You have been misinformed about fluoride in toothpaste and water. Please take the time to inform yourself and trust in facts, not propaganda.

Not meaning any disrespect or negativity towards you, just a heads up.

Jami?

I don’t think it’s much of a surprise when we look at America that they don’t value human life all that much.

As someone with a website, the AI scraper bot traffic is off the fucking scale. It’s like being under constant DDOS attacks. It isn’t like normal search crawlers that rate limit, do careful indexing and respect stuff like rel=“nofollow” and robots.txt. These AI scrapers just spam the shit out of anything and everything, hundreds of requests per bot. You block one IP, it seamlessly moves over to another IP. You do user agent detection, they just pretend to be a regular browser, totally fucking up all your stats while they are at it.

Having some form of bot protection like Cloudflare or Anubis is almost required these days. It’s like AI was designed specifically to fuck shit up, there is no reason they can’t just crawl the internet like a normal crawler. But they have to be assholes about it. Bad enough I won’t get anyone actually visiting my site, since the AI overview thing blocks that, but do they have to go the extra step to kill it altogether?

Sure in principle you could check all the output the AI shits out to see if it’s right and then spend time correcting it either by hand or by prompting some more. And in doing so, one might be able to do more in a given amount of time, or less. Recent studies have shown it might have felt like programmers were able to do more, but in reality did less in the same time. But that might vary from person to person and the given tasks.

However that skips over other issues:

Reading and understanding code is so much harder than writing code. This has been known for decades. So instead of doing the easier task of writing the code yourself, you are left with reviewing and understanding the generated code. This add a lot of extra cognitive load, which can lead to fatigue quickly. This fatigue feeds into another issue, where it’s so much easier to just hit approve on everything and skip out on the really in depth stuff. People tend to slack and just glance at the code, which is a huge trap, because LLMs are very good at writing code that looks right, regardless of if it is right.

Then there’s the issue where writing the code is a small part of the task usually. There’s also understanding the task and figuring out edge cases. It’s hard to do that all up-front and at least for me, while writing the code I think of edge cases or get a deeper understanding of the task. By flying through the writing part, the deeper understanding gets skipped as well.

And the issue of bias, where it’s often a lot better to think about an open question instead of a multiple choice question. With vibe coding it’s very easy to be lead down a path by the LLM, where it suggests a path which seems logical, but might actually be wrong. Then breaking out of that path can be hard. This might be an actual wrong path, or it might just stifle creativity. A common complaint is all AI generated stuff “feels” very samey, which makes sense because LLMs are designed to see common patterns in a lot of the data. The more common a pattern is, the more likely the LLM is to suggest it.

Another very common issue with LLMs is they tend to touch stuff they shouldn’t. This is because of how they work is by processing everything as a stream of text. So let’s say I want to expand a template with a new part, it has no choice but to read the entire template and then output the entire template as well. It’s supposed to just add the new part, but often it makes other changes as well. And this happens on a multiple-file base as well.

One big issue I’ve noticed is the regression of skills for people who use AI for their work (coding or other). It’s so tempting to just press the big green EASY button on just about any task. But then when the AI isn’t able to do the task right, people are stumped and are no longer able to do the things they used to be able to do for decades before. Especially with coding, it isn’t like riding a bicycle where once you know how, you are able to do it forever. It’s a lot more like a muscle you need to keep excising and if you don’t it’s going to lose power and capabilities.

And we’re not even touching other issues with LLMs in general, like concentration of power, vendor lock-in, obfuscated pricing, resource usage, (un)fair use of source data, hallucinations, manipulation, destruction of the internet etc.

So for me the people who say: “It’s just a new tool, you wouldn’t go back to hand punching paper tape right!??!!?” are being very disingenuous about the actual issues. Sure it’s just a new tool, but one with real consequences to using it. As with every tool we need to weigh the pros and cons and just because it’s available, doesn’t mean we have to automatically use it. We still see people enjoying a command line or text-based interface, even though most people use graphical interfaces. And I personally code without any form of autocomplete, because I find it annoying and distracting. Just because tools exist, doesn’t mean we should all use them and it certainly doesn’t mean we should be blind to the downsides attached to certain tools.

If you make that face, it’ll stay like that.

