Don't know about US, but I work within European Datacenter where we intend to have excess heat to be used for residential building heating [1]. You must be in proximity of the consumer for this to be possible. Not necessarily center is needed, but even then, DCs can be pretty :)
For example our office is heated using heatpump that has >22C of water heated by equipment as a source.
> excess heat to be used for residential building heating
In the late 90s I worked at an insurance company in leafy Surrey[1]. I was told that they used to use their IBM mainframe to heat the swimming pool[2] effectively for free; when they upgraded they had to buy and run a heating system for the pool as the new mainframe didn't pump out enough heat.
[1] In England, south west suburbs of London to be precise.
[2] yes it had an indoor pool, badminton courts, outdoor tennis courts and other facilities - a great place to work.
The fascinating thing is that it wasn't a primary part of the mission but got lots of excitement. For me it was the thing that it features many off-the shelf parts from smartphones, uses linux and other open source software and it beat the expectations on how long it will service - Planned ~30 days with 5 flights and it did almost 3 years with 72 flights. https://www.nasa.gov/news-release/after-three-years-on-mars-...
Reviewing and reading everything makes this feeling, yeah.
However where I can say 100% it saves time is discovery by answering these questions:
- At what state does bug X manifests?
- Explain how integration/feature works.
- I want to integrate with system X: Audit what items/features are used and what model changes are needed on my side
Can someone recommend a correct way for interior design ideas?
Yesterday tried GPT-6-Astra Light to have a kitchen remodel... well it did understand 2D space, an improvement when tried on GPT-5.6-Sol
But the image representation was way off and I was not satisfied... misplaced the window, drew a wall which was not on 2D image, cabinet size issues. Eh.
Last week I had to reuse homemade skills on different project. I very much liked the AI proposed solution and it works quite well: ship as a plugin and add your git repo as a marketplace.
The installation is effortless and I don't have to mess with symlinks as I may be working with same codebase on different platforms which would make things.. different.
codex plugin marketplace add "https://path-to-my-git-repo"
codex plugin add agent-tools@mycompany
claude plugin marketplace add "https://path-to-my-git-repo"
claude plugin install agent-tools@mycompany
Let the AI generate .json files for marketplace.
Haven't got to these bits yet, but I'm sure they will work as easy as install does.
claude plugin marketplace update mycompany
claude plugin update agent-tools@mycompany
Uh, I tried feeding 5.6 Sol High my 2D DXF drawings of my house floor layout & house exterior to generate 3D visualization within blender via MCP... and it was miserable. No understanding on how windows attach to walls, misaligned bearing walls between floors, gaps all around the places, chimney not continuous, windows don't line up and are in wrong places, house parts swapped. And still struggling when I explain those things - that it is a house and real-life architectural constraints should be taken into account. But I just had to keep prompting to fix this, that, redo this and that and then it breaks other things until I fed up.
Part of it is probably struggle to understand the DXF and mixing up "wall lines" with "dimension/helper lines" (I tried also feeding PDFs)
Anyways, if someone has an idea how to improve 3D modelling with AI or how to make understand 2D drawings to understand rooms/walls/square meters, etc - would be nice.
I know few CEOs/Business owners who are non programmers (well one was exposed to it/learning, but didn't go down that path) and they do use AI for various work and non work related things. One told me how at manufacturing plant someone solved some unpleasant process to input specs into machine for manufacturing by having AI creating the automation.
His comment to me was: People who don't embrace AI will eventually be outcompeted by the ones who do.
And what happens when the price goes up by an extra zero on the end?
And then another one?
And then the cloud stuff goes away because all the vendors go broke, despite the price rises, and you have to switch to using local models?
That is, models that are hugely slower, unless you have a computer with hardware tensor-math acceleration, which costs 10x more because of the chip famine?
And then, suddenly, those local models cost an absolute bomb to license, because the companies that bought up the wreckage of the original model creators are trying to recoup their spend?
Meanwhile the company is being hit by nuisance litigation from people whose code the bots plagiarised, or customers who are annoyed it doesn't work?
There are so many ways all this stuff can just go away.
>And what happens when the price goes up by an extra zero on the end?
>And then another one?
Well so far the price trends towards going down by the zero at the end. Inference isn’t expensive, there’s a whole laundry list of providers to choose from. It’s training (for everybody) and salaries (for US labs) that are expensive.
>and you have to switch to using local models?
Many companies are interested in that, if for no other reason than to avoid uploading secret sauce to we-totally-dont-train-on-your-chats-pinky-promise API endpoints. A mid sized company can cough up $500k for dxg b200 which will be useful for years and years and the only ongoing cost is electricity. Put glm 5.3 on it and it’ll zip along for a number of employees at the same time.
>And then, suddenly, those local models cost an absolute bomb to license, because the companies that bought up the wreckage of the original model creators are trying to recoup their spend?
How are they recouping anything on a mit licensed model released into the wild? There are plenty of models released by "who?" companies and the cost to download those is zero.
>Meanwhile the company is being hit by nuisance litigation from people whose code the bots plagiarised
Any day now
The doom scenario makes no sense in the race to the bottom that’s happening now. China being the other big entity that’s invested in AI makes all the what-ifs about litigation and plagiarism moot; they will gladly offer everybody inference for dirt cheap, if for no other reason that they’d like it if you gifted them your IP that they will then use to outcompete you with their manufacturing prowess.
The genie’s out of the bag. AI is never going away, and we all need to adapt whether we like it or not.
But what when salaries would increase by factor 100-1000? This would make AI use even cheaper. (About as realistic...)
> And then the cloud stuff goes away because all the vendors go broke, despite the price rises, and you have to switch to using local models?
In this case there will be cheap inference hardware on the market as someone will sell all those assets. They don't disappear when a company goes broke (object permanence).
We could also speculate what would happen if all hyperscalers (AWS, GCP, Azure, Alibaba, ...) would suddenly be broke. Again, about as realistic a scenario.
For example our office is heated using heatpump that has >22C of water heated by equipment as a source.
https://delska.com/about/news-resources/delska-newsroom/pres...
reply