Hand-held devices for testing concrete properties would be more useful. Most concrete problems come from a bad mix - too much water, not enough cement, etc. Concrete testing usually involves cutting a core out of the poured slab and sending it to a lab. Something where you stick a probe in the mix and can reject it before pouring would help. Here are some on-site concrete testers.[1] They're heavy and a pain to use.
There should be an app for this. But that's so last-decade.
It’s customary to prefix these comments with credentials, so I’ll just say that I’m a roadway engineer. Sampling at the batch plant or even at the truck is not going to give you the whole story. While the most common crime of contractors is to overwater the concrete slurry to make it flowable, other problems in workmanship can arise from failing to vibrate the concrete in its forms, leaving voids, or vibrating it too much, creating segregation of the aggregate. If the finisher overworks the concrete or tries to correct the shape when it’s green, the that can compromise strength. If the concrete is finished too early, you can get delamination. If time allows and your contractor is careful they might protect the freshly poured concrete and let it cure wet. That makes a huge difference in cracking. There is also a whole world of chemical additives that structural engineers don’t even think about in the design process.
I’m not trying to say that mix doesn’t matter, or that I’m not pleased to see that Facebook is doing something a little more noble than surveillance technology, but as with a lot of construction issues, it’s just not that simple.
“it’s just not that simple” - my career in industrial data science in a nutshell. Lots of large companies come into the domains I’ve worked in with grand promises, and while sometimes they move the needle in terms of what executive leadership within the industry believes is possible, they also often poison the well for us smaller firms who provide much more leveled and concrete (heh) offerings. Curse IBM, for example.
AI is just the same. CEOs all over the world have fallen to the lure of the AI grifters, believing they can fire people en masse now and ride it out with the remaining staff until AI catches up with the remaining 20% of capability.
Small focused AI/ML companies however that don't deal in LLMs? They struggle to find customers, even with stuff that clearly works, because they hit the wrong buzzwords.
I wanted to mention that Concrete is far more complex and regional than folks might imagine. The quality of gravel and sand, local impurities - these all contribute massively. It's probably best to think of it like a wine's terroir - except, unlike a bottle of wine, it's prohibitively expensive to ship both the components and the finalized mixture to different areas. If a region's limestone has a massive clay impurity then it may simply be unsuitable for large structures or require extensive filtering to the point of being uneconomical.
It's important to be aware of just how much the local geological mix can impact the viability of building with concrete because while theoretically we could use perfect concrete for every project - at that point most projects would simply be too expensive to consider undertaking. There is a very large field of engineering around establishing the realism required in settling for what you've got for the price you can afford in. It can absolutely mean that the materials required to build a high rise in Philly might be priced starkly differently from the same structure planned in Milan even with adjustments for the labor impact on pricing.
And it's not just the gravel/sand that's important. The water itself also differs in its chemical composition (e.g. salts, minerals, basic/acidic pH), which can catch you really dirty when making concrete. Or when dealing with water at all, shout-out to Flint and its infamous water crisis that took eleven years to resolve - every single lead service pipe had to be physically dug up and replaced.
> it's prohibitively expensive to ship both the components and the finalized mixture to different areas.
We could do this if it is important. There are mines in Wisconsin the export sand to the middle east because that is known to work well for fracking and they don't want to risk a local sand not working well. (AFAIK they have never tested local sand properties, but it is possible they have and it doesn't work). In this case the value of the "perfect" is well worth the high shipping costs.
We certainly could - it's absolutely possible. The question is if it's economical and so far the market has ruled in most cases that it isn't. Either the project doesn't need such a perfect amalgamation of materials (maybe there is an expected deprecation that doesn't justify such an outlay - possibly earthquake risk would minimize any expected lifespan gain - possibly the materials contractor just can't internally justify the added material cost while remaining attractive to local contractors).
It's all a balance. Imagine a scenario where you can ship in specialized materials to build a bridge with an expected lifespan of 100 years and it'll cost 50M - or you could use local concrete that has an expected lifespan of 15 years and materials would cost 5M. This is a vast simplification of the math but, assuming those expected costs it'd be cheaper to build using local materials and just schedule replacement every 15 years. And, of course, there'll be egg on your face if you build the 50M bridge and then suffer a massive tsunami in two years that destroys the foundations anyways.
To paraphrase a Grady quote: "Engineering isn't a study of building the best thing - it's optimizing the quality we can get for the cost outlay."
for fracking, what they want is a perfectly uniform sized quartz grain thats rounded. You find this sand where multiple processes occur, notably glacial geology. You want uniform grains because frackings goal is to open, then support an porous structure when you can then pull the fluids/gas out without clogging.
It's not really hard to test for this property, but the cost efficiency is notable when you find a massive amount of it in one place. It still may be washed to remove further silt/clay, but they absolutely know the product works and they generally know the geology in other places don't tend to produce the same material.
There's a fair amount of materials size thats mostly "we found this geologic material and this is some magic shit" rather than some wholly manufactured human endevour.
>It remains the largest unreinforced concrete dome in the world, a staggering achievement for an structure completed around 126 AD during the reign of Emperor Hadrian.
Hopefully there's good empirical data powering the model here, which just added slump prediction:
> Alongside the event, Meta is releasing a new AI model for designing concrete mixes, Bayesian Optimization for Concrete (BOxCrete). BOxCrete improves over Meta’s previous models with more robustness to noisy data as well as new features including the ability to predict concrete slump (an important indicator of concrete workability).
Seems hard to imagine not doing a slump test, trusting AI when it comes to your multi/many million dollar build outs for something so important. But perhaps still useful for planning, as a starting place?
There is a lot of expense in the wasted concrete from all the different pours that are slump tested. There is a lot of cost from concrete that leaves the plant only to fail slump testing when it gets there - not only do you have to empty the truck someplace else, but there maybe contract provisions if you fail to keep the workers busy. Often more than one test is done - if the plant has an order that they know will be tested they test before it leaves the plant (if it fails they can redirect to a different customer who will knowingly accept lesser concrete - but concrete cures on the truck so it would be unacceptable if rejected at the site to go elsewhere). Many smaller jobs skip the test, but they would like it done if it was free.
