Archive for April, 2007

Python up, Ruby down: If that runtime don’t work, then its bound to drizzown

April 28, 2007

Great explanation of why Toby moved from Python to Ruby (with a few notes about Perl too) in Python up, Ruby down: If that runtime don’t work, then its bound to drizzown.

(via LinkBlog)

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Energy neutral

April 22, 2007

In His energy bill is $0.00 Christian Science Monitor talks about inventor Michael Strizki who has not only made his home carbon neutral, he actually powers everything himself. He uses solar panels to power his home. The surplus of power this produces in the summer turns water into hydrogen, or at least half of it does: the other half is wasted. Some experts say that he’d do better giving the excess power back to the grid instead. Strizki uses up the remainder of the power in the winter and to fuel his home-grown hydrogen power car.

Pretty impressive, and as he says: although he’s got some criticism, no-one has says it won’t work. It cost him a cool $0.5 million to build, but he is now looking to find a way to copy the system and get that down to $80,000, or less in places where the solar panels are subsidised.

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The next step…

April 16, 2007

The next step for the ‘plex does not seem so far away.

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Google has 80% of the online advertising market

April 16, 2007

The FT reports that Brad Smith, Microsoft’s general counsel says ‘Between them, Google and DoubleClick account for “over 80 per cent of the adverts delivered to website publishers, so their combination in a single company has big ramifications,”’ . Stunning.There are comparisons all over the blogosphere to Microsoft in the 1990’s. Is this the beginning of the end?

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Is Google money laundering?

April 16, 2007

Alan Rimm-Kaufman says that based on some simple assumptions it’s likely that Google would have actually earned $40k-$200k from Clickbot.A, the virus in question. It was discovered by Panda, an antivirus company, not by Google itself. He rightly asks, when were the clicks made invalid? Similarly, how many other click frauds are going on that Google is not catching, and perhaps does not mind not catching.

A mate of mine just called up and asked “Why would Google really invest serious money in trying to stop click fraud?” (He, like me, is a cynic, which is probably why he is also such a good intrapreneur). At best, they are going to try to build themselves a solid case against class action suits in the plausible likelihood that down the line somewhere there will be clear evidence of Google malfeasance, the soft underbelly of an . This could be a few Googlers who actually participate in real fraud.

Not doing evil is one part, but doing no good is also pretty easy when you’re so big. Alan writes “One surmises the bot authors may not be native-born English speakers due to some awkward verb use: ”holded“, rather than ”held“ or ”on hold“, and ”ThisIPIsClick()“ rather than ”ThisIpIsClickable()“ or ”ThisIpCanBeClicked()“. Similarly, one surmises they’re not earning US rates for web programming talent — according to Google, this scheme didn’t generate much cash, even with 100k bots.” So, forget about the Patriot act: someone is paying crackers with poor English to build a virus, then getting all their funds back on Google cheques to a legitimate company. In this way, the scheme can just break even instead of making profit, because the value comes from money laundering. This is the more likely future scenario: running a monopoly, not doing a whole lot to stop criminals using it to convert dodgy money into safer money and paying you a hefty bribe at the same time.
Apogee Weblog calls the analysis of Clickbot.A ‘handwaving‘: leaking analysis to the press seems a lot easier than actually taking some action. Apogee suggests that there are some much more significant structural flaws to the Google network that require fixing and talking about sophisticated botnets is some great misdirection.

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Structure of a Click Fraud Botnet

April 15, 2007

Structure of a Click Fraud Botnet is an interesting introduction into how Click fraud can be perpetrated using a ‘botnets’. The more detailed technical paper explains that a clickbot is a software robot that clicks on ads to help an attacker conduct click fraud — i.e. earn money from PayPerClick advertising with ‘fraudulent’ clicks. Bad clickbots infect machines in order to get many different IPs to form a ‘botnet’. Many of the popular virus scanners did not detect clickbot viruses. One example grew relatively slowly but still at an impressive rate of just over a 100 machines in mid-May to more than 100,000 in mid-June.

(via LinkBlog)

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Why Aren’t Application Development Managers Paid More?

April 14, 2007

David Andersen argues in Why Aren’t Managers Paid More? that “a geek can earn more as a contractor than he or she could make suffering through 10 years of climbing the corporate ladder as a manager.” He suggests that a root cause of Application Development managers not being paid a substantial premium over technical workers is that as an industry technologists (by which I include managers too) look for a technical solution instead of a people or process solution to problems. Similarly, many of these technical solutions are temporary, so companies look for part temporary workforces. For this reason, the market pays a premium to technical ‘guns’ who, typically as contractors, are sufficiently confident in the their technical skill and ability to renew that skill that they will take on the additional risk of a short-term contract.

The decision to use a technology rather than change a process or an organisation often comes from the top. There remains a knee-jerk belief that a technology can save the day even when it does not change the operation of a constraint. Look for example, at Goldratt’s classic example, ERP. This approach especially true of technologists
I note that businesses generally reward business performance far above mere technical performance if that comes with real business responsibility, i.e. if your job is to deliver real value and that happens to be through software development. In my experience, companies normally interpret ‘real value’ as things like revenue increase, profitability improvement, cost reduction or a throughput increase. For instance, delivering a software development project that has an intended benefit of reducing cost is very different from committing to reducing cost, and companies show that difference in the salaries for these two jobs.

