Because the people with power funding this shit have pretty much zero overlap with the people making this tech. The investors saw a talking robot that aced school exams, could make images and videos and just assumed it meant we have artificial humans in the near future and like always, ruined another field by flooding it with money and corruption. These people only know the word “opportunity”, but don’t have the resources or willpower to research that “opportunity”.

Can’t speak for the science libraries as I’ve never used em, and I’ll gladly just blindly accept that as truth, but for everything else it’s always a pain in the ass. For being designed to “run on anything” it sure is funny that 90% of the time I download a python app it doesn’t fucking work and requires me to look up and manually setup a specific environment for it. Doesn’t help that the error messages are usually completely random and unrelated to this…

I always dread when some fucking madman makes the installer for their app in python, knowing it’ll probably fail… God forbid it’s a script that’s supposed to modify something else. Always a good time for reflection upon the choices that led me to this point.

Even my old scripts I kept around for sentimental value. Half of those don’t work either, and I can’t be bothered to figure out what version I made em for.

I tried my best to scrub python from my pc out of principle, but as you say, it’s soo common my distro uses it as a dependency, fucking bullshit!

Assuming I’m an android fan for pointing out that Apple does shady PR. I literally mention that Apple devices have their selling point. And it isn’t UNMATCHED PERFORMANCE or CUTTING EDGE TECHNOLOGY as their adds seems to suggest. It’s a polished experience and beautiful presentation; that is unmatched. Unlike the hot mess that is android. Android also has its selling points, but this reply is already getting long. Just wanted to point out your pettiness and unwillingness to read more than a sentence.

Big leap for OpenAI, as in a kind of ML model they haven’t explored yet. Not that big for AI in general as others have done the same with similar result. Until they can make graphs where they look exceptionally better compared to other models than their own, it’s not that much of a breakthrough.

Dang, OpenAI just pulled an Apple. Do something other people have already done with the same results (but importantly before they made a big fuss about it), claim it’s their innovation, give it a bloated name so people imagine it’s more than it is and produce a graph comparing themselves to themselves, hoping nobody will look at the competition.

Just like Apple, they have their own selling point, but instead they seem to prefer making up stuff while forgetting why people use em.

On a side note they also pulled an Elon. Where’s my AI companion that can comment on video in realtime and sing to me??? Ya had it “working” “live” a couple months ago, WHERE IS IT?!?

It says a lot how the right keeps spamming us with AI images when making absolutely ridiculous shit up.

This process is akin to how humans learn…

I’m so fucking sick of people saying that. We have no fucking clue how humans LEARN. Aka gather understanding aka how cognition works or what it truly is. On the contrary we can deduce that it probably isn’t very close to human memory/learning/cognition/sentience (any other buzzword that are stands-ins for things we don’t understand yet), considering human memory is extremely lossy and tends to infer its own bias, as opposed to LLMs that do neither and religiously follow patters to their own fault.

It’s quite literally a text prediction machine that started its life as a translator (and still does amazingly at that task), it just happens to turn out that general human language is a very powerful tool all on its own.

I could go on and on as I usually do on lemmy about AI, but your argument is literally “Neural network is theoretically like the nervous system, therefore human”, I have no faith in getting through to you people.

Except for their low draw and thus unmatched battery life on portable devices, the M chips are honestly not impressive performance wise. Not really the appeal, even tho Apple is trying tooth and nails to pretend that that’s a selling point with their unlabeled graphs.

I mean if you really don’t want a GPU (which IMO is a must, given proper hardware acceleration which makes up for any CPU short comings, but I digress), that leaves you with a much bigger budget for the CPU, and now it’s no longer close enough to the M chips, but an absolute slaughter.

I don’t want to downplay or invalidate any of your preferences, but you HEAVILY miss represent the competition. Have you seen a non apple device in the past 5 years?

Other companies make metal body PCs now. From the dinky cheap ass laptop I bought just for fun, to my sister’s proper gaming laptop, there’s plenty of metal+glass laptops out there. And when it comes to android I only really follow Samsung, Sony and Google, but at least those 3 have had metal+glass flagship phones since I care to remember. (looked it up, Sony: 2013, Samsung: 2015, Google: 2018)

At 600 you can get a computer with an actual graphics card. The only outstanding feature of the M1/2 macs is the very low power consumption, the rest is quite subpar.

Sounds like a privacy nightmare honestly. Also a kind of black mirror like social point system.

Navigation is the only one that sounds neat, but also a bit brain rotting. I already don’t know where I am half the time because of navigation.

I’d like more basic things, like a floating music player, sticky notes/todo list, notifications bar or video/text, when looking at a restaurant seeing the reviews and menu with order options, looking at a product and getting more info. Just stuff that I’d need to manually look up otherwise or things that would be infinitely better without being hunched over a handheld device.

