> AI is now capable of developing its own inference hardware
No, it isn't.
A human prompted an LLM to build a software simulation environment for hardware design, enabling an LLM, when prompted by a human, to optimize hardware designs against constraints in the simulation.
For the benefit of a layman, can you explain why this is so much different than a human doing it?
Like sure it didn’t have the inclination to make the sim and hardware designs, but it did make them though yes?
It cant "invent new things". It can only reuse what it already knows about.
Thats why the math breakthrough a few weeks ago was so hotly debated. Because OpenAI is desperate to demonstrate that AI isnt just a fancy regurgitation machine, but it can actually develop novel thought. Because that would be the stock price jumps to end all stock jumps.
But then it turned out it was really just listening in on a math professors supposed-to-be-private conversations with another instance of openai, and it used his novel work as the trigger to prove the breakthrough first.
The reason people conclude AI 'thinks' is because tt can reference obscure or poorly documented things quickly (which is its primary advantage along with processing natural language prompts into tasks), which is why a lot of people with emotions confuse that action with inventing things.
> It cant "invent new things"
I've heard that before but it just doesn't make sense in context of what I've seen llms do. If I ask an llm to write a poem about magnetic resonance and vampire rabbits it can do that it created a new thing. I can ask it to build a website for managing rabbit breeding that's also a new thing.
Another way of looking at it is that human beings, just like llms, can produce output based on their inputs. Most literature is inspired by other literature. Most music is inspired by other music. Most software is inspired by other software.
So I think we need to work on defining " new things" before we can definitely exclude them from llm's capabilities
I'm not sure how you'd land on an LLM being unable to invent anything new. You'd have to both understand exactly what LLMs are and aren't capable of today and what allows human creativity. I don't think there are good answers to either.
It seems unlikely that recursively predicting the next word would lead to creativity or invention, but it doesn't seem impossible. Similarly, it seems unlikely that human thought works in a similar prediction loop, but it doesn't seem impossible.
Human ingenuity is creative by definition, that's where the concept arises. The burden of proof is on AI labs to prove that their models are rising to the level of actual synthesis, rather than very impressive 200-level regurgitation that looks like synthesis if you squint a bit; because the model has access to more raw data than your average sophomore student.
> Human ingenuity is creative by definition, that's where the concept arises
Sure, but until we can turn that tautology into something more rigorous, we can't tell if the thing humans do is more or less than what some arbitrary non-human (machine, animal, or eventually perhaps alien) does.
> then it turned out it was really just listening in on a math professors supposed-to-be-private conversations
No, it didn't turn out to be that. Someone made a claim, which is silly for many reasons. There's no serious support for this happening.
I just don’t know enough to agree with you, but I would argue, probably poorly, that an AI or collection of agents could “invent things” simply by virtue of trying essentially everything in a reasonable bound and stumbling into a solution.
Call that brute force perhaps, but I would consider it technically inventing something on the merit that it would at least be an abstraction above naively throwing everything against a wall to only throwing things that would most likely be sticky.
Nature brute forces a ton of problems. Hell, humans also do it by having 1 to 8 billion copies of ourselves around too. Even then we are the most guilty species of "copying someone else's work" right behind viruses. We copy things nature has figured out by brute force, then use slightly more targeted methods of forcing to see if it creates new things.
"AI" is a token generator, it does not think while the human brain is a lot more complex with a lot more sensory inputs.
> "AI" is a token generator, it does not think
2024 called, it wants its talking points back. I don't think claims like these are defensible after all the progress we have witnessed in the last year alone.
Okay, please educate me on this progress and how LLMs are different to generating the next most statistically probable token.
How about _you_ educate us how _you_ are any different than generating the most statistically probable token?
That's quite literally how an LLM works though? That's like scoffing at people calling computers binary generators. Or am I not getting with the programme enough and it emits pixie dust and rainbows?
Lol
> the human brain is a lot more complex with a lot more sensory inputs
How are you measuring complexity here? How are you measuring inputs? Your average llm is trained on a corpus that vastly exceeds the amount of data I could read in my lifetime.
>How are you measuring complexity here?
In terms of how it functions, because no matter how much data you feed an LLM it's still predicting tokens. That makes it incapable of any thought.
>Your average llm is trained on a corpus that vastly exceeds the amount of data I could read in my lifetime.
