The idea of copyright is to protect the financial rights of creatives, thus incentivising people to make more stuff, right?

Well even before AI, it wasn’t doing its job very well on that front. The only ones with the power and money to be able to leverage copyright to protect their rights are those who are already so powerful that they don’t need those protections — big music labels and the like. Individual creatives were already being fucked over by the system long before AI.

If you haven’t read the article, I’d encourage you to give it a try. Or perhaps this one, which goes into depth on the intrinsic tensions within copyright law.

Something that I’m super chuffed with is that a few years back, one of my most cheapskate friends asked me for advice on buying a new laptop. When I presented their options to them, they were reluctant to cheap out and get a mediocre laptop that wouldn’t last them very long, but they also balked at the price of even the midrange laptops (they weren’t keen on spending more than £250 on a laptop, which wasn’t enough to get anything that they’d consider to be decent and worth the effort/cost).

As a long shot offer, I told them that I could always try installing Linux on their laptop if they wanted to wring another couple of years out of their existing laptop. I was a tad surprised when they opted for this, and even more surprised at how well they took to it; I jokingly call them one of my “normie” friends, because they’re one of the people whose perspective I ask for when I’m trying to calibrate for what non-techie people know/think. I only had limited experience with Linux myself at that point, having only played around with things on live USBs before. I had heard that Linux could give new life to slow computers, but I was surprised at just how effectively it did this.

(A small amusing aspect to this anecdote is that when I was installing it, I said that one of the side benefits of running Linux is that it could boost nerd cred amongst folk like me. They laughed and said that they didn’t expect that this would be a thing that would ever end up being relevant. Later that year, they got a girlfriend who saw that my friend was running Linux, and expressed approval, which is quite funny to me)

That’s sad. Regardless of whether it’s one of the reasons for Microsoft’s nosedive, it does make me feel some unexpected sympathy for Satya Nadella. I also feel pity, because most high up CEOs do not seem happy with their lives — Many of them spend an absurd amount of time at work, even if they never seem to actually do much work, and I can’t imagine how hard it must be to weather grief under such conditions. No amount of money can buy you more time with a lost loved one.

It really seems like a hollow existence.

Being anti-capitalist is entirely fair, but I think being opposed to all businesses is a less justifiable position to hold.

Yeah, this really was an excellent answer. I’m impressed by how he used this example to illustrate the wider strategy without it feeling like a weird kind of “we will cut programs like this and then everything will be fine”. It gives the sense that this is being used as an example because it’s simple enough to be at the top of a large pile of potential savings, which will take time and work to dig through.

To put it a different way, his answer abstracts away the right stuff. He doesn’t pretend that everything will be as simple and easy as cutting this one program was.

Often the promised cost savings never materialise, because when the chatbot fucks up, it’s humans who need to clean up the mess.

That sounds super cool! Do you have any pics?

So many features like this have gotten so much worse over the years. Google assistant is the big stand out one for me. I first switched to Android in 2014ish, and I got heavily into tinkering and automating stuff. I could say “Okay Google, make a coffee”, or “pop a coffee on please”, and Google assistant would hear this, parse it and understand that this wasn’t a command it knew. This would lead to that input being passed over to Tasker, the app I used for automating stuff, and that would then do the behind the scenes magic of turning on the coffee brewer as I was on my way home (It was very funny, because I didn’t have a fancy smart coffee pot or anything — I just used a ball bearing on a track to hit the on button)

Nowadays, I say something simple like “Okay Google, make a note” and it will say “I’m sorry, I don’t understand that” more often than not. The speech recognition used to be so good, especially after training it on your voice for a while. Now it’s just shit.

It makes me disproportionately sad. Like, enshittification is everywhere, but this is something distinct, even if it is linked to enshittification. If they were gating better voice recognition behind paywalls, I’d be annoyed, but much less sad, because at least that functionality still exists. Modern software, especially that produced by the tech giants, has gotten so complex that I wonder whether even the most proficient engineers in Google understand their software nowadays.

Windows update will frequently reenable OneDrive. Microsoft systematically undermines people ability to understand and control their own device.

Makes such a useful piece of software, and is also wise enough to set boundaries to protect himself from the toxic pressure of open source development.

What a G.

I get what point you’re making in distinguishing between pedophile and ephebophile, but personally I don’t find the distinction particularly relevant. As an adult, the level of grossed out I feel at the prospect of sexual interactions with a young teenager Vs a literal child is approximately equal, because it’s not their physical attributes that cause ick, but rather the exploitation and power dynamics involved.

