The ads for apps, Xbox games, trial versions of Office preinstalled, the minesweeper and solitaire collection that are preinstalled but actually ad supported or non-free, depending on the region spotify/TikTok/Facebook also come preinstalled, “Movies & TV”, Bing/MS News…
I think all of those count as bloat. I haven’t included Edge because I guess having a browser is a necessity, or copilot/cortana because you said “excluding AI features”.
Oh no! They’re using an emulator! I choose you NINTENDO! Use “Sue for copyright”!
Unfortunately, it’s not very effective (Anthropic’s type is “AI Company”).
I’ve only started using Storygraph recently (which I also like) but I’d consider a federated alternative. Does anybody know whether its possible to migrate the history from SG to Bookwyrm?
Excellent in which specific sense? Most competitors offer better everything (performance, range, build quality) for a given price point.
The fact that Tesla has managed to make EVs that consistently rank below most ICE brands in terms of reliability is mind blowing.
Over the past 5 years, I’ve installed ubuntu about 30 times on different computers. Not once has an install on an SSD taken me more than an hour, with it typically taking me 30 minutes or less except for rare occasions where I’ve messed something up.
It’s the other way around, an Apple Silicon Mac would be able to run an intel binary through Rosetta (I think there’s almost no exceptions at this point). It’s intel macs that can’t run Arm specific binaries.
I thought a few days ago that my “new” laptop (M2 Pro MBP) is now almost 2 years old. The damn thing still feels new.
I really dislike Apple but the Apple Silicon processors are so worth it to me. The performance-battery life combination is ridiculously good.
Less conveniently while costing something like $700 plus a monthly $25 subscription.
I don’t get how it got pitched either.
It’s UE in Spanish, from Unión Europea. (Non-doubled letters because it’s a single Union, there’s no plural like in “States”).
Sometimes people in Spain do use the English acronyms for both EU/USA, but I don’t think I’ve seen it often. Both UE and EEUU are more common from what I’ve seen, and also people rarely say these out loud, it’s exclusively a written language problem.
I’m talking about running them in GPU, which favours the GPU even when the comparison is between an AMD Epyc and a mediocre GPU.
If you want to run a large version of deepseek R1 locally, with many quantized models being over 50GB, I think the cheapest Nvidia GPU that fits the bill is an A100 which you might find used for 6K.
For well under that price you can get a whole Mac Studio with those 192 GB the first poster in this thread mentioned.
I’m not saying this is for everyone, it’s certainly not for me, but I don’t think we can dismiss that there is a real niche where Apple has a genuine value proposition.
My old flatmate has a PhD in NLP and used to work in research, and he’d have gotten soooo much use out of >100 GB of RAM accessible to the GPU.
If it’s for AI, loading huge models is something you can do with Macs but not easily in any other way.
I’m not saying many people have a use case at all for them, but if you have a use case where you want to run 60 GB models locally, a whole 192GB Mac Studio is cheaper than the GPU alone you need to run that if you were getting it from Nvidia.
So the lack of apple-branded AI Slop is slowing down the sales for iPhones but not for Macs?
Edit for clarity: I’m aware sequoia “has” apple intelligence but in a borderline featureless state, so it’s as good (or as bad) as not having anything.
Some of these are for insurance, government organisations… They are naturally dry but we can’t get away from them.
Some others that I described like internal changelogs, I agree won’t ever get read. Then if that’s the case I don’t care (much) about the quality - just about doing it as quickly as possible.
There are tons more applications in the workplace. For example, one of the people in my team is dyslexic and sometimes needs to write reports that are a few pages long. For him, having the super-autocorrect tidy up his grammar makes a big difference.
Sometimes I have a list of say 200 software changes that would be a pain to summarise, but where it’s intuitively easy for me to know if a summary is right. For something like a changelog I can roll the dice with the hallucination machine until I get a correct summary, then tidy it up. That takes less than a tenth of the time than writing it myself.
Sometimes writing is necessary and there’s no way to cut down the drivel unfortunately. Talking about professional settings of course - having the Large Autocorrect writing a blog post or a poem for you is a total misuse of the tool in my opinion.
After the 6th of Jan, I can’t be convinced that the USA takes treason seriously.
Need more storage for windows bloat…
I think that’s exactly what’s needed, something that makes it mainstream without compromises. For example, if it came as standard with the PS6 and people could use it with all their games such as call of duty.
I don’t see what could be the tipping point that makes this happen; Sony certainly isn’t going to bundle a headset with the PS6, although I wouldn’t be surprised if Nintendo eventually tried something like this. What I know is that a legless version of the Wii avatars or a $3000 headset that requires you to carry a battery in your pocket wired to your head ain’t it.
I think it might have been because of the add-ons compatibility then.
This can be correct, if they’re talking about training smaller models.
Imagine this case. You are an automotive manufacturer that uses ML to detect pedestrians, vehicles, etc with cameras. Like what Tesla does, for example. This needs to be done with a small, relatively low power footprint model that can run in a car, not a datacentre. To improve its performance you need to finetune it with labelled data of traffic situations with pedestrians, vehicles, etc. That labeling would be done manually…
… except when we get to a point where the latest Gemini/LLAMA/GPT/Whatever, which is so beefy that could never be run in that low power application… is also beefy enough to accurately classify and label the things that the smaller model needs to get trained.
It’s like an older sibling teaching a small kid how to do sums, not an actual maths teacher but does the job and a lot cheaper or semi-free.