Sub five

I am mostly keeping up my daily ritual of doing the NYT crossword and generally getting faster, with most of my solves now below my historical average, but it’s getting harder to set a personal best. Every once in a while a puzzle comes along that is abnormally easy for the day-of-the-week, so that my best times are fairly far from the mean. It would be interesting to see the whole distribution over time, but as far as I know that data is not available.

Anyhow, determined to meet my entirely arbitrary goal of a sub-5 minute NYT crossword solve, I sat down today and did eleven Monday puzzles in a row. The eleventh (April 13, 2020) clocked in at 4:48. Success! When you do them back-to-back like this, it’s comical how frequently the same answer will appear from one to the next. Not just well-worn friends like ASEA, but slightly further out words: for example OKRA came up in almost the same grid location between this one and May 11, 2020. The other interesting thing about speed solving is how infrequently I’ll even notice the theme. I only just now went back to see the theme on this puzzle. DROPS/OCEAN were a nice touch.

I put some letters in squares

This weekend I burnished my geek CRED (clued as such in some puzzle) by participating in the virtualized 2021 American Crossword Puzzle Tournament. This year, they used Not-My-Software, which is a good thing because I would hate to be on tech support the year everyone that had to do virtual crosswording for the first time. I solved 6/8 puzzles cleanly which is enough to land just above the bottom 20% of the entrants! Of the misses, puzzle 5 was a beast, while puzzle 7 was pretty nice, but I didn’t get the theme quickly enough and lost five or ten minutes feeding the youngster breakfast during the solve. My fastest time was 6:58 on the (unscored) final which is no great shakes compared to the field but pretty good for me.

In other news, github thinks that I helped make the Mars helicopter fly. I’ve no delusions that my meager contributions to Linux are even compiled into whatever image that drone is actually running, but all the same, very cool!

House of Zephyrus

The one task I hate when gardening is hardening off plants. I tend to rush it and my poor seedlings pay the price. Usually, I am pretty good about limiting sun exposure but not so good about setting up wind breaks.

This year I decided to try introducing wind to my plants while they are still in the grow room. Sure, I could go plonk down $50 and get something bespoke here, but this is a perfect opportunity to use some of the extra PC case fans I have sitting around. It took all of two minutes to prototype a working “plant fan” by connecting a 9V battery across the fan terminals and cable tying the fan near my bell pepper plants.

That worked, until the battery gave out a few hours later. Also there was just one speed, “On,” and I might want to baby some plants or give them the occasional break. A good reason to dig through my parts box and pull out the trusty old Arduino.

There is basically nothing to fan speed control: just send a PWM signal on pin 4 and the rest is same as before. The microcontroller can send PWM signals for you so you just need to set the level. I put a pot between +5V and GND as a speed knob and wrote a quick sketch, and bam! Code here.

Power to the Arduino is on the same power strip as my grow lights, plugged into a smart power switch. The wind and sun get turned off according to the clock, or Alexa.

I don’t lack for Linux capable SBCs around here but there is something refreshing about the simplicity of Arduino.

House of Theseus

In case anyone was wondering: now is the point at which eight year old appliances are dying. Our house has just reached this venerable age, and in the last few months, the refrigerator, oven, and dishwasher all decided to quit working in some way or another. Thanks to COVID and YouTube, I fixed 2/3s of these appliances all by myself, which together with last year’s HVAC repair, means I am officially qualified to make twice my current hourly rate.

The snow is starting to melt here which means I am antsy for gardening season. My seeds, along with the rest of Canadian gardening population’s seeds, are still on backorder, so I’m making a go of it with some of previous years’ seeds. I added another 3’x4′ raised bed in which I hope to grow some cucurbits. So far, I have some radishes in the ground; bell peppers, kale, and basil germinating; and tomatoes and peppers just seeded.

35 seconds

After a bit of a break, I am back to doing the NYTXW every day, except when I forget. Out of laziness, I am just using their webapp instead of my own, thereby saving at least two clicks. As a result, I get their fancy stats deal for free.

As a completely pointless milestone, I’d like to break the five minute barrier sometime this year. I got pretty close with last Monday’s puz, and it didn’t feel like it was possible to type any faster. But I understand that in the competitive world, times are typically half that. Five minutes is somewhere around four seconds per answer, seems doable.

Finis

Dear reader, I am writing this from my bunker in lockdown. Here we are on the final day of 2020, and all I can say is, whew, we made it.

The front page of this blog goes back a year and a half which doesn’t say a lot about my level of commitment to this here writing thing of late. I shall try to make up for that by summarizing some of the projects I actually completed in 2020, but which I was too lazy to document contemporaneously so they might as well have not happened at all. Well here’s your bunch of write-ups all squashed into one blog entry, happy now?

I celebrated my first anniversary at Amazon in October, a year which saw us ship a huge cross-team project and deliver an outage-free Christmas. If you are one of the millions who interacted with Alexa this year, my many colleagues and I helped make that happen. If Alexa responded with something completely nonsensical or useless, well, then, that was probably some other team’s fault.

I’m happy to still be working in software, 22 years since I took my first full-time job. Back then, I took one of my first paychecks to the local hi-fi stereo vendor and purchased a Paradigm home theater setup. My roommate and I didn’t have any furniture to speak of, but who needs that when you can watch VHS tapes in 5.1 surround on a giant tube TV! These days, the surrounds and center channel speakers are gathering dust, but I still use the bookshelf speakers and sub. Recently, I noticed these poor old Atoms were rattling whenever the bass kicked in. Youtubers said that this is common and you need to replace your foam surrounds and you can buy a kit and do it yourself and did you know that you could just buy a new pair of monitors for as little as $5000 and also get some gold plated optical cables while you are at it for the warmest possible digital sound. So yes, I did buy such a kit and I did do it myself.

