Tag Archives: animation

Things 129: Kids Special (Strange Hill High, Octonauts, The Phoenix)

People tend to assume children’s entertainment isn’t as good as it was when they were young, probably due to a three-pronged attack of rose-tinted nostalgia, the best shows being renewed (Sesame Street) or repeated (Bagpuss) so giving each new generation a sense of ownership over them, and poor curation for adults out of the current crop.

Recognising that this is a highly subjective enterprise, I’m going to pick out a few good examples of current kids fare in attempt to at least fix the latter. There’s even a kid-entertainment-based puzzle at the end.

TV Series with Puppets: Strange Hill High
I occasionally take a look at current children’s TV to see what sort of animation techniques are being used, and Strange Hill High caught my attention through its fascinating combination of designer-vinyl-toy-style puppets combined with CG mouth animation.

The premise is entirely encoded in the name so I won’t bother to elaborate on that. Most importantly, it actually makes me laugh a few times per episode, which can’t be said of many other TV series. To be fair, 90% of it is fairly standard kids ‘comedy’, but it’s sufficiently fast paced that I don’t mind sitting through that to get to the other 10%.

If you seek reassurance from known quantities, it also features the voice of Richard Ayoade (The IT Crowd), and the head of the writing team is Josh Weinstein (The Simpsons).

It’s on iPlayer right now (I recommend starting with 99 cool things to do with a time machine), and you can start to get a bit of a flavour (though not really enough) from the opening few minutes:

Picture Books: Octonauts
Again, I first engaged with this franchise through the graphical design: I was impressed by the stylishness of their bath toys. It turns out there’s a whole CG animated series, which is quite good (mostly due to the use of regional accents), but it all started with a series of charmingly whimsical picture books. Here’s a few snippets to give you an idea:

Decoding the language of a sad fish:

Pictures that glow in the dark (from this book), which it turns out fascinate me just as much as when I was a kid:

Weekly comic: The Phoenix
Now I look back on it, more than anything The Beano looks like a primer on culture, mapping out the tropes and stereotypes of an idealised sort of pre-war age (vicars having tea, go-carts, hi-jinks, the threat of The Slipper), equipping the child with the reference points needed to navigate modern entertainment, while keeping said child entertained with a never-ending stream of speech bubbles that all end in exclamation marks (I only noticed this years later, and haven’t been able to read more than a few pages at once since).

The Phoenix is a modern kids comic that’s nothing like that. For one thing, it features work by James Turner, who I’ve featured in Things before (with this mind-bending 9-panel comic).

It’s also got a bunch of other surprisingly good stuff. Bunny vs Monkey by Jamie Smart features high-quality hijinks like this and ever so often will just go incredibly dark, like this:

For being simultaneously educational and entertaining, I’ve never seen better than Corpse Talk by Adam Murphy, in which he interviews the reanimated corpses of the “dead famous”, and doesn’t really sugar-coat things that much:

There’s wonderful art by Lorenzo in Long Gone Don:

Finally, ‘Professor Panels’ by Neill Cameron teaches kids to make their own comics, sometimes delightfully deconstructing the form, such as the episode in which a mecha-comic-creating-monkey starts to misfire when a banana is added to its workings:

If you’re interested, do check out their website, which has a free digital issue, a link to the iPad app, a starter pack you could buy, and a bunch of other good stuff.

Video: Tune-Yards My Country
I like this music, and the video is pretty good too. Be sure to stick around for the funky syncopated brass solo around 2’40”.

Puzzle: The Perfect Power-up Purchase Path
The LEGO console games are aimed at children, but provide some solid co-op entertainment for adults too, especially if you derive pleasure from smashing things and collecting coins – or in the LEGO-themed parlance of the game, ‘studs’.

In many (all?) of them, studs collected in the course of play can be used to purchase various upgrades. One such upgrade is the ‘x2′, which once bought, doubles the value of all the studs you subsequently collect – so a level where you might collect 100,000 studs will instead net you 200,000. There are other similar upgrades, like the ‘x4′, which multiplies by 4 – and they apply cumulatively, so if you have both x2 and x4, you get an 8 times multiplier, so that level would now net you 800,000 studs.

Naturally, the more powerful multipliers are more expensive to buy… but having a multiplier will help you save up for the others more quickly. Here’s a price list:

  • x2 = 1 million studs
  • x4 = 2m
  • x6 = 3m
  • x8 = 4m
  • x10 = 5m

So, the question naturally arises: if you want to eventually purchase all 5 of these multpliers, what order should you buy them in? (In case you were wondering, yes, they really do keep accumulating, so when you have them all you have a 2 x 4 x 6 x 8 x 10 = 3,840-times multiplier).

For the more mathematically inclined: what is the generic strategy for any multiplier series f and pricing series g? For the more game-design inclined: if you really wanted to encourage children to do some maths, how would you design the pricing for these multipliers? Alternatively, if you wanted to make the game as fun as possible, what multipliers and prices would you set?

