Every windows install I've ever done (in Australia) I picked "English (Australia)" when possible, and "English (UK)" before Microsoft provided that localisation option. I've never seen US letter as a default.
If we're being anecdotal, I haven't had a single outage of anything affect me at all this year, but have had many in previous years. Often the thing blamed publicly has been incorrect too.
there is the problem. We don't know what country is in question. There are some countries where the truth is not a defense against libel. Thus, depending on where the author is from, or for that matter the publisher or other people who might happen to be in the chain, there could be a libel case if the truth was stated.
The fact that people have lived and worked near data centres for decades and didn't even know what the term meant - let alone be adversely impacted by them - probably indicates they're broadly an non issue. All of a sudden out of nowhere, AI and data centres got intermingled by the media and now people seem to have big issues with them.
Because the dynamics have shifted enormously inside the rack.
10 years ago, I was running 4 CPU servers with 48 cores and 128GB of RAM in 2U enclosures with a maximum power consumption of 500W or so. I was able to stick ~20 of them in a 42U rack, totaling 10kW.
A data center full of these can be cooled with CRACs and hot/cold aisles without much problem. This is still too much for a bog-standard server colocation operation, but for HPC, that was normal and manageable.
Now, a ~1U server houses 4 SOTA NVIDIA GPUs, 64 cores, magnitudes more RAM. This server alone uses ~3KW of power. This means you go anywhere between 30kW to 50kW per rack, and you have many racks.
Of course this means more power comes in, more heat comes out. This means more sophisticated infrastructure: bigger and beefier primary and secondary power systems, beefier cooling, more heat, more noise, in short "more of everything".
Of course when you cram this much energy and heat into a relatively small space, its effect on the environment will be much more pronounced.
Facebook's previous SOTA datacenter used water infused, HEPA filtered free flowing air accross the datacenter. Now, it's server level direct liquid cooling with extensive water treatment and oversight on coolant parameters.
Compare this having a hand warmer vs. coal ember in your hand. The latter needs a much more elaborate setup to prevent it burning you badly.
Megawatt racks are coming.[1][2] 10x or 20x more than current practice. There is a lot of plumbing involved. See [2] for more than you really want to know about the plumbing. "You got 400 gallons per minute?" for his rack, the sales rep asks. He's saying that you need to start planning for power and coolant flow far beyond what data center planners previously considered.
Why are you implying all datacenters are GPU farms? You can't retrofit that kind of power density into existing buildings.
You can stuff GPU servers into existing buildings- but even with significant upgrades you end up with a lot of empty space on the floor that can't be used.
1. Article is about AI, so I have given the example for an AI datacenter.
2. In pure CPU datacenters, the power dynamics do not change much. I can add more servers to a single rack, but the rack power is again in the 30kW to 50kW range, so you're planning and building for the same power capacity.
> You can stuff GPU servers into existing buildings-
Yes.
> but even with significant upgrades you end up with a lot of empty space on the floor that can't be used.
Yes & No. It's not impossible to convert an old datacenter to support ~35KW/rack capacity, but it's not cheap, and you'll have more worries than holes, piping, building and power. Namely, can your floor handle that much weight to begin with?
Though, the new data centers are not entirely the same. Increasing use of onsite gas turbines to generate power instead of using grid power changes their noise+air pollution profile.
The problem these days is lack of nuance. It should seem entirely reasonable to be pro-datacenters-if-they're-done-right, but it feels like there are only two sides to any issue. Gas turbine whine noise isn't coming from the data center, it's being used to power the data center, but the camp is either pro data center or not, and fuck any nuance.
The problem is people keep trying to regulate businesses by name instead of by the effects they have.
If we had regulations on noise, vibration, emissions, water use, electromagnetic radiation, whatever else, then it wouldn’t matter what people tried to build — if it fits within the guidelines great, otherwise back to the drawing board.
Putting “data center” in your ordinances is as lazy and ineffective as putting “abattoir.”
> If we had regulations on noise, vibration, emissions, water use, electromagnetic radiation, whatever else, then it wouldn’t matter what people tried to build
We certainly do! It’s just often overridden and ignored for these companies and data centers
> If we had regulations on noise, vibration, emissions, water use, electromagnetic radiation, whatever else, then it wouldn’t matter what people tried to build — if it fits within the guidelines great, otherwise back to the drawing board.
Sane jurisdictions do have regulations regarding these things. Not all jurisdictions are sane, some of them are run by people who sell out their residents.
Suburbs and cities around me all have noise regulations, my state has its own pollution regulations, and the local water utilities don’t hook up customers that stress the system. Unfortunately there are places like Texas, Tennessee, Louisiana, Mississippi that don’t give two shits about their citizens and let companies run temporary natural gas turbines permanently and all kinds of other nonsense.
Because the reality is while we all debate the nuances companies just do whatever they want, and it’s usually whatever offloads the most issues to the public because it saves them more money.
