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Cake day: July 3rd, 2023

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  • Yeah, it’s specifically the not talking to a kid version that bothers me.

    I pick up a subtext of self-importance and I think that’s what I find irksome. A mom is a parent. A momma is a special parent who will do anything for their baby, you’d better watch out. A kid is a child. A kiddo is a specific child who has a close bond with their momma or teacher that you wouldn’t understand. That’s the vibe I get.




  • Uli@sopuli.xyztoTechnology@lemmy.worldThe most popular GenAI Tools
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    1 month ago

    My feelings are mixed. Everything you are saying is true. LLMs, right now at least, are a huge waste of resources. It’s triggering us to move closer to fossil fuels when we should be moving away. Every time I step outside to a nice balmy day, I think, am I going to miss this in a few years’ time? In a few decades, am I going to envy my current self who can do dishes without worrying too much about how much water goes down the drain? Are the generations to come going to look at my occasional can of tuna with contempt and jealousy? Or will they even have the luxury of retrospection?

    I understand what we have to lose and how little we are doing about it. But I have also grown up being subjugated inside a capitalist hellscape. And I’ve spent the past few days having ChatGPT help me set up a CI/CD pipeline and start coding some games I’ve wanted to make for years. It’s allowed me to take a few hours of free time and make progress that I expected would have taken a week. It doesn’t have that effect on every task, but when learning new software, it really feels like having someone knowledgeable sitting next to me to answer my questions and point me in the right direction.

    GPT 3 was kind of a neat party trick - sounds kind of like a person, but a pretty dumb person. GPT 4 sounded smarter, but still couldn’t code for shit. The o1 model still makes mistakes, but it retains the thread of our conversation weeks after the fact and has put together some code that I would have struggled to do myself. Even if it loses more money than it makes right now, I can see the value in progressing development until we achieve AGI.

    People have expressed hopes that AGI will solve a lot of the world’s problems. That it will know just what to do about climate change. That it will crack codes in our DNA and give us endless healthy life. I am doubtful that these dreams will come to fruition. At least not in the way people think. It might have the intelligence to tell us things that we should have already known. Like that we can’t get much better yields in scrubbing carbon from the air than nature itself and we should have reforested far more land than we currently are. And that immortality will take huge amounts of resources and will come at the expense of the health of the masses. More gain for the rich. More suffering for the poor. Business as usual.

    But I think there is a window of time where we can be hopeful about what AI has to offer. And we may even be able to leverage it to solve a big piece of the income inequality puzzle.

    If we make a social media app that is not designed for profit but instead for the good of the people, there are a lot of problems such an app could solve.

    We could design it to seek out real (non-bot) contributors. It will always be an arms race trying to sort real humans from bots but that is no reason to give up. It is a reason to get as far ahead in the race as we possibly can. We should build an app that both recognizes when someone is very likely to be real and when they have also contributed to a cause.

    Imagine an application that tracks creative innovation, such as the creation of a funny video or a new meme format. When someone makes an idea and it is popular, the AI model would determine how much of a given experience is improved by their idea and give them profit residuals based on their contribution. And the more ideas that get built on top of the original idea, the more the newer contributors are rewarded for their contributions.

    Think about if people could design a farm from the ground up using a socialized app for collaboration. Someone could design a camera system to keep track of livestock wellbeing and to head off diseases. They could make AI-empowered systems to track livestock happiness and find ways of increasing quality of life. And creating more humane automated methods of turning crops and livestock into food ready to transport. Some people would focus on creating ideal distribution methods. Others would create stores or restaurants. Others might work on the people themselves, encouraging them to give new more climate friendly meal options a try. Investors would be paid their dues, but there would be no CEO or board of executives. The means of production would belong to the people.

    When people talk about the potential of AI, that’s what I envision. If I can make some passive income with my games and apps, that’s the next project I’ll be diverting my time towards. Because this is a narrow window we have to make this happen. The technology is here, but barriers from climate change and income inequality are only going up. We can lament the fact that AI is currently not profitable and hurting the planet, or we can put more of that energy to use by taking the tools humanity has made and using them to dismantle the systems which made this timeline so intolerable to begin with. The only way to take the current system apart is to make a new one that outcompetes our old ways of life in every measurable way.








