Steam can absolutely be replaced if they fuck up. The thing is, they don't. Even GOG (which is my prefered platform for oldies) and itch.io (which is my prefered platform for indies), which are smaller and thus have less bloat and should iterate quicker didn't manage to install interesting feature Steam has added over the years. Remote play especially, as someone who bought in ~2019 128GB or RAM and a titan RTX (yeah, bad investment at the time, though i'm happy now when i see the cost) for his server and want to play on another computer, on a different room, was the best thing that ever happened to me.
And of course as a primary 4X multiplayer gamer, the "join game" button on steam profile is something every platform should look to implement (once they have a correct mod workshop equivalent).
I don't want to argue here, but once models are trained, using them is quite cheap. Also in the last few months most improvements I've seen are in the smaller sized models, which might make using models even cheaper.
There's this weird tension where small models are getting a lot better, but the gap between the frontier and "what I can run on my gaming GPU" at home isn't necessarily getting smaller. That said, Qwen-3.8-27B-Q3 runs on my 9700 XT and performs well enough for tool calling in agents, which is a critical floor in local model performance imo.
Do you use qwen for any coding? Do you make a frontier model orchestrate it? Are you running with llama.cpp? Sorry for the barrage of questions, but I've been interesting in local AI for a while, yet I've struggled to set up anything usable.
My Qwen testing has been with Hermes trying to do mundane (to me) things that hosted models understandably refuse to do, even open-weight ones like Deepseek V4.1 Flash. Example: I tried to get it to find a torrent for $tvshow and add it to qbittorrent (connected to hermes via MCP already). It certainly tried and I think frontier models would have done better. My biggest issue was context space more than anything else. I had to drop down a quant level to increase it to 128k. On 64k it was constantly compacting.
If the models are cheap to run, while good for customers, isn't that a problem for hyperscalers and all the investment poured into the AI data center build out?
No. If models become better, the natural expectation is for hardware to get more valuable, not less. (The hardware that was previously able to achieve X can now do 2X. Why would that make the hardware worth less?)
Likewise if models become commoditized, it's raising the value of the existing hardware (you'd expect the hardware owner to keep a bigger slice of the surplus when that's the scarce component).
For model improvements to be bad for the value of hardware, what you'd need is for demand for intelligence to be inelastic. But everything we've seen so far suggests that is not the case: the demand for intelligence (whether human or artificial) is highly elastic both in price and in quality.
its a false equivalence.... the dotcom boom wasnt just a fibre rollout, it was all the internet company startups that were overpriced and crashed. no doubt some of the hyperscalars will get busted out, but the models and LLMs are here to stay. just like dot com websites didnt disappear after the dot com crash, neither will AI transformer models
That's a big issue in my team. We cannot really review tests manually, we already have too much just reviewing the code. And even then, sometimes the 'is this change necessary' question is forgotten or ignored (happened to me 20 minutes ago) because I an tired of fighting my junior+AI. I try to make AI refactor the tests every weeks ande that's it.
I use soverin since I moved from gandi 3 years ago. I didn't had any problems in this time, but I also didn't registered my domain with them just in case.
I don't follow the car industry but I've worked on a project circa 2018 for all European manufacturers to help provide parts 15 years after the car was sold (I provided the Hadoop clusters and some of the predictive algorithms to try to predict which car parts will fail and how many will be needed over the car Lifetime.) BOOST4.0 or something. I don't know where it ended up going.
How stiff can you make the resin with those 3d printers ? Probably not as much as carbon fiber, but how does it hold against aluminium or fiberglass? Also, can you do composite fibreglass/resin with 3d printers ?
Surprisingly complicated question. Most hobbyist grade machines are low powered and can only cure resin with pretty poor mechanical properties. Industrial resin printers can actually make incredibly strong parts.
The studio 1 can apparently print in Formlabs Tough 1500 which is a decent strength resin. It’s noticeably better than the average “ABS like”.
Resin prints are also isotopic (unlike composites and fdm prints) which has a lot of advantages for mechanical parts.
Asking if resin prints are strong is a bit like asking if metal parts are strong; it really depends on the metal or resin being used
I think you misread. The article state tesla Semi has had 2 fire in 2 years. The first one because the truck hist stuff and left the road in Nevada, the second (this one, the subject of the article) in California for unknown reasons. This is relevant because the Tesla semi fleet is small (86 vehicles 2 years ago, probably below 500 atm) and because battery fire are hard to stop, so we want to know what caused it. If EV fire last 10 time longer than diesel fire, but happen 10 time less often (we need more studies but it seems this is the initial consensus), this is not really an issue, but if they happen more often, we _need_ to know why and fix it.