I'm hard pressed to think of anyone who believes that America has a healthy democracy. Even those most recently elected continually claim that democracy is under threat.
It's been pretty common in the past for tech companies to announce outages and quick updates about them on twitter for decades. I'm sure their status page etc will be updated soon, but it's historically been the fastest way to get things out to the wider audience whilst bypassing the "official mail out" review by marketing etc.
I think that was a lot more justifiable when Twitter reliably let logged out users read tweets. X seem to tweak it all the time, or maybe it’s just broken a lot, but sometimes I can’t even load a tweet in a browser that isn’t logged in.
It doesn't show live profile pages to logged out users since a while ago. You get cached summary pages, an age gate error, or sometimes a straight up 404.
Most individual permalinks (.com/username/1234...) don't work without logging in, either, and the official client now uses `/i/` in place of usernames for permalinks(bogus usernames always worked; pkey was the timestamp).
This means an organizationally shared Twitter account for announcements is not a viable concept, at least until Twitter is to be transferred again to whoever would be a better keeper of it.
AI companies bought up all the NAND manufacturing capacity, limiting the available manufacturing capacity for consumer products. These data centers also use hard drives for some of their data storage.
I suspect the type of person who is even aware of this 4GB blob is the type of person who would research its usage. Pretty high venn diagram crossover.
Yeah. The fictional user doesn’t know anything about AI but knows about this 4gb file…because of news stories about how bad a 4gb file must be. Outside of that, they don’t know or care and wonder if that means that need to add some more “memory” to their computer.
> It's a very dangerous gamble. Today incredible value is available for nearly everyone. But it may stop without any warning, for reason outside our control.
What stops you from running the best open weighted LLMs currently available on consumer grade hardware for the rest of time? They're good enough for 95% of use cases, and they don't have a used by date. From what I can see, the "danger" is not having the next tier that comes out, but the impact of that is very low.
For quite a lot of use cases, the current systems arguably do get worse over time if not continually updated. The knowledge cutoff date will start to hurt more and more as the weights age in a hypothetical scenario where you are stuck with them forever.
Coding, one of the most popular usescases today, would not be great if it say only understood java to a version from years ago etc.
One solution is not to advance anything of course. I'm not even joking, is there going to be a successor to React? I suspect not, with the vast amount of training data for React now, it's going to look silly to move to something else with less support. What is the last new popular programming language, rust? Will there be another one? I suspect not. Same reasoning. The irony of all this AI acceleration talk is it'll work best if we don't accelerate the underlying tech at all.
Yes. I am seeing a big push to use vanilla js for single file html apps that are easy to build, deploy and distribute because they have no build step. I could see component libraries emerging that make it easier build from chat interfaces with less ceremony
Small models are more useful for "doing stuff" than "knowing stuff" to begin with. Add in an agentic harness and a small model can happily read more current information on demand (including from e.g. a local wikipedia snapshot).
Nobody is unaware of the knowledge cutoff, and sharing the Wikipedia article is not helping anyone. Your point is easily rebutted by taking whatever open weights/source model has an outdated cutoff and training or fine tuning it on more data, which is again always going to be viable given a modicum of compute
I genuinely don't understand how can this possibly be a problem long term.
It feels very obvious that the solution is to have a smaller model that can be trained exclusively on Java information to augment the older model. If the architecture doesn't support it currently, then that's what the architecture will look like in the future.
Otherwise you'd be arguing that, to serve users who want to an up-to-date LLM on topic X, you have to train the model on the entire ABC all over again.
It's simply ludicrous to have a coding LLM that needs to be retrained on the latest published poems and pastry recipes to generate Java.
Ha yes I used to think this was not a notable issue, but just today I was getting qwen 3.5 to fix my network drivers and it immediately freaked out like: "kernel 6.17, what the fuck? that doesn't exist yet!". It almost had a mental breakdown over that detail and derailed the conversation towards checking what's wrong with the kernel version reporting lol.
What is really amusing to me is how N months ago, the latest SOTA was incredible, but now utterly unusable. Feels like there is a model reality-distortion field in play where people can only acknowledge the flaws in retrospect.
I’m pretty happy with what a 32GB Mac Studio can do for a lot of tasks. They’re the things I’d throw a model like Haiku at, but still genuinely useful. We don’t have an answer to frontier models in the consumer range yet, but we’re not totally trapped.
Side note though, it’s the speed that bothers me more than the reasoning. Qwen 3.5 is awesome, but my Claude subscription can tear through similar workloads an order of magnitude faster than my local LLM can when using Haiku. That’ll matter a lot to some people.
> What stops you from running the best open weighted LLMs currently available on consumer grade hardware for the rest of time?
Uh… the hardware requirements? And stop acting like some dog shit 8B model the average Joe can run on a laptop is even close to being comparable to what Claude or even Codex can currently do.