Answer: Spoilers Sometimes Matter
Last time I asked if we could really believe research demonstrating that spoilers always improve enjoyment. The consensus seems pretty clear – even though ‘mystery’ and ‘twist ending’ stories were included in the research, it nonetheless seems very likely that there exist a few counter-example stories in which experiencing them unspoiled adds a tremendous amount to the experience. Since one can’t tell reliably tell which these are in advance, it seems wiser to err on the side of caution, and continue to avoid spoilers.

-Transmission Finally Ends

Things 128: No spoilers, Beethoven played correctly, automation vs humans

Puzzle – Do Spoilers Matter?
Research looking into the enjoyment of short stories found that reading a ‘spoiler’ beforehand tended to increase enjoyment. That seems quite possible, but the strangest part is that it holds even for mystery or ironic-twist stories. They even have a chart with error bars, which looks pretty compelling (click for big):

So, you’ll generally enjoy all stories you read (or presumably consume in any medium) more if you read about the ending first.

The question, then: how can you justify not doing this?

Video – Omlette
Here’s a really lovely short (2’30”) animation about a dog and an omlette. If you’re having a hard day, I particularly recommend it.

Audio – Beethoven wants you to play faster
When Beethoven eventually got his hands on a metronome, he marked up symphonies with tempos that nobody can quite believe he really meant, and which are pretty much entirely disregarded. This excellent Radiolab podcast investigates. (The forced conversational ‘style’ gets a little irritating, but the demonstration at the end is fantastic).

Links – Race Against The Machine
Our old friend the Invisible Hand guides us to make work more efficient with technology: robots replace humans on production lines, computer work becomes automated, cars and vacuum cleaners operate themselves, and productivity increases. Brilliant.

From the Luddites on, people have been fighting this change to defend their old jobs, but with hindsight we can say they were mistaken, as prosperity has increased, every time, and will continue to do so.

Or will it?!

Despite the apparent historic benefits, it’s still hard to imagine this trend continuing indefinitely and remaining benevolent.

Now, one can imagine some sort of desirable end point, in which (say) solar power becomes incredibly cheap:

… and robots / algorithms are able to do everything humans don’t want to do, and everything is wonderful and everyone is happy.

Of course, quite how you would run such a society isn’t entirely clear, and as Voltaire points out, work isn’t only about earning money:

Work spares us from three evils: boredom, vice, and need

But of more concern right now is how we organise society as we transition towards that end-point. In particular, it seems reasonable to suggest that automation of jobs will tend to increase inequality, as (in a simplistic model), the few that own the robots / server farms reap all the rewards of that automated labour while everyone else loses their jobs.

In case you need reminding, inequality is bad for almost everyone. By the way, a concise point on this topic made by Nick Hanauer in 2011:

If the average American family still got the same share of income they earned in 1980, they would have an astounding $13,000 more in their pockets a year. It’s worth pausing to consider what our economy would be like today if middle-class consumers had that additional income to spend.

Here’s a fun sequence of slides putting the current economic situation (in the US) in 50 years of context (brought together by Business Insider):

Corporate profits as a % of GDP at all time high:

% of Americans with jobs is significantly down:

(Something interesting is happening here, because the more common measure of “unemployment rate” doesn’t look as bad)

Wages as a % of GDP at an all-time low:

(Side-note: these were extracted from a longer chart-based argument to do with wages and debt, which is quite interesting but somewhat disingenuously suggests that just “looking at the data” is some non-political process that can reveal answers, and doesn’t consider the fact that over the same time period the % of retired persons in the US increased from 8% to 13% and could reach 20% in the next 30 years. Still worth a look, though.)

Now, there are many other drivers of inequality (including the feedback loop of lobbying, which The Onion satirises perfectly), and while automation may not have been the biggest contributor so far, it’s worrying that we’re not in a good position just as automation is starting to look like a credible threat to prosperity.

There’s a book on this which characterises the problem in its title: “Race Against the Machine“. I haven’t read it, but apparently the authors make an interesting case and then fail to offer any realistic solutions. The absence of solutions and the seemingly inevitable progress along this line is why I consider this one of the major problems we need to solve (after climate change).

Finally, a really important sci-fi story on this topic: Manna by Marshall Brain, which demonstrates a method by which automation can creep into jobs without replacing them entirely, but the consequences are just as dire. Chapter 1 gives you the gist, but it’s worth continuing to see how he plays out the trend. (At the end he appears to suggest a solution, and unfortunately it appears to be much less realistic than the problem).

-Transmission finally ends

Things 112: Eyes, Guessing Cat, Amigara Fault

This week Things has a very slight Hallowe’en theme.

Puzzle
This is one where you should gather some people around the monitor and see who can do best: guess the cartoon (or CG) character from their eyes (mouse over the eyes to see the character outline that should tell you if you’re right).

And yes, it is pretty difficult – I only got 6, and I watch a lot of animation!

Video
Here’s a video that begs the question: is the cat playing the game, or just acting out of blind instinct?

To which the answer is to have a big argument about the definitions being used before concluding that you can’t tell.

Quote
In the wonderfully stylised animation The Secret of Kells, I heard the line “One beetle recognises another” and wondered if it was some kind of proverb. It turns out that it is, and actually – obviously – there are a whole bunch of Irish Proverbs, which in translated form become alternately profound, banal or hilarious, just as I imagine English proverbs must seem if you haven’t grown up with them. Here’s a list of them on Wikiquote, and here are a few of my favourites, for unstated reasons:

“Every beginning is weak.”

