AI for American-produced cement and concrete
engineering.fb.com
engineering.fb.com
There should be an app for this. But that's so last-decade.
[1] https://store.forneyonline.com/concrete-testing-equipment/fr...
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.
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.
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.
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."
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.
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.
> 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?
That said, I'm not sure if the value can ever be greater than a slump test just before pouring.
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.
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.
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.
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.
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.
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.
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.
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.
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’s really exhausting to feel negative all the time when faced with the cavalcade of terribly weak claims.
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).
https://dailygalaxy.com/2026/03/rubber-used-in-undersea-tunn...
"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.
> 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.
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.
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.
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.
Any improvements to concrete mixes will benefit them.
Testing your concrete takes too long. Just vibemix it.
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...
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
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.
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.
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.