Discussion

Mr_P: 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...

ajkjk: They sure are stretching to find a way to make this have something to do with being pro-America.

gwbas1c: I honestly thought this was going to be an April Fools gag.

seemaze: 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.

wxw: 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.

barbazoo: > 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 materialsUS 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.

ortusdux: 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/

kevin_thibedeau: > 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.

postexitus: What part of move fast and break things did you not understand?

tartoran: They have a new scapegoat to blame if things turn out badly.

simonw: I hate April Fools day so much. Is this a joke? I genuinely cannot tell.

triceratops: Not nearly entertaining enough to be one.

alephnerd: Most large scale DC projects I've know are primarily leveraging solar with grid batteries because of the low upfront cost and state incentives.

seemaze: 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.

danbrooks: It's not a joke - but it sure feels suspicious :D

sebastianeament: 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.

simianwords: It doesn't use an LLM

charcircuit: The date on the article is March 30th.

Animats: 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...

woah: 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.

AngryData: 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.

sebastianeament: 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.

mrbonner: 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.

mathisfun123: hn discourse is not nearly as high-quality as people would like to believe.

rootusrootus: It’s very bimodal.

mathisfun123: just like everywhere else? reddit has fairly good wheat among the chaff just the same?

MisterTea: On-site, before pouring, they use the slump test: https://en.wikipedia.org/wiki/Concrete_slump_test

harimau777: I'm surprised the ratios for a given situation isn't standardized by now. Is it just people cutting corners?

m4rkuskk: 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.

themafia: When you're making tons of something process variations get magnified.

zozbot234: Concrete mixer trucks are not new at all actually, they've been around for a long time.

richwater: 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.

k33n: AI isn’t just LLMs.

romaniv: 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.

Waterluvian: 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.

m4rkuskk: What do you mean by "onsite testing"? Wouldn't this be part of the pre-submittal process?