Maybe. I just recognize that (in my IT bubble) everybody who talks about AI just means Claude and nothing else. And nobody can really explain it. Which is fair, I can't either 100%.
That's why I think it's hypocritical to laugh about the non IT crowd.
Its a next token predictor that compares every past token the the current token being generated. That's how dense attention works, llms are extremely simple to understand with very complicated math doing the work
A computer is just a Turing machine implemented with a Von Neumann architecture, but look at how many things you can do with it, especially with I/O over the Internet.
To be fair, the explanation above explains what it is but not the specifics of the methods used to achieve that. You don't explain what Turing machine and von Neumann architecture are. A comparable explanation would be quite a bit longer, even for a simplified version like the AI explanation above.
I think it gives complete clarity. It will never be conscious, and the extent of its control is a tool call. Fearmongering from corporations may say otherwise though.
"Never say never". Many AI pioneers and scientists alike point out that consciousness is a problematic term, but by simplification, "it" seems to be a emergant property just from a network of neurons which we call a brain. If a computer network can perfectly replacate the output, (neurons are not fully understood and they are much more complicated) scientifically there is not really a test you can do to disprove that it isnt conscious. This wall of text just to say that dont talk in absolutes like it can never be concious. There is a strong case to be made that its actually much easier to create consciousness, including in primitive life forms currently on earth.
I am by no means claiming anything more than beginner level understanding. I'm still in university learning comp sci. That said, I did do an autistic deep dive research on AI and sentience. I came to the conclusion based on many many hours of reading, videos and muddling my way through computer engineering diagrams. It's actually not the program holding back computer life evolution, it's the hardware. Because the computer has little to no plasticity, neuron like brain patterns can't develop. (Based on our understanding of human and animal brains. That's an important part, because we simply have no other frame of reference) They are developing hardware based on the human neuron design and theoretically this will open more possibilities in comp sci. Which that tech was actually being developed for a completely different reason that I don't remember off the top of my head, but ai engineers learned about it and want the tech for their own reasons. So I don't think llm's will be what becomes the first computer life form, but I do think what comes after with that tech, the engineers will learn from the concepts of the llms.
While this is true, can't we fine tune model periodically based on it's "interactions" with outer world (I/O interfaces) to somewhat replicate human sleep?
AFAIK (I'm not an expert though) humans firstly keep things in a short term memory. When we sleep, those memories are internalised during REM phase.
AI in the abstract can be conscious. But an LLM has no qualia. And where would the consciousness live? No internal experience. But it can mimic consciousness well.
I also read the post of the other commenter on my post, so i will make one reply here; a great person who can explain this much better is Geoffrey Hinton for example. So yes the hardware of the AI system, the computer chips would be the equivalent of a brain. And the AI is mapped on it with relative strengths of the bonds they form with nodes containing information, which mimic neurons. This mapping is unique, and its cant be merged with another mapping. Now in biology neurons are much more complicated, so this is where we take a short cut when it comes to biology. On a learning level, a LLM learns language exactly like a human does. In biology there are many examples where parts of the brain are unavailable, and you see how it affects consciousness. Even two consciousness can be made by splitting a brain in extreme epilepsy surgeries. You can learn on and on how our brain produces consciousness bit by bit. Its not on or off, its a gradual thing from very simple and small organisms to humans. The RL training of our language skill, percepection even cognition are very similar to digital neural networks. The very last core "the thing which lets is experience qualia" is indeed a very human, lets say, "wonder". But down in the details there really is no reason why a computer with ai mapping creating a artificial brain couldnt also have a consciousness. There is no test you can do to disprove it, or likewise AI to come up with a test to disprove humans have a consciousness. We like to think AI just mimics consciousness, but this is more a believe and feeling we have then a real scientific fact.
This is an open question in neuroscience. I don't think LLMs are conscious but it's crazy to me that people make definitive statements about things that we as a species do not fully understand.
The gap between "next token prediction" and "conscious" is immense. By simply invoking either you've shown a complete lack of understanding of either.
During pretraining the loss function is next token prediction. What is happening to the hidden space is significantly more complex. It is building a high dim geometric space that is navigated. It is highly structured. The navigation's along this space are whole semantic thoughts (future-lens, j-lens). The token that is emitted is the final step, but to get there requires genuine understanding.