That said, I'm not sure if the value can ever be greater than a slump test just before pouring.
The predictions of the model are used as recommendations for onsite testing to accelerate finding mixtures with optimal strength-speed-sustainability trade-offs. We are not replacing canonical testing with the model.
> But perhaps still useful for planning, as a starting place?
Yeah, lots of value in just having an app go "the mix you're trying to do is likely to fail the slump test". So you still have time to adjust the water ratio, or get better sand.
Reasonable so, slump tests have been in use for as long as I can remember. There's a couple of other tests that need to be performed as well for fresh concrete. One for air content in the concrete, then temperature and volumetric weight.
IIRC the big tests that occur are the cylinder samples that are taken as well of the concrete and allowed to cure to full strength before destructively tested anywhere from a week to a month after pouring.
Working with multiple tons of material that dries out as you move it around is hard. There are a lot of steps between the concrete being mixed and when it finally reaches the pour.
Cutting out a piece of a slab and sending it to a lab is for post-pour validation in serious construction. There are pre-pour tests that are much simpler depending on the seriousness of what you’re building.
No - it's actually local variance in materials coupled with the difficulty in moving materials between markets economically. Some areas just have better suited limestone or gravel or sand and can afford to build resilient structures for a fraction of the price that it'd cost in other areas.
This issue here is mainly that it's very expensive to ship all the components of a Concrete in the volume necessary in an economical manner. Some areas of the world just lost the lottery when it comes to having resilient building materials.
Corruption absolutely is an issue as well - I don't mean to downplay it - but even if we remove it as a factor there are just a lot of variables involved in making a reliable Concrete... finding a good mix is an artform and if, for instance, your limestone quary suddenly hits a more clay-laden amalgamation then your Concrete that was reliably lasting for three decades under certain conditions might suddenly lose a decade off the expected lifetime. That change in material quality can also be difficult to detect so there are real quality assurance issues in Concrete mixtures outside of just corruption and cutting corners.
They are standardized for a given mix. A mix design that is based on a trial badge is submitted to the SEOR prior to pouring anything. The mix design shows the ratios ingredients (cementitious materials, find and coarse aggregates, water, air, admixtures). But Concrete is still a non-homogeneous material with lots of variations. Take for instance aggregates, if it rained the last two weeks, the moisture content will be higher but it may only be a layer on that pile. Same goes for gradation (particle size of the rock). Sometimes you get a batch with smaller rock. There are a 100 things that can go wrong to get bad mud.
But yeah, there are concrete plants that cut corners and try to save on cement (the most expensive part of the mix), which depending on the project may bite them in the ass when they have to pay to fixing it.
My grandpa used to be a concrete inspector (for the state of Minnesota - if you ever drive i394 there he was one of the inspectors for that). Different plants within a normal commute of his house often had very different sand and so needed a different mix.
Oh cool, did he work for MNDOT? I sell and run a lot of work at their facilities, they have a materials lab over in Maplewood off Hwy 36 and English St, and also the weird test surface area on 94 west of St Cloud.
Yikes, what a flippant comment. The mix composition (meta's AI is helping with this) is separate from the wet concrete product. The parent is suggesting a way to test that the mix is properly mixed before pouring, not suggesting a way for construction workers to determine that the chemical properties of the mix will be correct on site. Furthermore, they're not even using LLMs, so it's not "AGI".
Do you actually see construction workers being replaced? We need more stuff built than we have people or time. We have spent a century improving process and tools and if we 10 years from now could build 3 times as much with the same people we would find a use for them all.
You're absolutely right — that rebar was severely corroded. I should not have poured that concrete without first checking the integrity of the rebar. This was a catastrophic error in judgement. Let's go over next steps—
Awesome. People take concrete for granted. Even at small scales (e.g. your patio) with formulas provided on the cement bag, concrete can go wrong (crazing, scaling, cracks). There's a lot of unappreciated craft in the work, not only in the composition and mixing, which is what this research seems dedicated to, but also in the placing, leveling, curing, finishing.
Civil Engineering is hard, and concrete is a perfect example of how something as "simple" as concrete in reality requires significant interdisciplinary collaboration with domain experts in ChemE, MatSE, Physics, Applied Math, and CS.
Some of the most robust HPC applications I saw back when I was an undergrad were done by Civil and Structural Engineers in the ONG space.
That’s funny because I don’t see civil engineers being “glazed” much online. Usually they’re the butt of jokes and ridicule from other engineering majors who perceive civil engineering as less ‘rigorous’ than other disciplines. I’m curious where you see this civil engineering “glazing”?
They're usually held up to as the pinnacle of "real engineers" in discussions where software people are trying to portray software as insufficiently rigorous.
Yeah the other varieties of "real engineer" think of them about the same way that NPs think of MDs.
> As a result, producers need a way to rapidly explore and validate new formulations without spending months in the lab.
How do you bypass the normal process of pouring test articles and testing them months and years after cure? This is fundamentally a research activity that needs to conduct verifiable science. Not something you can guess at with an LLM.
Hi, I developed the model. We are not bypassing the regular testing process, and are not using LLMs, but Gaussian processes with vetted test data. The predictions are used as recommendations for onsite testing, to accelerate finding mixtures with optimal strength-speed-sustainability trade-offs.
Somebody needs to coin a new term for the scattershot zero-thought AI griping that is pervasive in online comments these days. Meatslop?
Obviously it's going to be more productive for a manufacturer to do a years-long curing test on 100 likely candidates instead of 100 random mixes. They obviously already screen candidates through traditional methods, but if this AI technique improves accuracy, all the better.
