Archive for the ‘Blog’ Category

Long Time Man

Tuesday, March 3rd, 2020

I saw an interview yesterday with a British bloke who is 112 years old. His earliest memory was from WW1 and was a Zeppelin attack on his town in the UK. This got me thinking of my oldest memories…

I lived an adventurous life as a baby, fighting off cannibals in the jungles of PNG before jet-setting half away around the world for an extended stay in Germany. I don’t remember any of those days, and the earliest memories I do have come from just before I entered Kindergarten, back in about 1976.

I have two very specific memories from that era. The first is of brushing my teeth at daycare. I would have been 4 years old, and while I have dim memories of the daycare itself (playing with Duplo, listening to stories being read to us and sleeping on cots) I have a strangely vivid memory of a lesson on how to brush our teeth where we all copied what the instructor (a dental nurse?) did in front of us.

The next vivid memory – also I suspect from around that time – was of a heavy metal cylinder falling onto my head and cutting me. It left a scar that remains to this day! Bernard was hoisting it up a tree for an inscrutable child-reason and I was standing directly underneath ‘helping’ when the string broke and it fell directly onto me. I recall crying and lots of blood! I bet mum almost panicked!

There are a couple of other trauma-related memories but they are incomplete and not as clear as the above: losing a toenail due to a fall, losing two teeth in one day, and cutting myself everywhere after a fall into a rose hedge 🙂

A year on and I have a very vivid memory from kindergarten about learning to write! We had books containing sentences that were missing words and we had to write using slates and chalk the missing words. As the book progressed we were writing more and more of the sentence until it was just pictures that we had to describe. I expect it’s all done using computers now, and that even in the day we may have found the slates old-fashioned.

Around 1977/8 my memories start becoming much more abundant and I can easily recall specific events at primary school or during the summers of those years. Maybe I’ve lost the correct order and I’ve certainly lost fine detail, but it’s reassuring to know my memories go back over 40 years ago now.

Over 40 years… where did all that time go?

2019 in Games

Saturday, December 7th, 2019

Another year, another ‘Year in Games’ blog post. It’s still my #1 hobby, and in some ways I’m more invested in it than ever. But it’s interesting to see how my spending (and playing) has changed over the years, moving ever-so-slowly more toward replaying old stuff than buying new.

In 2019 the numbers dipped upwards slightly this year, with 57 games bought for 10 systems at an average cost of about $25. The PS4 led in terms of games purchased and total dollars spent, but much like last year a decent amount of my spending was for retired (and in some cases distinctly retro) systems. Here are the charts, in another new format to please my critics:

The above is a proportional plot of games purchased by system. Yes your eyes don’t deceive you: I bought one game each for the Commodore 64 and PC-Engine in 2019. I can’t play either since I don’t own either system, but both were Wizardry games and I collect them so how could I pass them up? In fact more than a third of all my game purchases this year were for retired systems, and even more if you include the 3DS which is very much on the borderline these days.

And that is the breakdown of dollars spent. The 3DS has a large block since I bought an actual new 3DS system this year (which was my sixth…), and you’ll note that even though I bought more GBA games I spent more on the C64 and PCE games. This is because one of the GBA games was a mere ¥65, which is about US$0.60! The average game price remains low since I very rarely buy any new releases these days, instead waiting 6+ months until they inevitably drop in price. On Black Friday I bought nine PS4 games – all released within the last year – at an average cost of $18!

Despite the retro gaming (I’m not mentioning here the hours spent with the NES, SNES, C64 and Genesis Mini) I sunk a massive amount of hours into some extremely high quality new games as well. The following three were amongst my favorites of the year:

Monster Hunter World: Iceborne (PS4)

What can I say? Will there ever be a year a new Monster Hunter game doesn’t make this list? Iceborne – the expansion to world – added a higher difficulty, oodles of new monsters and lots and lots of fun. It was even better than World, and given they’re still adding content I doubt I’m done with it yet!

Nioh (PS4)

Imagine a hybrid of Dark Souls and Monster Hunter and this is what you get. An absolutely fantastic mission-based fuedal Japanese monster hunt, that has incredible amounts of content and oozes flavour. A wonderful, wonderful game and I look very much forward to the upcoming sequel.

Hollow Knight (PS4)

A ‘metroidvania’ set in a world of bugs. At times very difficult, but with a gigantic map and lots to see and do. I got lost in this one for weeks, which wasn’t bad for a digital game that cost me only $5!

I can’t end the year without a final farewell to the 150+ games and consoles that I parted with back in June. I ‘ve not regretted it and don’t miss them, and I very much hope they’ve gone on to new owners and are now featured on someone else’s “2019 in Games” list :

Snowpocalypse 2019

Tuesday, December 3rd, 2019

In the last 48 hours we received a lot of snow. I took regular photos from the same angle to show the accumulation. Here they are:

The above three run from noon to about 5 pm on Sunday. The snow was falling lightly at first, but picked up after nightfall.