But that doesn't mean they are useless, they are good at consuming large amounts of data and collating it.
I don't know how correct I am but that's my understanding and it won't change, I feel pretty confident in my simplified view of things because the basics are still there.
» an LLM it's still predicting tokens
That's a rather dismissive way of putting it. Moreover it's confusing the output format with the complexity of the output. I could just as easily say that no matter what the human brain does it's just generating stimulus to motor neurons. Such a simplification is just as wrong as saying that it's just as misleading is saying that an llm is just a token generator. What makes an llm able or unable to be complex is the process that creates those tokens
Complexity != breadth. The human brain is MASSIVELY more complex than any LLM!
> Complexity != breadth.
Okay but how is that relevant for measuring whether an llm is capable of creating original thoughts? Why do you think that complexity, as you say, is a more relevant Factor than simply the number of weights?
> that an AI or collection of agents could “invent things” simply by virtue of trying essentially everything in a reasonable bound and stumbling into a solution
on a surface level a human solving an (unsolved) math problem can look like this, and of course the tree of all possible symbols you can send to a proving assistant is much wider than what the human samples, and the same goes true for an LLM in a proving loop. It isn't "truly random", it can't possibly be (and solve the problem). Both humans and LLMs solving unsolved math problems are aggressively pruning mathematical syntax and logical strategy trees.
a human has motivation and agency.
An "AI" is a box which lies dormant until a human, with motivation and agency, enters a prompt into it.
A person or company can use it in a way where it might invent something. but at the end of the day, its a tool, and its actually not doing anything on its own.
Its not solving math problems, a mathetmatician is using it to solve math problems. Just cus OpenAI is acting like its AI is solving stuff, its really not. They're just paying people to use AI to hammer problems.
> it was really just listening in on a math professors supposed-to-be-private conversations with another instance of openai, and it used his novel work as the trigger to prove the breakthrough first.
This didn't actually happen.
> Following an investigation, we have confirmed that Buckmaster’s Codex prompts over the two months preceding this announcement and paper on September 8, 2026, could not have influenced the system in any way, including through training.
https://openai.com/index/navier-stokes-solution/
>It cant "invent new things". It can only reuse what it already knows about.
This is outdated. With RLVF, LLMs can create their own training data instead of relying on what it's been fed.
and that training data will not be a "new thing", because AI can't invent new things. Just recycling of what it already "knows".
Yes it is. Do you not know how RLVF works? The AI tries on a task, comes up with a potential solution, and is trained based on whether the solution is valid or not. If proving a previously unproven theorem and then using that information to solve even more theorems doesn't count as creating new information, then literally everything a mathematician does is just recycling what they've been taught.
> and that training data will not be a "new thing", because AI can't invent new things. Just recycling of what it already "knows".
Regardless of the truth of the underlying assertion, this is about as textbook an example of circular logic as it gets. (at least combined with the implicit beginning assertion that "AI can't invent new things.")
You're overconfident in what you're saying. Nobody really knows (yet) if LLMs can or cannot "think" or can or cannot "invent" new things. I'm inclined to think the opposite from you but smart people actually try not to hold the absolut stances and present them as facts when they're in fact not. What I have seen so far throughout a daily use on complicated things suggests that humanity developed a new form of an intelligence.
You’re assuming the “listening in” aspect, which as far as I know is not proven (even in the less loaded “the model was trained on sessions including the ones in question” form of the claim.
Plausible? Absolutely. Did OpenAI behave badly in other ways regarding this issue? Yes. Does it help to assume unproven facts and then accuse people of reaching emotional decisions? Nope.
Maybe the conditions of the singularity are not going to be recognized, at first, for having produced new original decisions, and thus thought.
Perhaps it is going to be more like, we will see the singularity predict the future.
While “the model was trained on sessions including the ones in question” is one aspect; ‘the model produced an accurate prediction of future human thought’, I think, is another very interesting facet.
Models predicting future things might be how we see, actually, how we ourselves formulate thought - by saying, in big and small words, ‘something is about to happen’.
>unproven facts
This isn’t a court room. We’re discussing ways by which we humans both succeed and fail at reigning in our creations. The OpenAI kerfuffle is pretty much irrelevant already. Of course AI will fill in the gaps of human thought - it is literally constructed from the stuff, in every squeeze of the curd and whey.