The current strategy of the AI hype machine is to exhaust people's reserves of attention by presenting a never-ending stream of hard-to-verify "positive" claims. It's Gish Gallop done on the Internet scale with a never-ending parade of tech influencers, proxy "journalists" and low-value accounts. The whole strategy aims for saturation and demoralized acceptance.
It's no surprise that people readjust their immediate reactions by expressing hostility and skepticism about anything AI-related without spending much time on analysis. In fact, it's an entirely rational repones.
Complaining about it without acknowledging the larger picture is disingenuous.
In this particular case, using the term "machine learning" would likely avoid the immediate negative reaction.
The Gaussian Processes underpinning this work are hardly a product of the 'AI Hype Machine' - they've been around for decades, have strong statistical underpinnings, and are being widely explored for experimental design across many disciplines. Reflexive and poorly-informed backlash to any variety of machine learning is no more productive than blindly hyping up LLMs.
Meta Platforms, Inc featuring this technology with a title announcing “AI for American-produced cement and concrete” is, on the other hand, 1000% a product of the AI Hype Machine.
Sure, it's clearly marketing. I think a private company pursuing marketing via open research with open source code (including datasets) is a good trade. A hypey blogpost + research is better than no blogpost and no research.
Was that the one immediately after the great paradigm shift of November 2025, and before the great paradigm shift of January 2026? I think I remember it.
There was no such paradigm shift. LLMs still suck just as much as they did before, in the exact same ways they did before. In 6 months you'll be trying to BS us about the "great paradigm shift of summer 2026".
Reddit's top contributors are decent, but there is an elite niche of people (granted, mostly of the technical variety) who somewhat regularly show up on HN but do not contribute much on Reddit.
It does help, of course, that HN is moderated in good faith and has a more pervasive commitment to self-moderation than Reddit has ever had (outside a few very niche subreddits).
They both share the same problem: nobody who gripes incorrectly like this suffers any consequences. So you may as well gripe at anything and everything. Griping feels good and you rarely ever get downvotes on HN because griping is such a part of the site culture, whether you're incorrect or not. There's a recent HN guideline about being curmudgeonly but we all know that guidelines on this site are rarely followed.
Tangentially related, but there is a new generation of trucks that mix the concrete on-site. They can output small batches and change the mix on the fly. They solve a lot of headaches!
This may work on a small scale, not in most commercial use cases. A typical deck pour (400cy) will pour at 70-80cy/hr. you got 9-10cy/truck. Meaning you have 7 to 8 minutes to back in the truck, empty it into the hopper and leave. You barely have time to add water to the mix.
Most high-volume concrete plants are "dry-batch", which means all the ingredients get dumped into the drum and the concrete will get mixed while driving to the project site. Also, changing mixes on the fly will not "fly". No one is going to authorize the adjustment, because what happens when the mix doesn't meet specs... It will need to get chipped out.
Traditional trucks pick up cement from a facility and rotate it to keep it from setting. They don't mix it on the fly. Any extra is considered waste is poured out.
"Special concrete transport trucks (in-transit mixers) are made to mix concrete and transport it to the construction site. They can be charged with dry materials and water, with the mixing occurring during transport. They can also be loaded from a "central mix" plant; with this process the material has already been mixed prior to loading. The concrete mixing transport truck maintains the material's liquid state through agitation, or turning of the drum, until delivery. "
> Meta’s AI for concrete model can help suppliers more quickly incorporate U.S. materials into their mixes through an approach called adaptive experimentation.
> Proposes high-potential candidates: The AI suggests new mixes most likely to meet target specifications and can compare performance between U.S.-made and foreign materials
US imports 22% of its cement
> In 2024, Portland and blended cement were produced in 99 plants in 34 U.S. states, led by Texas, Missouri, California, and Florida. Nevertheless, there was significant import reliance. Net imports were 22% of total consumption, with the major source countries being Turkey (32%), Canada (22%), and Vietnam (10%). U.S. exports of cement last year were negligible.
I'm assuming this isn't for national security reasons, probably more to help the domestic industry deal with tariffs. I hope Meta used their extensive connections to the government.
Given the model is several years old, I assume this write up with its focus on incorporating domestic materials is so Mark Zuckerberg has something “America First” to point to next time he meets with Trump.
This is not to denigrate the work—experimental design can be a huge force multiplier and making it more accessible to people on the ground is a great thing to do. One of my favorite grad school courses was an experimental design class with four students where we spent about half of the semester doing real life experimental design for a chemistry phd student who was trying (and mostly failing, before we got involved) to create a molecular filter with specific properties.
The website talks about making cement, but only describes making concrete. Making concrete involves mixing cement and fillers with water under controlled conditions. Making cement involves heating calcium carbonates and oxides with silicon dioxide or calcium silicate to form alite at a temperature of (so far as we understand) no less than 1250 C. Usually this is done with fossil fuels and any impurities in the raw materials (which are cost-constrained) go up the flue, making cement plants rather polluting. Carbon dioxide is a nearly inevitable byproduct (CaCO3 + SiO2 >> CaSiO3 + CO2) and is either captured at source (not implemented at most facilities) or released.
There is plenty of room for improvement in cement production. I'm not sure exactly how to apply AI to it but I guess I was hoping for more than this. If we are going to have the infrastructure renaissance that keeps being talked up by reformists of various stripes, we need more cement.
South America is also a surprising laggard in cement production, which is odd considering they have the materials and they need the roads. I think that environmental concerns and a continental aversion to coal might contribute.
This also feels like "we're about to build a bunch of datacenters and we cannot meaningfully verify the quality of the concrete at our sites." This enables them to monitor the variables and probably not pay if it's out of spec would be my guess.
In my concrete mixer experience that's just one part of the process, lot of other crap goes wrong, forms, vibing, water, additives. I'm not pouring foundations, so my xp is only to say there's a lot going on. Guess it's a first step?
Does anyone here have experience with or knowledge of diy wood ash cement?
I produce a fair bit of ash. Often enough from hardwood or something close enough and keeping it and going trough the calcification process in the fireplace sounds easy enough.