  • I used to work for a company that did various kinds of biometric recognition. I unfortunately was paraded past these cameras many times for testing purposes, so my face was compromised many moons ago.

    We had two kinds of products we installed in airports. When looking at large crowds most airports wanted cameras that would monitor the flow of traffic, determining if there were any bottlenecks causing people to arrive at their gate (or baggage claim) after their luggage.

    The other product was facial recognition for identification purposes. These are the machines you have to stand right next to. There are various legal reasons airports did not want to use any crowd-level cameras for identification. They hadn’t obtained consent, but also, the low resolution per face would lead to many more false positives. It was also too costly.

    But we did have high def cameras installed in strategic locations at large music halls. These private companies were less concerned with privacy and more concerned with keeping banned individuals out of their property. In those cases, we registered faces of people who were kicked out for various reasons and ignored all other faces.

    My point I guess is twofold: first, you might not be facially tracked in as many places as you think you are. Second, eventually you will be and there’s not a whole lot we can do to stop it. For many years, Target has identified people with their payment card, used facial recognition to detect when they return to the store, and used crowd tracking to see where in the store you go (and sometimes they have even changed ad displays based on the demographics of people standing nearby).

    Mostly, you will be identified and tracked when there is financial incentive to do so.



  • I finally got fed up with my Windows machine and upon seeing symptoms of motherboard failure, I’ve ordered all the parts for a new rig and intend on installing Linux as my primary OS.

    Haven’t decided on a distro yet. I’m a DevOps engineer with a few passion projects, so I plan on setting up a couple of kubernetes clusters where I can play. I do all the usual things (word processing, gaming, web browsing, multimedia, etc), plus some AI stuff (stable diffusion, local LLMs, OpenCV). Ideally don’t want to have to fuss with drivers too much, but I don’t mind getting my hands dirty every now and then.

    Is Chimera the kind of distro I should be looking at, or should I pick something else for my first go at full-time Linux?


  • Respectfully, I disagree. We’ve entered an AI boom, and right now, the star of the show is in a bit of a gangly awkward teenage phase. But already, these large data models are eating up mountains of energy. We’ll certainly make the technology more energy efficient, but we’re also going to rely on it more and more as it gets better. Any efficiency gains will be eaten up by AI models many times more complex and numerous than what we have now.

    As climate change warms the globe, we’re all going to be running our air conditioning more, and nowhere will that be more true than the server centers where we centralize AI. To combat climate change, we may figure out ways of stripping carbon from the air and this will require energy too.

    Solar is good. It’s meeting much of our need. Wind and hydroelectric fill gaps when solar isn’t enough. We have some battery infrastructure for night time and we’ll get better at that too. But there will come a point where we reach saturation of available land space.

    If we can supplement our energy supply with a technology that requires a relatively small footprint (when it comes to powering a Metropolitan area), can theoretically produce a ton of power, requires resources that are plentiful on Earth like deuterium, and doesn’t produce a toxic byproduct, I think we should do everything in our power to make this technology feasible. But I can certainly agree that we should try to get our needs completely met with other renewables in the meantime.






  • A lot of people describe the first moment of the big bang as infinitely small, dense, and hot. These descriptions may approximate that first moment of existence, but they slightly miss the mark because in the very first moment of existence, size, density, and temperature didn’t exist. There was nothing to compare anything else against.

    Instead, let’s visualize that moment as infinitely same. Erase all thoughts of violent explosions happening very quickly and instead just imagine a single point of light. Not big, because size requires multiple things. Not small because it encompasses everything. Just one infinite same.

    Now, since it’s hard for us to visualize change in an infinite void that is simultaneously nothing and everything, imagine that point of light as a magical tank engine at the front of a never-ending train. And our job as conductors of that train is to get to the caboose at the end.

    The train cars could theoretically go in any order, but because we conductors are beings of time who need them to arrive on a schedule, we must visit each car in a precise order. And before we can access a car, we must make it unique by showing it something that has never been seen before.

