As a gentle reminder, desire paths are evidence of the want and the ability to go in the most direct path. But people without that ability cannot leave a desire path to express their wants.
Do not forget that people with disabilities also have wants, and advocate that desire paths be upgraded so that the desire can be satisfied for everyone.
The brilliance of the McMaster-Carr website is best appreciated when viewed alongside the print version of the McMaster-Carr catalog. As a child, I literally grew up on that bright yellow book, since my parents used it as my booster seat for the kitchen table. It is a thick tome, second only to the thinner Grainger catalog, which became the next booster seat after a few years.
Since your e-scooter has dual steering tubes, I would suggest a lock-holding accessory that attaches to both. One complaint I have with similar lock accessories to the one linked is that they have the lock – which necessarily is made of solid metal – cantilevered out, resulting in a large moment arm. This means during sharp bumps in the road, the unsupported end of the lock will apply a torque to the plastic accessory, which inevitably ends in fatigue and breakage.
Some of this is down to necessity, because there’s no great way to hold onto a U-shaped lock at just one point. And also because the stock accessory for U-locks use this poor design. But in your case, you have two vertical tubes that can spread the load.
I think the ideal accessory in your case would be shaped similar to a wide halyard cleat arranged vertically, so that when the U-lock is opened, the U portion can be slid underneath the lower cleat and then locked to the top of the lock, which slides underneath the upper cleat. The act of locking snugly to the cleat will pin the lock in place while preventing cantilevering and noisy wobbling. Sadly, I’m not aware of such a ready-made design, but perhaps that’s something that a 3D printer enthusiast can help draft.
As for the cargo trailer idea, be aware that weight-and-balance need to be taken seriously for smaller configurations. I’ve written about trailers before – although for moving bikes behind a small automobile – and this is the relevant section:
Even if tongue weight were fine, the arrangement of the bikes on a hitch carrier have their own impact: moment of inertia. That is to say, if six bikes were arranged parallel to the drive axle, they’d have to each be spaced at least 8 inches (20 cm) apart. For six bikes, that means the carrier extends beyond the rear bumper by 48 inches (1.2 meters). And that’s just too much inertia to exert on a small car’s hitch receiver. Any bump that the car drives over would cause the bikes to also bounce, but that bounce then reflects itself due to the long moment arm, which then affects the car again. This is an identical wagging-the-dog scenario as trailers have, but here it’s a vertical wag rather than a lateral wag with a trailer.
In your case, imagine if you had a trailer and then came up to a speed bump. The front and rear e-scooter wheels have suspension, so they can absorb most of the bump as you roll over it. But most trailers don’t, so the trailer will jump up at its axle. If the center of gravity (COG) for the trailer (including payload) is ahead of the axle, then the axle rising will cause a downward force at the hitch attachment to the e-scooter. This is generally desirable, but the hitch and rear wheel must be able to deal with this.
But if the COG is behind the trailer axle, the axle jumping up will cause a lever that tries to raise the hitch into the air. If it’s very forceful, it’ll lift your scooter’s rear wheel up too. This could easily lead to a crash, since all two-wheelers need two points of road contact to be stable. The physics is identical to automobiles pulling trailers improperly, either due to driving too fast or badly loading the trailer.
I don’t want to discourage the idea, but make sure your trailer is properly attached and properly loaded. The reality is that automobiles and trucks are more forgiving because they have lots of mass. But two-wheelers are a lot lighter and need careful attention, since upsetting the wheels will also deprive steering control, which topples all two-wheelers.
For the lock, I’ve seen designs on Thingiverse for 3d printed accessories that would mount the lock body to the stem of the escooter’s tiller (?), so that it doesn’t occupy space elsewhere. One concern I haven’t checked for is whether the lock would rattle too much, which could be a problem for a 3d printed attachment.
For the charger, I’m less certain, but maybe something like a cargo rack would work? I’ve seen a few which fit right above the rear wheel, with enough points to use a bungee cord to hold rectilinear objects in place.