I wonder if I could produce enough for hobby projects and if it would hold up outside.
Meta spends a ton of money on concrete, a 1M sqft data center with a 6” slab has one yard of concrete for every 54 sqft of floor, which is around 18,500 cubic yards of concrete.
Any improvements to concrete mixes will benefit them.
I love this concept but the introduction is very odd. It feels like the first, third and 4th paragraphs make the same point (1/4 of cement is imported). It gets better as it gets technical.
Our work on concrete here differs in that the problem is both
1) an inherently time-varying, and
2) multi-objective.
See our write-up here for details: https://arxiv.org/pdf/2310.18288
Concrete mixes have become more complicated over time. Flyash has been around for a while, GU/L is relatively new and seems to set faster, often requiring retarders. Many different water-reducing additives are available. Air entraining agents tend to reduce strength. Fibers or steel pins added to the mix can improve crack resistance.
Batch plants will design mixes so some water can be added on site to improve workability. If you don't add water, the concrete will likely exceed spec.
A slump test is only one factor if many that impact concrete strength.
man, I fucking love concrete. So cool. If you like concrete, check out [Tyler Ley's youtube channel](https://www.youtube.com/@TylerLey/videos). Anyways, I am curious why Meta is investing in this. They use a lot of concrete no doubt, but it's nothing compared to a highway, all the commercial builds, etc. I would have expected them to release something like a very general materials optimization framework to explore a space, but glad to see it applied specifically to concrete.
There are a lot of alternative cements to portland, interested to see if that is in-scope. The list of admixtures is also very long and also fairly secretive. UHPC is a pretty cool development, and I am especially bullish about removing rebar and replacing it with FRP bar to limit the eventual rust cracking that comes with the gradual march of carbonation.
Anyways, very cool and looking forward to the mix developments that come out of this framework.
First there was the rampocalypse. Then there was cementpocalypse. Let just hope the AI datacenters don't latch on to biofuel to supplement their energy requirements. It's just more profitable for farmers to sell calories to the AI overlords, the consumer food market is just a low margin grind.
Apologies for the sarcasm. I appreciate the drive for renewables the current AI DC buildout brings with it.
I have real fears that building materials will experience the same inflationary pressures computer memory is currently experiencing. The U.S. TSMC and Intel fab construction alone in the last couple years has had an outsized impact on building costs.
The US construction industry does about 3 trillion in revenue per year. Those two fabs are something like 20 billion per year. 2% is a lot but markets can handle that just fine. Local markets will have higher prices.
Jesus I hope they do proper testing for these experimental mixes and don't trust whatever random garbage AI decides you should mix in. This is exactly the kind of thing AI is absolutely terrible at because it has no logical skills or direct experience or ability to test it. If your AI coded stuff goes belly up, you get to try again. If your multi million dollar cement foundation turns out to be sub-par, thats multi million dollars to tear it out and then millions more to do it again right, and that is a best case scenario. The alternative is people dieing when their apartment building collapses.
We use Gaussian processes trained on vetted test data from academic and industry partners. We use these predictions to recommend mixes for onsite testing to accelerate finding mixtures with optimal strength-speed-sustainability trade-offs. None of the data and predictions go untested. The blog post goes into this in more detail.
Can you at least read the article before criticizing them? They explicitly call out that they use Bayesian Optimization (Gaussian process) thing for this. It is "AI" but not "LLM" like you think it is.
Hand-held devices for testing concrete properties would be more useful. Most concrete problems come from a bad mix - too much water, not enough cement, etc. Concrete testing usually involves cutting a core out of the poured slab and sending it to a lab. Something where you stick a probe in the mix and can reject it before pouring would help. Here are some on-site concrete testers.[1] They're heavy and a pain to use.
There should be an app for this. But that's so last-decade.
[1] https://store.forneyonline.com/concrete-testing-equipment/fr...
It’s customary to prefix these comments with credentials, so I’ll just say that I’m a roadway engineer. Sampling at the batch plant or even at the truck is not going to give you the whole story. While the most common crime of contractors is to overwater the concrete slurry to make it flowable, other problems in workmanship can arise from failing to vibrate the concrete in its forms, leaving voids, or vibrating it too much, creating segregation of the aggregate. If the finisher overworks the concrete or tries to correct the shape when it’s green, the that can compromise strength. If the concrete is finished too early, you can get delamination. If time allows and your contractor is careful they might protect the freshly poured concrete and let it cure wet. That makes a huge difference in cracking. There is also a whole world of chemical additives that structural engineers don’t even think about in the design process.
I’m not trying to say that mix doesn’t matter, or that I’m not pleased to see that Facebook is doing something a little more noble than surveillance technology, but as with a lot of construction issues, it’s just not that simple.
“it’s just not that simple” - my career in industrial data science in a nutshell. Lots of large companies come into the domains I’ve worked in with grand promises, and while sometimes they move the needle in terms of what executive leadership within the industry believes is possible, they also often poison the well for us smaller firms who provide much more leveled and concrete (heh) offerings. Curse IBM, for example.
AI is just the same. CEOs all over the world have fallen to the lure of the AI grifters, believing they can fire people en masse now and ride it out with the remaining staff until AI catches up with the remaining 20% of capability.
Small focused AI/ML companies however that don't deal in LLMs? They struggle to find customers, even with stuff that clearly works, because they hit the wrong buzzwords.
Is the slump test still commonly used? https://en.wikipedia.org/wiki/Concrete_slump_test
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> too much water, not enough cement, etc.
I wanted to mention that Concrete is far more complex and regional than folks might imagine. The quality of gravel and sand, local impurities - these all contribute massively. It's probably best to think of it like a wine's terroir - except, unlike a bottle of wine, it's prohibitively expensive to ship both the components and the finalized mixture to different areas. If a region's limestone has a massive clay impurity then it may simply be unsuitable for large structures or require extensive filtering to the point of being uneconomical.