    For the first car, this is easy. We simply show it the tank engine at the front of the train. So, the inside of the first car transforms its interior into a copy of the tank engine it’s attached to.

    But when we arrive at the second car, things are more complicated. The cars have already seen the tank engine. So, instead, we show the second car the first car. And the second car transforms into a copy of the first car and the tank engine attached to that. And inside the copy of the first car is another copy of the tank engine.

    As you can imagine, the further down we get on this train, the more this starts to get out of hand. Copies of copies of copies abound. The magic train is powerful, but as mortal conductors of time, we worry our own powers may have limits. So, to reduce the burden on ourselves, we take some shortcuts. Instead of trying to visualize increasingly long nested copies of trains inside each new car we visit, we start to conceptualize these copies as amounts, or amplitudes. When we open the door to a new car, all of the amplitudes inside resonate and interact, becoming maybe more abstract than they are in reality. They form spatial dimensions and physical properties, as mediated by fundamental forces.

    These aren’t set in stone, but determined by the lens through which we view them. And when we look through specific lenses, we see these forces causing certain repeated amplitudes to intermingle and stabilize to the point that even though all of the train copies are further nested when we step into the next car, we can recognize and identify some of the same structures, just shifted slightly in their spatial relationships since we last witnessed them in the previous car. We call these persistent formations matter. And as their shared spatial relationships cause them to cluster and coalesce, we refer to that as gravity.

    While in the early cars, this continuum of space and matter is not impossible to conceptualize, the more cars we travel through, the more apparent it becomes that these increasingly complex objects are becoming more and more isolated from each other. At every scale of amplitude, each nested car is attached to its own tank engine. While these engines can interact with each other virtually, at the end of the day, they are all just virtual copies of the train we are on. It is entirely impossible for any one of these tank engines to travel so far that it reaches the edge of its bounding box. Because that bounding box is just a lens through which we imagine overlapping traits of increasingly many very similar objects. And the more of them we imagine, the more space is required to provide the virtual framework of this lens.

    So, when we feel like we are experiencing random events in our small subsection of the universe, those events are not truly random, but instead the result of our precise position in the the universal train we’ve been virtually sliding through for over 13 billion years. The universe has become so large that it contains every possible event that could have happened in this span of time. The events are not random but calculated, and duplicated every moment so that every time we enter a new train car, two copies of our observable universe exist at a distance so far apart it’s impossible to comprehend.

    And when we observe celestial objects apparently propelled away from each other at increasing speed, they are not really being pushed or pulled anywhere. It is simply an artifact of trying to keep track of the “same” object in rapidly advancing train cars, while each car doubles in size to contain everything the previous car had, as well as everything new that might emerge from the duplication event. The celestial objects year by year, and indeed ourselves from moment to moment, are never the same thing twice. It’s an illusion brought forth by our brains being born into a cosmic flipbook.

    Even something as simple as seeing multicolored pixels on this screen is not real, but the result of virtual “tank engines” moving into the same spatial zones occupied by our retinas, which are themselves constructed of virtual trains of varying size. The reason photons move at a set maximum speed which makes them exempt from experiencing time is because they are all just virtual copies of the real locomotive which is driving the whole train. Every photon in our universe is just a make-believe copy of the very first moment of the big bang. A specter of infinite sameness.

    So, objects in our universe aren’t moving apart as much as the space between them is increasing to account for the overhead of a universe with constantly growing entropy and uniqueness. The extra space represents a boundary which limits how far light can travel and affect matter in its realm of influence. If you’re still reading this, somewhere out there, in a part of our universe so far away that light from our known universe will never even remotely reach, there is an opposite you made of antimatter reading the exact same thing as written by an opposite me. But we are only made of matter because of a virtual compression of sameness, so that antiverse may be the exact place where the curvature of the entire universe loops back around and is overlaid upon itself. And the uncertainty of photons may arise from the fact that there are two identical universes overlapped and constantly exchanging probabilities. And this may be the compressive property which allows the fundamental forces to exist in the first place. So, say hi to yourself. You’re the reason you’re here.