Also i don't want trucks to catch fire everytime they hit a cow or a boar, the roads around where i used to live would be consistently closed :/
This vehicle was part of a manufacturer-owned highway fleet. That means it received proactive maintenance by trained personnel on a regular schedule, with full access to engineers for diagnosis and OEM replacement parts, and ran on good roads in the mild California climate. It's practically pampered compared to oilfield haulers, especially the ones that live long enough to be auctioned off. They're not comparable.
As an aside, some of the vehicles I've worked on serve in oilfields and I'd be horrified to discover 1% of them were catching fire annually.
For some other unscientific findings, that'd suggest 5 vehicle fires per year just from residents of my apartment complex. I've seen 1 in 8 years, and that was arson.
The fires/mile ratio seems like a good idea (skewed a bit by relative driving habits of professional vs typical drivers). It turns out those numbers are all pretty readily available. All miles from all sources (including semis) tally to 3.3T/yr. All car fires from all sources (including crashes, so in the context of semis spontaneously combusting these numbers will make the 1/100 rate look even better than it should be, though separate sources indicate that most car fires aren't from collisions, so that's perhaps a small effect) total to 210k/yr. You then find that, smoothing out all underlying subgroups and data, there's a fire every 15.5M miles.
Applied to residential apartments, there's an average miles per year of 14k or so (should be less here than average based on anecdata, high fuel prices discouraging driving, and everything being close even if you do drive and usually close enough to be walkable, but let's assume 14k/yr is a reasonable baseline), giving us a fire every 1100 vehicles, not every 100.
1/1k is more plausible to me (still "feels" high, but it doesn't trigger the baseline absurdity checks I have in the back of my mind). 1/100 suggests that every year in uni one of my classmates should've had their car burn down. 1/100 suggests that every year my hometown newspaper should report 30 cars burning down -- one every week or two (and given that the newspaper covers the entire county it should actually be 3/week). It's a pretty high rate. The typical person knows hundreds of people well enough that a car fire would often crop up in conversation eventually, and I don't think the typical person knows anyone whose car caught fire. Elaborating on that, I don't think the typical person doesn't know somebody whose car caught fire _ever_, much less in the last year.
In my personal experience pretty much every old farmer has had multiple vehicle fires. It's quite likely location dependent -- if you're in an area which clogs up air filters quickly, and or where dry straw getting in where it shouldn't is a likely experience, vehicle fires are very common.
Maybe. That hometown I referenced has 3k people in the city (not farmers) and 12k people in the county outside the city (mostly farmers in varying capacities). It's the only place I've lived where it's common for people to cut, mill, and dry their own lumber for economic reasons, or (ignoring parts of Alaska I've lived in) for hunting to be an economically rational thing to do. There are literally zero vehicle fires. A home or business per year or two burns down, but at the 1/100 vehicle fire rate we expect 3 fires per week, and there are zero in the last decade. It's a hot, dry climate made up of mostly farmers with extremely shoddy equipment.
Anecdotes aren't everything. If there are 1/1k fires annually then those have to come from somewhere, so your "location dependent" idea makes a lot of sense. I'm passionately curious now as to where those fires actually happen though. It's not just farmers with bad equipment in bad scenarios.
People can say it's 'years of neglect' and might even believe it, but to me it's clear train liberalisation directly caused 2 train incident in Spain this year. Yes trains are slightly cheaper (for now, look at GB to estimate how long the low prices will last), but I'm not so sure the redundancy you pay for in a public monopoly is worthless, especially in areas where an incident can cause this many deaths.
"Directly" is way too strong. Yes, it may have been a factor here that the train that remained standing still was from another operator, but there are many more important factors at play, the main one being apparent lack of safety mindset of the controller. In other European countries with even more operators, the safety record is not commensurably worse.
It is though. It's like the electricity market. We try to liberalize it, we see it doesn't work, so we add regulations and regulators (here the "controller"), and each time there is a failure, we blame regulation or regulators, or both. Sometime when it's too egregious we blame the particular company that was caught fucking up, because blaming the system that allows such fuck ups would cost to much: ideologues in power agreeing to the idea that maybe, market do not work everywhere.
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