This is so stupid.

To me, “AI” in a car would be like highlighting pedestrians in a HUD, or alerting you if an unknown person messes with the car, or maybe adjusting mood lighting based on context. Or safety features.

…Not a chatbot.

I’m more “pro” (locally hostable, task specific) machine learning than like 99% of Lemmy, but I find the corporate obsession with cloud instruct textbots bizarre. It would be like every food corp living and breathing succulents. Cacti are neat, but they don’t need to be strapped to every chip bag, every takeout, every pack of forks.

Not everyone’s a big kb/mouse fan. My sister refuses to use one on the HTPC.

Hence I think that was its non-insignificant niche; couch usage. Portable keyboards are really awkward and clunky on laps, and the steam controller is way better and more ergonomic than an integrated trackpad.

Personally I think it was a smart business decision, because of this:

It doesnt have 2 joysticks so I just buy an Xbox one instead.

No one’s going to buy a steam-branded Xbox controller, but making it different does. And I think what killed it is that it wasn’t plug-and-play enough, eg it didn’t work out of the box with many games.

With respect, this doesn’t make any sense. If you want a joystick controller, just buy an Xbox controller that everything’s compatible with anyway?

The trackpads shine when one needs to emulate a mouse/kb in non-controller games; a nightmare with joysticks.

My sister still has a working one that she treats like a religious artifact, as it’s the best way to play mouse/KB games from the sofa.

I see why they discontinued them though. They need custom configs for most games, and I think most people don’t like that much tweaking.

A lot, but less than you’d think! Basically a RTX 3090/threadripper system with a lot of RAM (192GB?)

With this framework, specifically: https://github.com/ikawrakow/ik_llama.cpp?tab=readme-ov-file

The “dense” part of the model can stay on the GPU while the experts can be offloaded to the CPU, and the whole thing can be quantized to ~3 bits average, instead of 8 bits like the full model.

That’s just a hack for personal use, though. The intended way to run it is on a couple of H100 boxes, and to serve it to many, many, many users at once. LLMs run more efficiently when they serve in parallel. Eg generating tokens for 4 users isn’t much slower than generating them for 2, and Deepseek explicitly architected it to be really fast at scale. It is “lightweight” in a sense.

…But if you have a “sane” system, it’s indeed a bit large. The best I can run on my 24GB vram system are 32B - 49B dense models (like Qwen 3 or nemotron), or 70B mixture of experts (like the new Hunyuan 70B).

DeepSeek, now that is a filtered LLM.

The web version has a strict filter that cuts it off. Not sure about API access, but raw Deepseek 671B is actually pretty open. Especially with the right prompting.

There are also finetunes that specifically remove China-specific refusals. Note that Microsoft actually added saftey training to “improve its risk profile”:

https://huggingface.co/microsoft/MAI-DS-R1

https://huggingface.co/perplexity-ai/r1-1776

That’s the virtue of being an open weights LLM. Over filtering is not a problem, one can tweak it to do whatever you want.

Grok losing the guardrails means it will be distilled internet speech deprived of decency and empathy.

Instruct LLMs aren’t trained on raw data.

It wouldn’t be talking like this if it was just trained on randomized, augmented conversations, or even mostly Twitter data. They cherry picked “anti woke” data to placate Musk real quick, and the result effectively drove the model crazy. It has all the signatures of a bad finetune: specific overused phrases, common obsessions, going off-topic, and so on.

…Not that I don’t agree with you in principle. Twitter is a terrible source for data, heh.

Nitpick: it was never ‘filtered’

LLMs can be trained to refuse excessively (which is kinda stupid and is objectively proven to make them dumber), but the correct term is ‘biased’. If it was filtered, it would literally give empty responses for anything deemed harmful, or at least noticably take some time to retry.

They trained it to praise hitler, intentionally. They didn’t remove any guardrails. Not that Musk acolytes would know any different.

Also a crime. Not just a great game in their niche, but a long history of them.

Never underestimate Phil Spencer.

Reads bit on dictator-propping via propaganda in Sudan.

Nods. Yep, that sounds like my government alright. And Big Tech. Cries inside.

Veers off to “Ukraine Proxy War” with no reference to ChatGPT as promised in the headline.

Sighs. Closes tab.

I’m constantly shadow banned on Reddit too!

I like the list, though I think it’s a shame animation is essentially cut out. I’d rank Pantheon, Arcane, Avatar well above, say, Person of Interest, as much as I like PoI.

(NCD Mode)

I hate to say it, but from Kim’s perspective, this makes sense. It battle tests equipment, gives troops real experience and gets kudos with someone other than China so they aren’t so reliant on them. It’s not directly aggressive to SK, either, and an unstable Russian neighbor is not what they want.

I can’t imagine what this is like from the troop’s perspective though. Live life in NK with the south as your enemy, then get shipped north to fight in the cold somewhere you know nothing about.

OK, while in principle this looks bad…

This is (looking it up) like an experienced engineer’s salary in Peru, in line with some other professions.

It’s reasonable to compensate a president, and for the expectation to not be coming in rich/connected enough to not need a salary. Nor for them to broker power for personal wealth, all as long as other offices and reasonably compensated too.

It avoids perverse incentives, doesn’t seem excessive and TBH is probably a drop in the Peruvian govt’s budget.

The junocam page has raw shots from the actual device: https://www.msss.com/all_projects/junocam.php

Caption of another:

Multiple images taken with the JunoCam instrument on three separate orbits were combined to show all areas in daylight, enhanced color, and stereographic projection.

In other words, the images you see are heavily processed composites…

Dare I say, “AI enhanced,” as they sometimes do use ML algorithms for astronomy. Though ones designed for scientific usefulness, of course, and mostly for pattern identification in bulk data AFAIK.

…iOS forces uses Apple services including getting apps through Apple…

Can’t speak to the rest of the claims, but Android practically does too. If one has to sideload an app, you’ve lost 99% of users, if not more.

It makes me suspect they’re not talking about the stock systems OEMs ship.

Relevant XKCD: https://xkcd.com/2501/

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Yep.

It’s not the best upscale TBH.

Hence I brought up redoing it with some of the same techniques (oldschool vapoursynth processing + manual pixel peeping) mixed with more modern deinterlacing and better models than Waifu2X. Maybe even a finetune? Ban.

Nah I meant the opposite. Journalistic integrity was learned through long, hard history.

Now that traditional journalism is dying, its like the streamer generation has to learn it from scratch, heh.

I got banned from a fandom subreddit for pointing out that a certain fan remaster was (partially, with tons of manual work) made with ML models. Specifically with oldschool GANs, and some smaller, older models as part of a deinterlacing pipeline, from before ‘generative AI’ was even a term.

Its kinda like influencers (and their younger viewers) are relearning the history of journalism from scratch, heh.