Thoughts of a Psych/Code Monkey/Guitarist

Note: I'd strongly recommend reading this earlier post first, at least the story within, as it is the prequel to the story in this post. * * * After its earlier horrible performance in front of the Investech board, financiers lost confidence in the predictions of Oracle Oracle ('O2'), and the company soon went into liquidation. As it was a large part of the problem, the O2 network itself ended up being sold quite cheaply to the state's energy grid management   company   FullPower ('FP'). FP already had access to present and historic data for the state's infrastructure and weather, so the plan was to use O2 to improve power planning and distribution. Things started well - seasonal and regional trends were learned, and O2 even predicted the increase in cooling usage after fishery oversupply led to more goods with high refrigeration needs. To assist in interpretation, O2's language module was improved, in an attempt to explain new predictions in mo...

One technique I have to admit to developing for passing short periods of time is watching clips of skilled Mario players streaming on twitch/youtube (e.g. this guy  is a good demonstration). I'm also a sucker for informational theories, in particular the asymmetry of knowledge: How you gain information ('learn') is very different from how you lose it ('forget').  At the intersection of Mario and Information systems is a thing called the Kaizo block. What is it? For some background, Kaizo ('reorganized') Mario is a name that originated from an early hacked version of Mario that upped the difficulty substantially, and is now associated with many of the more complicated mechanics. One in particular can be seen above: a Kaizo block is one that starts off invisible, and only appears when you hit it. Often placed in the most inconvenient locations, they force much more precise movement, but also are very easily hit the first time through when its exist...

[side note: if you are looking for the app, it is available here on the play store .] What does red look like? Maybe a flag, or an apple, or blood, but these are all relative terms. It's a notoriously tricky problem to figure out how to explain what it's like to see red to someone who's never seen it - maybe it's not possible? Even stranger is the common realization that maybe it's arbitrary...could it be that other people experience colours completely differently to how you do? Perhaps to them, red feels like green does to you, and vice-versa. They'd still call all the items above 'red', but they'd experience them in the same way you do green. What's more, if this were possible, perhaps you'd never know... It's known as the Inverted Spectrum problem, and it's a tricky one: it's very easy to assume everyone experiences things the same as you. Some people can go a long time before realizing they're colour-blind, where...

A very short update to say that Blogger has launched a collection of new templates . They're a lot cleaner and more modern looking, plus have some nice customization options, so I decided to make the switch. The main difference is the layout is a lot wider, and the non-post stuff on the right has now moved into the left. Hopefully everything still works, but if anything's broken let me know. Also, kudos to the Blogger team, the new ones look rather good! Plus threaded comments still work -(looks like the old code is still used for them, too :p) and the commenting experience seems a bit cleaner now.

Fourier transforms are interesting things - a way of converting repetition to single values and back (roughly). Most commonly known in music (see my earlier post ), it also shows up oddly as the relationship between position and momentum in quantum mechanics. While audio perception takes patterns over time and converts them to notes, our eyes do likewise, but taking patterns over space - called spatial frequencies . Just as with music, there's (bidirectional) ways to convert an image into its spatial frequency representation. Part 1: Frequency swapped images As an example, on the left is a (greyscale) photo of George Bush, and on the right is the frequency version. Note that frequencies are complex numbers: representing both how strong the frequency is (the power - top right greyscale image) as well as the phase - i.e. where in the cycle it starts. As this is cyclical, I'll represent it as colours, from red -> green -> blue -> back to red (bottom right). For co...

One class this semester is mostly aimed at coming up with ideas for what to study as a graduate student (not surprising, being a 4th year subject in a major that aims at getting people into grad school). I'm lucky enough to be in a position where I already have a project lined up for summer, but it was interesting instead using the time to come up with alternatives, and then try to convince myself they were worth discarding. Or at least...putting off until later. Hence this list, using a blog as my external memory  of interesting things, so I can look back later and see if I was stupid or if any turn out to be interesting. Split roughly by subject, from the more abstract/philosophical to the concrete/engineering: Philosophy:  1) For everything (possibly?) true, can it be thought? 2) For everything thought, can it be communicated? Consider this the philosophical version of the Incompleteness theorem (maths), or the Uncertainty principle (physics) or the Halti...

Source: pernambola.blogspot.com I've avoided working in the US for too long, despite being a (now-former) software engineer and it being the source of the majority of interesting opportunities. There's a lot of reasons why, but near the top is its healthcare system. There's lots (and lots) of reasons why it's bad, but despite hearing the problems, it can be easy for people to dismiss them ('hey, it's not really that bad, right?'). So rather than stats, I thought it might be good to present my own anecdote as a case-study instead. As someone lucky enough to have lived on three continents (worked & studied in Australia, worked in Switzerland, and studied in Canada) I'll also add observations of what I'd expect from other countries, for comparison. For some context: Last summer I accepted an internship position at Facebook, and after failing to secure a spot outside the US in their London office, I ended up living in Menlo Park (California) ...

Or: Predictably unpredictable. Source:  The Guardian It was about five months ago that I posted some post-Brexit-vote comment s about the reaction, and while I'm even more annoyed by the recent US election results than Brexit, now in the post-Election period it seemed worthwhile to revisit. First, going over the old stuff: STILL what not to do when a population votes opposite to how you'd like: -) STILL don't ask to change the result. Yes, it happened again. Technically it's asking for the electoral college voters to not match what turned out on election night, which isn't quite as bad as just asking for another vote, but I still don't see why 6 million votes in a petition should count over the 120(ish) million votes during the election. -) STILL don't ask to change the style of voting . There's a lot of problems with the electoral college system : all-or-nothing states, no instant-runoff, unusual weighting system, ... but that...

It's election time in the US, and it's hard to avoid hearing all about it here in Canada (or, I presume, much of the rest of the world). I'm not exception to that as you can probably guess by my previous post. I've been interested to see a few of the psychological aspects of polarization, especially after the Australian elections earlier this year had similar, although to a lesser extent. Two particular stand out, and are worth looking at closer: 1A) Conspiracy theory: Bayes and Unwavering beliefs. Bayes theorem is some maths regarding probabilities: The interesting thing is that it can be used as a way to model how something (e.g. you, or your brain) can end up holding beliefs about how the world works based off experience. To reword the equation above in prose: How much I should believe that a hypothesis is true, given some evidence [ P(H | E) ], is equal to my old probability [ P(H) ] times the chance of seeing the evidence assuming it's true [ P(...

(or: an exercise in selling falsehood. Apologies to the non-CS followers of the blog). My app is going to be the best app you've ever used. There's a team of folks I know - brilliant people, really brilliant people - who build the best apps in the world. THE best. I mean, users pay money to use these apps, and no-one does that. They do, it's true, these people build apps that users pay money for because they're that good. So these people will build an app because I tell them, and do you know what? It's going to be the best. It's going to be so cheap to build, just wait and see. I've got a lot of experience at this, I can build an app cheaper than anyone else out there, it's what I do. Do you know how? This app is going to be so great, Amazon will PAY us to host it. They will! They'll pay us to run our app on AWS. Usually it's the other way around! But they will, trust me - they're smart people, I've met the folks at Amazon, they'...