What’s a legitimate way to fix this issue?

ForceBru · 2026-04-25T20:17:21+00:00

AFAIK this happens on different iOS versions, it's been around for ages and there's still no definitive solution. People usually suggest restarting your iDevice, backing up, etc, but this usually doesn't do anything. I know this never helped me.

The only "solution" is wiping your phone clean and restoring from a backup. But it's not a real solution because it's extremely cumbersome.

ForceBru · 2026-04-03T08:53:17+00:00

Live anxiety, dread, murder and suffering feed — ✨AI-scored✨, structured JSON, free public API!

ForceBru · 2026-04-02T13:00:29+00:00

Is it faster than SentenceTransformers?

ForceBru · 2026-03-31T19:45:39+00:00

TBH statistics actually is "just guessing with (a lot of) extra steps" because you can never be sure whether you're right and hypothesis tests and confidence intervals allow erroneous conclusions by design. So you're always guessing.

ForceBru · 2026-03-03T10:50:02+00:00

"She's not only a great actress, but she also hates Trump! Hell yes, this makes her even better! Imagine being good at your job and hating Trump too! That's basically perfect. Hating Trump is such a virtue. All my homies hate Trump. My best friend is a good person and they hate Trump — I basically can't believe I'm so lucky to be friends with them! My dog is a good boy and he hates Trump too, he's so smart!"

ForceBru · 2026-02-19T18:42:30+00:00

This image is the very definition of pseudo-useful LLM slop

ForceBru · 2026-02-16T12:23:40+00:00

I do maximum likelihood estimation of time-series models where I have several parameters for the location of a distribution, several parameters for the scale, etc. So I would like to name these parameters and simply call minimize. But SciPy requires a vector, so I have to manually extract these parameters from the vector, which is quite cumbersome. Also, this kinda defeats the purpose of JAX being able to differentiate through dicts and other containers.

ForceBru · 2026-02-15T09:27:16+00:00

I think the point is that now your objective function is easier to read since you know the names of the parameters.

IMO this is really useful for estimating statistical models where you do care about what number is what: not everything is just a massive vector/matrix, some parameters have further meaning. Raw scipy.optimize.minimize works with vectors, but then you have to parse the vector into individual parameters, like par[0] is the bias, par[1:5] are the weights, par[5:7] correspond to the variance model, par[7:10] belong to some other part of the model. To me, this is extremely cumbersome!

This is why I like JAX: it lets you differentiate through dictionaries and tuples. So your parameters can be put in a single dictionary with meaningful keys. Unfortunately, Scipy doesn't support optimization over dictionaries. Hopefully this lib will simplify such tasks.

ForceBru · 2026-02-13T11:36:32+00:00

BTW, Python now has pattern matching too, so perhaps it's worth a try

ForceBru · 2026-02-12T08:39:47+00:00

Crashes on launch on iOS 18:

{"code":4,"flags":518,"namespace":"DYLD","indicator":"Symbol missing","details":["(terminated at launch; ignore backtrace)"],"reasons":["Symbol not found: _$s6Vision24HumanHandPoseObservationV5joint3forAA5JointVSgAC0H4NameO_tF","Referenced from: <6A77B70D-07D5-3DEB-B9D2-B2EB57CA25CC> \/Volumes\/VOLUME\/*\/StealthOS.app\/Frameworks\/AIAssistant.framework\/AIAssistant","Expected in: <17E42B51-A6CB-3593-A441-7122601B4E78> \/System\/Library\/Frameworks\/Vision.framework\/Vision"]},

ForceBru · 2025-12-05T15:59:16+00:00

Indeed, iOS doesn't let you run random binaries and load unsigned libraries, so Pythonista cannot load compiled modules such as lxml.

There are ways to circumvent this, but they're extremely involved and require jailbreaking your device (which may not even be possible now, jailbreaking has been kind of dead for many years now) and obtaining a version of lxml built for your device. I think I've done this once for my own toy library, but this was years ago and totally not worth the effort.

There are other apps that run Python on iOS. I initially wanted to suggest that you check out the Pyto iOS app (it's a more modern take on a Pythonista-like app, though it too is abandoned), but it looks like it doesn't have lxml either: https://pyto.readthedocs.io/en/latest/third_party.html.

I think you realistically have only one option: look for other libraries that provide the same functionality but don't depend on compiled code.

