PM_ME_VINTAGE_30S [he/him]

Anarchist, autistic, engineer, and Certified Professional Life-Regretter. I mosty comment bricks of text with footnotes, so don’t be alarmed if you get one.

You posted something really worrying, are you okay?

No, but I’m not at risk of self-harm. I’m just waiting on the good times now.

Alt account of Also if you’re reading this, it means that you can totally get around the limitations for display names and bio length by editing the JSON of your exported profile directly. Lol.

  • 9 Posts
Joined 1 year ago
Cake day: July 9th, 2023


  • PM_ME_VINTAGE_30S [he/him]@lemmy.sdf.orgtoMemes@lemmy.mlMath
    2 days ago

    Sounds like fun! I’m going to bed soonish but I’m willing to answer questions about multivariable calculus probably when I wake up.

    When I took multivariable calculus, the two books that really helped me “get the picture” were Multivariable Calculus with Linear Algebra and Series by Trench and Kolman, and Calculus of Vector Functions by Williamson, Crowell, and Trotter. Both are on LibGen and both are cheap because they’re old books. But their real strength lies in the fact that both books start with basic matrix algebra, and the interplay between calculus and linear algebra is stressed throughout, unlike a lot of the books I looked at (and frankly the class I took) which tried to hide the underlying linear algebra.

  • It can use ChatGPT I believe, or you could use a local GPT or several other LLM architectures.

    GPTs are trained by “trying to fill in the next word”, or more simply could be described as a “spicy autocomplete”, whereas BERTs try to “fill in the blanks”. So it might be worth looking into other LLM architectures if you’re not in the market for an autocomplete.

    Personally, I’m going to look into this. Also it would furnish a good excuse to learn about Docker and how SearXNG works.

  • LLMs are not necessarily evil. This project seems to be free and open source, and it allows you to run everything locally. Obviously this doesn’t solve everything (e.g., the environmental impact of training, systemic bias learned from datasets, usually the weights themselves are derived from questionably collected datasets), but it seems like it’s worth keeping an eye on.

    Google using ai, everyone hates it

    Because Google has a long history of doing the worst shit imaginable with technology immediately. Google (and other corporations) must be viewed with extra suspicion compared to any other group or individual because they are known to be the worst and most likely people to abuse technology.

    Literally if Google does literally anything, it sucks by default and it’s going to take a lot more proof to convince me otherwise for a given Google product. Same goes for Meta, Apple, and any other corporations.

  • simultaneously blame democrats … for having too much government reach and action on immigration and the border AND THEN turn around and complain that they are too soft on the border and immigrants are just flying through.

    I don’t think anyone around here thinks that Biden’s being “soft” on the border…or that we should even have a border in the first place…

    The phrasing “too much government reach and action on immigration” (because they should have none, which neither party offers) and “soft on the border and immigrants are just flying through” (because any maintenance of the border is unacceptable, whether “soft”-looking or not) really shows how silly it is to try and pigeonhole everything into partisan newspeak. Let’s say it like it is: borders suck and all of us here (I hope) are going to criticize any party or group that wants to continue hurting people because of them, regardless of who they claim to represent.

    it’s sooo cool to blame Democrats (and apparently liberals…

    I mean yeah it totally is lmao.

  • DSP (digital signal processing) is the field of applied mathematics and engineering dedicated to transforming and manipulating digital signals.

    Examples of real digital signals include audio files, image files, video files, and digitized recordings of various physical quantities by computers like the configuration of a robot as it moves in time, measurements of the processes in a factory, the trajectory of a spacecraft — almost anything that can be periodically sampled and take on a finite set of values [1] can be seen as a digital signal.

    DSP includes using tools like the Discrete Fourier Transform (DFT), the Z-transform, wavelet analysis, probability, statistics, and linear algebra to do things such as filter a signal (example: audio equalizer), predict future values (example: weather forecasting), data compression (example: JPEGs), system identification (example: fit a model of the earth to predict seismic activity), control (example: make a DC motor to respond to position commands), and stabilization (example: keep plane from “wanting” to smash into the ground). Particularly, it requires a careful consideration of the effect of sampling a signal (example: if done carelessly, you can make the sampled system unstable [read: explode]), as well as an interpolation process of some kind if you plan on using that signal outside your computer (example: you want to hear an audio signal stored on your computer).

    I got into DSP because I was an audio engineer and musician [2], and I wanted to design my own audio plugins. IMO I think almost everyone would benefit from some knowledge of DSP, but the math is really intense. Personally, I found out late in life that I have a nearly infinite appetite for math, so it’s a good fit for me.

    Here’s a playlist about DSP if you’re interested.

    [1] Actually, a lot of basic DSP books don’t restrict the signal to be in a finite set because it makes the math easier if the signal could be any real number. However, certain structures that would be exactly equivalent in theory are not equivalent on a real computer because ordinary computer arithmetic is approximate.

    [2] I still play music, but not as much as before engineering school.