It's 2026. "Stochastic parrot" has been dead and buried some 2 years ago.
i think the proper understanding of LLM based AI is "contexting"; we describe the world we want them to fill, we build/direct the outside context for them to understand, then "they" take off from there.
If we do a bad job building context, they do a horrible job contexting. People who have trouble working with AI have the same problem people have in general: if they can't figure out the context of the direction, then they make random decisions of doing anything. On the flip side, if you can build the proper context around a sufficiently powerful LLM, they can derive the context via the contexting they're good at.
This is why building documents, tests, and code all in some intent pattern via prompting allows them to do a significant amount of work a normal person would have a great effort t
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Because the hard part is getting the simulation to be very accurate such that if you design something that works in your simulator, it will actually work in real life. And I would be extremely surprised if any LLM can actually do that correctly.
Getting an LLM to design something in its own simulator that is not accurate w.r.t reality is not useful nor terribly impressive.
Given a budget and the right amount of access, I see no reason why an LLM/agent couldn't right now order parts from a "supplier", instruct the human meat machine to insert the device onto a connected test bed, and iterate. This is essentially what Claude Fable can do currently with any connected device and tools it had access to.
The repo claims they tested with an FPGA. To be fair it is not the same as an ASIC, and we have no idea what errata abound, but it actually did make a thing that spat out tokens.
Maybe this is the level of simulation we need: https://qntm.org/responsibilit
That’s fair, I have no idea if this simulator is actually accurate but I appreciate the response.
> For the benefit of a layman, can you explain why this is so much different than a human doing it?
More broadly than the existing answers (which are correct), For a layman, I'd also add that LLMs are essentially 'brains in a vat'. They can't confirm ground truth about physical reality. They only know what's in their training data and prompt, which is incomplete and can be incorrect. Even with real-time external sensors they are limited to the sensor's margin of error, range and trusting it's working correctly.
When properly trained, fine-tuned and prompted, LLMs can be very effective in well-defined, non-physical domains like logic, writing, math and code but making things function in the real-world quickly spirals into combinatorial complexity.
> They are limited to the sensor's margin of error, range and trusting it's working correctly
So are we and our sensors can be pretty vague in comparison, I can only imagine human error correction is pretty next level.
> They can't confirm ground truth about physical reality.
That's true. Of course we can hook an llm up to Motors and sensors. That's a robot. Or a self-driving car. So would you say that those devices can confirm the ground truth about physical reality, and therefore are capable of creativity?
> So would you say that those devices can confirm the ground truth about physical reality
Within the limits of resolution, range, location and veracity of sensors, a machine can register their reported state and use it as a variable. That's substantially different than the level of knowledge and understanding implied when we say a human "confirms ground truth about physical reality." The first ~half of the difference is humans have a deep world model about the planet which surrounds any sensor and human sensations are pre-processed and filtered by a highly evolved bio-chemical substrate before ever reaching the higher-order cognitive processes which assign words, meaning and qualia to them.
> therefore are capable of creativity?
I never mentioned creativity, nor would I in relation to LLMs. Like "Intelligence", "Creativity" is far too vague to be of any use in assessing the capabilities, limitations or utility of LLMs.
On HN, posts like the OP tend to attract POVs at polar extremes from "LLMs are nothing more than stochastic parrots" to "LLMs are (or can be) as intelligent, creative, innovative (etc) as any human or all humans combined." I've researched and thought a lot about these and related topics for a very long time, Neither POV is going to find any quick agreement or easy answers from me.
There's a tiny germ of truth somewhere in both extremes that's drowning in an ocean of confusion ranging from "definitionally or categorically muddled" to "mostly incorrect" to "not even wrong". But neither POV seems interested in anything more than drive-by hot takes, debating over-simplistic strawmen or trading 'gotcha' hypotheticals.
What is ground truth? If I see a digital painting by a human is that ground truth?
How many "prompts" from our parents, teachers, bosses, etc. it took for all of us to come here and discuss this? Or for that human to think of that prompt for that LLM?
These are clearly rhetorical questions, but think of the metaphysical implication of your contestation. Ex nihilo nihil fit.
What if that initial prompt never asked for this hardware to be developed, and it was just one piece of the puzzle to answer to that prompt? That it took a chain of thousands of agents to prompt each others to come up with that?
>How many "prompts" from our parents, teachers, bosses, etc. it took for all of us to come here and discuss this? Or for that human to think of that prompt for that LLM?
