AI is not self-sustaining yet. Nvidia is doing well selling shovels, but most AI companies are not profitable. Stock prices and investor valuations are effectively bets on the future, not measurements of current success.
From this Forbes list of top AI companies, all but one make their money from something besides AI directly. Several of them rode the Web3 hype wave too, that didn’t make them Web3 companies.
We’re still in the early days of AI adoption and most reports of AI-driven profit increases should be taken with a large grain of salt. Some parts of AI are going to be useful, but that doesn’t mean another winter won’t come when the bubble bursts.
You’re using “machine learning” interchangeably with “AI.” We’ve been doing ML for decades, but it’s not what most people would consider AI and it’s definitely not what I’m referring to when I say “AI winter.”
“Generative AI” is the more precise term for what most people are thinking of when they say “AI” today and it’s what is driving investments right now. It’s still very unclear what the actual value of this bubble is. There are tons of promises and a few clear use-cases, but not much proof on the ground of it being as wildly profitable as the industry is saying yet.
To preface this, I’ve used Linux from the CLI for the better part of 15 years. I’m a software engineer and my personal projects are almost always something that runs in a Linux VM or a Docker container somewhere, but I’ve always used a Mac to work on personal and professional projects. I have a Windows desktop that I use...
Updated to be specific, I’m using Cinnamon. Muffin is the builtin tiling window manager for Cinnamon and it does exactly what you’re describing. The problem is that it moves tiles, it doesn’t absolutely position them. You have to keep moving tiles around to get them where you want them, Rectangle just has hotkeys to immediately place and resize to fit the active window for each quadrant that it supports:
ctrl+cmd+left: top left quadrant
ctrl+cmd+right: top left quadrant
shift+ctrl+cmd+left: bottom left quadrant
shift+ctrl+cmd+right: bottom left quadrant
alt+cmd+left: left half
alt+cmd+right: right half
alt+cmd+up: top half
alt+cmd+left: bottom half
alt+cmd+f: full screen
It’s hard to express how natural that feels after using it for a bit, and I’m still using a Macbook for work so the muscle memory is not going away.
I do quite like the stability of Cinnamon/Debian, and I think this problem is solvable (even if I have to solve it myself). I generally do not want to spend a lot of time futzing around with my desktop environment, but this is one thing I need to have.
Maybe this comment will age poorly, but I think AGI is a long way off. LLMs are a dead-end, IMO. They are easy to improve with the tech we have today and they can be very useful, so there’s a ton of hype around them. They’re also easy to build tools around, so everyone in tech is trying to get their piece of AI now.
However, LLMs are chat interfaces to searching a large dataset, and that’s about it. Even the image generators are doing this, the dataset just happens to be visual. All of the results you get from a prompt are just queries into that data, even when you get a result that makes it seem intelligent. The model is finding a best-fit response based on billions of parameters, like a hyperdimensional regression analysis. In other words, it’s pattern-matching.
A lot of people will say that’s intelligence, but it’s different; the LLM isn’t capable of understanding anything new, it can only generate a response from something in its training set. More parameters, better training, and larger context windows just refine the search results, they don’t make the LLM smarter.
AGI needs something new, we aren’t going to get there with any of the approaches used today. RemindMe! 5 years to see if this aged like wine or milk.
I didn’t say it wasn’t amazing nor that it couldn’t be a component in a larger solution but I don’t think LLMs work like our brains and I think the current trend of more tokens/parameters/training LLMs is a dead-end. They’re simulating the language area of human brains, sure, but there’s no reasoning or understanding in an LLM.
In most cases, the responses from well-trained models are great, but you can pretty easily see the cracks when you spend extended time with them on a topic. You’ll start to get oddly inconsistent answers the longer the conversation goes and the more branches you take. The best fit line (it’s a crude metaphor, but I don’t think it’s wrong) starts fitting less and less well until the conversation completely falls apart. That’s generally called “hallucination” but I’m not a fan of that because it implies a lot about the model that isn’t really true. Y
You may have already read this, but if you haven’t: Steven Wolfram wrote a great overview of how GPT works that isn’t too technical. There’s also a great sci-fi novel from 2006 called Blindsight that explores the way facsimiles of intelligence can be had without consciousness or even understanding and I’ve found it to be a really interesting way to think about LLMs.
It’s possible to build a really good Chinese room that can pass the Turing test, and I think LLMs are exactly that. More tokens/parameters/training aren’t going to change that, they’ll just make them better Chinese rooms.
I wouldn’t shortchange how much making the barrier to entry lower can help. You have to fight Rust a lot to build anything complex, and that can have a chilling effect on contributions. This is not a dig at Rust; it has to force you to build things in a particular way because it has to guarantee memory safety at compile time. That isn’t to say that Rust’s approach is the only way to be sure your code is safe, mind you, just that Rust’s insistence on memory safety at compile time is constraining.
To be frank, this isn’t necessary most of the time, and Rust will force you to spend ages worrying about problems that may not apply to your project. Java gets a bad rap but it’s second only to Python in ease-of-use. When you’re working on an API-driven webapp, you really don’t need Rust’s efficiency as much as you need a well-defined architecture that people can easily contribute to.
I doubt it’ll magically fix everything on its own, but a combo of good contribution policies and a more approachable codebase might.
Hyperfixating on producing performant code by using Rust (when you code in a very particular way) makes applications worse. Good API and system design are a lot easier when you aren’t constantly having to think about memory allocations and reference counting. Rust puts that dead-center of the developer experience with pointers/ownership/Arcs/Mutexes/etc and for most webapps it just doesn’t matter how memory is allocated. It’s cognitive load for no reason.