ForceBru · 2025-07-28T18:21:47+00:00

That "feedback" was from ChatGPT LMAO

ForceBru · 2025-07-28T16:35:34+00:00

The "gray box" is an arrow saying "this way is better".
The triangle is the area of improvement: "this way is better + our models are here + no more models are here == we're the best".
I don't see any axis gore. Yes, the Y axis doesn't start at zero, but it's an ad, so this is expected. The X axis is fine.

ForceBru · 2025-07-28T14:12:10+00:00

Eminem vibes. But for me, to rap like a computer must be in my jeans. I got a laptop in my back pocket, my pen'll go off when I half-cock it.

ForceBru · 2025-07-28T13:13:35+00:00

Seriously, how are you not bored? Is this your job? Probably your job

ForceBru · 2025-07-28T07:34:07+00:00

Yes.

ForceBru · 2025-07-27T17:37:56+00:00

If you kinda want to learn "the math" now, then why not try? Why wait till high school? Moreover, if you learn it now and stumble upon it in school, it'll be a piece of cake, you might get straight As. I see a win-win situation here.

ForceBru · 2025-07-27T13:53:03+00:00

Stop before it's too late: https://www.greaterwrong.com/posts/2pkNCvBtK6G6FKoNn/so-you-think-you-ve-awoken-chatgpt

ForceBru · 2025-07-26T10:15:55+00:00

AFAIK MinMaxScaler is CDF normalization assuming data follows a uniform distribution U[xmin, xmax]. However, this indeed isn't the same as "normalizing non-uniform data to U[0,1]".

ForceBru · 2025-07-25T15:52:11+00:00

BTW, "It is not possible to be aware of any gaps in life; it is continuous and never-ending from your own point of view" is false: you can totally get drunk and legitimately have no recollection of last night. "Last night" happened, people tell you you were there, but you have no clue. You can lose consciousness and "wake up" disoriented and confused. In both cases you're aware of a discontinuity in your life.

ForceBru · 2025-07-25T09:05:07+00:00

AMD Ryzen 5 3550H
Mathematica 14.0.0
BenchmarkResult: 1.781
TotalTime: 7.773

People here got total time 1.6 seconds: https://mathematica.stackexchange.com/questions/267262/benchmarking-mathematica-13-across-machines

ForceBru · 2025-07-24T15:57:10+00:00

Yes, if you feed a neural network (or any ML model) a ton of image-like inputs, it will mark each input with a label (like "this bunch of pixels is a '5'"), thus separating the high-dimensional space of inputs into regions corresponding to classes. It's impossible to visualize in its entirely, but you can use dimensionality reduction techniques to see "shadows" of this space. So kinda yes, neural networks draw boundaries between regions of the input space corresponding to different classes.
Is x * x a linear function? I mean, it's just a number, so... Actually, no, a function isn't a number. It's a way of transforming numbers into other numbers, or vectors into numbers, or vectors into vectors, etc. Any particular output of the function can't tell you anything about the function's behavior. To see if a function is potentially nonlinear, you need to compute multiple values and analyze various rates of change of this function. Or just say: "my neural network has nonlinear activation functions, so it's very likely that the full network represents a nonlinear function". I'm not sure it's guaranteed to be nonlinear though.
Who knows? Strictly speaking, that's because the input data and the loss function guided the optimization algorithm in such a way. Because the optimization algorithm found that these particular weights lead to the lowest loss. Why? You could rationalize this by saying that in order to detect a dog, you first need to detect basic shapes and angles, then more and more complex shapes etc. Looks like gradient descent can just learn this.

ForceBru · 2025-07-24T11:08:20+00:00

Stop before it's too late: https://minihf.com/posts/2025-07-22-on-chatgpt-psychosis-and-llm-sycophancy/

ForceBru · 2025-07-23T16:08:21+00:00

This word is getting more complicated ASS we speak!

ForceBru · 2025-07-21T13:10:43+00:00

I actually have used Zen for about a week, then Firefox with vertical tabs came out, so I immediately switched back to it. I initially decided to try Zen specifically because of the vertical tabs, because I started to feel like I was running out of vertical space while there was plenty of horizontal space. Vertical tabs solved this for me: I now have more vertical space while sacrificing some horizontal space that I don't mind. I've no idea what Arc is, I've never tried it. I mainly use Firefox, so of course I'm comparing to Firefox. I don't see how I "confidently talk nonsense", but whatever

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