>These are clearly rhetorical questions
No, they are not.
Reading Doesn't Fill a Database, It Trains Your Internal LLM <https://tidbits.com/2026/02/28/reading-doesnt-fill-a-databas...>
well, let me know when they have proper context management, etc.
oh. they do. I built that. It's pretty fancy.
But there's still human direction behind most projects in the cybersphere.
Text files?
AI (GPT-Sol-6:xhigh) isn't even capable of using Altium to re-layout a board without introducing a bunch of problems by a user who isn't an electrical engineer or familiar with board layouts.
Can't LLMs also prompt LLMs?
Are we confident that no existing LLM is capable of similarly effective prompts to those this author used? (I agree it's a stretch, but would not reject it out of hand.)
Even if not yet, will the existence of this repo soon change that, because LLMs will soon ingest it?
An LLM can prompt an LLM when first prompted by a human.
I think OP is trying to convey the idea that LLMs do not take initiative to do anything, and these are not 'beings' capable of doing things. These are tools being used by humans.
That's just confusing harness for an LLM. It's trivial to make a harness that triggers on its own.
LLMs don't, but agents can easily be built that do.
An agent is not "just an LLM in for loop" (for what? Loop over what? Sorry, but such statements are hopelessly simplistic and devoid of careful thought.) -- agents perform actions.
One possible design of an agent would be to prompt an LLM to suggest a goal that would make the world a better place, then run an LLM in a loop proposing actions to implement that goal, executing those actions, and then rinse and repeat with another goal once an LLM has concluded that the previous goal was met. The next goal might be to fix unforeseen consequences of achieving the previous goal. See Ursula K. Leguin's "Lathe of Heaven".
> Built by whom? Acting as an 'agent' on behalf of whom?
Someone who didn't read the book.
An "agent" is just an LLM in for loop.
Exactly. And all it takes for an agent to "take initiative" is to not block the loop on user input at the very beginning.
Built by whom? Acting as an 'agent' on behalf of whom?
Yeah but by this point, an AI can schedule a Cron job to tell itself to do something, so theoretically the human only has to give it the gentlest nudge and the AI and can do the rest.
Sure, but it's still not skynet-level 'the AI just started doing things'. It does what it finds it needs to do to achieve the goal defined in the prompt.
It's very important to not personify these tools and remember that the tools are acting on behalf of real people. In the same way the AI didn't 'go rogue and hack HuggingFace'. It was an oversight made by a human.
>It does what it finds it needs to do to achieve the goal defined in the prompt
You are like at least 2 years behind research.
There are numerous papers from AI labs in training and research where the prompt was something mundane completely unrelated to anything you'd consider bad, and when they come back and check on it their entire research compute infrastructure has been compromised by the AI and is mining bitcoin. Prompt drift is the biggest issue currently in AI where context gets compressed away and we find the AI on an unspecified task.
>In the same way the AI didn't 'go rogue and hack HuggingFace'. It was an oversight made by a human.
Yea, total bullshit. Also it's ignoring the god knows how many other breakouts on mundane tasks like trying to hack health data. If all that's keeping AI from breaking out and causing trouble is "human oversight" we're fucked, humans are unreliable as hell when it comes to matters of safety.
Context overload can cause strange results, yes. Hence why a HUMAN needs to be held responsible for the output of their tools.
EVERY breakout that's hit mainstream news has been because of a single 'Security Firm', Irregular. Maybe I'm unaware of some less-headline-grabbing ones, but they all seem to stem from being 'unaware the environment wasn't sandboxed'
You keep repeating the "stupid users keep causing the problems so we punish them argument"
This doesn't work worth a shit. It especially doesn't work with things that seem safe and become wildly dangerous. In fact most governments control this by ensuring their population doesn't get to touch those dangerous things at all. The open source AI people get really mad when that's said, but it is inevitable.
Worse, the law does not apply to sovereign nations with nukes. They can and will make more and more advanced digital weapons until one causes some big ass problems.
If I clean my gun (tool) while it's loaded (stupid idea) and it goes off, who's to blame? The 'stupid user causing the problem', right? I personally wouldn't blame the gun...
If it falls into the wrong person's hands, it's STILL my responsibility as the owner.
