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Joined 11 months ago
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Cake day: August 11th, 2023

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  • It’s not lying or hallucinating. It’s describing exactly what it found in search results. There’s an web page with that title from that date. Now the problem is that the web page is pinterest and the title is the result of aggressive SEO. These types of SEO practices are what made Google largely useless for the past several years and an AI that is based on these useless results will be just as useless.










  • You seem to talk about different things when you say “visual clue”. Yes, there will be a small duration in the video where the event happens and maybe a short aftermath. That’s not a visual clue, that’s the thing you’re looking for. What all others mean by visual clue is a definite indicator that you can see when picking any random frame in the video that tells you if that frame is before or after the event. That allows you to exclude all other frames from your search, reducing your search range by half.

    A stolen bike, a broken window, your examples that trash the place or end up with a crowd of people in the area, all leave such a visual clue. At any random frame you can check if the bike is there or not, the window is broken or not, etc.

    But let’s say you have footage of the street facing CCTV and you need to find at what time the suspect left the scene (crime happened somewhere else). There’s nothing that tells you when looking at the halfway point if the suspect already passed or didn’t. You still have to look at both sides of that point in time.

    The classic example for binary search is looking for a word in a dictionary. You open it halfway and see if the words there are before or after the one you’re looking for. Then you know which half of the dictionary you need to look in next. Then you use the same method for that half and so on.

    But what if someone highlighted a word in the dictionary and you don’t know which word? Binary search is useless. You have to skim through the whole thing until you see it.



  • It probably depends a lot on where you live. My wife’s bike got stolen and she was woken up by police coming to check on it (one of the maintenance guys at our apartment noticed a man at 7-Eleven riding it and recognized it; came back running to check if it’s indeed missing and called the police). We fully expected the police would do nothing about it (it was the cheapest Walmart bike), but an hour later they called that they found the bike and have the culprit in custody. It did help that the bike was a girly mint green with a wicker basket, so they instantly recognized it when they saw it.

    Then again, in San Francisco, when my wife got her car window smashed and wallet stolen (she was late for class and dropped her wallet under the car seat, didn’t stop to take it; but it wasn’t the wallet that caught the thieves’ attention, it was the breast pump bag that looked like a laptop bag; they threw it on the floor when they saw what it was), we never heard anything back from the police.



  • I use it both ways. As a software engineer I use it for various packages, which don’t even need a releases page. But also as an end-user of open source software, I use it to download pre-built binaries of said software. Idk if you know, but there’s a lot of open-source software out there. And github is the most popular platform for hosting it. And when I say software, I mean the kind where you don’t expect your users to know how to build it from code themselves.




  • If you use it as a developer you don’t care about the releases page. You want to see the code and for latest version you just need the git tags. But I’ve also used it for stuff I just needed to run on my machine as an end-user. And for those you turn to the Releases page. That’s where pre-built binaries go.

    But it also depends on the target audience. Some projects, even if meant more as software to run than code to import, still target mainly developers or tech users in general and will not have more than just instructions on how to build them. Others, say a Minecraft launcher, or some console emulator, will target a wider audience and provide a good Releases page with binaries for multiple platforms.


  • Deep learning did not shift any paradigm. It’s just more advanced programming. But gen AI is not intelligence. It’s just really well trained ML. ChatGPT can generate text that looks true and relevant. And that’s its goal. It doesn’t have to be true or relevant, it just has to look convincing. And it does. But there’s no form of intelligence at play there. It’s just advanced ML models taking an input and guessing the most likely output.

    Here’s another interesting article about this debate: https://ourworldindata.org/ai-timelines

    What we have today does not exhibit even the faintest signs of actual intelligence. Gen AI models don’t actually understand the output they are providing, that’s why they so often produce self-contradictory results. And the algorithms will continue to be fine-tuned to produce fewer such mistakes, but that won’t change the core of what gen AI really is. You can’t teach ChatGPT how to play chess or a new language or music. The same model can be trained to do one of those tasks instead of chatting, but that’s not how intelligence works.


  • Any type of content generated by AI should be reviewed and polished by a professional. If you’re putting raw AI output out there directly then you don’t care enough about the quality of your product.

    For example, there are tons of nonsensical articles on the internet that were obviously generated by AI and their sole purpose is to crowd search results and generate traffic. The content writers those replaced were paid $1/article or less (I work in the freelancing business and I know these types of jobs). Not people with any actual training in content writing.

    But besides the tons of prompt crafting and other similar AI support jobs now flooding the market, there’s also huge investment in hiring highly skilled engineers to launch various AI related product while the hype is high.

    So overall a ton of badly paid jobs were lost and a lot of better paid jobs were created.

    The worst part will be when the hype dies and the new trend comes along. Entire AI teams will be laid off to make room for others.