Edit: I guess what I’m arguing is that in practice, we see the term “pedophilia” used as an umbrella term that encompasses pedophilia, hebephilia and ephebophilia, and I think that is a reasonable use of the term. It does muddy the waters a tad, given that pedophilia does still have its more specific use of referring to sexual attraction to pre-pubescent children, but I don’t think that an issue in the majority of contexts. When it comes to the law, an adult having sex with a child is equally illegal as an adult having sex with a 15 year old. Sure, we can split this hair and distinguish between the terms, but we don’t need to

I’d rather hone my skills at writing better, more intelligible code than spend that same time learning how to make LLMs output slightly less shit code.

Whenever we don’t actively use and train our skills, they will inevitably atrophy. Something I think about quite often on this topic is Plato’s argument against writing. His view is that writing things down is “a recipe not for memory, but for reminder”, leading to a reduction in one’s capacity for recall and thinking. I don’t disagree with this, but where I differ is that I find it a worthwhile tradeoff when accounting for all the ways that writing increases my mental capacities.

For me, weighing the tradeoff is the most important gauge of whether a given tool is worthwhile or not. And personally, using an LLM for coding is not worth it when considering what I gain Vs lose from prioritising that over growing my existing skills and knowledge

I see your point, but as you say, there would still be the tradeoff of missing more recent stuff. That might only involve missing a couple of years’ worth of stuff now, but AI isn’t going away any time soon, so it would mean that there’d be an increasing amount of human made music not being archived; One of the things I like about Anna’s archive is that they seem to look at this problem as a long term, informational infrastructure kind of way, so I imagine they wouldn’t be keen on stopping the archive at 2023.

It seems they’ve opted for a different tradeoff instead: lower popularity songs are archived at a lower bitrate, and even the higher popularity stuff has some compression. Some archives go for quality, and thus prioritise high quality FLACs, so Anna’s archive are aiming to fulfill a different niche. I can respect that.

I agree with the ethical standpoint of banning Generative AI on the grounds that it’s trained on stolen artist data, but I’m not sure how tenable “trained on stolen artist data” is as a technical definition of what is not acceptable.

For example, if a model were trained exclusively on licensed works and data, would this be permissible? Intuitively, I’d still consider that to be Generative AI (though this might be a moot point, because the one thing I agree with the tech giants on is that it’s impractical to train Generative AI systems on licensed data because of the gargantuan amounts of training data required)

Perhaps it’s foolish of me to even attempt to pin down definitions in this way, but given how tech oligarchs often use terms in slippery and misleading ways, I’ve found it useful to try pin terms down where possible

Yeah, that was my understanding of things too. What I’m curious about is how the Indie Game awards define it. Because if games that use ((Procedural Generation) AND NOT (Generative AI)) are permitted, then that would surely require a way of cleanly delineating between Generative AI and the rest of procedural generation that exists beyond generative AI

I’m not so much talking about machine learning being implemented in the final game, but rather used in the development process.

For example, if I were to attempt a naive implementation of procedurally generated terrains, I imagine I’d use noise functions to create variety (which I wouldn’t consider to be machine learning). However, I would expect that this would end up producing predictable results, so to avoid that, I could try chucking in a bunch of real world terrain data, and that starts getting into machine learning.

A different, less specific example I can imagine a workflow for is reinforcement learning. Like if the developer writes code that effectively says "give me terrain that is [a variety of different parameters], then when the system produces that for them, they go “hmm, not quite. Needs more [thing]”. This iterative process could, of course, be done without any machine learning, if the dev was tuning the parameters themselves at each stage, but it seems plausible to me that it could use machine learning (which would involve tuning model hyperparameters rather than parameters).

You make a good point about procedural generation at runtime, and I agree that this seems unlikely to be viable. However, I’d be surprised if it wasn’t used in the development process though in at least some cases. I’ll give a couple of hypothetical examples using real games, though I emphasise that I do not have grounds to believe that either of these games used machine learning during development, and that this is just a hypothetical pondering.

For instance, in Valheim, maps are procedurally generated. In the meadows biome, you can find raspberry bushes. Another feature of the meadows biome is that it occasionally has large clearings that are devoid of trees, and around the edges of these clearings, there is usually a higher rate of raspberry bushes. When I played, I wondered why this was the case — was it a deliberate design decision, or just an artifact of how the procedural generation works? Through machine learning, it could in theory, be both of these things — the devs could tune the hyperparameters a particular way, and then notice that the output results in raspberry bushes being more likely to occur in clusters on the edge of clearings, which they like. This kind of process would require any machine learning to be running at runtime

Another example game is Deep Rock Galactic. I really like the level generation it uses. The biomes are diverse and interesting, and despite having hundreds of hours in the game, there are very few instances that I can remember seeing the level generation being broken in some way — the vast majority of environments appear plausible and natural, which is impressive given the large number of game objects and terrain. The level generation code that runs each time a new map is generated has a heckton of different parameters and constraints that enable these varied and non-broken levels, and there’s certainly no machine learning being used at runtime here, but I can plausibly imagine machine learning being useful in the development process, for figuring out which parameters and constraints were the most important ones (especially because too many will cause excessive load times for players, so reducing that down would be useful).