Well, this was an epically bad glue job, but there are no longer any clicks while listening to Technotronic’s _Pump Up The Jam_, so we are good for another 20 years or so.

Dining: for those that don’t know, in 2020, we were hit with a global SARS-Cov-2 pandemic. Never a family to eat out much anyway, we cut out the few remaining visits to eateries in the interest of not dying. The odd craving did strike though, so I fashioned a cheesecake, bagels, fried chicken, lattes, and doughnuts _with my bare hands_!

As in previous years, I grew a garden over the summer. The new-to-me crops: cucumbers and potatoes. Of the former, I had a lot: I ended up with something like ten pints of pickles even after having cukes in salads every day. I had only a few potatoes, but was surprised to find that the home grown varieties had a much different, nuttier taste than supermarket spuds. Both will probably make an appearance next year but I’ll need to balance out the yields. Also ended up with quite a few jalapenos which turned into a dozen jars of pepper jelly, and the usual amount of tomatoes (sauces, paste, pizza toppers, and so on). All this despite a family of rabbits literally living in my raised bed.

Anyway, this is all I can remember doing in 2020, or at least those things I have pictures of. Here’s hoping we get some vaccines in 2021 and we can go outside again. Wake me when that happens.

In which I faked a person

Having successfully shipped a project at $dayjob after some extended crunch time, I took this week off to recharge. This naturally gave me the opportunity to, um, write more code. In particular, I worked a bit on my crossword constructor while also constructing a crossword. I’m a bit rusty in this area, so while I was able to fill a puzzle with a reasonable theme, I’m probably going to end up redoing the fill before trying to publish that one because some areas are pretty yuck.

Which brings me to computing project number two: a neural net that tries to grade crosswords. Now, I can and have done this using some composite scores of the entries, based on some kind of word list rankings, but for this go-round I thought it would be fun to emulate the semi-cantankerous NYT crossword critic, Rex Parker. Parker (his nom de plume) is infamous for picking apart the puzzle every day and identifying its weak spots. Some time ago, Dave Murchie set up a website, Did Rex Parker Like The Puzzle, which, as the URL suggests, gives the short-on-time enthusiast the Reader’s Digest version. What if we had, say, wouldrexparkerlikethepuzzle.com: would this level of precognition inevitably lead us into an apocalyptic nightmare, even worse than the one we currently inhabit? Let us throw caution into the wind like so many Jurassic Park scientists and see what happens.

I didn’t do anything so fancy as to generate prose with GPT-3; instead I just trained a classifier using images of the puzzles themselves. Maybe, thought I, a person (and therefore a NN) can tell whether the puzzle is good or bad just by looking at the grid. Let’s assume Rex is consistent on what he likes — if so we could use simple image recognition to tell whether something is Rex-worthy or not. Thanks to Murchie’s work, I already had labels for 4 years of puzzles, so I downloaded all of those puzzles and trained an NN on them, as one does.

I tried a couple of options for the grid images. In one experiment, I used images derived from the filled grids, letters and all; in another, I considered only the empty grid shape itself. It didn’t make much difference either way, which suggests the language aspect of the puzzle is not really useful or adequately captured by the model.

How well did it work? Better than a coin flip, but not by a lot.

When trained with filled grids, it achieved an accuracy of 58.7%. When trained with just the grid shape, it achieved an accuracy of 61.4%.

Both models said he would like today’s (10-31-2020) puzzle, about which he was actually fairly ambivalent. My guess is the model is really keying in on number of black squares as a proxy for it being a Friday or Saturday puz, which he tends to like better than any other day of the week and therefore this one was highly ranked. Probably just predicting on number of squares would have performed similarly.

Socially distant

I haven’t posted at all since COVID-19 hit in this area, partly because work (from home) has been all-consuming and a welcome distraction from the outside world, and partly because, during my non-work hours, the old brain has loaded up an endless patter of anxiety:

Was that coughing gentleman really two meters away or maybe one and a half? Is it drafty in here, or do I have the chills? Is the shortness of breath and periodic chest pain a sign of COVID-19, or just your run-of-the-mill heart attack? Should I write another blog post and if so, will it be my last one, and if is the last, would that really be the blog post I want to end on?

And so on.

But I have decided that in some future generation there will be a Ken Burns style documentary on this whole thing and the future Ken Burns will need contemporaneous writing for his voice-overs. And who am I to deny future Ken Burns that material.

So know, dear reader, that so far in Month Six of the Apocalypse, we are all doing well. We have our health, food, shelter, and depressions in the driveway where our cars have sat motionless for half a year.

One silver lining: it turns out my hobbies were fairly pandemic-aligned: I already had sourdough starter going, a garden planned, puzzles for months, and a sewing machine at the ready. Since then, I also learned how to cut my own hair, make my own espresso, and service my own furnace. The children have traded meat-space friends for 24/7 screen time and, from their point of view, this seems to have been an auspicious swap. If they are any indication, we’ll all be just fine when the singularity hits. Which will probably be next year at this rate.

Watts up

One of my goals with this new computer is to be more aggressive about power saving: keeping it in suspend more often, using wake-on-lan for external access, etc. To that end, I dusted off the old kill-a-watt and took some baseline measurements:

Off, but plugged in: 2W
Suspend: 2W
On, idle: 48W (old machine: 100!)
Kernel build: 200W (old machine: 150, but also took 15x longer)
ML training with GPU at 100%: 400W

So long as I don’t run ML training 24-7, I am already going to save a lot of energy with this build.