@timbray@cosocial.ca2025-07-04 23:22:03
O'Reilly: GenAI has adopted a colonialist business model.
https://www.linkedin.com/posts/timo3_proud-of-the-cloudflare-team-working-to-build-activity-7345899260506271745-mlHS
@timbray@cosocial.ca2025-07-04 23:22:03
@tiotasram@kolektiva.social2025-07-28 13:06:20
How popular media gets love wrong
Now a bit of background about why I have this "engineered" model of love:
First, I'm a white straight cis man. I've got a few traits that might work against my relationship chances (e.g., neurodivergence; I generally fit pretty well into the "weird geek" stereotype), but as I was recently reminded, it's possible my experience derives more from luck than other factors, and since things are tilted more in my favor than most people on the planet, my advice could be worse than useless if it leads people towards strategies that would only have worked for someone like me. I don't *think* that's the case, but it's worth mentioning explicitly.
When I first started dating my now-wife, we were both in graduate school. I was 26, and had exactly zero dating/romantic experience though that point in my life. In other words, a pretty stereotypical "incel" although I definitely didn't subscribe to incel ideology at all. I felt lonely, and vaguely wanted a romantic relationship (I'm neither aromantic nor asexual), but had never felt socially comfortable enough to pursue one before. I don't drink and dislike most social gatherings like parties or bars; I mostly hung around the fringes of the few college parties I attended, and although I had a reasonable college social life in terms of friends, I didn't really do anything to pursue romance, feeling too awkward to know where to start. I had the beginnings of crushes in both high school and college, but never developed a really strong crush, probably correlated with not putting myself in many social situations outside of close all-male friend gatherings. I never felt remotely comfortable enough to act on any of the proto-crushes I did have. I did watch porn and masturbate, so one motivation for pursuing a relationship was physical intimacy, but loneliness was as much of a motivating factor, and of course the social pressure to date was a factor too, even though I'm quite contrarian.
When I first started dating my now-wife, we were both in graduate school. I was 26, and had exactly zero dating/romantic experience though that point in my life. In other words, a pretty stereotypical "incel" although I definitely didn't subscribe to incel ideology at all. I felt lonely, and vaguely wanted a romantic relationship (I'm neither aromantic nor asexual), but had never felt socially comfortable enough to pursue one before. I don't drink and dislike most social gatherings like parties or bars; I mostly hung around the fringes of the few college parties I attended, and although I had a reasonable college social life in terms of friends, I didn't really do anything to pursue romance, feeling too awkward to know where to start. I had the beginnings of crushes in both high school and college, but never developed a really strong crush, probably correlated with not putting myself in many social situations outside of close all-male friend gatherings. I never felt remotely comfortable enough to act on any of the proto-crushes I did have. I did watch porn and masturbate, so one motivation for pursuing a relationship was physical intimacy, but loneliness was as much of a motivating factor, and of course the social pressure to date was a factor too, even though I'm quite contrarian.
I'm lucky in that I had some mixed-gender social circles already like intramural soccer and a graduate-student housing potluck. Graduate school makes a *lot* more of these social spaces accessible, so I recognize that those not in school of some sort have a harder time of things, especially if like me they don't feel like they fit in in typical adult social spaces like bars.
However, at one point I just decided that my desire for a relationship would need action on my part and so I'd try to build a relationship and see what happened. I worked up my courage and asked one of the people in my potluck if she'd like to go for a hike (pretty much clearly a date but not explicitly one; in retrospect not the best first-date modality in a lot of ways, but it made a little more sense in our setting where we could go for a hike from our front door). To emphasize this point: I was not in love with (or even infatuated with) my now-wife at that point. I made a decision to be open to building a relationship, but didn't follow the typical romance story formula beyond that. Now of course, in real life as opposed to popular media, this isn't anything special. People ask each other out all the time just because they're lonely, and some of those relationships turn out fine (although many do not).
I was lucky in that some aspects of who I am and what I do happened to be naturally comforting to my wife (natural advantage in the "appeal" model of love) but of course there are some aspects of me that annoy my wife, and we negotiate that. In the other direction, there's some things I instantly liked about my wife, and other things that still annoy me. We've figured out how to accept a little, change a little, and overall be happy with each other (though we do still have arguments; it's not like the operation/construction/maintenance of the "love mechanism" is always perfectly smooth). In particular though, I approached the relationship with the attitude of "I want to try to build a relationship with this person," at first just because of my own desires for *any* relationship, and then gradually more and more through my desire to build *this specific* relationship as I enjoyed the rewards of companionship.