Machine learning certainly wouldn’t be necessary in either of these examples, but it could be something that could make certain parts of development easier.

I don’t remember where I heard it, but a phrase I quite like is “AI is the death drive of capitalism”

How to Be Composed and Focussed: ADHD edition

• Step 1: throw away self help books that are aimed at neurotypicals. The advice in them is probably not helpful for us, and will just exacerbate internalised ableism. Not only will it take different strategies to get there, but “composed and focussed” will look different for you than it will for neurotypical people.

For example, a friend I had found that she was only able to complete her university essays when she engaged in an odd sort of task circuit-training, where she had multiple different tasks that she could cycle between as soon as she found herself losing focus. To an external, neurotypical observer, this looked like absurd chaos, but that was how she found her focus.

• Step 2: try your best to work against the aforementioned internalised ableism. This, unfortunately, is an ongoing task, because even once we throw away unhelpful frameworks, we can’t escape from the unreasonable expectations that the world places upon us. That is not your fault, and you are not broken just because you can’t fit into the pre built mould that society offers you. It is possible to build new frameworks that will comfortably fit and support you, but we’re going to have to do a lot of that work ourselves. This is a task that will be an ongoing one, so proceed to step 3 whenever you feel ready.

• Step 3: find neurodivergent community. This is the most important step, because it can do wonders for helping with step 2; it gets tiring to have to constantly remind ourselves that we’re not broken, so it’s helpful to have other people help remind us of this sometimes. Plus ADHD folk often find it’s easier to care for other people than for themselves, so you might find it easier to affirm other people than yourself. That can be a good starting point for learning how to extend that same grace to yourself.

It doesn’t matter whether it’s online or irl, a space specifically dedicated to discussing ADHD/autism or just a hobby community with lots of neurospicy folk — just find your people. It’s daunting to feel like you have to build an entire mode of living from scratch, but you’re not doing it alone. Ask people what strategies they have found useful for coping, and if you find anything, share that with others too. We’re not a monolith, so not everything will work for every person, but having these conversations about what works and what doesn’t is super useful.

• Step 4: Remember that there is no silver bullet here, no single strategy that will fix everything. I’m sorry to have to emphasise this, but the best tool is the one you use. Try not to fixate on the next shiny thing, because that’s a false comfort. I know that actually using the tools and strategies is the hard part, but that’s why we need to keep working at it. You will struggle with this, but that’s not failure, it’s part of the process. Refer back to Step 2 if you need to.

Step 5: Remember the big picture. What we’re building here is social and informational infrastructure. My own experience has been improved by having access to resources and communities online that are made by and for neurodivergent people; if I were born 100 years ago, I might’ve ended up in an asylum. It often doesn’t feel like it, but things are getting better. It’s overwhelming and scary to be building something new on the margins of society, but we have the ability to improve things both for ourselves, and the people who come after us.

We’re trying to do something radical here, and that will take time and a lot of work. Most of us were only taught how to be successful neurotypicals, which is something that we can never be. We are having to learn from scratch how to be successful neurodivergent people, but there isn’t a simple guidebook for that. We have to muddle along as best we can and write that guidebook ourselves. In this way, learning how to live as ourselves is a powerful form of political praxis^[1] (which may be a helpful thing to remember if you tend to beat yourself up about being too burnt out to engage in as much activism as you’d like).

[1] : Praxis can be generally defined as the process of putting theory or ideas into practice. In this case, we can say “we deserve better than to live believing that we are no more than failed neurotypicals”, but then there’s the tricky question of how do we put that ideal into practice? That’s the ongoing quest. Praxis in this context also draws from how it’s used in Marxist thought, which is that praxis is about actions that are oriented towards changing society.

Yeah, I’ve been seeing an increasing number of artists who are pro piracy, who basically say “steal our music, save your money, and if you want to support us, come to a gig and buy some merch”.

I’ve also seen more and more artists staying off Spotify entirely. One such artist is the wonderful folk artist Lucy & Hazel . This was the first time I actually bought music in years, and a big part of that was because I wanted to support their active choice to stay off Spotify.

An unexpected side effect of this is that because I’m aware these guys are situated less optimally for algorithmic discoverability, I find myself actively recommending them to people. It feels nice compared to the more passive mode of algorithmic music discovery

I’m not sure how they would go about doing that at scale without also getting some false positives and removing human music too