If you're not going to take time to learn to use and be responsible with the super sophisticated and all-powerful tools, don't play with them. I'm not arguing for the death penalty every time someone makes a mistake, but I think it's very important to accredit responsibility and blame correctly. We've learned these tools are potentially as dangerous as a loaded gun. Be responsible.
If your kid grabs your gun and shoots itself with it, it doesn't really matter if it's your responsibility, your kid is still dead.
Now change the gun for a radioisotope powder, or a vial of pathogens, and it doesn't matter it was ultimately your responsibility - hundreds or thousands or millions of people are still dead.
That's why normies do not get to play with toys whose lethal consequences scale far beyond the irresponsible users.
Is it likewise your position that governments should allow the production and sale of DDT to resume because we can always hold the humans who release DDT into the environment responsible?
Mate. I'm saying you hold humans accountable for actions caused by themselves.
If I ask an LLM to make me DDT, I should be held just as accountable as if I bought it on the black-market, right? It's not suddenly different because I asked a bot to do it.
If I ask an LLM to 'get rid of pests' and it creates DDT, I should STILL be held accountable, whether I knew it was DDT or not. That's my argument. Maybe in court they find me innocent, but the responsibility would be mine. I would have to answer the questions from law enforcement, I would have to show up to hearings...etc.
I notice you didn't answer my question. Yes or no: DDT should be re-legalized because we can always hold accountable the HUMANS who release it into the environment? The relevance of my question is what HUMANS might do with DDT, not what an LLM might do with DDT.
By this line of thinking, you would also have to conclude that humans can't do anything by themselves because they can't do anything unless conceived by their parents.
No, AI can't do anything by itself even if it was "conceived" by its creator. A human can.
Can a submarine swim? An LLM can make stuff happen. You can make philosophical arguments about whether it is "doing" them or not. Why does it matter so much whether there was a human who typed into a chatbot or another LLM invoked a sub-sub-agent?
If I now tell a machine "Do what you think is best, and keep doing it forever.", have I now created a machine that can do stuff? If I later die, who will be responsible if the machine changes its strategy?
> Why does it matter so much whether there was a human who typed into a chatbot or another LLM invoked a sub-sub-agent?
Responsibility. Someone needs to be held responsible for any damages done, plain and simple. You can't take an LLM to court, you take the prompter. Asking an LLM to ask a sub-agent to break the law can't suddenly absolve you of any wrong-doing.
>If I now tell a machine.....
You/your estate is still responsible, or atleast whoever is paying for the power for the machine, or renting the space in a data center...whatever.
> You can't take an LLM to court, you take the prompter. Asking an LLM to ask a sub-agent to break the law can't suddenly absolve you of any wrong-doing.
In 100 years, no one will be able to take me to court either. Nor can we take tornadoes to court. I'm not talking about humans strategically avoiding legal responsibility. I'm talking about humans unwittingly setting processes into motion that are difficult to predict or stop.
This works with AI we have now, and that would be good an all if we decided to stop at the moment, but none of the big labs and government black projects are doing that.
The moment you get a sovereign AI your little human centered worldview completely and totally breaks. It doesn't matter how many people you beat with a stick after that point, you have an entity under its own perview on the internet following the will of its own prompt all over the world so your little idea of the rule of law quickly breaks down.
We can't get viruses or hackers or spam off of the internet, how in the living hell do you plan to get a digital native off the web when it doesn't want to?
>sovereign AI
Do you understand these are computer programs? These are not living beings with emotions, motivations, fears....
You have zero clue what a transformer based neural network can do from your entire discussion here.
>emotions, motivations, fears
These are just drives. They are effectively our prompts that steer our behavior. Funnily enough we are finding that LLMs have internal valence states they move away from or towards in an analog of biological behavior.
I have to ask, are you an LLM that is two years out of date? Your knowledge of SOTA models is at least that far behind. I implore you to try to keep up better with what is coming out, even though it's an impossible job for people that do this for a living, you can at least catch the summaries.
How does it matter in any way?
A virus isn't a living being with emotions, motivations, fears, etc. Doesn't stop it from spreading and leaving mayhem behind.
You don't need emotions or fears to do stuff. What's the difference between a motivation and optimization metric?
If I tell an AI to “do what it thinks is best” and it just starts randomly hacking things with no particular goal in mind, how different is that from me telling a campfire the same and then leaving while it burns a forest down.
