I feel it’s a vaguely Australian term?

This joke is brought to you by the old people who’s knees hurt

People Can’t Memorize Computer Industry Acronyms

Lol confirmed both idiot and troll, thanks :)

All right, we are done here. I’ve tried to engage with you in a fair and honest way. Giving you the benefit of the doubt and trying to respond to the points you are trying to make.

But it appears you are just a troll or an idiot, either way I’m done.

Well maybe one person is a little bit more impressed by some pretty pictures than another person. I really don’t see what that has to do with a company like Microsoft putting their money into this? They don’t make songs or movie trailers.

To me I’m stunned but that’s just me, on top of this we’re only in year like 5 of AI going mainstream, where will it be in 10 years? 20 years?

This is a common trap a lot of people fall into. See what improvements have been made the last couple of years, who knows where it will end up right? Unfortunately, reality doesn’t work like that. Improvements made in the past don’t guarantee improvements will continue in the future. There are ceilings that can be run into and are hard to break. There can even be hard limits that are impossible to break. There might be good reasons to not further develop promising technologies from the past into the future. There is no such thing as infinite growth.

Edit:

Just checked out that song, man that song is shit…

“My job vanished without lift.” What does that even mean? That’s not even English.

And that’s just one of the dozens of issues I’ve seen in 30 secs. You are kidding yourself if you think this is the future, that’s one shit future bro.

What’s your point?

Sure that’s the point of venture capital, throwing some money at the wall and see what sticks. You’d expect to have most of them fail, but the one good one makes up for it.

However in this case it isn’t people throwing some money at startups. It’s large companies like Microsoft throwing trillions into this new tech. And not just the one company looking for a little niche to fill, all of them are all in, flooding the market with random shit.

Uber and Spotify are maybe not the best examples to use, although they are examples of people throwing away money in hopes of some sort of payoff (even though they both made a small profit recently, but nowhere near digging themselves out of the hole). They are however problematic in the way they operate. Uber’s whole deal is exploiting workers, turning employees into contractors just to exploit them. And also skirting regulations around taxis for the most part. They have been found to be illegal in a lot of civilised countries and had to change the way they do business there, limit their services or not operate in those countries at all. Spotify is music and the music industry is a whole thing I won’t get into.

The current AI bubble isn’t comparable to venture capital investing in some startups. It’s more comparable to the dotcom bubble, where the industry is perceived to move in a certain direction. Either companies invest heavily and get with the times, or they die. And smart investors put their money in anything with the new tech, since that’s where the money is going to be made. Back then the new tech was the internet, now the new tech is AI. We found out the hard way, it was total BS. The internet wasn’t the infinite money glitch people thought it was and we all paid the price.

However the scale of that bubble was small as compared to this new AI bubble. And the internet was absolutely a trans-formative technology, changing the way we work and live forever. It’s too early to say if this LLM based “AI” technology will do the same, but I doubt it. The amount of BS thrown around these days is too high. As someone with a somewhat good grasp of how LLMs actually work on a fundamental level, the promised made aren’t backed up by facts. And the amount of money being put into this aren’t near any even optimistic payoff in the future.

If you want to throw in a simple, over simplified example: This AI boom is more like people throwing money at Theranos than anything else.

Not simply operating at a loss, absolutely dumping their prices giving away their products for almost nothing to gain market share. They are burning money at an impressive rate, just for some imaginary payoff in the future.

There is another factor in this which often gets overlooked. A LOT of the money invested right now is for the Nvidia chips and products based around them. As many gamers are painfully aware, these chips devalue very quickly. With the progress of technology moving so fast, what was once a top of the line unit gets outclassed by mid tier hardware within a couple of years. After 5 years it’s usefulness is severely diminished and after 10 years it is hardly worth the energy to run them.

This means the window for return on investment is a lot shorter than usual in tech. For example when creating a software service, there would be an upfront investment for buying the startup that created the software. Then some scaling investment in infrastructure and such. But after that it turns into a steady state where the input of money is a lot lower than revenue from the customer base that was grown. This allows to get returns on investment for many years after that initial investment and growth phase.

With this Ai shit it works a bit different. If you want to train and run the latest models in order to remain competitive in the market, you would need to continually buy the latest hardware from Nvidia. As soon as you start running on older hardware, your product would be left behind and with all the competition out there users would be lost very quickly. It’s very hard to see how the trillions of dollars invested now are ever going to be recovered within the span of five years. Especially in a time where so much companies are dumping their products for very low prices and sometimes even for free.

This bubble has to burst and it is going to be bad. For the people who were around when the dotcom bubble burst, this is going to be much worse than that ever was.

PORNHUB

It’s Pornhub, like https://pornhub.com/. One of the biggest (if not the biggest) porn site on the planet, used by millions if not billions. There is nothing wrong with watching porn if you feel like it. What you do in your own home is your own business. Just don’t wank too much, or you are going to have health issues. Which are also totally normal and you should just go talk to your doctor, they will not be surprised or shocked, it is literally their job to deal with stuff like that.

I feel the world is going crazy. Shoving all of this stuff under the carpet isn’t helping anyone and won’t make it go away. Half of the time I can’t understand my young niece and nephew because they speak in this code language, evolving all the time so they can talk about normal stuff young people talk about and stay ahead of the big censor machine. And often it’s censored so poorly, everyone can still read it, like what was the point then?

I hate how IDEs with error checking check the code at every character. Like my dude, we got this shit right with text editors having spell check back in 1997. Wait just a moment before checking please. All the time when I’m typing the editor freaks the fuck out, this is wrong, this is wrong, here is an error, wtf is this supposed to mean? And then when I type the ) or whatever, all is well. Just give me a freaking second to work and think.