There’s plenty of room for improvement. I’m hoping we’ll see more stuff like the bigscreen beyond. The main reason I haven’t used my headset in like a year or 2 is just the annoyance of using it. Setting it up, cleaning it and my self, the weight because no-one wants to make a proper PC headset.

Calling the reward system hormones, doesn’t really change the fact that we have no clue where to even start. What is a good reward for general intelligence? Solving problems? That’s our current approach, which has the issue of the AI not actually understanding the problems and just ending up remembering question answer pairs (patterns). We need to figure out what defines inteligence and “understanding” in an easily measurable way. Which is something people knew almost a hundred years ago when we came up with the idea of neural networks, and why I say we didn’t get any closer to AGI with LLMs.

In theory. Then comes the question of how exactly are you gonna teach/train it. I feel our current approach is too strict for proper intelligence to emerge, but what do I know. I honestly have no clue how such a model could be trained. I guess it would be similar to how people train actual braincells? Tho that field is very immature atm… The neat thing about the human brain is, that it’s already preconfigured for self learning, tho it does come with its own bias on what to learn due to its unique needs and desires.

They are indeed. It has multiple steps, but pretty much. 3Blue1Brown has a nice visual explanation: https://www.youtube.com/watch?v=wjZofJX0v4M

You can think of the brain as a set of modules, but sensors and the ability to adhere to a predefined grammar aren’t what define AGI if you ask me. We’re missing the most important module. AGI requires cognition, the ability to acquire knowledge and understanding. Such an ability would make larger language models completely redundant as it could just learn langue or even come up with one all on its own, like kids in isolation for example.

What I was trying to point out is that “neural networks” don’t actually learn in the way we do, using the world “learn” is a bit misleading, because it implies cognition. A neural network in the computer science sense is just a bunch of random operations in sequence. In goes a number, out goes a number. We then collect a bunch of input output pairs, the dataset, and semi randomly adjust these operations until they happen to somewhat match this collection. The reasoning is done by the humans assembling the input output pairs. That step is implicitly skipped for the AI. It doesn’t know why they belong together and it isn’t allowed to reason about why, because the second it spits out something else, that is an error and this whole process breaks. That’s why LLMs hallucinate with perfect confidence and why they’ll never gain cognition, because the second you remove the human assembling the dataset, you’re quite literally left with nothing but semi random numbers, and that’s why they degrade so fast when learning from themselves.

This technology is very impressive and quite useful, and demonstrates how powerful of a tool language alone is, but it doesn’t get us any closer to AGI.

Nope, people are quite resilient. As long as it’s not a literal new born, the chance of survival isn’t THAT low. Once you get past 4 years and up, a human can manage quite well.

Also dying because no one takes care of you and you fail to aquire food and dying of a stroke/seizure are 2 very different things.

The 5 year old baby LLM can’t learn shit and lacks the ability to understand new information. You’re assuming that we and LLMs “learn” in the same way. Our brains can reason and remember information, detect new patterns and build on them. An LLM is quite literally incapable of learning a brand new pattern, let alone reason and build on it. Until we have an AI that can accept new information without being tolled what is and isn’t important to remember and how to work with that information, we’re not even a single step closer to AGI. Just because LLMs are impressive, doesn’t mean they posses any cognition. The only way AIs “learn” is by countless people constantly telling it what is and isn’t important or even correct. The second you remove that part, it stops working and turns to shit real quick. More “training” time isn’t going to solve the fact that without human input and human defined limits, it can’t do a single thing. AI cannot learn form it self without human input either, there are countless studies that show how it degrades, and it degrades quickly, like literally just one generation down the line is absolute trash.

Language models are literally incapable of reasoning beyond what is present in the dataset or the prompt. Try giving it a known riddle and change it so it becomes trivial, for example “With a boat, how can a man and a goat get across the river?”, despite it being a one step solution, it’ll still try to shove in the original answer and often enough not even solve it. Best part, if you then ask it to explain its reasoning (not tell it what it did wrong, that’s new information you provide, ask it why it did what it did), it’ll completely shit it self hallucinating more bullshit for the bullshit solution. There’s no evidence at all they have any cognitive capacity.

I even managed to break it once through normal conversation, something happened in my life that was unique enough for the dataset and thus was incomprehensible to the AI. It just wasn’t able to follow the events, no matter how many times I explained.

22 here, the only device in my apparent rn featuring a CD or DVD drive is an old ass iMac my gf intends to gut and put a mac mini inside just for fun, aka, likely disabling the DVD drive :(

We also probably have an external DVD reader in some drawer…

Considering we have like 5+ laptops and 2 desktops here, I’d say that says it all.

I predominantly download my music from bandcamp and my gf mainly uses Spotify.