I was told this as well, so I’d try to look as sad, afraid and angry as possible. I’d contort my face for hours, trying to push the corners of my mouth down till it hurt. I wanted it to stay like that, so when I went to school the next day somebody would ask me what’s wrong and I could tell them about my father beating the shit out of me every day. Unfortunately, it did not stay and nobody asked.

Yeah I can already see it, everything that is wrong, yeah its the Dems fault. We really really want to fix it, but those damned Dems are blocking everything.

I would not be surprised shit goes to absolute hell by the end of the year with the AI bubble popping and we get another terrible Republican president because of the timing with the election now.

Can’t even use sarcasm on the internet these days, thanks Obama!

And I still wonder if there even is any demand at all. Sure it’s used a lot, but most of that is free or highly subsidized services. And from startups that throw money at the wall and have no chance at all of ever becoming profitable. But there is demand from enterprise tho! Is there? The era of tokenmaxxing is over and enterprise is cutting down on AI costs after seeing spending balloon and no real increase in profits or revenue or even productivity. Some people claim to be more productive, but it’s not by a wide margin and the ROI is hard to see.

All AI is used for is filling the internet with slop. If generating an image of AI lobster Jesus would actually cost what it should cost, I wonder if they would still be generated as much. So these AI companies see high usage, more than they can handle, and claim high demand. They buy all the hardware, hardware producing capacity and force the construction of all these datacenters. Often by bribing officials, speed building, cutting corners and not caring about anything sensible like the environment. Instead of also investing in renewable energy, they just plop down gas turbines, because it’s cheaper and faster. And for what? So we can generate more slop?

But no worries guys, we’ll ask Grok how to solve climate change, not a problem! A little more fucking up the environment now doesn’t matter, we’ll get our magical genie to create a magical solution to all our problems. Which is so fucking dumb, it’s doubtful anyone actually believes that.

We already know how to solve climate change, we just choose not to because it would mean giving up some luxuries.

Also: The rainbow you see depends on your position. So a different position yields a different rainbow, even tho it’s the same source of light and the same bulk refraction. It isn’t like there actually is some kind of physical thing in the sky we see, it’s just the light being refracted into our eyes.

No I don’t think so. It think that specifically points to that specific image. The other images are from the final result, which was done by an artist as the author states.

I think they are just from testing tho, not a real situation, to show the different configurations.

I also don’t think the article was LLM written. It might be assisted by LLM, but I see some human patterns in there.

Holy shit, it’s 21 degrees out and this dude is rocking the wood burning stove till it’s hot as balls inside the home. No worries tho, the aircon is on in the bedroom. Holy shit it’s set to heat at 26 degrees. Dude must be a lizard or something.

Never slop, why would you use an AI image here? There weren’t enough images of teapots on the internet?

More QA is nice, the bug that broke pivot tables in Calc recently made a lot of people unhappy. Would be nice if often used features were tested before release.

Stop drinking the kool-aid my man, just because the AI companies label things as “thinking” and “reasoning” doesn’t it’s the same thing as those terms when applied to humans. There is an argument to be made the analogy works well enough with some terms, but especially with reasoning it’s pure marketing BS.

Internally reasoning is called “internal recursion” and it’s more of a scratch pad. It allows the model to split up tasks into smaller bits, where it would choke if it tried to tackle the whole thing at once. It goes through the question, tries to come up with results and writes those down in its scratch pad. That whole scratch pad including everything that came before (system prompt, prompt, context etc) gets put into the model again to produce the final result.

Not to be confused with Chain-of-Thought, which is similar but different. That’s where multiple passes get made and the tasks are actively broken up with different system prompts. This especially helps in tasks where the context would run out, but doing the same thing in smaller steps does work.

It’s very annoying how AI companies heavily anthropomorphize everything related to LLMs, right down to calling it AI instead of just an LLM and leave the intelligence out of it. This easily dupes and confuses people into thinking the tool is something it’s not. People think because they use terms like reasoning and thinking that these models have motivations, internal dialog, actual thoughts and even do things like planning, anticipating and predicting. This simply isn’t the case, it’s a mathematical model, you input numbers and it spits out numbers. When you input the same numbers, the same numbers come out (although parts can apply randomization, usually controlled through a parameter called temperature). It isn’t alive, it isn’t thinking or reasoning or smart. It doesn’t have motivations or evil intentions. It’s just numbers.

Even if it were all above board, it’s just gambling and should be heavily restricted just as all other forms of betting.