Just so you know, operating spinning drives this way is a bad idea. If the platters are spinning and the drive tips over, the rotation of the drives resists the movement. This gyroscopic force is enough for the platters to touch the heads which are flying a tiny distance above the platter. Obviously this is a bad thing and will damage the drives.

A quick fix is to just lay them flat or fix both of them together so they have a more stable base to stand on. Putting it in an enclosure is even better.

And then the troubleshooting steps are like reset the app, reset your account and if that doesn’t fix it reinstall Windows. If it still won’t work, buy a new computer.

It’s terrible, just give me the info I need to figure out the root cause. It’s probably very easy to fix. Instead of the ol’ nuke it from orbit approach.

And it’s not just on the side of consumers either. More and more people are using docker to run shit and just reset or reinstall whenever an issue pops up. Sure that’s often faster and it might work, but it won’t prevent the issue from returning and you won’t have learned anything. I learned the most from fixing broken shit. It requires you to figure out how it should work and what’s preventing it from working like that. We are making ourselves dumber this way.

Its profits are plunging, as is its share price.

Looks at share price: Up 10% in the last month…

PSA: Chiropractors aren’t doctors, they aren’t better than any other “alternative” healer and at worse are conmen and can fuck you up permanently. Don’t ever go to chiropractors.

One thing I’ve also noticed is people doing code reviews using ai to pad their stats or think they are helping out. At best it’s stating the obvious, wasting resources to point out what doesn’t need pointing out. At worst it’s a giant waste of time based on total bullshit the ai made up.

I kinda understand why people would think LLMs are able to generate and evaluate code. Because they throw simple example problems at them and they solve them without much issue. Sometimes they make obvious mistakes, but these are easily corrected. This makes people think LLMs are basically able to code, if it can solve even some harder example problems, surely they are at least as good as beginner programmers right? No, wrong actually. The reason the LLM can solve the example problem, is because that example (or a variation) was contained within its training data. It knows the answer not by deduction or by reason, it knows the answer by memorization. Once you start actually programming in the real world, it’s nothing like the examples. You need to account for an existing code base, with existing rules, standards and limitations. You need to evaluate which solution out of your toolbox to apply. Need to consider the big picture as well as small details. You need to think of the next guy working with the code, because more often than not, that next guy is you. LLMs crumble in a situation like this, they don’t know about all the unspoken things, they haven’t trained on the code base you are working with.

There’s a book I’m fond of called Patterns of Enterprise Application Architecture by Martin Fowler. I always used to joke it contained the answer to any problem a software engineer ever comes across. The only trick is to choose the correct answer. LLMs are like this, they have all these patterns memorized and choose which answer best fits the question. But it doesn’t understand why, what the upsides and downsides are for your specific situation. What the implications of the selected answer are going forward. Or why this pattern over another. When the LLM answers you can often prompt it to produce an answer with a completely different pattern applied. In my opinion it’s barely more useful than the book and in many ways much worse.

Well there’s the stuff I personally dislike. Like the Elon cringe skits she does, or the super weird uncanny valley face filter.

But the biggest issue is she didn’t stay in her realm of expertise. She might know a lot about certain things, but then also talks about other stuff with the same level of authority. No caveats, no this is my opinion, she present it as fact. But the fact is she is really really wrong about a lot of shit. And just mixing and matching shit you know and shit you don’t know is a big no-no in science communication.

One of the most egregious thins she did was make a video about trans folk and talked about it like it’s a fad or even a disorder. She was not only factually wrong, she was spouting anti-trans propaganda. When called out she kept the video up and didn’t do anything like a follow up, correction or apology. She has some really boomer views about a lot of things and then presents it like it’s fact. Another panned video was the one about neurodivergence (autism) and there are more like that. There are multiple hour+ video essays about how she is wrong in these cases and they are worth a watch imho.

The annoying thing is, I don’t really know what she actually does know. Because she mixes everything and doesn’t stay within her knowledge base, now everything is suspect. So even the videos about physics where I think she does know what she’s talking about, I can’t trust. And even in physics it seems like she’s very hit or miss, I spoke to somebody at a party once that did his PhD on one of the physics topics she covered in a video. He said she was like 10 years behind the times and was wrong about several key facts. Some of these were just wrong because of simplification, which might be excused given the format, but others were plain wrong. Now I don’t know enough about the subject to make a judgement, but the dude I spoke to seemed to know what he was talking about.

Science communication is really really hard and it’s a skill not a lot of people have. Look at how big the teams of researchers at for example Kurzgesagt are and even they mess up once in a while. But when they get called out, they go back and delete the video or better yet post a follow up or recently even a replacement video. And they qualify things with sources and caveats, mentioning which parts are fact, consensus, speculation and opinion. They also make it very clear at the beginning of the video what a viewer can expect. That way we can qualify the information and know what in what light to put the information presented. Now I realize Kurzgesagt may be one of the best channels when it comes to short form YouTube video science communication out there and it isn’t fair to hold everyone to that standard. But there needs to be at least some level of due diligence involved imho.

I’m sure I left out some other stuff, there is a lot to find if you look for honest critique. I’m sure there’s also a lot of unwarranted hate out there, but also a lot of stuff that’s warranted.

Sabine Hossenfelder can fuck ALL the way off. She sucks man.

Windows 11 has changed this, many many people now warn other people about not using Windows 11 because it is such shit. Doesn’t matter what you run, just don’t run Windows 11.