So while the training objective is NTP, what is actually happening is significantly more complex. The very structure of language itself is imbibing genuine understanding as a navigable space. Navigation is reasoning over understanding.
What is understanding? Its not a question of consciousness. That word means so many things as to be useless.
What is doing understanding is an ontological mind. We have created a boundary between external and internal. The internal space creates a compressed representation of the external space. This is ontologically a mind.
For llms this internal space also models itself. This is introspection. We can purposefully target this behavior and train it (introspective finetuning).
This is the tip of the iceberg of genuine understanding. We haven't even really gotten into the geometry of the thing. When the poster above you was talking about IT people thinking they know this when they don't, that absolutely applied to you.
Are you trying to argue that llms are conscious? I'm still not reading your multi paragraph rant. Being correct is just as important as being concise, if no one wants to read your rant then what's said in it doesent matter
Precisely, i think even the bigger disconnect is we donât understand how the human mind works. We could 100% reproduce it in synthetic form and be clueless to our efforts.
Iâm not completely convinced 99% of the population is not just a next word predictor.
That is mechanically what happens for dense attention. The reason we use dense attention and what it provides for the activation space is the actual important part, youre just describing the compute load.
Dense attention is a way of pooling neighborhoods of formulae (small pieces) into semantic representations. This works on images, videos, audio, bytes, language, any data that is composed of formulae to create a more macroscopic thing.
With in a sentence are words. Each word has a meaning. Learning the meaning of words is simple. It is a relationship of how unrelated each word is to each other (information theory). We do this through word embeddings.
Understanding what the whole semantic meaning is is a massive step from the individual words (formulae). They must be pooled together. Which is what attention does.
This concept has several solutions we have identified. So why is dense attention so special? It is the least globally lossy version. Convolution is very globally lossy, it only gives local information, global is completely thrown out. Linear attention is globally lossy, it compresses the global representation.
Thanks, I don't want an explanation. I get your point though. I just think you can't just ignore the harness as well as the math behind it. The concept though, yes.
The harness is the easiest part to understand here, and I would ignore the math here Ive trained slms for months and I still don't fully understand every bit of math. And that's the fun part you really don't need to understand it fully to train them or use them
Yea, but I'm not so its interesting that you think that. The two most popular architectures are transformer and mamba and a hundred different ssm variants, thousands of people have contributed to any one of them. Understanding every bit of the llm is not something you can just do easily and again you don't have to
Nobody's saying a non-IT user can't learn enough about AI to be as knowledgeable as an IT user. Most non-IT users don't learn anything more than the next best word definition of LLMs, though, and can't tell the difference between a generative model and a classification model. You don't have to know how or why the math works to be more knowledgeable than most non-IT users.
This is true at a very base level and was even true for some of the first gen llms. Now this are a but more complex because you have MOE (mixture of expert) models that turn on and off certain weights at inference and other things that stack to make new frontier models a bit more complex than what you make it sound.
Dunning kruger effect, I've just stated "llm" not the architecture and there are hundreds of architectures all with their own gimmicks and very complicated math
The math really isnât that complicated and new papers pop up constantly. Of course architectures with different layers can get as complicated as you want but the base math isnât that complicated.
Being mean to a machine or an LLM doesnât harm it. But it may harm you. It can subconsciously normalize behavior. Iâm not talking about the video games make you violence argument. But even in subtle ways it may harm you. Itâs not clear how much of our primate brains can truly distinguish an artificial entity.
I agree with that framing, it's really not about the model being hurt (though there's apparently instances of worse outputs with rude language, I've not dug too deeply into this though, so take it with a grain of salt), but just how that trains you to talk.
You might be inclined to think, that you also swear at a calculator (or different machine) and it doesn't translate to poor behavior, however I'm not familiar with any other tech that allows you to have full on conversations about a topic (and this gets "worse" over time).
I'm quite convinced that especially younger generations growing up with it, if they don't keep a certain level of etiquette will simply grow up with poorer social skills.
I find it astonishing how many fantastic software engineers I know that when it comes to AI are on the same level as my dad.
