Category: Thinking

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Computers Thinking

Installing Arch Linux as an incremental game

A laptop screen open at the Arch Linux installation media's shell.
Let's install Arch

Once in a decade or so the time comes to install (or reinstall) my personal computer. This time the occasion is getting a new laptop, something more modern, something more capable. The time passed and the changes in technology since the last time I had to do this means that the installation is likely familiar, but still different – sometimes subtly, sometimes in unrecognisable ways.

Setting up my laptop is now in its 3rd day, and the experience made me think of incremental games. Incrementals1 are where you make some progress in gathering some resource, then have to reset your progress that gives you some small buff or gain. You then start again – but better. The cycle repeats and you might have the same experiences countless times, but after a while the game can be much faster or even unrecognisable due to the accumulated effects.

While I was installing Arch Linux this time I went through the following cycle:

  • Partitioned my disk and installed the system, but then couldn’t boot into it
  • Redo the partitioning, system, and bootloader install, now I can boot into it, but don’t have any network access
  • Redo the system config, now I have network access, but have to figure out what desktop environment am I going to run, and what do I need for that. A hot mess ensues after trying out all main desktop environments for kicks
  • Reinstall the system, cleaner, with my desktop environment of choice, now the high resolution environment makes everything either: tiny, gigantic, and/or blurred.
  • Sorted out most of the sizes of things, have network, have Bluetooth, but the sound and the media buttons don’t work
  • Sorted out sound, now the power management locks me out while watching a video….

… and so on. I know I have a few more rounds (few more “crunches”) to do get there, and the multilingual typing input setup will be a doozie with bopomofo, but I’m getting better and feeling better every round – that’s how a good incremental game goes. A power up there, a know-how of a semi-obscure, quality of life config here2.

Of course I could have gotten an Ubuntu or Fedora image, installed everything in way less time than writing about the experience, and could already be using it — but that’s a whole different game3.

The games we choose to play show our values. On an optimistic day I feel I value increased knowledge; on more realistic days it certainly seems like procrastination. Now let’s keep this in mind when I finally have high enough level of Linux buffs that they change the game mechanics and I get to do something with my computer.

  1. Keep away from Universal Paperclips and give a very wide berth to Antimatter Dimensions ↩︎
  2. Such as enabling tapping on the touch pad for a click, without needing to actually press…. ↩︎
  3. A game that might be won, while I’m not sure whether the one I’ve chosen has a win condition. ↩︎

Categories
Computers Machine Learning Thinking

Software Engineering when AI seems Everywhere

A cat sitting behind a computer screen
Kitty musing about the future of AI coding assistants.

It’s pretty much impossible to miss the big push to use AI/LLM (Large Language Model) coding assistants for software engineers. Individual engineers, small and large companies seem to be going “all in” on this1. I’m generally wary of things that are this popular, as those often turn out more cargo cult than genuinely positive. So what’s a prudent thing to do as a software engineer? I believe the way ahead is a boring piece of advice, taht applies almost everywhere: instead of going easy, do more of the difficult stuff.

I genuinely think that putting the AI/LLM genie back into the bottle is unlikely (the same way as some people want the Internet, or smartphones, or cryptocurrencies put back into the bottle, which also not really gonna happen). That doesn’t mean that uncritical acceptance of the coding assistant tools should be the norm, au contraire, just like any tool, one needs to discover when they are fit for for the job, and when they are not. I have used GitHub CoPilot for a while, now digging into Cursor as it starts to conquer the workplace, and ChatGPT & Claude for individual coding questions. I don’t think it’s controversial to say that all these tools have their “strengths and weaknesses”, and that currently the more complex, more “production” the problem is, the further away it is from a proof-of-concept, the less likely these tools are of any help. They are help, they can be a large force multiplier, but they are big multiplier when one goes in with the least amount of input (knowledge, awailable time, reqirements for the result…)

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Categories
Computers Thinking

I’ve learned this about hacking, inspired by Mr. Robot

The second season of Mr. Robot has just finished last week. While it’s one of the most amazing thing I’ve ever seen, it is also held as the TV show with the closest depiction how computer hacking works for real (see for example Quora or Reddit). Looks like  it inspired a lot of people to “try out” the tools the characters use on the show (adding to the popularity of Kali Linux, or the Wickr chat app for example), which does feel a natural way to relate to your favorite characters, in a geek way.

I couldn’t resist either, and tried to dig a bit deeper, learning some geek (ie. not professional) lessons about how hacking works, party from the events in the show directly, partly by following for a few steps what were done in the show, and deconstructing the results. Here’s what I’ve collected so far:

Social engineering is likely a big part, a crucial enabler of most “successful” hacks. The show works with characters so it might be biased towards human actions, but it makes sense that social engineering can open door where the “bits” are closed. All the shows main hacks I remember included social engineering (not going to spoil here anything). This also made me a lot more aware in life, for example when talking with my bank online, or trying to get official things done in a way that it involves trust. Very much seems to me, that social engineering vulnerabilities and “opportunities” are really abound, and that makes me a lot more careful. For example, when calling to the bank, my verification data is three pieces of information that is available online or relatively easy, and I think of how I’ve seen such situation abused (in fiction, mind you), then I get a little jumpy. Not sure how other countries are like, but it feels like so many weak points in Taiwan, that she is just protected by the language barrier from western hackers/scammers – but sure that doesn’t deter another hostile nation. So yeah, my lessons is trying to improve on things, be mindful of trust-based situations encountered, while do be more confident to get things done better (in a non-malicious way of course), as confidence is one of the key ingredients of social engineering as well.

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Categories
Thinking

Changing the World

My father picked me up from school one day and we played hooky and went to the beach. It was too cold to go in the water so we sat on a blanket and ate pizza. When I got home my sneakers were full of sand and I dumped it on my bedroom floor. I didn’t know the difference, I was six. My mother screamed at me for the mess but he wasn’t mad. He said that billions of years ago the world ‘s shifting and ocean moving brought that sand to that spot on the beach and then I took it away. Every day he said we change the world. Which is a nice thought until I think about how many days and lifetimes I would need to bring a shoe full of sand home until there is no beach. Until it made a difference to anyone. Every day we change the world. But to change the world in a way that means anything that take more time that most people have. it never happens all at once. Its slow. Its methodical. Its exhausting. We don’t all have the stomach for it.

— Mr. Robot (eps1.4_3xpl0its.wmv)

Categories
Maker Thinking

Is there an Uncanny Valley for hardware projects?

The concept of the Uncanny Valley comes from robotics, its hypothesis says that when humanoid robots move and feel almost, but not completely like the real thing, they can be more off-putting than the robots that have less human likeness.

Working on quite a few hardware projects these days, I started to wonder (okay, say it out loud: worry), that there’s an uncanny valley for hardware projects as well. My theory goes such that hardware projects that are almost, but not completely professional can be more off-putting (or underwhelming) than less advanced, clearly maker projects and prototypes.

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