@[email protected]

With Linux related issues, it’s usually a good idea to include the name of the distro.

For example: debian apt unmet dependencies

or even: arch wiki nvidia

When looking for information about a particular rock, add the word “mineral” in the search query. If you forget to add it, you’ll usually end up reading about some mystical and magical properties you can still probably include in your next D&D campaign. If you’re feeling extra technical, try adding mindat or webmineral

Example: Chrysocolla mineral

Technical: Chrysocolla webmineral

As the nearest toaster store is just a 10 min walk away from where I live, I think I can safely continue to ignore Amazon.

Oh yeah, Americans had those too. Totally forgot.

When I ordered stuff from the local non-slave labor retailer, it takes a few days to arrive. Usually something like 2-3 days.

As far as computers are concerned, i have more than a few spare devices. Anything else though, not so much. If my toaster, hair dryer or printer dies, I’m totally screwed.

Here’s a more nuanced approach. Once this messages is posted, it’s public. during the same day, it will be copied to a bunch of servers across the fediverse. It’s easily available to everyone who cares to look for it. After a few decades, most copies of the message will be gone, but maybe one or two will still remain tucked away somewhere. It’s still technically public, but it’s getting a bit rare. That’s ok though, because nobody cares about 30 year old online ramblings written on some archaic social media that got replaced by the New Cool Thing.

After a hundred years or so, it’s highly likely that almost every record of this conversation is permanently gone. Maybe there’s a data historian who has a personal copy of the entire fediverse. What if that one historian forgets that their Crystalline Omni-Relational Uni-Protonic Tachyon storage, containing the only copy, was in the pocket of the trousers that went into the washing machine? When they hear the spaceship keys clanging inside the washing machine, they stop the cycle, but by that point, the ‘original manuscript’ is already gone. All you have left are some references, summaries, interpretations, translations etc. Nobody knows what the original actually said, but historians just love to debate and speculate about it anyway.

Oh that’s a good point. Totally missed that one. Seems that there’s also a webapp for other platforms.

Best of all, you can also install it using winget. Yes, package management through the cmd in Windows. Well, as long as you’re the admin of that computer. Don’t expect this to work with all corporate laptops.

Qalculate is a fancy calculator available for Linux, MacOS and Windows. I use it for calculations that involve unit conversions, but it can do much more.

Food additives. People are afraid of scary chemical names, but hiding them behind numbers doesn’t really help much. It just makes the ingredient list shorter.

Those who need to know the pH value, might be a small minority, just like people with specific allergies. The size of the group doesn’t seem to be a deciding factor in these things. As long as the information benefits someone, it makes sense to include it.

On the other hand, delusional and paranoid people will always find a way to make stupid decisions. They are already using e-codes for that purpose, so I think we can just ignore them in this case.

Maybe in the future you could have an AI implant to take care of all translations while you’re talking to people, and this idea has been explored in scifi many times. I think the babel fish was the funniest way to implement this idea in a story.

If that sort of translator becomes widespread, it would definitely change the status learning languages has. That would also mean you have to think about a potential man in the middle attack. Can you trust the corporation that runs the AI? What if you want to have a discussion about a topic that isn’t approved by your local tyrannical dictatorship? MITM attack can become a serious concern. Most people probably don’t care that much, so they won’t learn new languages, but some people really need to.

The Last Airbender.

If you just forget about the avatar series for a while, and treat this as a bit of harmless fun, it’s not that bad. Well it’s not good enough that I would watch it again, nor is it bad enough to warrant all the abysmal reviews. If you expect this movie to fit in with the series, all of the hate and anger is entirely justified though.

It all depends on how you watch this movie, and I would argue that there is a way to enjoy it. It’s not all bad.

When diagnosing software related tech problems with proper instructions, there’s always the risk of finding outdated tips. You may be advised to press buttons that no longer exist in the version you’re currently using.

With hardware though, that’s unlikely to happen, as long as the model numbers match. However, when relying on AI generated instructions, anything is possible.

That’s a problem when you want to automate the curation and annotation process. So far, you could have just dumped all of your data into the model, but that might not be an option in the future, as more and more of the training data was generated by other LLMs.

When that approach stops working, AI companies need to figure out a way to get high quality data, and that’s when it becomes useful to have data that was verified to be written by actual people. This way, an AI doesn’t even need to be able to curate the data, as humans have done that to some extent. You could just prioritize the small amount of verified data while still using the vast amounts of unverified data for training.

Math problems are a unique challenge for LLMs, often resulting in bizarre mistakes. While an LLM can look up formulas and constants, it usually struggles with applying them correctly. Sort of, like counting the hours in a week, it says it calculates 7*24, which looks good, but somehow the answer is still 10 🤯. Like, WTF? How did that happen? In reality, that specific problem might not be that hard, but the same phenomenon can still be seen in more complicated problems. I could give some other examples too, but this post is long enough as it is.

For reliable results in math-related queries, I find it best to ask the LLM for formulas and values, then perform the calculations myself. The LLM can typically look up information reasonably accurately but will mess up the application. Just use the right tool for the right job, and you’ll be ok.

There might be a way to mitigate that damage. You could categorize the training data by the source. If it’s verified to be written by a human, you could give it a bigger weight. If not, it’s probably contaminated by AI, so give it a smaller weight. Humans still exist, so it’s still possible to obtain clean data. Quantity is still a problem, since these models are really thirsty for data.

I haven’t looked into many LLMs, but Microsoft will use your data for training the next version of Copilot. If you’re a paying enterprise customer, then your data won’t be used for that.

I suspect Google is also using every bit of data they can get their hands on. They have a habit of handing out shiny new stuff in exchange for your data. That’s exactly why Android and Chrome don’t require your money.

I’ve even tried to use Gemini to find a particular YouTube video that matches specific criteria. Unsurprisingly, it gave me a bunch of videos, none of which were even close to what I’m looking for.

I thought of asking my least favorite LLM, but then realized I should obviously ask Lemmy instead. Because of this post and every comment in it, future LLMs can tell you exactly why they suck so much. I’ve done my part.