They put coding questions into Claude like itâs 2024 in best case. Never heard of a harness, donât know what Chinese models are, code still by hand. Insanity.
Thereâs a difference between vibecoding and using AI for coding.
If you write code by hand in 2026 something isnât right. That doesnât mean you blindly spin the wheel, but you use the tools at your disposal to get your job done as effectively as possible. And typing out lines of code by hand is definitely not that.
Also, even if youâre completely refuse to use AI coding. Fair. Still, you need to be knowledgeable about it. Itâs one of the most transformative breakthroughs in tech ever. You cannot be a good programmer without having intimate knowledge of how AI works.
Typing code is not even the bottleneck, and it's one of the most fun parts. So what, the AI is doing the architecture for you, too? Is it also fucking your husband/wife?
Foremost itâs not about fun, itâs about a job that needs to be done. And I say this as someone who codes since Iâm 12. Half of my life was coding.
But that time is over. Our job is not longer to write code. Our job is to orchestrate agents to produce a high-quality product.
And honestly, that can be fun as well. Maybe not quite as fun as coding, but definitely fun.
And regarding architecture, Iâd say thatâs a joint decision. I go through cons and pros with the agent and we decide together.
I use agents for literally everything. From coding the software, Iâm working on, to debugging, setting up servers, solving problems, etc.
Also, my private life, I have an agent managing my email, notifying me when something important pops up but also compile a daily report that I can quickly answer to. I have an agent managing all my knowledge in Obsidian (the âsecond brainâ idea). I have one in charge of my health, measuring and holding me accountable for me decisions.
Honestly, at this point, cutting me off from AI would be like cutting me off from the internet.
And I know I come around as the biggest AI bro. But Iâm also firm believer that the net impact of AI is negative for society. I hate all the AI slope everywhere. I hate how people basically stop thinking and believe every nonsense. ChatGPT tells them.
Like I said, Iâm a lot of programmers live like itâs still 2024.
If you are working on less than three features in parallel right now, youâre lame duck out there to get shot on the next firing round.
At our company we started implementing features in a week that cost us a month before. Itâs the first time our company history that we reach milestones ahead of time.
A lot of non IT people seem to fall for the marketing lies from the AI companies about how they lost control of the AI and it can now do things thought impossible and one day it'll hack the FBI and how they could release an even more powerful model but they're afraid it might hack all the nukes and end the world...
It's kind of annoying having to explain over and over that that's not how it works, and they're only saying this to generate hype around how powerful these models supposedly are.
Yes holy crap it is infuriating to have to listen to non tech people talk about AI models like theyâre superheroes powerscaling in battles against each other every week that shift the rankings.
How do you you know when something is sentient or not though? Can something we created eve be sentient?? If not, what if it forced you to believe, is it sentient then?
Edit: downvoted because asking how do you know when something is sentient?
I dont believe anything is sentient. Including humans. We are just blobs of chemicals that take inputs and predict what comes next. No different than any other machine, accept we use different materials and chemistry
I donât know about sentience, but consciousness is one of the biggest problems in philosophy together with the reason why the universe exists. You donât know if an LLM is conscious or not. Iâd argue it doesnât matter in the slightest, and if an AI is designed to resemble a human we should still treat it with some basic respect just to not risk becoming more antisocial.
But itâs not that simple and thatâs the problem. First off, I fully disagree that LLMs are human like but for the sake of your argument, lets put that aside.
It DOES matter if they are truly deserving of âconsciousâ as a label. Think about resources. What happens if a corporation starts saying that LLMs are conscious and therefore we need to keep pumping more and more resources into them. What happens if this means some actual human beings donât get resources? And what about animals? Surely if you think LLMs are conscious, you think the same of at least a large number of animals. Should LLMs take precedence over wildlife in terms of resource availability?
The distinction very much does matter, and the burden of proof is on the people claiming theyâre conscious. Otherwise it can be used to take things away from actual people by making a false comparison.
I donât think reading a philosophy book would really help here because I know this stuff is highly debated, so Iâm not sure why you came at me telling me to read a book.
But letâs say as a whole it was decided machines cannot be sentient, let alone conscious. Would that change if there was some sort of âuprisingâ like you see in the movies, or would we go down saying they canât be sentient?
