Comment by nakamoto_damacy 5 hours ago
Wait. What if the AI gold rush contributes to better industrial robotics and ushers in an AI industrial revolution? China already has dark factories with no humans on the assembly line. Isn't that a possible outcome of the AI gold rush? (I mean omitting the fact that ChatGPT 5 Pro still says stuff like: "You’re right. I made a bad inference and defended it. That’s on me." We don't want that behavior on the assembly line.
I am not an expert in this, and don’t necessarily believe it. But the pitch is that existing manufacturing automation requires that specificity due to technical constraints. And that much of the factory automation that hasn’t happened is because it’s too costly to get to that level of specificity in that the existing automation requires higher scale to be cost effective. If you had more general purpose intelligence you could get around those constraints.
The video models are the ones that seem to be attracting the most attention in this area as it seems do similar to sight recognition.
> existing manufacturing automation requires that specificity due to technical constraints
Rather the opposite, I'd say: existing manufacturing automation is built around repetitive motions because an assembly line is making multiples of the same product. Having AI reinvent the wheel for every individual item is completely pointless.
One-off manufacturing can to a certain extent be automated. We're already seeing that with things like 3D printing and dirt-cheap basic PCB assembly. However, in most cases economies of scale prevent that from widespread generalization to entire products: ordering 100 or 1000 is always going to be have significantly lower per-unit costs than ordering 1, and if you're ordering 1000 you can probably afford a human spending some time on setting up robots or optimizing the design for existing setups.
There are undoubtedly some areas where the current AI boom can provide helpful tooling, but I don't expect it to lead to a manufacturing revolution.
Manufacturing robotics is all about movement. All movement exists on a spectrum of difficulty and context needed to perform. For instance, welding the steel plates together in an empty and repeatable consistent 3d space is now on the lower end of difficulty. Navigating through a partially manufactured vehicle cab to install a complicated dash assembly requires a lot of context and is incredibly difficult for a robot to do.
The more we can bring down all the difficulty of all these processes, the more we can accelerate manufacturing locally.
That's at odds with everything I know about manufacturing robotics, having worked with people doing that work. The complexity of the environment is irrelevant because the robot is programmed to make a specific motion and to adjust that motion in predictable ways based on the appearance of specific features. That is by design, not because (or at least not just because) the robot is incapable of planning its own motion. The whole system is designed to be predictable instead of adaptable because that's what you need to do to do the same thing millions of times.
> The whole system is designed to be predictable instead of adaptable because that's what you need to do to do the same thing millions of times.
That final "millions" is the problem. Automation is great and easy when you will do the same thing millions of times. Sure it might cost half a million to program the robot (which itself cost half a million) - but that is $1.00 per part, and it goes down as you make more. When you are only building 10 though a million dollars is a lot of money and so you want humans - or robots that are "CAPABLE of plannings its own motion".
Costs have been going down. In high school I took the class on how to write g-code (I have one free period so I took shop for non-college bound kids for fun even though I was college bound - it was a great time that I highly recommend even though it was only for fun). These days almost everyone just uses their CAD/CAM and isn't even aware that the g-code is supposed to be a human readable programming language. (it probably isn't)
> Navigating through a partially manufactured vehicle cab to install a complicated dash assembly requires a lot of context and is incredibly difficult for a robot to do.
Not really. The robots are programmed by having a human manually guide it, so the robot itself doesn't really have to do any navigation - it just has to follow a predefined path.
Want to install different variants of dash components? Split it up into methods and have the robot return to a neutral position after each method. You're literally programming it.
And yet China already has 100% automated vehicle production lines.
https://www.telegraph.co.uk/business/2025/10/12/why-western-...
I've heard that the general transformer architecture (not specifically LLMs, which imply a language model, but applied to sensory perceptions and outputting motor commands) has actually been fairly successful when applied to robotics. You want your overall assembly line to have a tiny, repeatable instruction set, but inside each of those individual instructions is oftentimes a complex motion that's very dependent upon chaotic physical realities. Think of being able to orient a part or deal with a stuck bolt, for example. AI Transformers potentially would allow us to replace several steps in the assembly that currently require human workers with robots, and that in turn makes the rest of the assembly much more reproducible (and cheaper).
Training these models takes a bunch more time, because you first need to build special hardware that allows a human to do these motions while having a computer record all the sensor inputs and outputs, and then you need to have the human do them a few thousand times, while LLMs just scrape all the content on the Internet. But it's potentially a lot more impactful, because it allows robots to impact the physical world and not just the printed word.
And it's a nice problem to solve with AI of many kinds because you can forward-solve the kinematic solution and check for "hallucinations": collisions, exceeding acceleration limits, etc. If your solution doesn't "pass", generate another one until it does. Then grade according to "efficiency" metrics and feed it back in.
As long as you do that, the penalty for a a slop-based fuckup is just a less efficient toolpath.