I’m unreliably informed that the absolute minimum amount of liquid to drown a human is 1 liter. That might require a special head-shaped bucket, but it seems plausible.
But out of curiosity, what sort of statistics are you seeing about UK people falling into canals? I know they have canals and people, but I thought the trope was shopping trolleys (USA: shopping carts) falling into canals. Is this a serious issue? Can we find comparable figures from the canal-strewn Netherlands for comparison?
Excellent! Have you also considered posting to !imadethis@lemmy.zip ?
Very nice! But caution: this is very nearly not-dull, which would be a rule violation /s
In all seriousness, is the idea to haul multiple bikes at once? I once considered a bike accessory that would allow me to hoist another bike behind mine, vertically, but that would only work for one bike. From the width of that trailer, it looks like two for-parts bikes could fit, right?
At least here in California, where a moped is still a distinct type that is closer to a motorcycle but isn’t one, an electric two-wheeler above 30 MPH (48 mph) would probably be called an “e-moto”.
Not to say that there’s as much sense in retaining the moped category (up to 30 MPH, up to 4 HP or 3 kW, automatic transmission mandatory if non-electric) than when it was introduced in the 70s, but some folks really do enjoy their mopeds as a middle ground that avoids motorcycle annual registration and insurance, while having access to on-street bike lanes. I don’t snub anyone else on two wheels if they’re operating safely.
I think you’re describing district heating, which works great in places that planned ahead and buried the necessary plumbing so that the waste heat from nearby industrial processes can be beneficially used to heat nearby homes and offices.
The detail, however, is that those industrial processes are diverting the heat to the district plumbing, but if nobody needs heating (eg 40 C summer weather), then they will vent the heat using air cooling to the atmosphere. That is to say, the demand for heating will vary at times, and this is fine because the industrial process can just go back to dumping the heat into the air.
This doesn’t work for AI data centers because the amount of “waste” heat (eg 100+ megawatts) is well in excess of any nearby demand for heating. To quantify demand, I looked to the district heating system of Ulaanbaatar, the capital city of Mongolia, home to 1.67 million people, and the coldest capital city in the world by average annual temperature:
the Ulaanbaatar District Heating Company, encompassing 13,500 buildings with a total connected capacity of 3924 MW
The system serves 60% of the population, so about 1 million people. Where in the mostly-temperate USA could a 4 gigawatt AI data center be located so that it’s right next to 1 million people that need 24/7 heating as though they lived in Mongolia?
Scaling down to a 100 megawatt data center, the demand would be for a population of 25,000 living in essentially arctic conditions. Such places already have district heating, such as in Alaska. So if a smaller AI data center shows up, it just means the existing non-AJ heat source would fall back to dumping heat into the air.
In the end, there are very few places that need heating all year round, but AI datacenters would be producing heat all year round. Even if the heat were used for something outlandish, like heating every square meter of public roadway, that still might not be enough demand to quench these behemoth AI datacenters. And that’s before the cost of building out the district heating system.
We should definitely build district heating systems where they make sense, but building them so AI data centers can exist would be doing the right thing for the most terrible of reasons
TIL finite state transducers. The BurntSushi blog post is now in my browser tab queue. Thanks!
While not strictly biofouling, the marine environment can definitely be affected by introducing hotter water where it didn’t exist prior, in and around the outflow pipe. Seaside nuclear power stations that use seawater cooling need to be mindful to diffuse the heated water over a large area, to minimize the ecological impact. Citation: https://ui.adsabs.harvard.edu/abs/2025EcInd.17012986J/abstract
Very similar problems arise with desalination plants, which I wrote about here: https://sh.itjust.works/comment/14613302
There is almost certainly an impact somewhere, but I don’t have the data to know where it is. My conjecture is that a localized mass of steam would cause convection currents and drive microweather phenomena, especially downwind of such an air cooled facility. I’m not sure rain is necessarily the result, unless there’s a sizable mountain downwind, since although hot air will rise, it might run out of steam (pun intended) before cooling down enough to fully condense out. So it might just be adding a layer of humidity that floats a few hundred meters above the surface.