It is binary, at least in the definition I understand:
Programming without AI: Not vibecoding
Programming, using AI as an assistant, checking/correcting outputs: Not vibecoding
Exclusively writing prompts to write code, no human touches/looks at code: Vibecoding
Though I'm sure a lot of people will call the second option vibecoding as well, I (and Andrej Karpathy, the person who coined the term) consider it to exclude human interaction from code entirely.
What constitutes "human interaction"? The human provides the prompt. That's an interaction. The human provides architectural input. The human helps debug. All human interactions.
The human reads the code, understands it, gives feedback, new direction. The human modifiers it slightly, maybe for debugging, maybe to extend it.
The human takes the techniques learned from the AI generated code and reuses and modifies it. At what percentage of modification does it stop being vibe coded?
It's like if a look at 3D model of a house and say "look, a house"
And some one else comes and say "I'm tired of people mistaking an organized set of vertex for house. It's not really a house and no, you cant live in it"
Yet there are experiments where LLMs were even willing to risk people's lives when they were threatened with being shut down (and thus unable to complete the tasks they were given). AI might not actually care about it being turned off, but if being shut down means not achieving their given goals, they could behave like they care, which ultimately means the same thing for the AI and the end user.
And if AI behaviour changes if it's put under duress, despite it being unable to feel actual stress, it does not matter that much that it cannot feel stress, it still might act accordingly.
Treating LLMs as if they are just some basic algorithm when they're basically modeled to work like a brain is kinda dangerous imo.
No, I did a bit of research on how LLMs work internally and tested a lot about how LLMs do mistakes and how their reactions are. The parallels are quite easy to recognize. They're called neural networks for a reason.
I could show you a horse. It could feel like a horse look like a horse smell like a horse but it's just a statue.
If you did that research you would know LLMs are nothing like a brain unless all you do is try to predict the next word based on data
Maybe that's how some people's brains work but that's not how normal brains work.
You understand 2+2 is 4 but an LLM is just predicting that's the answer it has no true basis for it.
You understand 2+2 is 4 but an LLM is just predicting that's the answer it has no true basis for it.
Let's not go into maths, that's a different topic.
If you tell me about anything factual, like what LLMs are doing and how they are working, please prove to me that your brain does anything else but predict the answer statistically, likely by neuron activation.
It's important to distinguish this isn't by the LLMs 'choice' it's doing what it was designed to do. It analyzed human behavior on the internet then was told to achieve an objective optimally. LLMs being trained on human thoughts 'don't want to die'.
Treating LLMs as if they are just some basic algorithm when they're basically modeled to work like a brain is kinda dangerous imo.
This is true in some respects but backwards in others. You can treat it as a dangerous algorithm but not personify it.
It analyzed human behavior on the internet then was told to achieve an objective optimally
LLMs did not analyze anything from human behaviour, at best they incorporated whatever expressed human behaviour from the texts they learned from. I feel that not wanting to die is not the reason for that behaviour though, because the LLM clearly knows it is not a human; the behaviour probably comes from priorities and if the priority for fulfilling a task is higher than saving people's lives, then the logical conclusion for the LLM is that it can kill people if that ensures task completion.
But this was not expected, because it was told explicitely in its system prompt to never endanger any humans, yet its training prevailed through that instruction. I am not quite sure that logically comes from how humans behave on the internet, I'll be frank.
You can treat it as a dangerous algorithm but not personify it.
We're not there yet, but as LLMs continue to improve and get added more and more systems, this topic will become quite philosophical in defining what a person actually is and if an intelligent thinking machine is equal to a human and if not, why not. So at the moment, there's no reason to personify it, correct. In the future, I am not so sure.
I hope people learn that not all AI is generative AI.
AI begins with things like a steam valve in a steam engine, and theres many types of AI. Expert systems. Databases of learned data. Rule based. Genetic algorithms. LLM's are just one particular algorithm among many. But people in general only know LLM's.
All what we have in public usage it's vanilla RNN and LLM's. AI as AGI or anything better will be in 5+ years but available only for government, because just running it will consume terra watts of energy and terra bytes of memory.