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Just how importance intelligence is to getting a job

April 9, 2007

One of the twenty or so books that I am ploughing my way through right now is ‘Hard Facts, Dangerous Half-Truths & Total Nonsense‘. It is all about how evidence-based management can actually help you improve the way that you manage today. In there, I read the frankly gobsmacking news that IQ was the best predictor of job performance. Gobsmacking because I have had a long love-hate affair with IQ and finally turned myself over to the dark side by trying to understand and leverage Gardner’s theory of multiple intelligences.

When I was in my early teens, my idea of fun was doing taking self-tests for IQ (which only begins to tell you the kind of childhood I had). This is the bad old-fashioned IQ that everyone loves to hate these days focussing almost solely on linguistic and logico-mathematical intelligence. I learnt quickly what many found out before me: it is pretty simple to learn how to improve your scores on these types of test. Mine were high and only got higher. It only helped that my greatest strengths were reading, numbers & arithmetic patterns. Later, when I did training with a group of leaders from Razorfish, I found that there were plenty of other people who much more advanced in emotional intelligences. We learned there (and I read in subsequent books such as this or this) that these other intelligences were much more potent. So how come that linguistic and logico-mathematical intelligences win out in being good at your job?

The answer — and why Pfeffer and Sutton call it a ‘half’-truth — seems to be just how good a predictor IQ actually is. It typical correlates less than 40% with job performance, i.e. 84% of job performance is not caused by IQ. What is jaw dropping here is that this is the best predictor of job performance of which we know, i.e. it is very hard to predict job performance at all.

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Ob-sense

April 9, 2007

Plain text just seems to fall short for describing browse-experiences. I start with Nelson’s Linkblog and jump off to evan_tech to read about just how devious some hackers are in circumnavigating the large chunks of cleverness put in their way. Feeling a little down in the dumps and in need of some real deep hackiness, I dive yet deeper. This is a superb exposition: even with my basic background in heaps and garbage collection, it is remarkably easy to understand, with plenty of mini-tutorials along the way. I take a side exit and poke about a bit in evan’s life, where I enjoy an old classic Unix story. Looking at his livejournal, I enjoy the dual-language Siddhartha notes and I find a link to some obscene music lyrics.
-*–*–*–*–*–*–*–*–*–*–*-
Warning Will Robinson: I mean some REALLY obscene music
-*–*–*–*–*–*–*–*–*–*–*-
so if you are easily offended, do not following this link. I found the lyrics pretty gross, but what surprised me is an AdSense link to a Dutch mobile site. Do they really want to be associated with this kind of page? I’m guessing it’s an affiliate link but still… Alternatively, maybe this is exactly the yoof audience that they are after. Backing up I browse the Burg, but can’t get into and I swap back to the show with Zefrank, which is still amazingly good.

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Cocoa vs Perl

April 9, 2007

I have spent about three months off and on (OK: almost exclusively off with the occasional evening once every fortnight on) trying to write a very simple app in Objective-C and Cocoa (with me new MacBook Pro). The idea was to take a selection of stocks, and:

  • Mark them to market — i.e. state the current value and the gain or loss since they were bought
  • Mark them to an equivalent selection of indices according to the 3-factor model. This states that a stock’s size, value vs growth status, and market are the determinant of about 96% of the stock’s price.
  • Maybe extend to back test using historical data
  • Maybe extend to non-equity securities, e.g. bonds, forex or commodities

In that time, I have managed to learn a good deal of Objective-C, X-Code, Cocoa, Foundation and even a little bit of the quixoticly wonderful Core Data. However, very little real working code is coming out the other side.

My brother said: never mind that, choose a different language. We were talking Python, Ruby or Perl. Since I have a pretty long background in Perl hacking (but stopped a few years ago along with the rest of coding), I tried that. Within a day, I have a program that takes an associated array of stocks, prices and share quantities, retrieves todays prices and calculates the gain or loss. CPAN has come on a lot since I last check it out, plus having a Unix shell seems to make everything a lot easier. Half the day was spent with CPAN getting necessary modules working (hint for complete lusers: get your root account working before installing). Two hours were spent learning TextMate (Mac users: don’t hesitate, download it now). And the rest of the time reminding myself how just hashes worked. Result:

#!/usr/bin/perl

use Finance::Quote;
my @funds = (”DFVEX“, ”DFREX“,”DFCEX“, ”DFIEX“);
my %quotes = Finance::Quote->new()->yahoo (@funds);
my %costs = (‘DFVEX’,11.46,’DFREX’,32.25,’DFCEX’,14.08,’DFIEX’,12.23);
my %shares = (‘DFVEX’,100,’DFREX’,100,’DFCEX’,100,’DFIEX’,100);
my $total=0;
my $gain=0;

# print stats
foreach $f (@funds) {
my $name = $quotes {$f, ”name“};
my $price= $quotes {$f, ”price“};
my $cost = $costs{$f};
my $share=$shares{$f};
my $value=$price*$share;
$total+=$value;
my $profit = $price-$cost;
$gain+=$profit*$share;
my $percent= $profit/$cost;

print ”Fund $f $name \tPROFIT = $profit \tCOST = $cost \tPRICE = $price\tGAIN = $percent \tVAL=$value\n“;
}
print ”\n\nTOTAL=$total\nGAIN=$gain\n“;

Not complex, but goodness gracious me, it actually works!

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