So for example, while I think my wife is objectively beautiful, she's also *subjectively* very beautiful *to me* because having decided to build a relationship with her, I actively tried to see her as beautiful, rather than trying to judge whether I wanted a relationship with her based on her beauty. In other words, our relationship is more causative of her beauty-to-me than her beauty-to-me is causative of our relationship. This is the biggest way I think the "engineered" model of love differs from the "fire" and "appeal" models: you can just decide to build love independent of factors we typically think of as engendering love (NOT independent of your partner's willingness to participate, of course), and then all of those things like "thinking your partner is beautiful" can be a result of the relationship you're building. For sure those factors might affect who is willing to try building a relationship with you in the first place, but if more people were willing to jump into relationship building (not necessarily with full commitment from the start) without worrying about those other factors, they might find that those factors can come out of the relationship instead of being prerequisites for it. I think this is the biggest failure of the "appeal" model in particular: yes you *do* need to do things that appeal to your partner, but it's not just "make myself lovable" it's also: is your partner putting in the effort to see the ways that you are beautiful/lovable/etc., or are they just expecting you to become exactly some perfect person they've imagined (and/or been told to desire by society)? The former is perfectly possible, and no less satisfying than the latter.
To cut off my rambling a bit here, I'll just add that in our progress from dating through marriage through staying-married, my wife and I have both talked at times explicitly about commitment, and especially when deciding to get married, I told her that I knew I couldn't live up to the perfect model of a husband that I'd want to be, but that if she wanted to deepen our commitment, I was happy to do that, and so we did. I also rearranged my priorities at that point, deciding that I knew I wanted to prioritize this relationship above things like my career or my research interests, and while I've not always been perfect at that in my little decisions, I've been good at holding to that in my big decisions at least. In the end, *once we had built a somewhat-committed relationship*, we had something that we both recognized was worth more than most other things in life, and that let us commit even more, thus getting even more out of it in the long term. Obviously you can't start the first date with an expectation of life-long commitment, and you need to synchronize your increasing commitment to a relationship so that it doesn't become lopsided, which is hard. But if you take the commitment as an active decision and as the *precursor* to things like infatuation, attraction, etc., you can build up to something that's incredibly strong and rewarding.
I'll follow this up with one more post trying to distill some advice from my ramblings.
#relationships #love
@mgorny@social.treehouse.systems2025-07-05 15:24:22
A while ago, I've followed the example given by #Fedora and unbundled ensurepip wheels from #Python in #Gentoo (just checked — "a while ago" was 3 years ago). This had the important advantage that it enabled us to update these wheels along with the actual pip and setuptools packages, meaning new virtual environments would get fresh versions rather than whatever CPython happened to bundle at the time of release.
I had considered using our system packages to prepare these wheels, but since we were already unbundling dependencies back then, that couldn't work. So I just went with fetching upstream wheels from PyPI. Why not build them from source instead? Well, besides feeling unnecessary (it's not like the PyPI wheels are actually binary packages), we probably didn't have the right kind of eclass support for that at the time.
Inspired by @…, today I've tried preparing new revisions of ensurepip packages that actually do build everything from source. So what changed, and why should building from source matter now? Firstly, as part of the wheel reuse patches, we do have a reasonably clean architecture to grab the wheels created as part of the PEP517 build. Secondly, since we're unbundling dependencies from pip and setuptools, we're effectively testing different packages than these installed as ensurepip wheels — and so it would be meaningful to test both variants. Thirdly, building from source is going to make patching easier, and at the very least enable user patching.
While at it, I've refreshed the test suite runs in all three regular packages (pip, setuptools and wheel — we need an "ensurepip" wheel for the last because of test suites). And of course, I hit some test failures in testing the versions with bundled dependencies, and I've discovered a random bug in #PyPy.
https://github.com/gentoo/gentoo/pull/42882 (yes, we haven't moved yet)
https://github.com/pypy/pypy/issues/5306
@blakes7bot@mas.torpidity.net2025-05-30 21:18:06
Series D, Episode 02 - Power
TARRANT: Why?