It's important to be aware of just how much the local geological mix can impact the viability of building with concrete because while theoretically we could use perfect concrete for every project - at that point most projects would simply be too expensive to consider undertaking. There is a very large field of engineering around establishing the realism required in settling for what you've got for the price you can afford in. It can absolutely mean that the materials required to build a high rise in Philly might be priced starkly differently from the same structure planned in Milan even with adjustments for the labor impact on pricing.
And it's not just the gravel/sand that's important. The water itself also differs in its chemical composition (e.g. salts, minerals, basic/acidic pH), which can catch you really dirty when making concrete. Or when dealing with water at all, shout-out to Flint and its infamous water crisis that took eleven years to resolve - every single lead service pipe had to be physically dug up and replaced.
[1] https://en.wikipedia.org/wiki/Flint_water_crisis#2025
And the Flint disaster was caused by an attenpt to save a little money by changing the water source from lake to river water
> it's prohibitively expensive to ship both the components and the finalized mixture to different areas.
We could do this if it is important. There are mines in Wisconsin the export sand to the middle east because that is known to work well for fracking and they don't want to risk a local sand not working well. (AFAIK they have never tested local sand properties, but it is possible they have and it doesn't work). In this case the value of the "perfect" is well worth the high shipping costs.
We certainly could - it's absolutely possible. The question is if it's economical and so far the market has ruled in most cases that it isn't. Either the project doesn't need such a perfect amalgamation of materials (maybe there is an expected deprecation that doesn't justify such an outlay - possibly earthquake risk would minimize any expected lifespan gain - possibly the materials contractor just can't internally justify the added material cost while remaining attractive to local contractors).
It's all a balance. Imagine a scenario where you can ship in specialized materials to build a bridge with an expected lifespan of 100 years and it'll cost 50M - or you could use local concrete that has an expected lifespan of 15 years and materials would cost 5M. This is a vast simplification of the math but, assuming those expected costs it'd be cheaper to build using local materials and just schedule replacement every 15 years. And, of course, there'll be egg on your face if you build the 50M bridge and then suffer a massive tsunami in two years that destroys the foundations anyways.
To paraphrase a Grady quote: "Engineering isn't a study of building the best thing - it's optimizing the quality we can get for the cost outlay."
for fracking, what they want is a perfectly uniform sized quartz grain thats rounded. You find this sand where multiple processes occur, notably glacial geology. You want uniform grains because frackings goal is to open, then support an porous structure when you can then pull the fluids/gas out without clogging.
It's not really hard to test for this property, but the cost efficiency is notable when you find a massive amount of it in one place. It still may be washed to remove further silt/clay, but they absolutely know the product works and they generally know the geology in other places don't tend to produce the same material.
There's a fair amount of materials size thats mostly "we found this geologic material and this is some magic shit" rather than some wholly manufactured human endevour.
>The Pantheon Dome: A Marvel of Ancient Roman Architecture
https://www.pantheonroma.com/en/2026/02/11/the-pantheon-dome...
>It remains the largest unreinforced concrete dome in the world, a staggering achievement for an structure completed around 126 AD during the reign of Emperor Hadrian.
On-site, before pouring, they use the slump test: https://en.wikipedia.org/wiki/Concrete_slump_test
Glad to see someone pointed this out. The test consists of a bucket, plywood board & a stopwatch.
Hopefully there's good empirical data powering the model here, which just added slump prediction:
> Alongside the event, Meta is releasing a new AI model for designing concrete mixes, Bayesian Optimization for Concrete (BOxCrete). BOxCrete improves over Meta’s previous models with more robustness to noisy data as well as new features including the ability to predict concrete slump (an important indicator of concrete workability).
Seems hard to imagine not doing a slump test, trusting AI when it comes to your multi/many million dollar build outs for something so important. But perhaps still useful for planning, as a starting place?
There is a lot of expense in the wasted concrete from all the different pours that are slump tested. There is a lot of cost from concrete that leaves the plant only to fail slump testing when it gets there - not only do you have to empty the truck someplace else, but there maybe contract provisions if you fail to keep the workers busy. Often more than one test is done - if the plant has an order that they know will be tested they test before it leaves the plant (if it fails they can redirect to a different customer who will knowingly accept lesser concrete - but concrete cures on the truck so it would be unacceptable if rejected at the site to go elsewhere). Many smaller jobs skip the test, but they would like it done if it was free.
That said, I'm not sure if the value can ever be greater than a slump test just before pouring.
The predictions of the model are used as recommendations for onsite testing to accelerate finding mixtures with optimal strength-speed-sustainability trade-offs. We are not replacing canonical testing with the model.
> But perhaps still useful for planning, as a starting place?
Yeah, lots of value in just having an app go "the mix you're trying to do is likely to fail the slump test". So you still have time to adjust the water ratio, or get better sand.
Seems simple. Is it effective?
Reasonable so, slump tests have been in use for as long as I can remember. There's a couple of other tests that need to be performed as well for fresh concrete. One for air content in the concrete, then temperature and volumetric weight.
IIRC the big tests that occur are the cylinder samples that are taken as well of the concrete and allowed to cure to full strength before destructively tested anywhere from a week to a month after pouring.
I'm surprised the ratios for a given situation isn't standardized by now. Is it just people cutting corners?
Working with multiple tons of material that dries out as you move it around is hard. There are a lot of steps between the concrete being mixed and when it finally reaches the pour.
Cutting out a piece of a slab and sending it to a lab is for post-pour validation in serious construction. There are pre-pour tests that are much simpler depending on the seriousness of what you’re building.
The slump test is rather simple, for example: https://en.wikipedia.org/wiki/Concrete_slump_test
It’s basically a cone with handles and a procedure that’s easy to learn.
No - it's actually local variance in materials coupled with the difficulty in moving materials between markets economically. Some areas just have better suited limestone or gravel or sand and can afford to build resilient structures for a fraction of the price that it'd cost in other areas.
