Ángel
@angel@triptico.com
Location: 40.4235492,-3.6617828
103 following, 221 followers
most #mobilek fans don't know about his son who appeared briefly in an episode of Simone
Japanese Jesus did invent logging off and turning off the computer though.I sometimes turn off my computer! Thank you, Japanese Jesus!
I’m taking these to @cebulacamp all money go to:
You can also buy it online here: https://ko-fi.com/s/0850ff2a1d .
You can also bootleg it if you don’t want to give me money, it’s CC0.
You can read it online if you don’t have money, it’s free: https://kamiokan.de/entropysrotoscope/issue1 .
#entropysrotoscope #kamiokande #unix_surrealism #comic #art #noai #fediart #mastoart #cebulacamp
RE: https://donotsta.re/objects/bb14e20a-1b37-45c7-99af-e30c8686a1ce
You can now buy a printed version of Entropy’s Rotoscope #1, available in A4 and A5 format.
Get it either on ko-fi: https://ko-fi.com/s/0850ff2a1d or send an email to eigengrau <at> kamiokan <dot> de or just meet me on some event, I will take these to cebula camp and c3 (by c3 I hopefully will also bring issue 2).
For those in the UK puzzled why we Americans are so distraught over the passing of Dolly Parton: try to remember how you felt when you heard Queen Elizabeth had died. Then imagine how much worse it would have been if Queen Elizabeth had ever helped anyone
"L'erba cattiva non muore mai"In Spanish we say "mala hierba nunca muere", which means exactly the same.
But, really, what is happening, the ratio of good people / scumbags dying is alarming.
As a footnote to this, there *are* animals with absurd regenerative powers: Salamanders can regrow limbs, as well as pretty much any non-lethal organ damage. Virtually anything that doesn't kill a salamander ... doesn't even make it stranger, it just makes it hunker down for a while and regrow. This is because cells at injury sites can actually de-differentiate into stem cells, and then form a new limb using exactly the same process as in embryonic development.
This is likely to be an ancestral ability! But amniotes (the shared lineage of reptiles, birds and mammals) appear to have lost it, in place of a much more aggressive and complex immune system (which would attack and destroy de-differentiated cells).
Frogs are a strange halfway example: In adulthood their healing (and immune response) is a lot more like that of a reptile or mammal than like that of a salamander - their cells lose the ability to de-differentiate, but instead develop the ability to rapidly close a wound by forming scar tissue. As tadpoles, they regenerate just as well as salamanders.
The good news: we're seeing more article pitches lately for LWN.
The bad news: yep. They're almost certainly LLM-generated from people clearly hoping they can low-effort a quick (small) payout.
This, my friends in the LLM-enjoying community, is just one reason why so many people really have strong anti-LLM feels.
Because for every "I only use LLMs responsibly" person, for every "I just use LLMs for personal projects" person, and for every "I know my stuff and can review LLM output" person, there is at least one prompt jockey looking to use LLMs for quick wins without any concern for the people who have to wade through their slop.
And, I don't care how much LLMs improve, it *is* slop when it's just some person shoveling in prompts and hosing the output at other, unsuspecting and unwilling, people.
i love seeing creative qr code designs, so i made this guide explaining what tricks you can (and can't!) do with qr codes while still keeping them very much readable
have fun and make cool stuff!!
ADDRESSING THE ALLEGATIONS
if you enjoy my art, please consider supporting it financially.
https://liberapay.com/analognowhere
https://analognowhere.redbubble.com
Thank you!
THEODORE ROOSEVELT SHOT BY CRANK IN MILWAUKEE STREET
#content_review #unix_surrealism #fediverse #loops #mastodon #lemmy #art #mastoart #javascript #cats #snac
The following is a valid DOS COM executable that prints "HELLO" in the lower right corner of the screen.
You can copy these emoji into a text editor, and save it as EMOJI.COM. it should be 141 bytes.
It will run in DosBox-X, with the following options:
cpu cputype=8086
machine cga
🐸☺️🐰🐎♐🗃️🧯🧯🧯🐮💗🦮♐🐰🐹🗃️🧯🧯🧯🧯💗🪗🧯😗🧮😗🧮😗🐮😪😔⭐
may god have mercy on my soul.
David Chisnall (*Now with 50% more sarcasm!*) » 🌐
@david_chisnall@infosec.exchange
By the bubble, or by the bubble bursting? 'AI' has had little impact on most industries, which is one of the major signs that it's a bubble: if it were significantly improving productivity outside of a handful of niche cases there would be some possible justification for the $3T sunk into it.
The bubble bursting is a very different story. My back of the envelope calculation on the US stock market was that about $30T was overexposed to the AI bubble. I've seen people who actually know what they're talking about with numbers between $15T and $40T, the consensus seems to be around $20T.
That's somewhere between a quarter and a half of the total value of the US stock market that has a significant chance of evaporating when the bubble bursts. Even if it's 'only' $15T, that's going to cause an enormous liquidity crunch. Any business that's dependent on being able to get loans to grow or on customers having free cash to spend is likely to be affected.
