Archive for Apple II

ten computer codes that transformed science

Posted in Books, Linux, R, Statistics, University life with tags , , , , , , , , , , , , , , , , , , , on April 23, 2021 by xi'an

In a “Feature” article of 21 January 2021, Nature goes over a poll on “software tools that have had a big impact on the world of science”. Among those,

the Fortran compiler (1957), which is one of the first symbolic languages, developed by IBM. This is the first computer language I learned (in 1982) and one of the two (with SAS) I ever coded on punch cards for the massive computers of INSEE. I quickly and enthusiastically switched to Pascal (and the Apple IIe) the year after and despite an attempt at moving to C, I alas kept the Pascal programming style in my subsequent C codes (until I gave up in the early 2000’s!). Moving to R full time, even though I had been using Splus since a Unix version was produced. Interestingly, a later survey of Nature readers put R at the top of the list of what should have been included!, incidentally including Monte Carlo algorithms into the list (and I did not vote in that poll!),

the fast Fourier transform (1965), co-introduced by John Tukey, but which I never ever used (or at least knowingly!),

arXiv (1991), which was started as an emailed preprint list by Paul Ginsparg at Los Alamos, getting the current name by 1998, and where I only started publishing (or arXiving) in 2007, perhaps because it then sounded difficult to submit a preprint there, perhaps because having a worldwide preprint server sounded more like bother (esp. since we had then to publish our preprints on the local servers) than revolution, perhaps because of a vague worry of being overtaken by others… Anyway, I now see arXiv as the primary outlet for publishing papers, with the possible added features of arXiv-backed journals and Peer Community validations,

the IPython Notebook (2011), by Fernando Pérez, which started by 259 lines of Python code, and turned into Jupyter in 2014. I know nothing about this, but I can relate to the relevance of the project when thinking about Rmarkdown, which I find more and more to be a great way to work on collaborative projects and to teach. And for producing reproducible research. (I do remember writing once a paper in Sweave, but not which one…!)

Alien Xmas

Posted in Books, Kids, pictures, Travel with tags , , , , , , , , , , , on December 25, 2020 by xi'an

As I had never watched an Alien film in its entirety, while having glimpsed some portions from my neighbours’ screens on many a long distance flight, I decided to indulge into the series over the Xmas break, which was sort of relevant since both stories are about an alien species parasiting a human body to grow their children… (Aliens 3 actually offers a further religious thread as the population of the convict planet Fiorina 161 is made of Christian-like sociopaths.) The first and most famous film, Alien (1979), is certainly the most interesting in that it looks quite its age, from old fashion space vessels and equipment, to [vim type!] green light pre GUI computer interface reminding me of my first Apple II, to everyone smoking in the space ship. While the scenario is on the light side, although the underlying theme of a super-adaptive, super-aggressive and super-intelligent alien species is most compelling,…

…the greatest appeal of the film (as in the greatest horror masterpieces) is in keeping the grown alien as hidden as possible with only glimpses and sudden dashes in poor visibility. Besides Jones the cat, Sigourney Weaver is really giving the film its backbone, growing as it proceeds, as the other actors are somewhat transparent (or are unhappy with their early demise!). I read that her role was originally planned for a male actor, which would have emptied the film of all its appeal faster than opening a space shuttle door expels an unsuspecting alien… Weaver moves to a form of Rambo pastiche [duck-taping two weapons into one at some point!] in the second installment, Aliens (1986), while keeping the leading role against a platoon of space marines and keeping the high moral ground against the profit-obsessed Company amoral representative. Having a heavy weaponry component (as in so many blockbuster movies) makes the film more efficient but also less outstanding than Alien (and who would fire grenades and such in the vicinity of a nuclear reactor!). There is an interesting opposition in Weaver fighting tooth and nail (and flame-thrower) to save the surviving human child while destroying the children of the other species and ultimately the alien mother queen (who can manage an elevator on her own, mind you!). It could have brought out an Ender’s moment… This second episode is much less old-fashioned and again falls more within the standard of the genre, but with such efficiency that it keeps up with the original. And with this, I almost let the remaining films in the franchise rest in peaceful horror.

