I would trust Linus Torvalds to use AI to do this because the AI is literally trying to copy him when it writes that code. In that context, he is the training data.
I always knew that man would become senile one day. It’s either that, he’s been morally compromised by a/n ai company, or both. Especially since we all know he wasn’t a mentally deficient person.
Some real delusional folks in here.
If you don’t learn how to use an llm for coding you’ll be replaced.
I’ve decided to start moving to NetBSD. The copyright status of genAI code is {very questionable](https://hachyderm.io/@BoydStephenSmithJr/116964500365807149), and it’s likely any project that integrates it, with be “extinguished” via legal action in the future.
Clickbait feeding the Big Lai.
In reality there was no “AI” involved because it doesn’t exist.
Dude used a LLM which is a statistical program with absolutely zero “intelligence”.
A lot of stuff was called ai and wasn’t intelligent. Stop using this argument, it weakens any discussion that wants to argue against ai/llm usage
You’re a statistical organic blob with absolutely zero intelligence.
Unfortunately for you, the English language has shifted to include LLMs under the “AI” umbrella.
The English language shifted to make “drugs and alcohol” a saying so as to disassociate alcohol with drugs.
This shift is incorrect and does damage, it’s called a false dichotomy.
Just because language shifts does not make it right, the dude you’re replying to is absolutely right and just letting AI companies define our world is cowardice.
I’m not in favor of big corpo AI in the slightest, and think that all the data centers should be nuked from orbit, but splitting hairs about LLMs being called or not being called AI is the most greasy neckbeard thing you could possibly do and takes energy away from actually resolving the issues. The language is flexible and it really does not matter whether we call them AI or force a distinction, so long as everyone understands what we are talking about.
Stop wasting everyone’s energy on pedantery and go out and actually solve the problem instead.
Changing language is a subtle way to manufacture consent that has been used as long as humans have been scamming. Just because you’re too stupid to figure that out, isn’t my problem.
You’re a fucking moron.
unpopular opinion, especially on the fediverse, but: AI is not inherently bad.
it is a tool, that can do everything to a pretty low standard but rather fast. so it is up to the learnt human to use the thing at the right time. i use the company ai at regularly at work, but treat it as an apprentice: every line of code has to be checked, because it will fail hilariously. but it does type faster than me, so simple and boring jobs can be done by it.
i don’t see the appeal of avoiding generated code at all cost. it is not different from human code in that it can fail horribly. the important thing is oversight. is there someone with the knowledge and keen eye to ensure no BS is merged. Linus, in my opinion, spent a lifetime building that reputation.
Oh, please… is it still a text generator, or is it already a religion?
I’m just a movement generator.
Saying “it’s a text generator” cannot be the full force of your criticism, if the text it generates is incredibly useful. What could AI be on a screen if not a text generator?
Your views have got to be formed by WHAT text is generated given that AI cannot express itself through any other channel than text.
If you can give AI a deeply complex code base and ask it to find the likely cause of an obscure bug, and the solution is right, then you’ll have to acknowledge that some form of reasoning is going on, no?
And given that no other system has previously enabled this form of reasoning, it seems a shame to judge AI on semantics, rather than usefulness.
I’m just a movement generator.
Which is way more complex than just predicting text, because you have to predict physics and all that stuff. There is a reason most robots controlled by neural nets have failed hilariously so far.
then you’ll have to acknowledge that some form of reasoning is going on, no?
By that logic you could say a compiler is reasoning. But the reasoning displayed was happening when the compiler (or LLM training material respectively) was written.
If you can’t see the difference between a compiler and a large language model, may I propose you read more about both and then return to this debate.
And if the entirety of your argument is a mystic “and all that stuff”, I am finding it hard to generate a convincing counter-argument.
You might be a few years behind. We have robots outpacing human performance in specific tasks using neural networks.
Also, LLMs can perform on tasks they weren’t explicitly trained for. This line is not as well defined as you make it sound.