AVON: Because that was my instruction.
DAYNA: You told Orac not to crack the code?
TARRANT: Why do that?
https://blake.torpidity.net/m/402/505 B7B6
@tiotasram@kolektiva.social2025-06-21 02:34:13
Why AI can't possibly make you more productive; long
#AI and "productivity", some thoughts:
Edit: fixed some typos.
Productivity is a concept that isn't entirely meaningless outside the context of capitalism, but it's a concept that is heavily inflected in a capitalist context. In many uses today it effectively means "how much you can satisfy and/or exceed your boss' expectations." This is not really what it should mean: even in an anarchist utopia, people would care about things like how many shirts they can produce in a week, although in an "I'd like to voluntarily help more people" way rather than an "I need to meet this quota to earn my survival" way. But let's roll with this definition for a second, because it's almost certainly what your boss means when they say "productivity", and understanding that word in a different (even if truer) sense is therefore inherently dangerous.
Accepting "productivity" to mean "satisfying your boss' expectations," I will now claim: the use of generative AI cannot increase your productivity.
Before I dive in, it's imperative to note that the big generative models which most people think of as constituting "AI" today are evil. They are 1: pouring fuel on our burning planet, 2: psychologically strip-mining a class of data laborers who are exploited for their precarity, 3: enclosing, exploiting, and polluting the digital commons, and 4: stealing labor from broad classes of people many of whom are otherwise glad to give that labor away for free provided they get a simple acknowledgement in return. Any of these four "ethical issues" should be enough *alone* to cause everyone to simply not use the technology. These ethical issues are the reason that I do not use generative AI right now, except for in extremely extenuating circumstances. These issues are also convincing for a wide range of people I talk to, from experts to those with no computer science background. So before I launch into a critique of the effectiveness of generative AI, I want to emphasize that such a critique should be entirely unnecessary.
But back to my thesis: generative AI cannot increase your productivity, where "productivity" has been defined as "how much you can satisfy and/or exceed your boss' expectations."
Why? In fact, what the fuck? Every AI booster I've met has claimed the opposite. They've given me personal examples of time saved by using generative AI. Some of them even truly believe this. Sometimes I even believe they saved time without horribly compromising on quality (and often, your boss doesn't care about quality anyways if the lack of quality is hard to measure of doesn't seem likely to impact short-term sales/feedback/revenue). So if generative AI genuinely lets you write more emails in a shorter period of time, or close more tickets, or something else along these lines, how can I say it isn't increasing your ability to meet your boss' expectations?
The problem is simple: your boss' expectations are not a fixed target. Never have been. In virtue of being someone who oversees and pays wages to others under capitalism, your boss' game has always been: pay you less than the worth of your labor, so that they can accumulate profit and thus more capital to remain in charge instead of being forced into working for a wage themselves. Sure, there are layers of management caught in between who aren't fully in this mode, but they are irrelevant to this analysis. It matters not how much you please your manager if your CEO thinks your work is not worth the wages you are being paid. And using AI actively lowers the value of your work relative to your wages.
Why do I say that? It's actually true in several ways. The most obvious: using generative AI lowers the quality of your work, because the work it produces is shot through with errors, and when your job is reduced to proofreading slop, you are bound to tire a bit, relax your diligence, and let some mistakes through. More than you would have if you are actually doing and taking pride in the work. Examples are innumerable and frequent, from journalists to lawyers to programmers, and we laugh at them "haha how stupid to not check whether the books the AI reviewed for you actually existed!" but on a deeper level if we're honest we know we'd eventually make the same mistake ourselves (bonus game: spot the swipe-typing typos I missed in this post; I'm sure there will be some).
But using generative AI also lowers the value of your work in another much more frightening way: in this era of hype, it demonstrates to your boss that you could be replaced by AI. The more you use it, and no matter how much you can see that your human skills are really necessary to correct its mistakes, the more it appears to your boss that they should hire the AI instead of you. Or perhaps retain 10% of the people in roles like yours to manage the AI doing the other 90% of the work. Paradoxically, the *more* you get done in terms of raw output using generative AI, the more it looks to your boss as if there's an opportunity to get enough work done with even fewer expensive humans. Of course, the decision to fire you and lean more heavily into AI isn't really a good one for long-term profits and success, but the modern boss did not get where they are by considering long-term profits. By using AI, you are merely demonstrating your redundancy, and the more you get done with it, the more redundant you seem.