That's not how the LLMs should be used in manufacturing. It is still the current assembly lines robots that will do that. LLMs can be used by the humans who design the automation workflow, as coding assistants. That can lower the breakeven number of items that can be automated. Maybe if today it only makes sense to automate the manufacturing of a widget only if you can sell more than 100000 of those widgets, then with LLM assistance that number can be reduced to 1000. Whenever you have a 10x improvement of something, there's scope for a mini-revolution to happen.
Journalists keep conflating LLMs with AI. You don't use an entire DC with its own power plant to keep a line of robotic welders online and working.
FWIW journalists are just following the lead of tech executives and others hyping LLMs as "AI" so it's hard to fault the journalists specifically.
I beg to differ. Journalists are supposed to do their own investigation and analysis of the people, institutions, and events that they report on. If they just parrot the talking points of executives, then they’re producing advertisements, not journalism.
Fair, but there have never been very many journalists in the world. Between lazy fact checkers and there being more money in sensationalist reporting (My American history classes covered this back in the 1800s, and I have no doubt other history classes of earlier times will as well) there has never been much.
They've been trained by a decade of referring to advanced cruise control as "full self-driving".
Someone has to run the robots. And i bet it's not going to be the educated but spoiled workforce of the developed western world, but that will be outsourced to offshore destinations.
I think there's something cultural about wanting office jobs related to power over people, where you can always slack instead of waking up every day at 8 to go to the factory
This is great for ordinary Americans. It means you don't have to do the boring assembly jobs, but you still get the benefits for vast amounts of mass produced goods. (some of it is junk, but that is a different topic). Those goods should be cheap as well because they are mass produced with little labor costs. The only ones who lose are those who are want to do boring work instead of something creative. (or those who are incapable of doing something else)
There is the constant argument that what when machines do everything. We are not there yet, and so far there is no reason to think we will be anytime soon.
> The only ones who lose are those who are want to do boring work instead of something creative.
Aren’t the creative jobs also being taken by LLMs and image generators?
> This is great for ordinary Americans.
If that's true, why isn't unrestricted immigration[1] good for them? It means that the citizens don't have to do the boring immigrant jobs, but still get the benefits for vast amounts of immigrant-produced goods and services.
The only ones who will lose out are ones who 'want to'[2] do the boring immigrant jobs.
AI can't just handwave all this shit away because 'technology good'. Whether or you agree with these concerns or not, there's a massive backlash from various flavors of nativists about jobs. Why isn't it directed at all of these pie in the sky AI promises?
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[1] Or, you know, just buying imports from China. What difference does it make to me where a factory is located, when that factory doesn't employ me or my neighbours? The people collecting profits from it aren't going to share them with us.
[2] What does it mean to 'want to' do a 'boring' job? Rent's due in two weeks, 'wants' don't enter into it much.
China has been building robots and robotic manufacturing without AI. So why AI? Because the AI is a grift for those who can get exposure to its potential gains during the exuberance, while China builds actual capabilities. Profits and fiat are shared delusions, monetarily speaking, robots and factories are real, and will build real things.
Western executives who visit China are coming back terrified - https://news.ycombinator.com/item?id=45563018 - October 2025
Was Made in China 2025 Successful? [pdf] - https://www.uschamber.com/assets/documents/Was-Made-in-China... - May 5th, 2025
ASPI’s two-decade Critical Technology Tracker: The rewards of long-term research investment - https://www.aspi.org.au/report/aspis-two-decade-critical-tec... - August 28th, 2024
> Now covering 64 critical technologies and crucial fields spanning defence, space, energy, the environment, artificial intelligence (AI), biotechnology, robotics, cyber, computing, advanced materials and key quantum technology areas, the Tech Tracker’s dataset has been expanded and updated from five years of data (previously, 2018–2022) to 21 years of data (2003–2023). These new results reveal the stunning shift in research leadership over the past two decades towards large economies in the Indo-Pacific, led by China’s exceptional gains. The US led in 60 of 64 technologies in the five years from 2003 to 2007, but in the most recent five years (2019–2023) is leading in seven. China led in just three of 64 technologies in 2003–2007 but is now the lead country in 57 of 64 technologies in 2019–2023, increasing its lead from our rankings last year (2018–2022), where it was leading in 52 technologies.
What if it contributes to an evisceration of the middle class, instead? Hiring for new grads is already dead because of it, and it's not going to be coming back.
It's having the same sort of impact as unlimited immigration, except that in this case, the workers don't need weekends, or pay taxes.
I'm unclear on what people see in the current AI tech advancements that makes them think it will contribute to better manufacturing. The new feature of LLMs that makes them so interesting is their ability accept input and flexibly follow arbitrary instructions, meaning they're really good for varied work, especially when there are a wide range of acceptable answers ("creative work"). Everything I know about manufacturing at scale is that you want a person or machine that follows a tiny instruction set (at least in comparison to the potential flexibilities of an LLM) and nails the execution every time. This seems to me like the complete opposite of the strengths of an AI system like the ones that Wall Street are cheering.