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Cake day: June 20th, 2023

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  • One of my childhood best friends transitioned and another came out as bi. I think a lot of it is just that people with ADHD and/or on the spectrum tend to get along really well with other ADHD/spectrum people. Since those traits heavily overlap with also being LGBTQ+, those who don’t fall into that overlap end up making friends in their youth with a lot of people who eventually come out later once they figure themselves out.




  • Not as drastic as the headline makes it out to be, or at least so they claim.

    “We acquired Tumblr to benefit from its differences and strengths, not to water it down. We love Tumblr’s streamlined posting experience and its current product direction,” the post explained. “We’re not changing that. We’re talking about running Tumblr’s backend on WordPress. You won’t even notice a difference from the outside,” it noted.

    We’ll see how that actually works out. Tumblr’s backend has always seemed rather… makeshift, so I’m curious to see how they manage to do that. Given Tumblr’s technical eccentricities, a backend migration could probably do a lot of good for the functionality of the site, if done properly. I have my doubts that WordPress’ engineers will be given the time and resources to do a full overhaul/refactor though, so I’m fully expecting even more janky, barely functional code stapling the two systems together.




  • “Product Degradation” has been the modus operandi for nearly every online service for like 10-15 years now, but it’s the Gamepass price increase is what got the FTC’s attention? Where was the FTC when the movie/TV streaming service market balkanized itself in an arms race to reinvent cable?

    Granted, I doubt the FTC could really do anything meaningful to stop enshittification given that corporations are effectively above the law these days, but it’s been blatantly obvious that this was going to be Gamepass’ strategy from day one. If this actually surprised anyone at the FTC, they really haven’t been paying attention.








  • In that case, I’m still not sure what the Intellivision brand even has left that Atari would want… I guess they could do one of those nostalgia re-release collections of old Intellivision games, but I feel like the nostalgia market for a nearly 50-year-old console mostly known for being a failed competitor to the 2600 is… very niche.


  • Huh, first I’m hearing of this Amico thing. I don’t know if it really has the support to capture enough of the market it seems to be going for… It looks like it’s trying to go for the “family-friendly, easy-to-use” concept that the Wii had, but the Wii had Nintendo behind it, along with other major publishers making games for it. The games included also look rather… basic.

    …Annnnd it’s also a Tommy Tallarico thing. Of course it is. Why on earth does Atari want this?


  • I hate that the focus of AI/ML development has become so fixated on generative AI - images, video, sound, text, and whatnot. It’s kind of crazy to me that AI can generate output with the degree of accuracy that it does, but honestly, I think that generative AI is, in a sense, barking up the wrong tree in terms of where AI’s true strengths lie.

    AI can actually turn out to be really good at certain kinds of problem-solving, particularly when it comes to optimization problems. AI essentially “learns” by extremely rapid and complex trial-and-error, so when presented with a problem with many complex, interdependent variables in which an optimal solution needs to be found, a properly-trained AI model can achieve remarkably effective solutions far quicker than any human could, and could consider avenues of success that humans otherwise would miss. This is particularly applicable to a lot of engineering problems.

    Honestly, I’d be very intrigued to see an AI model trained on average traffic data for a section of a city’s street grid, taken by observations from a series of cameras set up to observe various traffic patterns over the course of a few months, taking measurements on average number of cars passing through across various times of day, their average speed, and other such patterns, and then set on the task of optimizing stoplight timings to maximize traffic flow and minimize the amount of time cars spend waiting at red lights. If the model is set up carefully enough (including a data-collection plan that’s meticulous enough to properly model average traffic patterns, outlier disincentives to keep cars at little-used cross streets from having to wait 10 minutes for a green light, etc.), I feel that this sort of thing would be the perfect kind of problem for an AI model to solve.

    AI should be used on complex, data-intensive problems that humans can’t solve on their own, or at least not without a huge amount of time and effort. Generative AI doesn’t actually solve any new problems. Why should we care if an AI can generate an image of an interracial couple or not? There are countless human artists who would happily take a commission to draw an interracial couple (or whatever else your heart desires) for you, without dealing with investing billions of dollars into developing increasingly complex models built on dubiously-sourced (at best) datasets that still don’t produce results as good as the real thing. Humans are already good at unscripted creativity, and computers are already good at massive volumes of complex calculations, so why force a square peg into a round hole?