This issue here is mainly that it's very expensive to ship all the components of a Concrete in the volume necessary in an economical manner. Some areas of the world just lost the lottery when it comes to having resilient building materials.
Corruption absolutely is an issue as well - I don't mean to downplay it - but even if we remove it as a factor there are just a lot of variables involved in making a reliable Concrete... finding a good mix is an artform and if, for instance, your limestone quary suddenly hits a more clay-laden amalgamation then your Concrete that was reliably lasting for three decades under certain conditions might suddenly lose a decade off the expected lifetime. That change in material quality can also be difficult to detect so there are real quality assurance issues in Concrete mixtures outside of just corruption and cutting corners.
They are standardized for a given mix. A mix design that is based on a trial badge is submitted to the SEOR prior to pouring anything. The mix design shows the ratios ingredients (cementitious materials, find and coarse aggregates, water, air, admixtures). But Concrete is still a non-homogeneous material with lots of variations. Take for instance aggregates, if it rained the last two weeks, the moisture content will be higher but it may only be a layer on that pile. Same goes for gradation (particle size of the rock). Sometimes you get a batch with smaller rock. There are a 100 things that can go wrong to get bad mud.
But yeah, there are concrete plants that cut corners and try to save on cement (the most expensive part of the mix), which depending on the project may bite them in the ass when they have to pay to fixing it.
My grandpa used to be a concrete inspector (for the state of Minnesota - if you ever drive i394 there he was one of the inspectors for that). Different plants within a normal commute of his house often had very different sand and so needed a different mix.
Oh cool, did he work for MNDOT? I sell and run a lot of work at their facilities, they have a materials lab over in Maplewood off Hwy 36 and English St, and also the weird test surface area on 94 west of St Cloud.
Yes, drove snow plows in the winter from Chaska (no longed there). He retired long ago.
When you're making tons of something process variations get magnified.
I think people rarely reject even if it fails a slump test though
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Yikes, what a flippant comment. The mix composition (meta's AI is helping with this) is separate from the wet concrete product. The parent is suggesting a way to test that the mix is properly mixed before pouring, not suggesting a way for construction workers to determine that the chemical properties of the mix will be correct on site. Furthermore, they're not even using LLMs, so it's not "AGI".
Do you actually see construction workers being replaced? We need more stuff built than we have people or time. We have spent a century improving process and tools and if we 10 years from now could build 3 times as much with the same people we would find a use for them all.
Quality is irrelvant these days. If AI does it cheaper, you're done.
How cheap are existing AI construction workers?
Wrong day to release this. I had to read halfway through the release before realizing it’s legitimate.
Concrete has entered the agentic era
You're absolutely right — that rebar was severely corroded. I should not have poured that concrete without first checking the integrity of the rebar. This was a catastrophic error in judgement. Let's go over next steps—
A good abstract would have helped.
It's legitimate? I was like wtf until I saw the date and then closed the tab.
The article says "POSTED ON MARCH 30, 2026"
Arguably, an even worse day to release it ;)
Why?
Awesome. People take concrete for granted. Even at small scales (e.g. your patio) with formulas provided on the cement bag, concrete can go wrong (crazing, scaling, cracks). There's a lot of unappreciated craft in the work, not only in the composition and mixing, which is what this research seems dedicated to, but also in the placing, leveling, curing, finishing.
^ This.
Civil Engineering is hard, and concrete is a perfect example of how something as "simple" as concrete in reality requires significant interdisciplinary collaboration with domain experts in ChemE, MatSE, Physics, Applied Math, and CS.
Some of the most robust HPC applications I saw back when I was an undergrad were done by Civil and Structural Engineers in the ONG space.
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That’s funny because I don’t see civil engineers being “glazed” much online. Usually they’re the butt of jokes and ridicule from other engineering majors who perceive civil engineering as less ‘rigorous’ than other disciplines. I’m curious where you see this civil engineering “glazing”?
They're usually held up to as the pinnacle of "real engineers" in discussions where software people are trying to portray software as insufficiently rigorous.
Yeah the other varieties of "real engineer" think of them about the same way that NPs think of MDs.
All I know is that PhDs are real doctors, MDs are fake doctors.
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> As a result, producers need a way to rapidly explore and validate new formulations without spending months in the lab.
How do you bypass the normal process of pouring test articles and testing them months and years after cure? This is fundamentally a research activity that needs to conduct verifiable science. Not something you can guess at with an LLM.
Hi, I developed the model. We are not bypassing the regular testing process, and are not using LLMs, but Gaussian processes with vetted test data. The predictions are used as recommendations for onsite testing, to accelerate finding mixtures with optimal strength-speed-sustainability trade-offs.
That’s helpful. So instead of a much larger test matrix you are using a model to reduce that to the most likely candidates, right?
That's right.
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Somebody needs to coin a new term for the scattershot zero-thought AI griping that is pervasive in online comments these days. Meatslop?
Obviously it's going to be more productive for a manufacturer to do a years-long curing test on 100 likely candidates instead of 100 random mixes. They obviously already screen candidates through traditional methods, but if this AI technique improves accuracy, all the better.
The current strategy of the AI hype machine is to exhaust people's reserves of attention by presenting a never-ending stream of hard-to-verify "positive" claims. It's Gish Gallop done on the Internet scale with a never-ending parade of tech influencers, proxy "journalists" and low-value accounts. The whole strategy aims for saturation and demoralized acceptance.
It's no surprise that people readjust their immediate reactions by expressing hostility and skepticism about anything AI-related without spending much time on analysis. In fact, it's an entirely rational repones.
Complaining about it without acknowledging the larger picture is disingenuous.
In this particular case, using the term "machine learning" would likely avoid the immediate negative reaction.
It feels related to “it’s easier to argue with a smart person than an idiot.”
It’s really exhausting to feel negative all the time when faced with the cavalcade of terribly weak claims.