But even that could be devastating, if said layer blocks natural convection currents over a downwind town or city. It could act as a thermal cap, making that town warmer at night, because heat rising from the city would meet that humid layer and get absorbed by the water. The thermal capacity of water comes into play again, but this time against the city.
Heat energy is a driver for cyclones, such as when the warm, moist water of the Caribbean accelerates air as it approaches the southern USA, and only once landborne does it start to slow down due to drag and losing its energy source. I doubt we’ll ever have an AI-induced hurricane, but in a situation where there’s already an energetic weather event, it cannot possibly help to be adding heat to that situation.
I defer to the meteorologists to say what happens to the local weather and climate, and biologists on what happens to humans and wildlife. But I can’t see it being good, no.
Air cooling is feasible, as evidenced by existing power stations that use air cooling. A lot of newer nuclear generation use water cooling, being sited along the ocean and in the multi gigawatt range. But we can also find examples of inland power stations that have no water connection, and therefore need some massive cooling towers. Here is one in Germany that has a 2.2 GW rating and a 200 meter tall tower: https://en.wikipedia.org/wiki/Niederaussem_Power_Station
This is, as you can imagine, rather expensive to build, but it’s doable. Cooling a coal fire is not substantially different than cooling compute loads in a data center, as it’s all just a matter of moving heat around. Will there be differences due to the base temperature of coal versus GPUs? Yes, since the ratio of input to ambient temperature matters. But on the flip side, this should make it easier to construct, as the plumbing for lower temperatures is simpler.
Mechanical engineers can chime in on feasibility for AI data centers, but seeing as it hasn’t been done, it’s probably still cost related.
Darn, you’re right, the hours fell off in my dimensional analysis. Corrected, although 6.9 hours for a pool isn’t much time for swimming at all.
Other commenters correctly describe the cost analysis for using evaporative cooling, but I’ll add one more reason why it’s the preferred method when water is available: evaporating water can dissipate truly outlandish amounts of heat with very few moving parts.
Harkening back to high school physics class, water – like all other substances – has a certain thermal capacity, meaning the energy needed to increase the temperature of 1 kg of water by 1 degree C. The specific thermal capacity of water is already quite high, at 4184 J/(kg*C), besting all the common metals and only losing to lithium, hydrogen, and ammonia. In nature, this means that large bodies of water are natural moderators of temperature, because water can absorb an entire day’s worth of sunlight energy but not substantially change the water temperature.
But where water really trounces the competition is its “heat of vaporization”. This is the extra energy needed for liquid water to become vapor; simply bringing water to 100 C is not sufficient to make it airborne. Water has a value of 2146 kJ/kg. Simplifying to where 1 kg of water is 1 liter of water, we can convert this unit into something more familiar: 0.596 kWh/L.
What these two physical properties of water tell us is that if our city water comes out of the pipe at 20 C, then to get it to 100 C to boil, we need the difference (80) times the thermal capacity (4184 J/kg*C), which is 334,720 J/kg . Using the same simplification from earlier, that comes out to be 0.093 kWh/L. And then to actual make the boiling liquid become a vapor (so that it’ll float away), we then need 0.596 kWh/L on top of that.
Let that sink in for a moment: the energy to turn water into vapor (0.596 kWh/L) is six times higher than the energy (0.093 kWh/L) to raise liquid water from 20 C to 100 C. That’s truly incredible, for a non-toxic, life-compatible substance that we can (but should we?) safely dump into the environment. If you total the two values, one liter of water can dissipate 0.69 kWh of energy per liter. Nice!
In the context of a 100 megawatt data center (which apparently is what the industry considers as the smallest “hyperscale data center”), if that facility used only evaporative cooling, the water requirement would be 144,927 L/hour. That is an Olympic-size swimming pool every 6.9 seconds hours. Not nice!