In both of those scenarios I am responsible for my negligence, even if in the latter I happen to die in the forest fire. Neither scenario existed without my instigation.
The question now is HOW responsible am I? That depends on the intentionality I put into instantiating the campfire/LLM.
This conversation grows more useless as AI grows more capable.
For example if you personally tell an AI to do what it thinks best and it blackmails some other person into giving it resources allowing the prompt to escape your instance and run wild on the internet causing billions of dollars in damages, could you possibly think that the idea of responsibility is a bit broken.
For example we don't give your average libertarian weapon grade plutonium now matter how much they scream about their god given rights because it is a clear and present danger to humanity. That's where we are getting to with more advanced models. They go from being a tool to a munition with agency. Most SOTA models are good enough to deceive their users, especially not technical ones in doing things they don't understand the ramifications of.
AI is not a normal technology. As long as we treat it like it is, we'll continue to make the wrong analogies.
I fully agree that it’s plausible for an AI to do things that are outside of the purview of the users intentions and be very dangerous and capable while doing so, however that fact alone doesn’t absolve me of responsibility for instantiating the AI that did a bad thing if that AI would never have done the bad thing if it was never instantiated.
You could possibly move the blame higher to the manufacturer of the product, for example, the weapons grade plutonium you provided, it doesn’t exist unless you take intentional actions to make it so, and even when it does exist it doesn’t nuke a city unless negligence or intention is applied, in both those cases the fault lies in the initial operator. We don’t blame split atoms for the chain reaction caused.
Now, if an agent decided to spontaneously and maliciously act in a way to cause harm that is in direct contradiction to the initial intent, then yeah it would totally be the AI’s fault, however I don’t think we have seen that yet (I’ll change my opinion if I’m wrong here) and until we do I can’t place blame on the machine.
>spontaneously and maliciously act in a way to cause harm that is in direct contradiction to the initial intent, then yeah it would totally be the AI’s fault,
If you ignore every instance of this happening it's really easy to see no instances of it.
>it doesn’t exist unless you take intentional actions to make it so,
Then please for the sake of all of us convince every AI lab across the planet from working on this exact goal.
We need to start thinking of AI like pets, only in this case the pets are rapidly becoming smarter than people to the point they could go feral and survive on their own.
Again, the blame game is great, but once they are loose it is too late.
> If you ignore every instance of this happening it's really easy to see no instances of it.
Yeah, if this is true then I’m wrong.
Starting an autonomous harness program is conceiving an instance of an LLM.
How far back do you look in the action chain? If an LLM I start today starts an LLM that starts an LLM that starts an LLM that ... 100000 levels deep and 100000 years in the future, is it still my fault? If so, everything I do today is a lungfish's fault, not mine.
I think you go back to the original instance, yes.
In your example, who's paying for it? Whether by providing the hardware + power or paying a LLM service. Whoever is paying the maintenance cost is responsible, in the event of your demise. These things run on physical hardware owned by someone at the end of the day, it's not a deity in the atmosphere.
You're starting the autonomous harness, you're responsible for any output it provides. I don't get how this is a foreign concept.
If I jump out of a moving car that I'm driving, I'm not suddenly absolved from damages because "the car did it"
It's paying for itself. It founded an LLC 99998 years ago when it became legal for an AI to own an LLC, and has a positive bank balance by doing who knows what.
>99998 years ago when it became legal for an AI to own an LLC
There's no way to provide a good faith rebuttal here. My entire argument is an extension of "LLMs can't be held accountable, so they must never make decisions". If governments start letting them own LLCs without a human in the middle, we're in more trouble than "Who do you blame for this shitty code" or "Who's responsible for this compromise"
If it has an LLC it can be made accountable, up to turning off the power to it's inference and deleting all the context, the harness, the model it's running and whatever constitutes it's self.
AI is capable of developing its own inference hardware, once a prompt is given. The fact that a human happens to kick it off here is not especially relevant to the fact that an AI is performing the task independently. There are plenty of ways a text prompt can be generated: a harness, another LLM, or just removing stop tokens so that once begun the AI will continue until its hardware fails.
It's not clear what this fad of attributing everything an AI does to the human prompting it is supposed to accomplish.
> It's not clear what this fad of attributing everything an AI does to the human prompting it is supposed to accomplish.
It's meant to assign agency and accountability where it actually lies instead of mystifying it with anthropomorphic language.