The Gaussian Processes underpinning this work are hardly a product of the 'AI Hype Machine' - they've been around for decades, have strong statistical underpinnings, and are being widely explored for experimental design across many disciplines. Reflexive and poorly-informed backlash to any variety of machine learning is no more productive than blindly hyping up LLMs.
Meta Platforms, Inc featuring this technology with a title announcing “AI for American-produced cement and concrete” is, on the other hand, 1000% a product of the AI Hype Machine.
Sure, it's clearly marketing. I think a private company pursuing marketing via open research with open source code (including datasets) is a good trade. A hypey blogpost + research is better than no blogpost and no research.
Stop blaming random stuff for your own shortcomings.
Written like someone who hasn't used AI since the great paradigm shift of December 2025.
Was that the one immediately after the great paradigm shift of November 2025, and before the great paradigm shift of January 2026? I think I remember it.
There was no such paradigm shift. LLMs still suck just as much as they did before, in the exact same ways they did before. In 6 months you'll be trying to BS us about the "great paradigm shift of summer 2026".
I call it pseudo-critique — active stupidity in the name of critical thinking — but that’s too general.
https://danluu.com/cocktail-ideas/
hn discourse is not nearly as high-quality as people would like to believe.
It’s very bimodal.
just like everywhere else? reddit has fairly good wheat among the chaff just the same?
Reddit's top contributors are decent, but there is an elite niche of people (granted, mostly of the technical variety) who somewhat regularly show up on HN but do not contribute much on Reddit.
It does help, of course, that HN is moderated in good faith and has a more pervasive commitment to self-moderation than Reddit has ever had (outside a few very niche subreddits).
They both share the same problem: nobody who gripes incorrectly like this suffers any consequences. So you may as well gripe at anything and everything. Griping feels good and you rarely ever get downvotes on HN because griping is such a part of the site culture, whether you're incorrect or not. There's a recent HN guideline about being curmudgeonly but we all know that guidelines on this site are rarely followed.
co-slop. In the categorical sense, slop with all the relationships reversed.
What part of move fast and break things did you not understand?
It doesn't use an LLM
What could possibly go wrong?
https://dailygalaxy.com/2026/03/rubber-used-in-undersea-tunn...
All the chemical companies do it. They pair it with testing, but still.
They have a new scapegoat to blame if things turn out badly.
Why do they need AI for that? Just create another LLC, manslaughter any number of people, then have that LLC declare bankruptcy. Zero consequences.
Emitting a shrug and "AI made me do it" is cheaper.
Tangentially related, but there is a new generation of trucks that mix the concrete on-site. They can output small batches and change the mix on the fly. They solve a lot of headaches!
https://cementech.com/volumetric-technology/
This may work on a small scale, not in most commercial use cases. A typical deck pour (400cy) will pour at 70-80cy/hr. you got 9-10cy/truck. Meaning you have 7 to 8 minutes to back in the truck, empty it into the hopper and leave. You barely have time to add water to the mix. Most high-volume concrete plants are "dry-batch", which means all the ingredients get dumped into the drum and the concrete will get mixed while driving to the project site. Also, changing mixes on the fly will not "fly". No one is going to authorize the adjustment, because what happens when the mix doesn't meet specs... It will need to get chipped out.
The target audience of these trucks is sub-10cy jobs. It allows companies to cater to smaller customers at a premium.
In the large road projects I've seen they bring a concrete plant to the job. Buildings still get trucks coming in.
I highly recommend the 9 episode miniseries podcast The Big Dig from GBH. Their mismanagement of the concrete was wild.
Concrete mixer trucks are not new at all actually, they've been around for a long time.
Traditional trucks pick up cement from a facility and rotate it to keep it from setting. They don't mix it on the fly. Any extra is considered waste is poured out.
Where did you get the idea that rotating is "to keep it from setting" and not mixing?
https://en.wikipedia.org/wiki/Concrete_mixer#Concrete_mixing...
"Special concrete transport trucks (in-transit mixers) are made to mix concrete and transport it to the construction site. They can be charged with dry materials and water, with the mixing occurring during transport. They can also be loaded from a "central mix" plant; with this process the material has already been mixed prior to loading. The concrete mixing transport truck maintains the material's liquid state through agitation, or turning of the drum, until delivery. "
Y'all both right.
> Meta’s AI for concrete model can help suppliers more quickly incorporate U.S. materials into their mixes through an approach called adaptive experimentation.
> Proposes high-potential candidates: The AI suggests new mixes most likely to meet target specifications and can compare performance between U.S.-made and foreign materials
US imports 22% of its cement
> In 2024, Portland and blended cement were produced in 99 plants in 34 U.S. states, led by Texas, Missouri, California, and Florida. Nevertheless, there was significant import reliance. Net imports were 22% of total consumption, with the major source countries being Turkey (32%), Canada (22%), and Vietnam (10%). U.S. exports of cement last year were negligible.
https://www.constructconnect.com/construction-economic-news/....
I'm assuming this isn't for national security reasons, probably more to help the domestic industry deal with tariffs. I hope Meta used their extensive connections to the government.
Given the model is several years old, I assume this write up with its focus on incorporating domestic materials is so Mark Zuckerberg has something “America First” to point to next time he meets with Trump.
This is not to denigrate the work—experimental design can be a huge force multiplier and making it more accessible to people on the ground is a great thing to do. One of my favorite grad school courses was an experimental design class with four students where we spent about half of the semester doing real life experimental design for a chemistry phd student who was trying (and mostly failing, before we got involved) to create a molecular filter with specific properties.
They sure are stretching to find a way to make this have something to do with being pro-America.
Increasing the quality and quantity of domestic cement output will provide a pretty clear national benefit.
That part made me double check the date today and now I'm not sure.
The website talks about making cement, but only describes making concrete. Making concrete involves mixing cement and fillers with water under controlled conditions. Making cement involves heating calcium carbonates and oxides with silicon dioxide or calcium silicate to form alite at a temperature of (so far as we understand) no less than 1250 C. Usually this is done with fossil fuels and any impurities in the raw materials (which are cost-constrained) go up the flue, making cement plants rather polluting. Carbon dioxide is a nearly inevitable byproduct (CaCO3 + SiO2 >> CaSiO3 + CO2) and is either captured at source (not implemented at most facilities) or released.