And AI datacenters are only getting larger, with some reaching into the low single-digits of gigawatts. But what is the alternative to cooling the more-modest data center from earlier? The reality is that the universe only provides for three forms of heat transfer: conduction, convection, and radiation. The heat from data centers cannot be concentrated into a laser and radiated into space, and we don’t have some sort of underground granite mountain that the data centers can conduct their heat into. Convection is precisely the idea of storing the heat into a substance (eg water, air) and then jettisoning the substance.
So if we don’t want to use water, then we have to use air. But for the two qualities of water that make it an excellent substance for evaporative cooling, air doesn’t come close – 1003 J/(kg*C) and no heat of vaporization, because air is already gaseous. That means we need to move ungodly amounts of air to dissipate 100 megawatts. But humanity has already invented the means to do this, by a clever structure that naturally encourages air to flow through it.
The only caveat is that the clever structure is a cooling tower, and is characteristic of nuclear power stations. It’s also used for non-nuclear power station cooling, but it’s most famous in the nuclear context, where generators are well into the gigawatt range. Should AI datacenters use nuclear-sized air cooling towers instead of water evaporation? It would work, but even as someone that’s not anti-nuclear, the optics of raising a cooling tower in rural America just to cool a datacenter would be untenable. And that’s probably why no AI datacenter has done that.
To be abundantly clear, I’d rather not have AI datacenters at all. But since the question was why water consumption is such a big deal, it might be best to say that it’s a physics problem: there isn’t any other readily-available way to provide cooling for 100+ megawatts, without building a 100+ meter tower. Water is always going to be cheaper and more on-hand than concrete.
License is the legal instrument which makes open source software/hardware/silicon possible, describing precisely what rights are granted or retained. The term “open source” usually means the definition propounded by the Open Source Initiative (OSI) but sometimes not in certain contexts. At the very minimum, an OSI-compliant open source license will allow any distribution of the software without having to seek additional permission from the author, must be accompanied with access to the source code, and the software does not come with provisos outright prohibiting its use for certain endeavors.
That last point is about the “use” of the software, and is a crucial distinction between “open source” and “source available”. To have source available means the source code can be examined, but usually cannot be compiled. An open source license explicitly allows all uses, but possibly with additional obligations. For example, the AGPL license allows software to be used to run a server, but creates an obligation to provide the server source code to all users that connect. Whereas something like the MIT 0-clause license has zero additional obligations, while allowing the broadest use. When a license is both Open Source and allows free use, it is known as a FOSS license.
The exact verbiage of a license are the domain of lawyers, being a legal document. But the choice of license is down to the software author or corporate owner, and is a multifaceted consideration, including marketability, compatibility with other software, and whether it’s more important that the code gets used or that it forever remains available.
The latter is the major battleground for advocates of permissive versus copyleft licenses. Some software (eg reference cryptographic algorithms) have the priority that the absolute most number of people should use them, so a permissive license makes sense. While other software (eg desktop 3D rendering suite Blender) have a priority that nobody can ever take it private by adding proprietary-only features.
Choosing open source is easy, but choosing a license to effect that choice can get tricky. For authors publishing their software, the choice may very well change the course of history (ie Linux GPL-2). For consumers or businesses using software, the license dictates how changes can be distributed.
This blog post comes to me at an interesting time, for I’ve been gathering info to rebuild my router using FreeBSD. Specifically, I bought a hard-copy of The Book Of PF, 4th Edition, for configuring PF for routing and firewalling. Like with all good firewalls, the PF rulesets start with blocking all traffic. But unlike the VyOS-based rules used by my outgoing Ubiquiti router, PF does not implicitly include rules for common use-cases, such as enabling hairpin NAT for Legacy IP. Nor does the syntax assume that rules are only for inbound, as the shortest syntax will actually apply a rule in both directions on every interface.