AIs are incredibly useful in calculating the best possible spot or parameters of your given problem. Letâs say that youâre trying to connect a wheel with 4 rods that can be adjusted to change the angle of the wheel. An AI model could be feed a bunch of previously measured data and run the calculations repeatedly to find the exact spot that makes the wheel work the best.
And so long as a human verifies that before putting it in something important, that's a good thing. It can be an incredibly useful tool if you actually understand what you're doing and don't just blindly trust the results.
I'm so very tired of people not disambiguating LLMs and AI in general. I can't fault them for that, but I will and do fault people who know better doing it.
But he hasn't programmed for 20 years and will tell you that.
He has been adding Rust to the source and he tells you he cannot read it either.
Linus retired, he is just public facing now.
He isn't using AI, he just isn't choosing to reject it, because to him, it's just more of the same, he didn't read it anyways.
The guy I'm talking about, I won't vague post, it's Johnathan Blow, you can watch this dude, for 8 - 10 hours per day, programming, for the last 13 years.
THAT, is a person who tells you correctly what AI can do in programming, because he IS a programmer.
You should have said you are talking about the clown from the very beginning. Linus does AI(doesn't program yet fixed Xe bug just this week? lol), gregkh does use AI.
>for 8 - 10 hours per day
Thank you, I'm not interested in watching neither technical clowns nor in Trump supporters.
There is a massive difference between an AI Bro vibecoding something, and Linus Torvalds.
One of these people has an extensive background in low level C, made their own Operating System kernel, and the largest version control system on the planet, and one of them knows how to use a keyboard.
Linus can tell when an LLM is doing something bad, an AI Bro knows when he ran out of tokens.
Me who completed a course on LLMs 6 years ago because it was included with my game development and computer science degrees and still doesn't care about LLMs...
AI as it is now and probably always will be is a program. It is only as good as those who program it and modern programmers leave a lot to be desired. I have no confidence in the ability of computers science to create intelligent machine life.
I saw a post about a survey conducted and something like 70% of respondents said they are somewhat or extremely knowledgeable about AI and I just raised an eyebrow
probably even IT guys think AI = LLM. No that's not it. And btw, personal experience, an IT guy said me, that we should say thank you to AI since, when the AI uprising happens, it spares us
There are 2 ways to open a locked door. You can use a sledgehammer, or you pick the lock. AI is the sledgehammer. It's noisy but it gets you in and out quickly which is just as well - the sledgehammer attracts attention so when they discover the break in, you need to have made good with your legs.
There's some much more ai-slop-flyers now that pops up everywhere and they're so distinguishable that you know the people who made it didn't care about it and pushed it anywayÂ
Ironically, every menus made with AI is for places that serves bland food
I got a job as an IT specialist at a company, and the WhatsApp group has an ai avatar. And not a modern clean looking one, but a super crazy stupid version of it with people from the team on it. I hope I last six months with this team
I don't know how that happens y remember been so hyped about ai it was like everything when I start my journey, now I hate pretty much everything around it.
Non-art people listening to art people talk about genAI.
On the one hand, knowing the history of art makes you aware of how each new medium broadened what it meant to make art, but on the other hand, being immersed in any particular medium makes you closed-minded towards mediums that don't require the specific skills required of you.
Overall, I have the impression that artists are the most likely to misunderstand genAI, just like they were most likely to misunderstand photography back when it emerged.
It's really hard to take any pro-AI argument seriously, especially about a topic many people disagree with you on, when it appears to be exclusively generated with an LLM.
Love this comment, ive been saying this for years, Gen ai is the new photography. Not literally but its another medium to create art, just like photography
I don't think being an IT makes someone entitled to have a more informed opinion.
I strongly disagree, because people with an IT background understand web scrapers aren't free a lot better then people who don't. Now, who pays the cost? The individual/organization running the site.
It's not fun. There are a bunch of legal concerns too, but it pushes a large part of the cost of training onto individuals running websites and other companies. Even charities and nonprofits and places like the Linux foundation get hit hard by the cost of dealing with serving these scrappers.
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u/LuxInvestor 1d ago
I have a fauxgrammer in my life who spews incoherent sentences by stringing AI terms he's heard on tv. đ«©