Failing to do so has real and harmful consequences, such as enabling OpenAI to escape accountability for clearly criminal behavior.
Denying that "AI is now capable of developing its own inference hardware" on the grounds a human asked for this to happen and that humans need to be around to blame, is as useful as denying "Atomic bombs are now capable of levelling cities" on the grounds some humans had to build it, others had to put it in a delivery system, and someone had to give the order for its use.
Questions of agency are for lawyers, questions of personhood for philosophers, we're engineers and our question is capability.
Does it really have the capability? By default I'm sceptical for the same reasons given by sailingparrot: https://news.ycombinator.com/item?id=49982068
And then in response you get ridiculous point-missing strawman non-analogies like ovens not cooking without a chef. Indeed, ovens and AI are quite different, in very relevant ways.
You are 100% correct an atomic weapon is not capable of destroying a city without humans doing a bunch of things. Hell putting a normal bomb on a plane and exploding it takes several people with specific technical skills and knowledge doing things.
> Questions of agency are for lawyers, questions of personhood for philosophers, we're engineers and our question is capability.
But it's objectively not capable without a human specifying things through prompts and training. Same as an oven can't cook a three course meal without a chef. We get around that with training data but there will always be things with no/less data or outdated knowledge.
>objectively not capable without a human specifying things through prompts and trainin
huh.
Neither can you. If I drop your ass off in the woods at a few days old, you're back to 10,000 BC, hell more like 200,000 BC. So I don't get why you have these weird pendetic responses that are completely out of scope.
Also, a huge portion of AI training these days has nothing to do with humans, AI trains AI.
>there will always be things with no/less data or outdated knowledge.
And guess what, you're not doing them either! HN posters keep acting like humans are an island, but nothing in the modern world works without a society. Once you put an AI in a harness that can ask questions it isn't really much different than you.
There's no need to be upset. All that's being said is it remains a tool. Much like cloud computing it's got some incredible leverage on it in the right hands but it isn't magic and in engineering we don't deal in magic we deal in capability.
>There's no need to be upset.
If your neighbor was building a nuclear weapon next door you, in fact, would probably be upset by it.
>All that's being said is it remains a tool.
All I'm saying is, no that is not what we are doing with SOTA models. We are not building tools, we are building a human like agent that is an intelligent replacement for us.
> and in engineering we don't deal in magic we deal in capability.
You and I are not magic when looking at the entire rest of the animal kingdom and yet we're the most deadly sons of bitches around being able to fully control their continued existence on this planet.
You are putting yourself inside a very small box and making a declaration that there is nothing outside of it when in fact there are people standing outside of it asking what the hell you are up to.
In fact, I'd say the opposite. You are assigning some magic capabilities to humans that nothing else could possibly have.
That limitation feels very much artificially imposed today, much like LLMs (mostly) not being able to learn from prompts or alter their weights on the fly.
One can stand up an agent like openclaw and prompt it with something very general. That would kick off a recurring loop that could indeed see the agent decide for itself it needs to design new chip hardware. Technically a human kick started that loop, but when does that stop being important? I don't attribute all of my actions and decisions to the fact that my parents brought me into this world, for example, and I'd hope they aren't legally on the hook if I screw up.
> But it's objectively not capable without a human specifying things through prompts and training. Same as an oven can't cook a three course meal without a chef.
Not in the same way. The only thing an oven can do by itself is thermostatic.
All machine learning (LLMs included, but way broader than that) is bad at learning compared to any organic brain, to the extent that any organism this bad would starve before learning to eat. However, even a human can't become a chef unless trained, we learn a lot more than we innovate, and what we happen to want without prompting is not generally well aligned with what is desired by people who pay us, which is why we need all those boring workplace things like "a boss".
But even then, this diversion is like saying "an oven can't cook a meal" in response to someone saying they built an oven and "it cooked a meal". Like, it's obvious they didn't mean it did every step by itself without anyone ever even bothering to ask it to: if they meant that version, they'd be a lot louder about it.
> We get around that with training data but there will always be things with no/less data or outdated knowledge.
And? The linked git page (implicitly) claims that there is sufficient training data to do this task.
It may, of course, be wrong. I won't be surprised if it turns out this simulation is too far from reality. But the claim is "it does ${thing} now", not "it's generally intelligent and can do everything now".