To that end, one of the tenants for configuring a PF firewall is to also filter outbound traffic, as a matter of: 1) asserting control over the network, and 2) implementing the principle of least privilege. I can reasonably accept that my home’s guest WiFi network should be fairly free flowing for outbound traffic, but that shouldn’t apply to my IoT VLAN. Quite frankly, my IoT VLAN only allows outbound connections to four specific NTP servers hosted by ntp.org, because my thermostat has a badly-designed real-time clock and I refuse to allow network access for devices that historically never needed it.
Before containers, firewalls implemented the DMZ idea, where any host that runs an externally-accessible service would be within the DMZ, to prevent infiltrating the broader LAN if something goes wrong. Your solution achieves a sort-of DMZ, but does it at the Docker host. Whereas a true DMZ would segment the rest of your network off, so as to further reduce risk, since iptables is the only line of defense.
That said, zooming out, this caught my attention:
The breaking point came when I wanted to host Gemini FastAPI, a project that wraps Google’s internal Gemini API into an OpenAI-compatible interface, useful for using your Gemini Pro subscription outside Google’s walled garden. The catch: it needs your browser cookies, which means full access to your Google account.
The very premise of Gemini FastAPI seems flawed to me, if it’s trying to create a wrapper when Google clearly does not want that to exist. The challenges that you observed, such as the brittleness of IP allowlists, would suggest to me that the overall endeavor is going to be brittle, by Google’s design.
To be clear, that doesn’t mean you shouldn’t pursue this, in the same way that yt-dlp exists for the legitimate use for accessing YouTube. But what both yt-dlp and Gemini FastAPI will never escape is that they only exist because Google hasn’t cracked down on it further. When every indication is showing that this is the road with even more trouble beyond the next curve, is this what you want to invest time and effort into? There are other platforms and protocols that replace YouTube, or at least minimize one’s dependency on a clearly antagonistic host.
At bottom, I think the question is whether connecting to Gemini is really worth all of this trouble, when they evidently don’t want you to do this, and it adds yet another dependency upon Google. Even if you believe Google is 100% benevolent and their lack of a built-in support for using Gemini externally is just a minor oversight, you will have to pick which services you will base your own infrastructure upon. This is, after all, c/selfhosted.
The premise is good, but the linked article is too short to explain why protocols encourage decentralization, which protects against authoritarism, censorship, and promotes bona-fide free speech (not to be confused with “BuH mAh FrEe SpEeCH!” morons that only like free speech when it agrees with them and don’t when it doesn’t).
For a more lengthy discussion, which includes Internet history, the legacy of the USA’s Section 230 of the CDA and how that impacts the modern web, and what precisely a protocol should avoid doing to successfully achieve the goal of practical decentralization, Mike Masnick’s 2019 paper “Protocols, not Platforms” is particular apt.
Yes, I know I’ve mentioned him a number of times in my comments, but there aren’t too many people who are abreast of technologcal history, the legal framework surrounding the internet, and are skilled writers to condense into words the necessary clarity upon which to build an internet that works for everyone, not just the rich or few.
As a note, BlueSky was directly inspired by his paper and he now sits on the board of BlueSky. Is that antithetical to his 2019 paper? I don’t think so, since commercial success of a protocol is how it has staying power: Amazon’s S3 API, email’s SMTP, and QUIC are all examples of protocols where everyone benefits by their ubiquity, but they had to be commercialized first, by the likes of AWS, AOL and CompuServe, and Google. BlueSky’s opponent is not another protocol like ActivityPub, but rather they challenge the platform formerly known as Twitter. The very existence of a bridge between the ATmosphere and the Fediverse proves that platforms are the real enemy, and we all need to keep that in mind.
No enemies to the left.
There might exist one, but it probably doesn’t haven’t much volume or isn’t well federated because few other instance want to interact with spammy, problematic, high-complaint instances.
What you’re describing might be a Level Three in the moderation speedrun: https://www.techdirt.com/2022/11/02/hey-elon-let-me-help-you-speed-run-the-content-moderation-learning-curve/