In fact, there's even a third dimension to this: by using generative AI, you're also providing its purveyors with invaluable training data that allows them to make it better at replacing you. It's generally quite shitty right now, but the more use it gets by competent & clever people, the better it can become at the tasks those specific people use it for. Using the currently-popular algorithm family, there are limits to this; I'm not saying it will eventually transcend the mediocrity it's entwined with. But it can absolutely go from underwhelmingly mediocre to almost-reasonably mediocre with the right training data, and data from prompting sessions is both rarer and more useful than the base datasets it's built on.
For all of these reasons, using generative AI in your job is a mistake that will likely lead to your future unemployment. To reiterate, you should already not be using it because it is evil and causes specific and inexcusable harms, but in case like so many you just don't care about those harms, I've just explained to you why for entirely selfish reasons you should not use it.
If you're in a position where your boss is forcing you to use it, my condolences. I suggest leaning into its failures instead of trying to get the most out of it, and as much as possible, showing your boss very clearly how it wastes your time and makes things slower. Also, point out the dangers of legal liability for its mistakes, and make sure your boss is aware of the degree to which any of your AI-eager coworkers are producing low-quality work that harms organizational goals.
Also, if you've read this far and aren't yet of an anarchist mindset, I encourage you to think about the implications of firing 75% of (at least the white-collar) workforce in order to make more profit while fueling the climate crisis and in most cases also propping up dictatorial figureheads in government. When *either* the AI bubble bursts *or* if the techbros get to live out the beginnings of their worker-replacement fantasies, there are going to be an unimaginable number of economically desperate people living in increasingly expensive times. I'm the kind of optimist who thinks that the resulting social crucible, though perhaps through terrible violence, will lead to deep social changes that effectively unseat from power the ultra-rich that continue to drag us all down this destructive path, and I think its worth some thinking now about what you might want the succeeding stable social configuration to look like so you can advocate towards that during points of malleability.
As others have said more eloquently, generative AI *should* be a technology that makes human lives on average easier, and it would be were it developed & controlled by humanists. The only reason that it's not, is that it's developed and controlled by terrible greedy people who use their unfairly hoarded wealth to immiserate the rest of us in order to maintain their dominance. In the long run, for our very survival, we need to depose them, and I look forward to what the term "generative AI" will mean after that finally happens.
@rberger@hachyderm.io2025-05-24 20:03:14
@…
Not sure why it won't let me respond to your comment directly..
If you look at my feed at all, you will see I am far from a "Republican"
If one watches PBS Newshour with any critical media literacy their drift to the right is clear. They are always doing the "both sides", treating Trump and his Reublican minons as normal, etc. But the Republicans (who I am definitely not one of) have been working on this since Reagan and they really got going in 2005 https://www.democracynow.org/2005/5/12/a_right_wing_coup_at_pbs
https://www.markey.senate.gov/news/press-releases/june-23-2005-corporation-for-public-broadcasting-hires-former-rnc-chair
@tezoatlipoca@mas.to2025-07-28 16:15:40
When you get the option to `Sign in with Google/Microsoft/Facebook` you're really using #OAuth. Aside from those platforms knowing what you're doing everywhere all the time, there are compelling reasons for both 3rd party services and users. (not many, but a few).
But if you DO link your #Microsoft /
@blakes7bot@mas.torpidity.net2025-05-30 21:18:06
Series D, Episode 02 - Power
TARRANT: Why?
AVON: Because that was my instruction.
DAYNA: You told Orac not to crack the code?
TARRANT: Why do that?
https://blake.torpidity.net/m/402/505 B7B6
@inthehands@hachyderm.io2025-06-12 14:35:10
❝But why does Trump want chaos? Many pundits and, I’m sorry to say, all too many Democrats assume that performative cruelty, both in the form of those ICE arrests and in roughing up demonstrators, will work to Trump’s political advantage.