The actual code running for the majority of webapps (including Lemmy) is not that complicated, you’re just applying some business logic and doing CRUD operations with datastores. It’s a lot more important to consider how your app interacts with your dependencies than how to get your business logic to be hyper-efficient. Your code is going to be waiting on network I/O and DB operations most of the time anyway.
Hindsight is 20/20 and I’m not faulting anyone for not thinking through a personal project, but I don’t think Rust did Lemmy any favors. At the end of the day, it doesn’t matter how performant your code is if you make bad design and dependency choices. Rust makes it harder to see these bad choices because you have to spend so much time in the weeds.
To be clear, I’m not shitting on Rust. I’ve used it for a few projects and great for apps where processing performance is important. It’s just not a good choice for most webapps, you’d be far better off in a higher-level language.
I think operating at 5V input might be a technical constraint for them. Compatibility revisions for existing hardware are a lot more difficult if the input voltage is 9x higher. Addressing that isn’t as easy as slapping a buck converter on the board.
Not saying requiring 5A was the right call, just that I can see reasons for not using USB-PD.
Why do you think ventilators made people worse? They only put people on ventilators when their O2 stats dropped so low they were going to die of oxygen deprivation.
Part of the reason these rules are similar is because AI-generated images look very dreamlike. The objects in the image are synthesized from a large corpus of real images. The synthesis is usually imperfect, but close enough that human brains can recognize it as the type of object that was intended from the prompt.
Mythical creatures are imaginary, and the descriptions obviously come from human brains rather than real life. If anyone “saw” a mythical creature, it would have been the brain’s best approximation of a shape the person was expecting to see. But, just like a dream, it wouldn’t be quite right. The brain would be filling in the gaps rather than correctly interpreting something in real life.
This is an honest question, not a troll: what makes The Last of Us groundbreaking from a technical perspective? I played it and loved the story, but the gameplay was utterly boring to me. I got through the game entirely because I wanted to see the conclusion of the story and when the HBO show came out I was thrilled because it meant I wouldn’t have to play a game I hated to see the story of TLoU 2.
It’s been years, but my recollection is the game was entirely on rails, mostly walking and talking with infrequent bursts of quicktime events and clunky shooting. What was groundbreaking about it?
In reading this thread, I get the sense that some people don’t (or can’t) separate gameplay and story. Saying, “this is a great game” to me has nothing to do with the story; the way a game plays can exist entirely outside a story. The two can work together well and create a fantastic experience, but “game” seems like it ought to refer to the thing you do since, you know, you’re playing it.
My personal favorite example of this is Outer Wilds. The thing you played was a platformer puzzle game and it was executed very well. The story drove the gameplay perfectly and was a fantastic mystery you solved as you played. As an experience, it was about perfect to me; the gameplay was fun and the story made everything you did meaningful.
I loved the story of TLoU and was thrilled when HBO adapted it. Honestly, it’s hard to imagine anyone enjoying the thing TLoU had you do separately from the story it was telling. It was basically “walk here, press X” most of the time with some brief interludes of clunky shooting and quicktime events.
I get the gameplay making the story more immersive, but there’s no reason the gameplay shouldn’t be judged on its own merit separately from the story.
Dear lemmy, someone very close to my heart is starting to fall into conspiracy theories. It’s heartbreaking. Among other things, he has now told me that soy beans are not supposed to be consumed by human beings and is convinced that despite the literal centuries of human soy bean cultivation and consumption, we shouldn’t eat...
People from east and southeast Asia have been cultivating and eating soy beans as a staple food since before Babylon. I mean that literally; there is evidence of soy bean cultivation in what is now China from like 7000 BC.
It’s tough to take a phrase like, “Soy makes men weak,” as anything other than racism when it puts down a quarter of the population of the planet. At best, it’s ignorance, but in my experience the people who hold this opinion don’t change their mind when you explain this to them.
Evidence that LLMs are reaching a point of diminishing returns - and what that might mean (garymarcus.substack.com)
Rectangle for Linux?
To preface this, I’ve used Linux from the CLI for the better part of 15 years. I’m a software engineer and my personal projects are almost always something that runs in a Linux VM or a Docker container somewhere, but I’ve always used a Mac to work on personal and professional projects. I have a Windows desktop that I use...
Experimental Video Game Made Purely With AI Failed Because Tech Was 'Unable to Replace Talent' (www.ign.com)
PSA: You can't delete photos uploaded to Lemmy. So don't (accidentally) upload a nude (tech.michaelaltfield.net)
Raspberry Pi is now manufacturing 70,000 Pi 5s per week, will surge to 90,000 in February (www.tomshardware.com)
Drug that Trump called a ‘miracle Covid cure’ is linked to 17,000 deaths (www.independent.co.uk)
A drug infamously touted by Donald Trump has been linked to nearly 17,000 Covid deaths in a new scientific study....
Rule (lemmy.blahaj.zone)
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Why do people want games that are just stories without any gameplay, these days? Why not just watch a movie for that?
Why are there so many conspiracy theories regarding soy beans?
Dear lemmy, someone very close to my heart is starting to fall into conspiracy theories. It’s heartbreaking. Among other things, he has now told me that soy beans are not supposed to be consumed by human beings and is convinced that despite the literal centuries of human soy bean cultivation and consumption, we shouldn’t eat...