EddieRingle

Likewise, a younger, more idealistic me thought it'd be great to use a GitHub-esque platform for laws. Pull Requests to suggest laws, gated behind reviews/approvals, branches so each house could work on their own versions before finally reconciling and merging into the Code, literally.

I have no issues using it with llama.cpp.

I currently have a few VMs in a Proxmox cluster that serve as sandboxes, talking to various inference machines, all self-hosted (so I don't have to worry about having "enough credits" either).

Very neat. Almost reminds me of Android's databinding era (i.e. type-safe generated interfaces to XML Views). Though Android development quickly moved on to Compose UI, since Kotlin is expressive enough to cover all of the bases, I guess. And ever since then, I've personally grown annoyed with how much other ecosystems rely on templating. (In fact, I'm doubly annoyed that JetBrains picked YAML for Amper/Kotlin Toolchain. Since they had to add special templating to it anyway, why wouldn't they just use Kotlin or some subset?)

Like the other comments, I'm very confused at what this is meant to do other than promote a wanna-be Git competitor and yet another hyper-specific "conference". The post doesn't really make any arguments, even in the section that's suppose to make an argument. And for some reason they're adding GraphQL into the mix, somehow?

Dense models run at a very usable speed (Qwen 3.6 was running at ~50t/s last I looked) on my dual 7900 XTX desktop. (And before anyone brings it up, I did not buy them for this purpose, so the up-front cost is irrelevant in my case.)

> There’s no way to justify their valuations if they get downgraded to a pair programming tool.

Honestly I still don't see how they justify their valuations, period. If anything they're serious liabilities.

Open-weight models are improving and reaching "good enough" levels for more and more tasks. They're also known quantities; you know what you're getting with them and don't have to worry about the model silently (or not so silently) being switched out from under you (whether that's because Anthropic/OpenAI decides you're not worthy of their latest and greatest for one reason or another, or they switch you to a quantized model to save on compute, or they simply sunset the specific model you've been relying on).

And if the open-weight model doesn't run on your local hardware already, there are any number of hosting providers that will handle that for you (so you're back to just paying for colocation/cloud usage instead of nebulous tokens).

Closed models are improving as well, sure, but diminishing returns will eventually kick in (as they already have for various tasks, as I said).

So if not their models, where does their value come from? Just simple network effects/lock-in? "Normal" users will drift to other options if they start showing more and more ads, and enterprise customers will surely be looking for opportunities to avoid lock-in and reduce risk.

I think the last argument I've heard is that these valuations are basically a bet that Anthropic and/or OpenAI will achieve AGI that can fully replace human labor, so they'll essentially be able to sell that replacement labor to everyone. They haven't managed to pull that off, yet, however. Businesses that have tried to replace humans almost immediately realized either that the AI's capabilities were oversold or that they at least needed a human in the loop still, to some degree. And even if they do achieve AGI, that would surely become an issue of national security (they're already flirting with that today), so who's to say governments won't simply nationalize the best AI labs and either remove them from the economy entirely or perhaps even provide models as a public service to level the playing field?

That all sounds like a giant gamble, if anything. And it's incredibly frustrating to watch as someone that's been unemployed for a year because (a) budgets are being burned on tokens and (b) LLM-generated applications are flooding hiring teams and preventing real people from being seen. (Not to mention, as someone that spends a lot of time in gaming circles, the fact that DRAM and flash storage is quickly becoming inaccessible is just an additional frustration that means people can't even find temporary relief in entertainment.) I can only hope this bubble finally implodes before I lose my house.

Compose UI apps can be compiled to native binaries already, via Kotlin's LLVM backend, though at the moment only the macOS/iOS targets have proper (official) support. Last I looked (a few years ago now), the Linux and Windows targets shouldn't be too far off, since it's all built on top of Skia already, someone just needs to care enough to put in the work. (But since right now you already get coverage for all platforms between JVM and Wasm, not to mention hot reload support on the JVM, there's little motivation to do so.)

Both can be true, no? The administration has a vendetta (justified or not), and Anthropic's behavior gave them a reason to act on it.

Let's expand the actual quote we're responding to:

> the borrow checker woes can be offloaded to the model, you focus on all the other programming logic

Then the person you responded to asked if "you" really do "focus on all the other programming logic", given that "the model" deals with the borrow checker. In other words, they're asking about the work the actual human is doing at that point. You then replied talking about the model again and token budgets. In effect, you brushed the question under the rug and imply that _everything_ is offloaded to the model, no focus by the human required.

They're not talking about the model, and they're not talking about token budgets.

> Speaks volumes to the strengths of the language, also speaks volumes that LLMs lift the barrier of entry for Rust programming, the borrow checker woes can be offloaded to the model, you focus on all the other programming logic.

I get the opposite impression. If they aren't confident enough to write it by hand, I think it means the language is either hard to write, hard to read, or both. And by delegating to a LLM, there's no "barrier of entry" being lifted, it's just saving you typing time (like it would if it was being translated to C or Kotlin). If they actually decide to "focus on all the other programming logic" and they aren't just vibe coding this, they'll still need to be able to understand and reason about the code.

I wouldn't say Compose UI/Flutter/SwiftUI are "implementing React", but if your point is that other platforms have better solutions than JSX (plus all the bloat React adds to applications), I absolutely agree.