Saying “it’s a text generator” cannot be the full force of your criticism,
That is no criticism, just a statement.
My criticism goes to people who assign some metaphysical meaning to AI, or want to treat all it’s output like a contagious pest.
If you can give AI a deeply complex code base and ask it to find the likely cause of an obscure bug, and the solution is right, then you’ll have to acknowledge that some form of reasoning is going on, no?
Absolutely not. LLMs are just prediction engines for words.
If a LLM has the right answer, it only means that the model had the correct training data for your issue. Nothing more.
That is absolutely not how it works at all
What do you mean? That’s exactly how LLMs work. That’s why they “hallucinate”.
No they hallucinate because they lose context but are tasked to answer anyways. They also don’t really lose context as much as they did a year ago.
Their training data has nothing to do with it unless you’re using a local one without web access.
No they hallucinate because they lose context but are tasked to answer anyways.
Nothing to do with context. Context windows are an LLM specific thing, but all neural networks no matter the kind or size “hallucinate” because they are a piece of linear algebra where you put numbers in on one side and get numbers out the other.
Their training data has nothing to do with it unless you’re using a local one without web access.
Did you know that the ones you access online are also trained?
Did you know that any chatbot that can connect to the web was given that capability?
ML is my career and I’ve been doing it for decades. You’re wrong. LLMs hallucinate with full context.
I miss when we thought the future was ML.
Uh huh, and how does it work?
You are on Lemmy so defending AI use will net you down votes. I am an anti-AI person, practically, but you make a very fair and objective point. 👍 I up vote you, not because I agree with AI use but because this is a proper point to make in a proper discussion, which is what this place should be about.
Kudos.
Yes AI is definitely a topic that seems to have a fairly united front. I’ve worked in software engineering for 25+ years and I can see the impact AI has on our discipline. So it’s not like I’m hailing it to be an all-positive force - I just think “all it does is generate text” is a weird, flat form of criticism.
It can’t reason. It doesn’t think. It makes shit up as it was trained to do. It can sort of detect patterns and make a guess about what response would get it the highest score, but it’s so error-prone that a human has to verify the output anyway. It’s difficult to tell whether the perceived benefits outweigh the costs. There are many different types of LLMs and use cases.
As a person who values life and our environment, I’d rather not participate in the sloppification of our world. As a Linux user, I am wary of vibe coded flaws slipping under the radar and screwing up my system.
I have to verify the output of what humans generate, too. I’m constantly looking at the source of claims. The AI is no different and it’s not nearly as wrong as a Person is.
Again, we are stuck in a semantics debate. What I call reasoning you don’t, it seems.
But all I know, as someone that has worked in software engineering for 25+ years, is that the output of whatever it does, and whatever you call it, is incredibly useful.
Saying “it just generates text” is a reflexive reaction that attempts to flatten the nuance.
All Columbus did was sail west.
All America did was throw some fuel into a tube and put Neil Armstrong on the top.
All Picasso did was to throw some paint onto a cloth.
All this PhD student did was generate text.
Surely we’ve got to have some more nuance in there. If there’s a difference between 10000 monkeys hacking on a typewriter and a human writing their doctoral thesis, the quality of their act isn’t in whether text was generated but WHAT text was generated.
Didn’t you love T9 back in the days?
The problem with majority of “LLM critics” is that they are brain dead luddites that argue with ragebait emotion rather than rationality.
Unsurprisingly LLMs are just computers that can be useful, can be wasteful, can be life saving and can be society destroyed - it’s a tool.
It’s a tool like any other. If used correctly it can provide a great value to the world. If used incorrectly then in this case it can also do the opposite. AI isn’t good or bad intrinsically. It boils down to our relationship to it. The same can be said for all the other tools, radio, television, internet and so on.
