• 5 Posts
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Joined 1 year ago
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Cake day: June 18th, 2023

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  • I have gone through the links, and I still cannot find the answer to my question on what makes UPI “absolutely horrible when it comes to privacy” when compared to the other options in your original comment.

    I still maintain that all practical means of digital transactions are inherently poor for privacy, regardless of the channel/medium. One is not less private than the other.

    Of course, mediums like cryptocurrency exists which “promise” privacy while transacting. But they are not practical in India, and also do not operate at the scale of the options we are discussing about.

    Also, I really appreciate responding back with links, but a line directly answering my question would have saved some time, especially since the links you shared are irrelevant to our discussion. None of the links actually do a comparison of the options or even state that one is outright better than the other. If anything, some of the comments in the linked forum posts only echo what I am saying about the lack of privacy across all digital transactions.







  • Not just song lyrics, but any piece of media

    rant

    This is horribly rampant issue on Reddit. Swaths of comments reduced to three-word dialogues from movies that even most Americans may not have seen.

    While it might be acceptable in a community specific to that piece of media, it always comes across as lazy everywhere else.

    A simple link to a relevant clip or snippet would help contextualise the reference, but if commenters were willing to put in that effort, they probably wouldn’t resort to quoting three-word phrases in the first place.

    Unfortunately, this practice is becoming common on Lemmy.

    Some might see my rant as gatekeeping, but it genuinely hinders meaningful discussion on the topic at hand.

    It is a pet peeve of mine that led me to unsubscribe from many, otherwise good, subreddits and eventually leave that platform altogether (thanks to a push from its CEO).




  • I have experienced this myself.

    My main machine at home - a M2 Pro MacBook with 32GB RAM - effortlessly runs whatever I throw at it. It completes heavy tasks in reasonable time such as Xcode builds and running local LLMs.

    Work issued machine - an Intel MacBook Pro with 16GB RAM - struggles with Firefox and Slack. However, development takes place on a remote server via terminal, so I do not notice anything beyond the input latency.

    A secondary machine at home - an HP 15 laptop from 2013 with an A8 APU and 8GB RAM (4GB OOTB) - feels sluggish at times with Linux Mint, but suffices for the occasional task of checking emails and web browsing by family.

    A journaling and writing machine - a ThinkPad T43 from 2005 maxed out with 2GB RAM and Pentium M - runs Emacs snappily on FreeBSD.

    There are a few older machines with acceptable usability that don’t get taken out much, except for the infrequent bout of vintage gaming





  • Refurbished ThinkPads are available in countries where Framework, System76, and Pine64 do not ship.

    Besides, ThinkPads are really well-built machines that perform well for everyday tasks at a fraction of their (or the aforementioned competition’s) original price.

    I love my two machines, which are from before Lenovo took over completely. Their keyboards, port selection, and repairability are almost unparalleled compared to today’s competition.




    • Windows 95, 98, 2000, XP, 7 spanning a decade and a half.
    • Ubuntu 10.04 going up to the release where Unity became the default DE (11.04, I think). Came back to 10.04, as it was an LTS release.
    • Linux Mint Maya because of Cinnamon, and it was terrible.
    • Fedora 16 to 25 or 26.
    • Linux Mint 19

    Been with Linux Mint ever since. It just works. LM19 was also around the time when I stepped into Apple’s walled garden with iOS and macOS.



  • I do not agree with @FiniteBanjo@lemmy.today’s take. LLMs as these are used today, at the very least, reduces the number of steps required to consume any previously documented information. So these are solving at least one problem, especially with today’s Internet where one has to navigate a cruft of irrelevant paragraphs and annoying pop ups to reach the actual nugget of information.

    Having said that, since you have shared an anecdote, I would like to share a counter(?) anecdote.

    Ever since our workplace allowed the use of LLM-based chatbots, I have never seen those actually help debug any undocumented error or non-traditional environments/configurations. It has always hallucinated incorrectly while I used it to debug such errors.

    In fact, I am now so sceptical about the responses, that I just avoid these chatbots entirely, and debug errors using the “old school” way involving traditional search engines.

    Similarly, while using it to learn new programming languages or technologies, I always got incorrect responses to indirect questions. I learn that it has incorrectly hallucinated only after verifying the response through implementation. This makes the entire purpose futile.

    I do try out the latest launches and improvements as I know the responses will eventually become better. Most recently, I tried out GPT-4o when it got announced. But I still don’t find them useful for the mentioned purposes.