The above is a 10 pm shot. It looks brighter than the 5 pm one due to the remarkable low light camera mode of my new iPhone. You can clearly see the snow has been coming down since the last shot: the driveway is barely visible here.

Above shows 6 am Monday morning. According to the weather service we’d received about 16 inches (~38 cm) overnight, and it was heavy snow which proved difficult to remove. Down near the street it was as deep as our snowthrower can handle, and although we have a powerful machine it really struggled.

That’s immediately after we finished clearing the snow. It was still falling lightly at this point. Although it was Monday almost everything was cancelled and we were both staying home for the day.

By around lunchtime not much had changed. The footprints were from the postman, who isn’t stopped by ‘a bit’ of snow!

By evening though (this is around 8 pm Monday) you can see it had built up somewhat again: there had probably been another 3-4 inches by this point.

And then we woke today to this: another 6+ inches since yesterday. Once again it was tricky to remove due to heaviness and the cold (it was -4 C) but at least it had stopped falling.

And here’s the final shot, after we had finished this morning. All told the official tally is 22.6 inches of snow (57.4 cm) in Albany and slightly more where we live just to the south. It was the 8th biggest snowfall of all time in this city. I expect well remember it for a while 🙂

Lunar Module

Sunday, November 24th, 2019

As soon as I saw the above in the LEGO store window I had to have it.

It was built in three stages; the lunar surface first:

Of course I had ‘help’ 🙂

The descent stage was next, and was a lot of fun to build including a lot of ‘metallic’ parts.

It also contains lots of little details, including a tiny model laser reflector, which I often use in examples during one of my lectures!

The finished Lunar Module:

It’s a fantastic kit, and one of the most fun LEGO builds I’ve ever done. I give this my highest LEGO score 🙂

Infinite Ape Simulator

Thursday, November 14th, 2019

I’ve been thinking about the Infinite Monkey Theorem, which postulates that an infinite amount of monkeys banging away on keyboards randomly forever would eventually produce the works of Shakespeare. You can read about this in detail here.

I thought to myself, rather than use dirty monkeys to reproduce Shakespeare (which has been attempted), why not use a machine brain? So I turned to an actual honest-to-goodness computer and wrote a simulation.

My machine was the Commodore 64, and I wrote a simple piece of code to randomly generate three letters in order and test to see if they spelled ‘act’, the first word of Hamlet. I was testing the water, so to speak, instead of diving right into a full reproduction of the entire play.

Now it’s fairly simple statistics to calculate that of the 17576 possible three letter words, only one is ‘act’. But I started by looking for words that started with ‘a’ (ie. of the form a–) of which there are 676, and then words starting with ac-, of which there are 26. I timed my result to see if – as expected – each successively correct letter took approximately 26 times as long to generate as the previous.

Here’s my code alongside one example output looking specifically for ‘act’:

The time is in seconds, and I ran 12 searches each for a– and ac- and 5 (due to the time required) for act. Here are the average times to generate each type of result:

A–: 3 seconds
AC-: 84 seconds
ACT: 2027 seconds

These numbers are close to 26x multiples of each other as expected, and I imagine were I to do enough tests they would converge to that value. From these results we can speculate how long it may take for my C64 to recreate Hamlet…

But first some facts: Hamlet has 132680 letters and 199749 characters in total including spaces and seven punctuation signs. Including these but ignoring case, there are 34 potential candidates for each character and 199749 characters need to be generated. My predictions that follow are based on times equal to 34/26 of those listed above.

The expected (ie. 50% chance) time it would take my C64 to randomly generate Hamlet would be 34^199746 times 1908 seconds which is (approximately) 34^199739 million years. The minimum time is about 1.7 hours ( if it got it right on the first go) and the maximum is of course infinity.

But – given our universe is only less than 14,000 million years old – this means I’m confident in saying my C64 would never randomly generate Hamlet. In fact were I to expand the sim to look for the sequence ‘Act 1’ I would expect the average successful attempt to take about one month. If I extended the sim all the way to the first spoken word – over 100 characters in – I’d expect the Earth would be consumed by the sun before my C64 did it.

Some of you say “that’s just a C64!”, which is primitive compared to the device you’re reading this on. But even if your fancy phone or laptop is a trillion times more powerful, this is nothing compared to a factor of ~10^200k.

It’s pleasant to think of infinite typing apes (or computers) randomly spewing out a work of art, but it would never happen 🙂

(Incidentally and somewhat related; the world is still awaiting the results of B’s testing of this!)