“Time is a good story teller.”

“A lamb becomes a sheep with distance…”

“The quiet are guilty”

Comic
The Enigma of Amigara Fault is a horror comic that impressed me with its unconventional approach. It’s 32 pages, and originally in Japanese so you have to read the panels right to left. But if you want a comic that will freak you out for Hallowe’en, it’s worth it. Unless you’re particularly claustrophobic, in which case you should probably steer clear of it entirely.

Answer – Malady X
In Things 111 I asked what the probability of having Malady X is if a randomly administered 99%-accurate test for it comes back positive. As Phil and Thomas noted, you can’t actually answer from this information alone: you also have to know what the probability of a random person actually having Malady X is. A lot of people don’t have an intuition for this fact. I’m going to attempt to explain ways to apprehend that hand-wavingly, mathematically, and visually.

Argument from hand waving and examples:
Imagine the probability of having Malady X is 0% – nobody has it. In this case, it’s certain that getting a positive result means you were simply in the 1% of cases where the test comes back incorrect.
Conversely if the probability of having it is 100% – everybody has it – then you must be in the 99% of cases where it is accurate. In this way, it’s clear the underlying probability influences the chances that the test is correct!

We might worry that these extremes somehow break the puzzle, so let’s imagine less extreme alternatives. Imagine 1,000 people are tested. If 50% (500) really have Malady X, on average we expect the test to come back positive for 99% of them (495) and also for 1% of the 500 that don’t have it (5). In this situation, 495 out of the 500 people for whom the test was positive actually have the disease – 99%.

Alternatively, if 1 person (or 0.1%) out of the 1,000 has the disease, they’re very likely to be correctly diagnosed, and we expect roughly 10 of the other 999 to get a positive result. In this case 1 out of 11 people with a positive result actually have Malady X – fewer than 10%. So clearly the underlying incidence level matters.

Argument from maths:
There are two probabilities at work: the chance the test is correct (99%) and the chance of anyone having Malady X (unknown – let’s call it X%). When you combine probabilities you multiply them, so for example the chance of anyone actually having Malady X AND getting a postive result is 99% times X%.

If someone gets a positive result and that’s all we know, we reason as follows:
A = Probability someone has Malady X and tests positive = X% times 99% times
B = Probability someone does not have Malady X but still tests positive = (100% – X%) times 1%
If you test positive, the chance you actually have it is C = A / (A+B). But if you haven’t studied probability carefully, I’m not sure you could infer this, which is why I like to come up with other ways of getting a feel for the correct answer.

Argument from visualisation:
Since there are two probabilities in question, and we combine probabilities by multiplying, this naturally suggests a visualisation where probability is represented by rectangular area (since area is calculated by multiplying height by breadth).

For example, if we imagine the actual incidence rate of Malady X is 50%, the picture would look like this (click for big):

If the test result is positive, you either have it and the result is correct (big yellow area) or you don’t have it but the test was incorrect (small dark blue area). The chance of you actually having Malady X is equal to the proportion of those combined areas that is yellow. In this case:
Yellow = 99% x 50% = 49.5%
Dark blue = 1% * 50% = 0.5%
Probability you have it = Proportion that is yellow = 49.5% / (49.5% + 0.5%) = 99%.

Alternatively if the incidence rate is, say, 2%, it looks like this:

Here we see the yellow and dark blue areas are very similar, so the chance of you being one or the other is much more even. In fact, it’s:
Yellow = 99% x 2% = 1.98%
Dark blue = 1% x 98% = 0.98%
Probability you have it = Proportion that is yellow = 1.98% / (1.98% + 0.98%) = 67% (ish).

As Peter Donnelly shows in this TED talk, this actually has some severe ramifications, because when the probability of the thing being tested for is extremely low, it becomes overwhelmingly likely that a positive result is false, but people intuitively feel that a 99% accurate test should be correct 99% of the time.

Thomas also noted:

If anyone is interested in playing around with the probabilities (even if you’re not familiar with the maths), I recommend GeNIe:
http://genie.sis.pitt.edu/
It lets you create networks of dependencies, set evidence and work out probabilities in problems just like these.

-Transmission finally ends

Things 65: Trololo, Animation Analysis, Numerical Keyboards

(Originally sent March 2010, maybe)

Video
What sort of old TV clip would spawn a dedicated site whose main purpose is simply to play it on loop? (Sound is essential)

Link
I did a bit of analysis on the data that went into Disney’s decision to give up on 2D animation, including the correlation between how good a film is and how much money it makes:

Quote
Bad guy to henchman:

“Don’t you know what a rhetorical question is?!”

(From Leroy and Stitch)

Puzzle
Why do the numbers on phone keypads read left to right and down (so 1, 2, 3 are in the top row) whereas calculators and keyboards run the numbers left to right but upwards (with 1,2,3 in the bottom row)?

Picture
I think we’re just scratching the surface with the kind of art Photoshop helps us create.