And I should have stopped there. But reading that William Gibson was involved into writing the scenario of Alien 3 made me indulge farther into the series. Which in its description of the penal colony planet had some dystopian feel that indeed relates to part of the political sci’-fi’ literature, with the paradox that the colony has no computer (and no weapon). One cult scene is when Weaver gets her hair shaved, for preventing lice infestation (in the scenario) [rather than for getting rid of a terrible hairstyle!] and to fit a return to pre-modern times, when melting furnaces were top of the industrial chain. While the very final scene of Weaver’s almost Christic sacrifice redeems a somewhat messy scenario (which in some versions properly erase the last alien emergence), closing the cycle. The end. No jesurrection!

future of computational statistics

Posted in Books, pictures, R, Statistics, University life with tags , , , , , , , , , , , , , , on September 29, 2014 by xi'an

I am currently preparing a survey paper on the present state of computational statistics, reflecting on the massive evolution of the field since my early Monte Carlo simulations on an Apple //e, which would take a few days to return a curve of approximate expected squared error losses… It seems to me that MCMC is attracting more attention nowadays than in the past decade, both because of methodological advances linked with better theoretical tools, as for instance in the handling of stochastic processes, and because of new forays in accelerated computing via parallel and cloud computing, The breadth and quality of talks at MCMski IV is testimony to this. A second trend that is not unrelated to the first one is the development of new and the rehabilitation of older techniques to handle complex models by approximations, witness ABC, Expectation-Propagation, variational Bayes, &tc. With a corollary being an healthy questioning of the models themselves. As illustrated for instance in Chris Holmes’ talk last week. While those simplifications are inevitable when faced with hardly imaginable levels of complexity, I still remain confident about the “inevitability” of turning statistics into an “optimize+penalize” tunnel vision…  A third characteristic is the emergence of new languages and meta-languages intended to handle complexity both of problems and of solutions towards a wider audience of users. STAN obviously comes to mind. And JAGS. But it may be that another scale of language is now required…

If you have any suggestion of novel directions in computational statistics or instead of dead ends, I would be most interested in hearing them! So please do comment or send emails to my gmail address bayesianstatistics

Steve Jobs: 1955-2011

Posted in Travel, University life with tags , , on October 7, 2011 by xi'an

I bought my first Apple in May 1983, it was an Apple IIe computer, just out from the factory, and I spent most of my savings on the [approximately 13,000 francs] 8K machine. Then most of my summer programming in Pascal games and algorithms. (I even had a special suitcase built by my brother-in-law to carry the thing back and forth between Paris and Normandy, on the train! An early version of the portable computer.) This Apple computer did run most of the simulations for my thesis on the James-Stein phenomenon, running for days and days, the top lid often removed to let the heat out.

In 1991, I brought an Apple Macintosh IIc back from Purdue. I remember that the custom officer in the airport was so clueless about computers that he asked me whether the RAM was under 64K or not. I used this second Apple computer at home for writing my first books and for logging to the Paris 6 mainframe by shaky modem connections, but not for computing apart from some Mathematica formal calculus. (At that time, CREST still did not have Internet and I had to rely on the rudimentary Minitel…) Then in 1996 we bought a PowerMac that was so pleasantly efficient (a NeXT would have been even better but the cost was just too high without a research grant!) that we kept using it till 2000 or 2001 (when my then young son ruined the CD reader by stuffing all his color pen into the slot). At that point, I had moved to exclusively using Linux and laptops, so there was little point (and even less money) in buying Macs, and it is only three years ago that I tried using them in conjunction with an Ubuntu system, not a perfect combination but smooth enough for my own purpose and idiosyncrasies… (Plus the guaranty of reliable material and hardware.) Thus, a long and still going relation with Apple computers. Hence a sincere salute to Steve Jobs for his vision and charisma in keeping the technology and innovation ahead of the crowd over these 35 years.

(Counterpoint #1: I am always wary of the easy trend to turn individuals into geniuses without accounting for their environment: Mr Jobs was head of a huge company with an army of engineers, designers, publicists, &tc. and they contributed to the success of Apple, the more as the years went on, I presume. So I have more trust in the law of large numbers than in black, gray, or white swans. Nonetheless, it can be argued Apple would not have impacted our daily life the way it did without Steve Jobs. An exception to my rule above.)

(Counterpoint #2: Apple is a commercial company. That it delivers fairly good products and keeps an innovative research policy does not absolve it from corporate flaws. Nor does it exclude other high tech companies from delivering other types of innovation.)

Randomness through computation

Posted in Books, Statistics, University life with tags , , , , , , , , , , , , , , on June 22, 2011 by xi'an

A few months ago, I received a puzzling advertising for this book, Randomness through Computation, and I eventually ordered it, despite getting a rather negative impression from reading the chapter written by Tomasso Toffoli… The book as a whole is definitely perplexing (even when correcting for this initial bias) and I would not recommend it to readers interested in simulation, in computational statistics or even in the philosophy of randomness. My overall feeling is indeed that, while there are genuinely informative and innovative chapters in this book, some chapters read more like newspeak than scientific material (mixing the Second Law of Thermodynamics, Gödel’s incompleteness theorem, quantum physics, and NP completeness within the same sentence) and do not provide a useful entry on the issue of randomness. Hence, the book is not contributing in a significant manner to my understanding of the notion. (This post also appeared on the Statistics Forum.) Continue reading