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@wraithe@mastodon.social
2026-05-19 20:29:12

My actual reaction:
bsky.app/profile/did:plc:7exlc

Video clip from “Highlander”, showing the Kurgan walking out of a dive hotel, about to turn around and choke the front desk clerk for speaking to him
@azonenberg@ioc.exchange
2026-07-20 05:08:58

Just set up some new IAQ monitoring stations around the house. Still want to put one in the bedroom to see how stuffy it gets at night with the door closed, but I only had four units so this is what I started with.
Particle counts are Sensirion SEN5x, CO2 and most other atmospheric data SCD4x.
Haven't done any kind of zero cal on the CO2 and they've been sitting around idle for a while, so there's probably a bit of offset that will need to be corrected - the one on th…

Graphs of air pressure, CO2 concentration, and relative humidity in the lab, office, living room, and back porch. Not enough history to see much in the way of trends yet
@jake4480@c.im
2026-04-20 01:17:08

In Rogue-FP on Steam, EVERYTHING is made of letters. When you kill a monster and come back later, there will often be flies (capital 'F' letters) flying around the remains 😂
#Rogue #Steam #SteamDeck

A dead emu in Rogue-FP and flies around its corpse, shown as capital 'F's
@jonippolito@digipres.club
2026-06-17 14:51:47

Another way to see data centers aren’t just about AI: even by EPRI’s most generous forecast, AI accounts for less than half of the load added since ChatGPT. You may not like what the rest of the buildout is being used for.
blog.still-water.net/what-if-d

Pie chart titled “Loads on data centers built since ChatGPT.” It shows AI workloads accounting for an estimated 35% (conservative) to 44% (liberal) of load, while non-AI workloads account for 56–65%. The chart emphasizes that a majority of load on recently built data centers is still non-AI, despite AI representing a substantial share. Source: EPRI estimates (2024, 2026); calculations by Jon Ippolito.
@hex@kolektiva.social
2026-05-19 07:09:57

Logistics in the technical sense (part of supply chain management) is a subset of logistics in the vernacular sense ("the handling of the details of an operation"). You can explore this second and more general sense, and thereby build an understanding of the first and more technical sense, by iteratively asking the question, "how does one make that happen" and follow questions from there.
A big part of organizing is figuring out the (vernacular) logistics (and helping others figure it out). You want to organize a seed swap? Ok. How does one make that happen? Well, you need seeds, people, a place, and perhaps a time. How does one make that happen? You can forage seeds or you can buy seeds for a garden and swap extras. How do you get people to come? Well, figure out where you want people to come from and choose an accessible place. What's the easiest thing to do? Get people from your neighborhood. How does one make that happen? Well, maybe put up flyers. How does one make that happen? Well, print them on your printer if you have one, or at a library, then go post them up. Etc.
Keep asking questions until you either find a roadblock that you can't find a way around, or you find things you can do yourself (one of those things you can do yourself is asking friends to help).
If you practice the exercise of thinking about how things happen, you can start to find things that you can do yourself. You can start to understand what exists now, and you can imagine what's possible. By thinking about logistics, you can figure out how to replace things when they collapse or are dismantled. You can also identify things that can't easily be replaced, and try to figure out alternatives.
This practice is good for figuring out how to build, but it can also be a valuable practice for figuring out how to resist. Concentration camps and ethnic cleansing also require logistics. Mass displacement means moving people. How does one do that? People are generally going to be moved in planes or buses. How does one do that? Well, people get loaded on to planes or buses in specific places. Planes and buses need fuel. Planes are fueled at their airports, which may well be the same places where people are loaded on to them. There is a fuel depo and a fuel truck that makes flying people out of a specific place possible. How does the fuel get to that fuel depo? Well, that fuel is probably also delivered by truck. Someone drives those trucks. Someone fuels those planes. Someone clears the planes for takeoff. Someone fuels those busses. Someone drives those busses. And so on.
Logistics networks can be highly complex. The more complex the operation, the more possible points of failure and more possible points where pressure can be applied, where operations can be disrupted. Ethnic cleansing is a complicated operation. The logistics of disrupting complicated things tend to be much less complicated than the logistics of the complicated things themselves.
The Right has exploited this fact for a long time. Centralized social services are logistically complex. Public infrastructure is logistically complex. By destroying these things, they can loot public resources by privatizing the infrastructure and functionality.
But the things that support the Right are even more logistically complex. Oil, cars, AI data centers, internal paramilitary, these are extremely complicated and fragile. There are numerous pressure points, all of which can respond to numerous strategies.
If we want to win, we should reduce the influence of politics over the things we care about. We should focus on building distributed mutual aid networks that don't rely on state funding and aren't subject to the whims of politicians. This is also known as "dual power." That is, creating counter-institutions outside of the dominant political system. The Right already does this in the form of churches and corporations.
As we reduce our complexity, we can then press our complexity advantage against the things for which the Right *needs* the state: the apparatus of violence needed to maintain capital and enforce the dominant order.

@stiefkind@mastodon.social
2026-06-17 11:07:29

Strolling through my book shelfs, I found »The Holy Grail of Data Storage Management: What Every Enterprise Needs to Know to Solve Its Data Deluge« by John William Toigo.
This book was published in 2000, and working in and around computer storage industry since 1998, I pretty much doubt the deluge is solved yet. #vintagecomputing

@mia@hcommons.social
2026-06-15 12:52:01

Last week I was reminded about this super-accessible article on 'The Seven Principles of Data Feminism' by Catherine d’Ignazio and Lauren Klein - especially for those who never got around to reading the book! responsibledata.io/anniversary

@azonenberg@ioc.exchange
2026-06-17 21:03:36

Simulations of the three BGA fanouts I've been comparing are done.
I'll probably wait until I have a few other things finished to close it out and film the video I was panning.
But in short... insertion loss behavior of the two routings is very close, within half a dB or so almost the entire path and criscrossing a few times. The "good" is actually about a dB worse at 35 GHz but this is beyond the 3rd harmonic of the data rate so I don't really care.
T…

ngscopeclient screenshot showing three insertion loss plots and three TDR traces

The no-cutouts version (green) has massive ripples in the S21 plot from reflections reaching almost -8 dB at 35 GHz and huge corresponding dips in the TDR response, down to almost 80 ohms at the BGA launch and 72 at the ARF6.

The old-fanout version is significantly improved, with the BGA launch dip down to 90 ohms and almost no dip at the ARF6, but has a wide jump to around 112 ohms in the escape routing area whe…
@wraithe@mastodon.social
2026-05-14 15:19:57

The only good thing about that David Roberts post is that it’s spurred a number of really smart folks to slap it around and provide some really good threads.
bsky.app/profile/did:plc:hko3e

@jonippolito@digipres.club
2026-06-11 12:25:43

If AI accounts for only 20% of data center use, why is it the justification for nearly every new data center? I did the math and suspect Big Tech is using AI as a cover for unpopular uses like surveillance advertising.
blog.still-water.net/what-if-d

A chart showing a log-log scatter plot that shows big tech is spending far more on AI than it earns from it.  The x-axis shows annual data-center and compute spend in billions of dollars on a logarithmic scale from $25B to $300B. The y-axis shows AI revenue run-rate in billions of dollars on a logarithmic scale from $0.35B to $320B. Seven companies are plotted as purple dots. xAI sits at $31B spend and $0.5B revenue, the lowest revenue point. Oracle is at $60B spend and $12B revenue. OpenAI is …