I have a desktop which has / had a similar problem.

Originally I built it with a g-series Ryzen which has integrated Radeon Vega graphics. Upgraded to a 3060 and wanted to run Linux for gaming instead of windows.

I couldn’t get a distro to reliably use my graphics card without the issues you describe. Stuttering, crashing, generally unusable.

Garuda was the answer (to be fair I’d try Bazzite too but I just didn’t get there as Garuda worked). In fact, it worked out of the box for me and I enjoyed it so much I made it my work OS.

I like the GUI utilities they’ve made for front-ending a bunch of Arch CLI utilities and I’ve been saved by BTRFS snapshots more than once.

What is success here? The few founders and VC get filthy rich as the larger population dumps their money into Discord stock while the users and teams with limited foresight, who’ve moved their communities to discord, suffer?

I mean yeah I guess that’s the success Cory Doctorow warns us about again and again.

But that’s not my definition of success.

For context I’ve been on the receiving end of an IPO and the founders and investors made out like bandits while a fair number of employees were stuck holding the bags thanks to lock-ins, dilution and over priced shares.

So maybe we’re kinda staring at two sides of the same coin. Because yeah, you’re not misrepresentin my point.

But wait there’s a deeper point I’ve been trying to make.

You’re right that I am also saying it’s all bullshit - even when it’s “right”. And the fact we’d consider artificially generated, completely made up text libellous indicates to me that we (as a larger society) have failed to understand how these tools work. If anyone takes what they say to be factual they are mistaken.

If our feelings are hurt because a “make shit up machine” makes shit up… well we’re holding the phone wrong.

My point is that we’ve been led to believe they are something more concrete, more exact, more stable, much more factual than they are — and that is worth challenging and holding these companies to account for. i hope cases like these are a forcing function for that.

That’s it. Hopefully my PoV is clearer (not saying it’s right).

Ok hear me out: the output is all made up. In that context everything is acceptable as it’s just a reflection of the whole of the inputs.

Again, I think this stems from a misunderstanding of these systems. They’re not like a search engine (though, again, the companies would like you to believe that).

We can find the output offensive, off putting, gross , etc. but there is no real right and wrong with LLMs the way they are now. There is only statistical probability that a) we’ll understand the output and b) it approximates some currently held truth.

Put another way; LLMs convincingly imitate language - and therefore also convincing imitate facts. But it’s all facsimile.

Really?

I read your reply as saying the output is (can be) libellous - which it cannot be because it is not based on a dataset which resolves to anything absolute.

Maybe we’re just missing each other - struggling to parse each others’ output. ;)

Surely you jest because it’s so clearly not if you understand how LLMs work (at the core it’s a statistic model - and therefore all approximation to a varying degree).

But great can come out of this case if it gets far enough.

Imagine the ilk of OpenAI, Google, Anthropic, XAI, etc. being forced to admit that an LLM can’t actually do anything but generate approximations of language. That these models (again LLMs in particular) produce approximations of language that are so good they’re often indistinguishable from the versions our brains approximate.

But at the core they cannot produce facts because the way they are made includes artificially injected randomness layered on-top of mathematically encoded values that merely get expressed as tiny pieces of language (tokens) - ones that happen to be close to each other in a massively multidimensional vector space.

TLDR - they’d be forced to admit the emperor has no clothes and that’s a win for everyone (except maybe this one guy).

Also it’s worth noting I use LLMs for work almost daily and have studied them quite a bit. I’m not a hater on the tech. Only the capitalists trying to force it down everyone’s throat in such a way that we blindly adopt it for everything.

It’s all hallucinations.

Some (many) just happen to be very close to factual.

It’s sad to see that the marketing of these tools has been so effective that few realize how they work and what they do.

While there are many reasons to dislike (or outright avoid) Apple - if you purchase music from them, it’s DRM-free and useable anywhere.

I believe they were one of the first official channels to do this.

Still, hadn’t heard of Quobuz and will check them out!

You’ve described Ghost. Subscriptions for content are a first class citizen.

It’s primary a writing platform with built-in monetization options and the ability to self host. We switched to it from Substack. It’s been fantastic to use and operate. Super slick.

I think that depends on what you’re doing. I find Claude miles ahead of the pack in practical, but fairly nuanced coding issues - particularly in use as a paired programmer with Strongly Typed FP patterns.