For reference, the Wall Street Crash, which triggered The Great Depression, involved around 50% of the value of the stock market being wiped out in the first crash and a total of 89% over a bit more than two years, but that was in an economy where far less was linked to the stock market (for example, few people had pensions that were linked to the stock market).
My question is not how bad the crash is going to be, it's whether the rest of the world can sufficiently firewall the USA so that the crash is mostly contained there. Preventing contagion when there's a massive liquidity crunch requires international cooperation. Trump is incapable of cooperating for the common good, or even for the good of the USA: he'd happily let the US economy burn if it made him and his friends a few billion.
David Chisnall (*Now with 50% more sarcasm!*) » 🌐
@david_chisnall@infosec.exchange
@briankrebs The amazing thing is: none of this is even slightly hidden. Everyone investing in it knows it's a bubble. None of his warnings are even slightly surprising to anyone who has been paying attention for the last two or three years.
But that doesn't matter because you can make money in a bubble as long as you get out soon enough. I posted about this in another thread, but a lot of 'investors' are 'gambling with the house's money':
They jumped in early. When things in the bubble doubled in value, or maybe a bit more, they cashed out their initial investment. After this point, there is no way that they can lose money. Maybe they invested $10 M in NVIDIA in early 2016 and sold $10 M of NVIDIA in late 2016, still holding $10 M. By 2024, it was an obvious bubble. If they sold half of their stock then, they'd be $350 M up. No matter what happens with the bubble, they've made $350 M in eight years with $10 M in seed capital. That's over a 45% average annual RoI. If the bubble continues to grow and they cash out at the right time, they may make another half billion or more, but if the bubble pops so badly that NVIDIA goes bankrupt, they still made $350 M.
This is the opposite of the 'betting on the margin' that smaller investors do before catastrophic crashes (the Wall Street Crash in the 1920s and Korea last week), where you borrow against your existing investment and invest more based on that, but often both are happening at the same time and these are the people funding the big payouts to the former category.
David Chisnall (*Now with 50% more sarcasm!*) » 🌐
@david_chisnall@infosec.exchange
@junesim63 There are a few things I disagree with in this:
First, a couple of small nits, it says:
The big tech companies have spent $1 trillion on capital investment since the start of the AI boom
That's a very low estimate, most estimates are closer to $3 T.
First, there’s too much competition among US LLM providers. It’s not just ChatGPT and Claude now – Gemini and Copilot are nipping at their heels
There's some conflation of models and end-user products here, which is important because it hides the shape of the supply chain.
But then we get to:
And the world will be left with hundreds of massive data centres without enough customers. Compute will become extremely cheap – just like accessing the internet did after the telecoms companies spent billions competing to lay fibre optic cables in the 1990s.
Accessing the Internet didn't immediately get cheap. Companies laid a lot of fibre. This was very expensive to do and had low returns. These assets became available cheaply. Those assets were useful because it's easy to light up dark fibre. The equipment at the ends that you need to provide (and which can be a newer technology than was available when the fibre was laid) is much cheaper than digging up streets or laying very long runs of fibre between cities. And most of that fibre is still useful 20+ years later, with an expected lifespan of 25-50 years.
'AI' datacentres are not like this, for several reasons:
First, they are very expensive to operate. They're measured in GWs: even if all of the capital is a sunk cost that you can write off, the cost of simply turning them on is enormous. That sets an absolute lower bound on the price. And, because they're such massive grid consumers, they're likely to be blocked from that much consumption as soon as the hype wave's marketing shield wears off.
Second, the GPUs wear out. The average lifetime for NVIDIA GPUs in these things is estimated at three years. So even if you buy one for pennies on the dollar and can afford the electricity, it won't stat working at maximum capacity for long. And those GPUs are aggressively tailored for specific kinds of ML workload. Even if they're basically free, they are unlikely to be the most cost effective way of running any other kind of workload.
Finally, these datacentre designs are very specialised. These kinds of machine-learning workloads are incredibly memory-sensitive. This means that you need to put very fast memory next to very dense floating-point compute to get performance. This, in turn, means that it isn't just enough to have a lot of power, you need a a lot of power per rack. That places a lot of strain on cooling and makes it very expensive to cool. If you're building a datacentre for any other workload, that's unnecessary. Land is not that expensive in the places where they're built, so you build at a much lower power density, which reduces your cooling costs.
It's not at all clear that refitting an 'AI' datacentre to be a useful datacentre will be cheaper than building a new datacentre from scratch. If you visit the outside of Taipei, you can see the history of semiconductor fabrication because it's always been cheaper to build a new factory than refurbish an old one. 'AI' datacentres may well end up like this.
The boom will get going again after the bust – with valuations returning to more sensible levels. A few of the massive tech companies will buy up the remnants of the others, leaving the market even more concentrated.
There are a lot of assumptions here. Currently, we are seeing that the market for these things is around 1% of the cost of building and running them. Training an LLM costs an enormous amount. Companies are basically eating those costs because they expect to be able to make it up by charging for access to the models. And they're also losing money providing the models as a service because they're expensive to operate.
After the bubble bursts who will fund training of new models? Old models gradually use utility (people are already complaining about LLMs that don't know about anything that happened after 2024 because that's the end of their training data set). If inference is not bringing in as much money as it costs to operate the systems, who will continue doing it?
