I'll probably manage with Mac OS well enough, but my linux distro comes out of the box with all the latest OSS tooling I'm familiar with, plus a package manager, and it has linux cgroups and namespaces that power the container technologies we all know and love.
If I switch to Mac OS, I have to sort out a package manager and install all the stuff that's missing, and when it comes to containers... they're just linux VMs. I'd happily cut out the weird proprietary middleman if I could.
Linux for argument’s sake, may have a few things that are better than Mac OS but Apple being the last vertical computer company from the 1980s, I don’t think they have any interest in using Linux, not after Next, Motorola, IBM, Intel and Nvidia in the past. They don’t need to they appear to navigate thru tech very well in comparison to Microsoft or Intel, for example.
I think people responded that way because you strongly implied he was an unserious vibecoder who was just fooling around, and you called him suspicious as fuck.
In my own professional life, I've found this to be a very divisive statement. For some, it is a sign of wasting time and effort. For others, they use this to describe themselves when they want to do exploration for the goal of finding improvements, without any clear goal because they have a few ideas but none worth putting forward. I've been told to spend time learning AI and have found that saying "Yeah, I'm playing around with it." was the wrong thing to say because it was seen as not doing anything worthwhile. It doesn't matter that I would also say the majority of my tech skills were developed when I was "playing around".
I wonder if this is purely a linguistics breakdown, or if this is tied to some deeper difference in a person's relationship to tech?
Agree it's divisive, and I would argue it speaks more to a person's perception of work vs play more than a relationship to tech. If (the general) you think that play is for children and work is serious biz, then yeah I could see how you wouldn't take someone seriously when they say they're "playing around with it". It's usually not obvious which attitude a person has though without getting to know them a little bit.
Yes, I think it can be a sign of a very deep difference. When they say "spend time learning AI," they mean work through some teaching materials to learn how to replicate what others are doing. This often doesn't result in a deep understanding, but it can be enough to allow them to do their job.
Ironically, people with this mindset will sometimes ask people who they recognize as having strong skills to share their magic secret, which is assumed to be some books they read, videos they watched, courses they attended, etc. If you tell them that experimenting, playing around, etc. is a key element, they may assume you're just selfishly hoarding your fount of knowledge.
I don’t see anything from your parent commenter on the other thread that deserves that classification. On the contrary, while they initially had suspicious of vibe coding, on later comments they are cordial and even admit their own misunderstanding.
What am I missing? Where does “called him suspicious as fuck” come from?
Not to mention the author themselves say "Yes, there's a lot of vibe-coding in many places [...] We'll prune AI slop over time.", and then they both moved on to discussing the actual questions.
The whole "Wow, looks AI" > "Yeah, some of it is, we'll fix it later" was such a small part of the conversation, but then there are countless of other people chiming in about specifically the "Is It Slop Or Not?", rather than the meat of the conversation. And here we are adding even more meta-comments about it.
The thing they don't show is the one we really need, especially because model providers can skimp on quality (run lower quantization, lower kv cache precision, etc) to improve their pricing and performance. I agree that it's probably too expensive to keep running the benchmark, but we need some way to hold the providers to a certain standard, otherwise every user has to discover the problems on their own.
As a user/reader/viewer I absolutely hate Anubis and usually turn around when I see it pop up (at least on my phone where it takes ages to compute), but with stats like that, I get why a site operator would resort to using it.
I think the kernel.org post proves the parent point rather than contradicts it.
> At any one time, across 5 geo-distributed nodes, there are 14 CPU cores doing nothing but rendering git commits as html.
14 CPU cores total for running a website like kernel.org is laughable. This is not worth burning cycles in Anubis on client's devices, this is not worth the time of the engineer who worked on it. Provisioning more hardware would have been literally better for everyone.
> But no, let's in fact choose the stupidest possible way of doing it — by rendering everything as HTML commit by commit and then parsing it.
This drives me crazy with so-called SOTA LLMs that have "achieved AGI".
Fable, Sol, Astra, will start by trying to reverse engineer a binary to figure out how something works when software is open source and one search query away.
You let them know it's open source, and they will start using github API instead of just cloning and grepping.
I had a discussion about this with a friend recently. I was using an LLM with a serial console that it wrote to allow us to share a connection to a Z80 computer running CP/M. I was having trouble with the assembler, it wouldn’t assemble in user 1 of a particular disk, so I asked the LLM for help. It debugged ASM.COM and the BDOS, walked through the source compared to memory dumps, basically banging its head on the wall for an hour or more, until it finally figured out and verified that my disk had a bad block. I never would have put in that much effort to find the root cause of the problem.
Some LLM interfaces allow you to modify and “continue” an agent response. It’s very useful for guidance, including jailbreaking. Need the model to go in a certain direction? Got a refusal that you want to bypass? Just start it off in the appropriate direction and then have it continue from there.
llama.cpp (but maybe not for reasoning models?) and sillytavern, maybe others... I'm half a country away from my desktop right now so I can't verify much right now.
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