It’s almost as if it’s better in real-world situations than artificial benchmarks.

And their new CLI client is pretty decent - it seems to really take advantage of the hybrid CoT/standard auto-switching model advantage Claude now has with this week’s update.

I don’t use it often anymore but when I reach for a model first for coding - it’s Claude. It’s the most likely to be able to grasp the core architectural patterns in a codebase (like a consistent monadic structure for error handling or consistently well-defined architectural layers).

I just recently cancelled my one month trial of Gemini - it was pretty useless; easy to get stuck in a dumb loop even with project files as context.

And GPT-4/o1/o3 seems to really suck at being prescriptive - often providing walls of multiple solutions that all somehow narrowly miss the plot - even with tons of context.

That said Claude sucks - SUCKS - at statistics - being completely unreliable where GPT-4 is often pretty good and provides code (Python) for verification.

Recently switched from VsCodium to neovim - but still use Codium for some specific tasks.

My setup customization focuses around Telescope, Treesitter, Trouble & Blink.

But the advice I got was to start with vim keybindings in VSCode. I used those for six weeks until I got the hang of the basics and it had gone from frustrating to somewhat second nature.

Then I made the move.

I still use Codium for Terraform work (I have struggled to get the Terraform LS working well in neovim and I don’t use it often enough to warrant the effort) and as a GUI git client - I like the ability to add a single line from multiple files and I haven’t looked up how to do it any other way - I’ve got other stuff to do and it’s not slowing me down.

But I grew to hate Codium / VS code tabs in larger codebases. I was spending so much time looking for open tabs ( I realise this is a me problem). While neovim has tabs, it’s much more controlled and I typically use them very differently and very sparingly.

If I need to look up a data structure I just call it up temporarily with Telescope via a find files call or a live grep call (both setup to only use my project directory by default), take a peak, and move on.

The thing is - security risks are going to exist anywhere you install plugins you haven’t audited the code for. Unless you work in an IDE where there’s a company guaranteeing all plugins - there are always going to be risks.

I’d argue that VSCode, while a bigger target, has both a large user base and Microsoft’s security team going for it. I don’t see the theme being compromised as much as problem because it got solved and also prompted some serious security review of many marketplace plugins. Not ideal, but not terrible.

As per my other comment - the algorithm is only part of it.

A big aspect however is the slickness and ease-of-onboarding for mega-Corp apps. It’s a thing that would relatively easy to begin work on.

I’ve seen first hand the amount of time and money even growth-stage startups spend on onboarding and have lots of first-hand reports from peers at the big girls - it’s a critical part of success. Make it easy to get started and easy to stay using.

It’s missing from most fediverse experiences. Pixelfed being a serious contender for an on-boarding rethink.

“time-to-value” - we want that as low as possible.

Found the other NixOS user. ;)

My advice: don’t change anything else right now.

The temptation is high to pack it all in at once; make all the big changes.

2 hours a day is a lot. Not too much, just a lot. So, since you asked, don’t change your diet yet. Get into the groove of building this new thing into some level of consistency. Once you’re 90 days in, start modifying something else. Diet. Sleep. Intensity.

Work on one routine at a time.

Now if you’re going too far into calorie deficit then you can think about what your energy needs are but keep the other changes to bare necessity.

Lying liar lied. News at 11.

I can’t imagine that being the case for most users. I’m absolutely a power user and I keep being surprised at how consistently high the performance is of my base model M1 Air w/16GB even when compared to another Mac workstation of mine with 64GB.

I can run two VMs, a ton of live loading development tooling, several JVM programs and so much more on that little Air and it won’t even sweat.

I’m not an Apple apologist - lots of poor decisions these days and software quality has taken a real hit. While 16GB means everyone’s getting a machine that should last much longer, I can’t see a normal user needing more any time soon, especially when Apple is optimizing their local machine learning models for their 8GB iOS platforms first and foremost.

You come to my door. You get candy.

Young, old, costume or not.

You get candy.

I found my people here.

Recently decided to try Linux for gaming. It wasn’t without a hitch or two, but largely fine. A number of games I play don’t even need an emulation tool like Proton.

The only reason windows was lying around was for gaming.

Looks like it’ll only get used for flight simulation.