And, when the 'it will massively improve your economic competitiveness' claims are proven to be lies, will governments keep giving companies a free pass from massive copyright infringement?
If you want to claim that companies will keep selling these things after the bubble bursts, you need to answer these questions.
The economics of LLMs are terrible. They have high costs to train (capex) and high costs for inference (opex). The most successful things in the market generally have a different mix:
High capex and low opex means ahigh barrier to entry for new competitors but then increasing profits the larger you are. Microsoft, Google, and Amazon's core products all look like this. The best products in this case have per-unit opex that drops as you increase the number of units, because even a new company with the same amount of up-front capital as you isn't able to match your price without losing money until they have as many customers as you.
Low capex and low opex means things become cheap commodities. They will often become ubiquitous, but generic. It's hard to gain a dominant market position because it's trivial for a new competitor to pop up. A lot of consumer goods look like this.
Low capex and high opex often survives as boutique services. Things like Michelin-starred restaurants: easy to create (lease a building), expensive to operate (hire some very expensive staff).
But there are very, very few examples of things where the capex and opex are both high becoming major parts of an economy. Private jets, for example, are in this class and they're a tiny niche in the corner of travel.
Wealth and power will become even more concentrated, as the largest tech companies buy up their defunct competitors, before leveraging their control over the technological infrastructure that most other businesses require to function
I suspect the latter part of this is misdiagnosed. Big tech firms are massively over leveraged at the moment. NVIDIA has loans that amount to more than its pre-bubble valuation and its current valuation is predicated on completely unattainable growth. It makes sense only if you imagine that it's a company that will, over the long term, be able to sell more than 10x as many chips as Intel at its peak. When these companies' stock prices collapse, they're going to find it very hard to raise money for anything and they won't be able to buy companies with their stock (that's partly why they're on a buying spree now).
The people who will make money are the people who have other liquid assets. Either cash, or things like real estate that they can borrow against as safe assets when the bubble bursts.
my fellow european sibs, here is my unbiased review of w.eu, i mean w.social, i mean wsocial.eu 👍
#eu #wsocial #w #unix_surrealism #mobilek #phone_bad_book_good
Entropy’s Rotoscope Issue I; new page everyday starting today: https://kamiokan.de/entropysrotoscope/issue1
RSS: https://kamiokan.de/entropysrotoscope/rss.xml
Support me on ko-fi: https://ko-fi.com/j_g00da
CC0 / Public Domain
@RootMoose snac is great. Mastodon is good, but yeah, it's big. littleFedi will be added to the list as soon as it'll be ready 😉
There are nice things in this "timeline", so let's find opportunities to be grateful!
Storage has grown to 1.7gb, memory and cpu utilization are still negligible.
This is easily the lightest weight fedi host I have run to-date, and I've run just about all of them.
I'm still hestitant to move to it full time, but it is pretty appealing.
Conclusion: people will adapt to whatever timezone they like, as absurd as it may sound.
Today is Artificial Intelligence Appreciation Day for some reason, so everyone please celebrate appropriately.
On 10 March 2021, I had only just fallen asleep when my phone started buzzing. Then another notification, and another. In a matter of minutes, 142 of my servers went up in the clouds. And not the cloud-computing kind.
Most of them were physically going up in a column of smoke in Strasbourg.
My wife looked at me and asked if I wanted a coffee. I nodded. It was going to be a very long day.
At EuroBSDCon 2026, I won't be giving a theoretical lecture on high availability. Instead, I’m going to tell the raw story of that night: the emergency recovery, the architectural choices that actually saved us, and the ones that crumbled under pressure (because we rarely talk about what fails).
Most of all, I’ll explain why that night changed my perspective, and why I’ve come to see BSD systems not just as operating systems, but as essential, practical tools for building simpler, more resilient infrastructure.
The official schedule is now live. If you want to hear a real-world post-mortem, join me on Saturday, 12 Sept at 11:15 (Room D.0.02).
EuroBSDCon Full schedule: https://events.eurobsdcon.org/2026/schedule/
See you there! ☕️
#FreeBSD #NetBSD #OpenBSD #DragonFlyBSD #RunBSD #EuroBSDCon #SysAdmin #SelfHosted #IT #EuroBSDCon2026 #BSDCon
I Did Not Kill Stanley Lieber: How to draw (with 9front)
The penultimate paper on paint(1) and the 9front art machine.
https://triapul.cz/automa/i_did_not_kill_stanley_lieber
#unix_surrealism #plan9 #9front #art #guide #computers #oldcomputerchallenge
A rough analogy:
Threads → Fox News
Bluesky → The Atlantic
The fediverse → zines stapled to a lamppost outside your favorite queer and/or communist bookstore
It’s not Tuesday yet, but it will be soon.
And I want to thank @grunfink for creating and maintaining snac. Tomorrow I’ll talk about FediMeteo at DevConf, and it would never have come to be if it weren’t for snac and for the help the author gave me in fixing some things to optimize its use.
True Open Source, made with passion, by people who do things for the love of the things themselves.