm days being higher/lower than consensus.

I'm just curious what happens when the comments get really thin.

MA Mathematics from Oxford; MSc in 'Evolutionary and Adaptive Systems' from Sussex.

"1089 and all that" by David Acheson is charming and very readable. It covers a variety of different types of maths but more importantly get across what maths is really about. I've bought it for friends and family with a wide range of maths backgrounds (graduate mathematicians to not-since-school-forty-years-ago).

Also "Alice and Numberland", Baylis and Haggarty; and "The Foundations of Mathematics", Stewart and Tall. These are both pitched somewhere between high school and university level and bridge the gap well.

Grew up with computers (started with a ZX-80) but for some reason lost interest as a teenager. Maths degree at university; mainly pure maths, group theory, number theory, topology etc.

Didn't want to do research so sought a mathsy job and joined an actuarial consultancy, advising pension schemes through calculations and mathematical models. Found out that it was less technical than I'd expected and consulting was quite repetitive. Unofficially carved out an hour or so each day to get better at broader finance theory (derivative pricing, corporate finance etc) and programming, and re-discovered why I liked computers so much as a youngster. Not a well-defined career path, but more a case of doing things I found interesting, earning trust, and pushing myself and the firm in different directions.

Then quit and did an MSc in artificial life for a year - unrelated but challenging and great fun.

Then back to the same company, doing similar things. I'm reminded of an article posted here a few months back saying that it's tough to be the best in a narrow field, but being in the top decile in lots of areas is easier and makes you valuable. I'm not the world's best programmer, mathematician, finance theorist, researcher or communicator; but I'm not too shabby at any of them and the combination seems to work well, particularly when coupled with a good knowledge of a particular domain (pensions in my case).

Some parallels to the startup world, even though I work for a big firm. In particular pg's The Power of the Marginal (http://www.paulgraham.com/marginal.html) resonates and translates to my own experience.

R&D unit of a actuarial consulting firm. Problem-solving and hacking in areas where pensions, investment, finance and technology meet.

Agreed. There's quite a diversity of solutions ranging from brute-force, through "computer science" optimisations, to clever mathematics. And as someone who had mainly programmed in various versions of Basic before it's been eye-opening to see a range of different languages and their strengths and weaknesses. In particular some of the solutions in J (http://www.jsoftware.com/) struck me as quite remarkable.

Not sure if it's the one albertcardona was referring to; but this sounds like Thomas Ray's Tierra simulator. Details at http://www.nis.atr.jp/~ray/pubs/tierra/tierrahtml.html

From his abstract: "Digital organisms have been synthesized based on a computer metaphor of organic life in which CPU time is the 'energy' resource and memory is the 'material' resource. Memory is organized into informational 'genetic' patterns that exploit CPU time for self-replication. Mutation generates new forms, and evolution proceeds by natural selection as different 'genotypes' compete for CPU time and memory space. In addition, new genotypes appear which exploit other 'creatures' for informational or energetic resources."

Or poormanatee to follow zach's adjective + animal line.