There is plenty of room for improvement in cement production. I'm not sure exactly how to apply AI to it but I guess I was hoping for more than this. If we are going to have the infrastructure renaissance that keeps being talked up by reformists of various stripes, we need more cement.
South America is also a surprising laggard in cement production, which is odd considering they have the materials and they need the roads. I think that environmental concerns and a continental aversion to coal might contribute.
This also feels like "we're about to build a bunch of datacenters and we cannot meaningfully verify the quality of the concrete at our sites." This enables them to monitor the variables and probably not pay if it's out of spec would be my guess.
In my concrete mixer experience that's just one part of the process, lot of other crap goes wrong, forms, vibing, water, additives. I'm not pouring foundations, so my xp is only to say there's a lot going on. Guess it's a first step?
Tangential question:
Does anyone here have experience with or knowledge of diy wood ash cement? I produce a fair bit of ash. Often enough from hardwood or something close enough and keeping it and going trough the calcification process in the fireplace sounds easy enough. I wonder if I could produce enough for hobby projects and if it would hold up outside.
Only (April) fools would trust Facebook's technology with anything as safety critical as construction work.
Meta spends a ton of money on concrete, a 1M sqft data center with a 6” slab has one yard of concrete for every 54 sqft of floor, which is around 18,500 cubic yards of concrete.
Any improvements to concrete mixes will benefit them.
Move fast and break things coming to high rise and bridge construction.
Testing your concrete takes too long. Just vibemix it.
I love this concept but the introduction is very odd. It feels like the first, third and 4th paragraphs make the same point (1/4 of cement is imported). It gets better as it gets technical.
Wet cement is kind of sloppy, so this makes some sense.
I had to double check that this wasn't an April Fools joke. The GitHub project has commits from 2 weeks ago, so it's not.
Looking more closely though, this looks a lot like the Google "AI Cookie" from 2017, which also used Bayesian Optimization: https://blog.google/innovation-and-ai/technology/research/ma...
Google's "Smart Cookie" indeed also used techniques from Bayesian Optimization. For some technical detail, see their write-up here: https://static.googleusercontent.com/media/research.google.c...
Our work on concrete here differs in that the problem is both 1) an inherently time-varying, and 2) multi-objective. See our write-up here for details: https://arxiv.org/pdf/2310.18288
Concrete mixes have become more complicated over time. Flyash has been around for a while, GU/L is relatively new and seems to set faster, often requiring retarders. Many different water-reducing additives are available. Air entraining agents tend to reduce strength. Fibers or steel pins added to the mix can improve crack resistance.
Batch plants will design mixes so some water can be added on site to improve workability. If you don't add water, the concrete will likely exceed spec.
A slump test is only one factor if many that impact concrete strength.
man, I fucking love concrete. So cool. If you like concrete, check out [Tyler Ley's youtube channel](https://www.youtube.com/@TylerLey/videos). Anyways, I am curious why Meta is investing in this. They use a lot of concrete no doubt, but it's nothing compared to a highway, all the commercial builds, etc. I would have expected them to release something like a very general materials optimization framework to explore a space, but glad to see it applied specifically to concrete.
There are a lot of alternative cements to portland, interested to see if that is in-scope. The list of admixtures is also very long and also fairly secretive. UHPC is a pretty cool development, and I am especially bullish about removing rebar and replacing it with FRP bar to limit the eventual rust cracking that comes with the gradual march of carbonation.
Anyways, very cool and looking forward to the mix developments that come out of this framework.
First there was the rampocalypse. Then there was cementpocalypse. Let just hope the AI datacenters don't latch on to biofuel to supplement their energy requirements. It's just more profitable for farmers to sell calories to the AI overlords, the consumer food market is just a low margin grind.
Most large scale DC projects I've know are primarily leveraging solar with grid batteries because of the low upfront cost and state incentives.
Apologies for the sarcasm. I appreciate the drive for renewables the current AI DC buildout brings with it.
I have real fears that building materials will experience the same inflationary pressures computer memory is currently experiencing. The U.S. TSMC and Intel fab construction alone in the last couple years has had an outsized impact on building costs.
The US construction industry does about 3 trillion in revenue per year. Those two fabs are something like 20 billion per year. 2% is a lot but markets can handle that just fine. Local markets will have higher prices.
I hate April Fools day so much. Is this a joke? I genuinely cannot tell.
It's not a joke - but it sure feels suspicious :D
Not nearly entertaining enough to be one.
The date on the article is March 30th.
If it reduces the cost of concrete (which has been going crazy in NYS), have at it. If it's just another clever bot trick, save it.
I honestly thought this was going to be an April Fools gag.
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The masons just showed up their involvement with AI and everything wrong in our times. The masks have fallen. /s
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Jesus I hope they do proper testing for these experimental mixes and don't trust whatever random garbage AI decides you should mix in. This is exactly the kind of thing AI is absolutely terrible at because it has no logical skills or direct experience or ability to test it. If your AI coded stuff goes belly up, you get to try again. If your multi million dollar cement foundation turns out to be sub-par, thats multi million dollars to tear it out and then millions more to do it again right, and that is a best case scenario. The alternative is people dieing when their apartment building collapses.
We use Gaussian processes trained on vetted test data from academic and industry partners. We use these predictions to recommend mixes for onsite testing to accelerate finding mixtures with optimal strength-speed-sustainability trade-offs. None of the data and predictions go untested. The blog post goes into this in more detail.
What do you mean by "onsite testing"? Wouldn't this be part of the pre-submittal process?
AI isn’t just LLMs.
Can you at least read the article before criticizing them? They explicitly call out that they use Bayesian Optimization (Gaussian process) thing for this. It is "AI" but not "LLM" like you think it is.