For what it’s worth, that’s not what the available polling says.❞
https://paulkrugman.substack.com/p/this-is-not-a-drill
1/
@arXiv_astrophSR_bot@mastoxiv.page2025-07-24 08:45:00
Premature Ignition: Why the Single-Degenerate Channel Leads to Type Iax and Not Type Ia Supernovae
Amir Michaelis, Hagai B. Perets
https://arxiv.org/abs/2507.16907 https://
@jeang3nie@social.linux.pizza2025-06-23 14:54:59
Ughhh, autotools....
Not naming the project here.. Why would you assume that malloc and realloc are both broken just because you're cross compiling? Are you just being lazy? Even worse, don't '#undef malloc' and replace it with your own *broken* version.
Better yet, just don't even use autotools at all.
@rperezrosario@mastodon.social2025-05-21 14:22:26
Quanta Magazine authors Janna Levin and Steven Strogatz strike up a conversation with Ellie Pavlick (Research Scientist at Google Deep Mind) about the differences and similarities between the way people understand language, what NLP algorithms do, and the fact that such conversations more often than not shed light into more than Linguistics' computational side.
"Will AI Ever Understand Language Like Humans?"
@jensilber@mastodon.social2025-07-15 13:36:44
But why not both? I think both are true. https://mastodon.social/@aaron.rupar@threads.net/114857435266584273
@midtsveen@social.linux.pizza2025-06-18 20:45:51
When the family calls me a tankie, I just drop Rudolf Rocker’s black-and-red flag and remind them: Rocker spent his life critiquing both state capitalism and authoritarian socialism, he literally wrote book's on why real liberation means smashing all forms of state power, not trading one boss for another.
Anarcho-syndicalism: Theory and Practice
@m0les@aus.social2025-06-21 07:08:24
A clear sunny Winter solstice day, so why not Chicken katsu udon soup with roasted rice tea for lunch at Tokyo Canteen in Kingston?
The soup had citrus-pickled vegetables in it (daikon, carrot, cauliflower and Brussels sprouts) - which was a pleasant surprise (I just expected dashi or miso or something).
#food #canberra
@paulbusch@mstdn.ca2025-07-16 12:28:47
Good Morning #Canada
It has been well reported that OTD in 1880 Dr. Emily Stowe became the first woman licensed to practice medicine in Canada. But actually she was the 2nd as Jennie Kidd Trout (born Gowanlock; April 21, 1841 – November 10, 1921) was the first woman in Canada to become a licensed medical doctor on March 11, 1875. Not sure why Trout was misplaced in the history books for a few years, but perhaps she was overshadowed by Stowe's much more public lifetime dedication to fighting for women's rights. Regardless, both were pioneers that helped establish educational opportunities in medicine for women in Canada.
#CanadaIsAwesome #CanadianHeroes
https://en.wikipedia.org/wiki/Jennie_Kidd_Trout
@arXiv_statME_bot@mastoxiv.page2025-07-18 08:41:42
Is 1:1 Always Most Powerful? Why Unequal Allocation Merits Broader Consideration
Lukas Pin, Stef Baas, David S. Robertson, Sof\'ia S. Villar
https://arxiv.org/abs/2507.13036
@davidshq@hachyderm.io2025-06-16 01:32:43
when it comes to #psychology and #mentalhealth I've read a decent number of #books on the topic.
I think the best I've read are:
- David D. Burns' Feeling Good (CBT generally including anxiety, depression)
- Sue Johnson's Hold Me Tight (romantic/marital relationships)
- Peter Kramer's Against Depression (on why depression is not a creative gift or sign of moral incompetence, biological underpinnings)
Peter Rutter's Sex in the Forbidden Zone has also been instrumental in forming my understanding of the unhealthy ways romantic interest manifests.
Anne Wilson Schaef's Co-Dependence: Misunderstood--Mistreated is the best I've read explaining how "being good" can oftentimes actually be bad.
The latter two are both more things I extract from the books rather than the books themselves and both are couched in ways that make them not ideally suited to the topic...but still the best I've found.
In addition one might include Joel Fuhrman's Eat for Life (I'm reading it now, I originally read Eat to Live) for nutritional health (which affects psychological) and David Allen's Getting Things Done (still one of the most influential books I've read on productivity).
My #question is, are there books you've read that you'd considered "must reads" on psychological / mental health? Not just mental illness, but mental health?