I have pretty good hardware and I’ve tinkered with the best sub-150B models you can use and they are awful compared to Anthropic/OAI/Grok.
What if the harness and loops get sufficiently better though? CC is using haiku for code-base gripping and such, you don't see a local commodity model being "good enough" for the 80% case when matched with better harnesses and tool calls?
honest question, i'm very interested in this, but too casual as of now to know any better.
I think the main issue is, as the other guy also alluded to, the parameter discrepancy. I know Mixture of Experts models are popular specifically becaue they save a lot of space and memory, but if your initial answer space is two orders of magnitude smaller on a local machine compared to the frontier cloud models, that knowledge gap just gets wider as the conversation continues, and the initial answer isn't even going to be as good to begin with. I don't know how to solve that parameter gap without hardware - there's only so much optimisation you can do, but at the end of the day parameterised knowledge takes up some minimum amount of bits that you can't excise without the actual knowledge and intelligence suffering.
> And stop acting like some dog shit 8B model the average Joe can run on a laptop is even close to being comparable to what Claude or even Codex can currently do.
I'm not, you've actually illustrated my point. LLMs in 2022 were very impressive. By 2024 the general public was finding them an acceptable replacement for many research driven tasks and massive shortcuts for other tasks (coding, image work, document preperation, etc).
Those models are absolutely runnable on consumer hardware now, and we were extremely happy with the results. It's no different to how we used to think CRTs were amazing or early smartphones, but going back now they seem awful.
We're long past "danger". If what we have is the best we'll ever have open source, we're already in an excellent position.
No they weren't. They were a gimmick - it is only in the past 6 or so months that frontier models have started to do stuff beyond mere gimmicks when it comes to coding, and you could make the argument that Mythos has been the first 'Holy shit' moment that we've had that has stepped us beyond 'Yeah that's really neat but...'
> Those models are absolutely runnable on consumer hardware now,
A sub 50B model is awful and can't even write proper English sentences half the time, to say nothing of how bad its world knowledge is. Try the 32B Gemma 4 local model for a week and then go back to Claude and then get back to me.
> We're long past "danger". If what we have is the best we'll ever have open source, we're already in an excellent position.
Not sure what to tell you other than that you and I have very different standards. What we have locally right now is barely more than a glorified autocomplete, and it feels worse than using ChatGPT 2 years ago because the context window is less and it doesn't have good webhooks on consumer setups. Another thing I'd say is that you clearly have no clue what 'consumer hardware' means, or what consumers that can even get this stuff running locally would have to do to get it to even rival the frontier models in terms of their usability (most consumers are't going to just boot into Ubuntu and run this thing from a command line) flow, to say nothing of the hardware requirements. I'd love to never use Claude or Gemini or ChatGPT again for both privacy and money reasons, but the quality of outputs and depth of thinking and writing ability between even the very best local models you can run right now is many orders of magnitude less than what you get using distributed frontier models, and those 'very best' local models require a top of the line machine that 99.9999% of consumers don't have and would never consider buying. The cloud models all have like a trillion(!) parameters now. It isn't even close.
I sure hope the local side of things massively improves over the next 2-3 years, but based on how this has gone my guess is that in 3 years you'll be lucky, if you have very top of the line hardware, to get benchmark performance that we had 6 months ago with the frontier models. The distributed hardware/memory gap is just too big.
> No they weren't. They were a gimmick - it is only in the past 6 or so months that frontier models have started to do stuff beyond mere gimmicks when it comes to coding
This is simply untrue. Using agentic orchestration I was writing production code daily 3 years ago. Hallucinations happened sometimes and context window was smaller (so you had to do some funky workarounds to deal with larger codebases), but it was workable. There have been a lot of marked improvements from a code perspective then - a lot model related yes, but also a lot in the ease of use, interfaces, etc.
> Another thing I'd say is that you clearly have no clue what 'consumer hardware' means, or what consumers that can even get this stuff running locally would have to do to get it to even rival the frontier models in terms of their usability (most consumers are't going to just boot into Ubuntu and run this thing from a command line) flow, to say nothing of the hardware requirements.
You've moved the goalposts. My point was that the "danger" of no new open models being released isn't that high as the existing ones are already impressive. Their ease of use or daily driving isn't relevant to that. If there were a need, someone could wrap a clean interface and support around it, or run it as their own cloud solution.
You seem to be arguing something adjacent to my point, which is fine I guess but I have little to say. Also multiple of your comments have come across quite aggressive and rude. Just food for thought if you want to work on that or not.
Hardware. Frontier labs are driving up demand so much that it's priced significantly above cost making it far less affordable. Just look at Nvidia's profit margins.
Maybe. The use cases people primarily use LLMs for (documents, coding, design, research) existed decades ago with different tooling. Who knows if the future will have a slew of new problems that require new models or will continue to be similar?
Me! Sounds great. Ideally a full fold up laptops or some sort of HUD, but I'll take a pocket folding tablet for now.
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