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Cake day: June 14th, 2023

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  • That’s hard for me to answer because I’m usually at home plugged in, and I set the max charge in the bios to only 65% so the battery will physically degrade slower (I don’t need the charge). A few hours is really all I can say with any accuracy. Worth noting a few things -

    1. Since I bought my laptop they came out with an improved battery I could upgrade to, so you’d get a better experience.
    2. I believe(?) battery life is improved a fair bit at least with the AMD ones; less sure on the newer Intel ones.

    I will say that if long battery life is your #1 concern this may not be the laptop for you.






  • I think it really strongly depends on what you’re programming - I know in some instances Julia’s performance can be nearly identical to languages like Rust. I suspect in my case it related to Julia being a garbage collected language, as my algorithm involved creating very large dynamic structures in memory before serializing them, clearing the memory, and building another one. Since Rust has no garbage collector it knew exactly when and what to drop from memory. In my case I had roughly a 10x(!!) speed-up. Funny enough an even earlier version of that algorithm was programmed in Java, and Julia was roughly 10x faster that it, so Julia isn’t the worst of the pack.


  • So at my previous employer I developed using Julia a custom ML model which ran, but the performance just wasn’t good enough for what I needed despite trying to aggressively optimize. I ended up rewriting in Rust (and calling through R) which ended up being like 10x faster. At my current job I program a mixture of Rust and Python.

    If Julia were more peformant then it could potentially be an alternative to Python/R users having to learn Rust - but if you’re looking for top performance, some of your codebase is already written in R/Python, and you’re already willing to learn another language, then learning something like Rust naturally seems the better choice over Julia.

    The one thing I did like about Julia - it took barely anytime at all to build a working prototype.











  • festus@lemmy.catoAsklemmy@lemmy.mlWhat's with all the tech layoffs?
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    10 months ago

    Sometimes I like to think of the economy as a small village where people directly goods with each other. The invention of money means you can make a living off of selling to just one person and still have something to offer the farmer, but for this thought experiment this I want to focus on the actual, real, goods and services of the economy.

    So imagine a small village. You have the farmer who grows food. You have the blacksmith who builds car parts, and the mechanic that builds cars and tractors. And you also have the village fool who makes people laugh in exchange for tips. The mechanic gives tractors to the farmers in exchange for food, and gives some of that food to the mechanic in exchange for parts. When any of them need a laugh they’ll give something to the fool to hear a joke. And you have your other industries, etc. One day a new person comes to town, who will represent the new tech industry. They realize that they can build a machine that tells the farmer the best days to plant and harvest which will help the farmer grow more food. The farmer happily accepts, paying the tech person some food in exchange. Similarly they’re able to help optimize the other industries, and with the value they’re providing and them being in short demand they’re able to get great wages.

    With their prosperity, other tech people start coming to the village and helping the other industries get more efficient. Most of the concrete efficiencies are optimized, so they start working on more abstract ones. Someone builds an app to help the villagefolk find someone to trade with (“I have 2 gears but I need 3 loaves” gets matched with “I have 2 wheat bushels and need 2 gears” which gets matched with “I have 3 loaves and need 2 wheat bushels”), in exchange getting a small cut of those resources, and a larger cut if someone pays for preferential matching (advertising). Other tech people find work helping the other tech people at their jobs (IDEs, libraries, issue trackers, etc.) And other tech people build animatronic village fools to entertain the village themselves (video games).

    More tech people come as they’ve heard of how much they can earn at this village. Eventually they start having some trouble finding work to do, everything seems optimized. Some of the wealthy members of the town (let’s say the farmer of the biggest field) says to many of these tech people that they’ll pay them food in exchange that the farmer gets a portion of whatever the tech person ends up earning with what they build (low interest rates). With all the good ideas used up, the projects these tech people are working on aren’t working well (crypto) or are duplicates of already existing tools (how many social media apps do we need, etc.). Still though, the farmer is giving them a lot of food so yet more tech people come to the village, and many of the children of the village (like the farmer’s son) are becoming tech workers too.

    Eventually, after a bad crop season (maybe because the farmer’s son didn’t help harvest), the farmer is short on food and stops lending out food to these tech workers. They try to go around to the other villagefolk but most have already been optimized. The tools that optimized life are already built and the required tech people for maintenance is a lot less than those needed to build it, and the number of truly new opportunities to help new industries isn’t enough to provide work to all the tech people.

    TL;DR

    Tech people earned their crazy salaries when they were helping migrate the non-digital world to the digital world. There were so many obvious opportunities for efficiencies and not enough tech people to go around. ‘Spreadsheet’ calculations literally used to be a day-long affair with a team of people - of course a business would pay anything to a tech person to automate that. Now that times the whole economy.

    These obvious efficiencies are finite but we treated them as infinite and kept training new tech workers. Low interest rates helped keep us employed for longer than we should have as we were paid to work on bad products in the hope that maybe there’d be a diamond in the rough and yet we STILL kept training new workers. Meanwhile other careers that provide more concrete value, like mechanics & HVAC professionals, have had a labour shortage as Tech attracted so many young people to itself. This eventually led to persistent inflation which then ended low interest rates. With higher interest rates a lot of speculative tech can’t get funding; Tech is only getting paid for the actual new value it can provide today, which is way less than it used to be.