If the model is adequately FOSS, i.e. open weights, and can run on a single consumer GPU (or NPU), and the “author” (quotations because I’m personally undecided if one can claim code generated by an aforementioned model is theirs) understands it, then I really don’t see what the problem is…
Personally I have nothing against SLMs/LLMs as a technologically, to me my grievances against ChatGPT or Claude are mostly about their environmental impacts and selling us back our own art, also keeping knowledge behind a for-profit black-box - if those aren’t appropriate for a specific model, then I say using that model is fair, and good for productivity.
The problem with open weight models is that they are still hard to deploy. For DeepSeek for example you require NVIDIA HGX B200, these things are expensive.
If you are really using those things for work, a 32GB VRAM Blackwell currently costs around 3800-4000€. My own experience with local models on my 5070/12GB with 64GB DDR4 has shown me:
- I can run a Qwen 3.8 35b Q_8 quant (BF16 is a tad too large) using CPU offloading, while still reaching acceptable speeds for private use.
- Ternary Models are a game changer. Built to be used in edge computing, Bonsai-27B-Ternary from Prism ML runs completely on my GPU (using ca. 10GB of my 12GB VRAM incl. MMProj, 9 when disabling vision) and even leaves enough VRAM to run subagents (when killing my plasmashell lol -but i tend to offload these to the CPU in favor of increasing the context of the main model). currently you have to install a costum fork of llama.cpp to run ternary models, but the needed changes will be applied upstream soon. (There is a Bonsai quant which aims to run on iPhones with below 6GB VRAM footprint - the limit of what Ios currently allows)
If this scales linear, it would mean that the 32 GB of a smallish Blackwell would be enough to run Ternary models with around 70B parameters plus a ton of context window without breaking a sweat.
These are strange times. I absolutely love the technology and the advances, and i fucking hate the companies pusting these technologies.
Altman, Amodei, Musk, Nadella, Huang and all of the othe AI evangelists can go choke on a bag of dicks in my opinion. This technology never should have been this divisive, it should have just become another tool in humanities toolbox. I fear that these people have tainted the general populations outlook on this tech for a very long time.
I’d take a model whose training data is open source and legitimately obtained. The only ones I know about are Apertus and OLMo, and they aren’t really competitive.
Unfortunately not yet, no, true FOSS models are likely many years away, but I would argue that that follows typical FOSS lifecycles. Emerging technology is typically outperformed by proprietary endeavors, which creates an audience, and then that audience undertakes a FOSS implementation that initially underperforms, then just about competes, then eventually overtakes (i.e, GNU/Linux).
They should ask for a refund
Well it’s not that this shit CAN’T be useful, it’s that it’s being pushed at people heavily in ways that aren’t.
AI psychosis swings both ways. There is definitely the c-suit managers who got marketed to and now fully embrace the insanity. Everything AI.
Then there are the people who think their feelings are valid logical reasons to start religious wars over. Apparently the existence AI insulted their ego and their “creativiae!” (in Cartman’s voice) by being better at writing and drawing than they are.
I would have more sympathy with the latter because they must be in incredible intellectual pain from disillusionment that all their poems and illustrations were in fact not art after all. But then the puritan loudmouths keep yapping on about what others can and cannot do. At this point I’m tempted to side with the Nerd Reich.
Aehm. I might be slightly affected as well.
What AI haters don’t get is that the people fanning the flames of AI(LLM’s) hate are the same people who want you to buy their subscriptions, because they know the only place where the real damage will occur is in OpenSource communities.
AI use for Open Source projects is arguably the one use case that benefits everyone, plus it’s a sweet irony against corps and their locked-down proprietary software. Denouncer will loudly hawk that LLMs will make it trivial to circumvent the GPL, but they fail to mention that the pendulum swings both ways; with LLMs, it’s now easier than ever to reverse engineer proprietary systems and programs, recently there was a similar discourse on lemmy due to the mario kart wii decompilation.
They want loud people to sow division into OpenSource communities so that true opensource LLMs solutions are shunned and never reach maturity, corporate meanwhile is unaffected.
Please can someone fork the kernel, it would be so fucking funny