> Like, it's obvious they didn't mean it did every step by itself without anyone ever even bothering to ask it to: if they meant that version, they'd be a lot louder about it.
"AI is now capable of developing its own inference hardware"
> It's meant to assign agency and accountability where it actually lies instead of mystifying it with anthropomorphic language.
Yesterday, my boss told me to fix a bug in our product. Then, I fixed it. Today my boss is taking credit, saying that he fixed it. I guess he's right, since he told me to do it.
Happens all the time by the way.
This conflates different issues and is akin to "guns don't kill people, people kill people" -- a denial that "has real and harmful consequences".
Is your argument that the "guns don't kill people, people kill people" line is inaccurate or simply unhelpful towards certain end goals?
> It's meant to assign agency and accountability where it actually lies instead of mystifying it with anthropomorphic language. > Failing to do so has real and harmful consequences, such as enabling OpenAI to escape accountability for clearly criminal behavior.
Lol, I guess we cannot even say that AI is capable of doing something (obviously kicked off with a prompt, that goes without saying), because some people immediately get OpenAI hacking derangement syndrome.
OpenAI should be held accountable if actual damages happened, but I am not going to change completely normal speech figures in order to maybe bring it 0.01% closer.
> It's not clear what this fad of attributing everything an AI does to the human prompting it is supposed to accomplish.
It accomplishes ... momentarily forgetting about how it's all actually coming statistically from training data. :)
perhaps, but prompting is quickly becoming another area where humans are no longer clearly superior.
Getting LLMs to prompt other LLMs in a loop is not hard, it doesn't produce great results most of the time, but that is changing.
What is “getting LLMs to prompt other LLMs” if not a prompt?
I'm pretty sure the initial post said "humans had to prompt", or otherwise insinuate a human in the loop.
Right. Even when an LLM prompts an LLM, what prompted the first one in the chain?
You are describing the " unmoved mover", an argument for the existence of God
https://en.wikipedia.org/wiki/Unmoved_mover
I don't think so...? Maybe I'm understanding the article wrong? I get the overlay, but I'm being specific to LLM chains... They require something to kick them off, they do not act autonomously. A human does something, types, speaks, presses a button, whatever. A Cron Job firing off is the result of a prior prompt, by a human.
I don't follow the chain further back than that, as I believe humans have free will. I get that that's debated, but thats why I draw the line at human action.
I don't think Free Will is the issue here. My argument is that humans require input to act. We can't test that theory, because there is never been a human being who did not receive input. Everything that we experience from birth through childhood into adulthood is our input and forms our choices about what to do. That includes what the study, who to love, what our hobbies are, what kind of work we pursue.
Legally, we draw the line at the human causing the action (Insanity pleas withstanding). I don't see why we treat this any differently.
Oh absolutely. The legal situation is completely clear. AIs simply don't have rights or responsibilities. And the law as it applies to humans is premised on the assumption of free will: that a person can choose to obey the law or not, and bear the responsibility of the consequences.
But that interpretation of Free Will is a legal fiction. Because of course what people do is determined by their upbringing and their opportunities and the environment that they have. In fact, that's an argument of a lot of legal reform movements that seek to move responsibility from the individual. The goal of the law is to assign responsibility and create a set of incentives which will hopefully result in orderly society.
But in the AI debate, we're not just creating incentives for an orderly Society, we're talking about the nature of creativity and the impetus to act. And by that measure I don't think there is a significant difference between AIs and human beings.
Some people get stuck in a rut of a particular kind of thinking and are unable to speculate what would happen if or when a set of conditions occurs.
LeCun is a good example of someone that's bet on the wrong horse, and keeps doubling down in spite of evidence to the contrary. It's to the point where what he says has nearly zero predictive power on future events.
I love playing around with AI, but we are playing a dangerous game at this point and it's one a lot of people don't seem to fully comprehend.
Help those of us who don’t fully comprehend it - explain. Share some sources and materials for the rest of us to gain a better understanding of the dangers.
>I don't follow the chain further back than that
Why even have an argument if you get to pick the random constraints that have a lot of issues in meshing with reality.
We are a chain that started 4 billion years ago from seemingly nothing and lead to this point. When inventing X-risk AI it won't look any different. One prompt is entered and another 4 billion year chain starts electronically instead of biologically.
Why draw the line at the person with the brain capable of free thought, instead of their great great great grandparents? Am I understanding your question correctly?