> 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.)
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.
> 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.
I'm always taken aback a little when I read through HN and see how little mind share Kotlin and its ecosystem has here. JetBrains has done a pretty good job of creating something that can fill many different niches (especially considering they're not one of the giant tech companies with virtually unlimited budgets), but it seems people don't even realize it exists, for whatever reason. It doesn't even need to run on a JVM in many cases, if that's some sort of barrier.
> I think ECS is a new enough architecture that the patterns are still very much folk lore.
ECS is a pretty old idea, built on concepts that are even older. I was playing around with an ECS-like engine of my own in C over 10 years ago, based on blog posts and talks that are now 20-25 years old. Even the Wikipedia article for ECS can trace the origins back to the 1960s. (Though obviously it hasn't been applied to video games for quite that long.)
Nowadays I'd probably reach for Godot and Kotlin if I just wanted to build a game in an ergonomic language on a solid foundation. You could still apply ECS concepts there, as well.
According to that article, the data they analyzed was API prices from LLM providers, not their actual cost to perform the inference. From that perspective, it's entirely possible to make "the cost of inference" appear to decline by simply subsidizing it more. The authors even hint at the same possibility in the overview:
> Note that while the data insight provides some commentary on what factors drive these price drops, we did not explicitly model these factors. Reduced profit margins may explain some of the drops in price, but we didn’t find clear evidence for this.
Sent an email out just a bit ago! Please let me know if it doesn't arrive for whatever reason.
EDIT: Looks like my comment was detached from its thread (https://news.ycombinator.com/item?id=46857847) without a comment explaining why. It's not breaking any of the stated rules at the top, and it seems like it would be common sense to let someone know they should expect a message (especially considering how temperamental email filtering can be these days). If this _is_ against the rules, I'd appreciate it if future hiring threads stated as such so that people like myself that have been trying to find a job for 7+ months can stop wasting our time here. I understand how it can be challenging to moderate a forum like HN, but the moderation priorities seem pretty disappointing, unfortunately.
> I applied and got rejected without feedback. They stated that there was a high volume of strong applicants (if there were, why are they posting again?)
This is the case for the vast majority of companies posting jobs here and elsewhere (e.g., LinkedIn) right now. I've been looking for the past 7 months after a lay-off and that exact reply is the most common response I've seen (because it's an automated response). Well, most common after not hearing back at all, of course.
> Plus, it seems some of y’all love to hate the very industry which puts a roof over your head. You’re hoping and praying that it all burns down—yet where will that leave you? How do you feel about becoming a plumber—-until the robots take that job?
This probably isn't a line of argument you want to go down. I've been unemployed for 7 months, in part due to how difficult it is to get so much as an intro call because so many people have totally automated the process of spamming every open job posting with as many resumes (many of which were likely LLM-generated as well) as possible.
I didn't get as far as experiencing their billing system; I decided to finally look into Claude recently and discovered that their pricing page's content area was completely blank. It loads on my phone if I'm off WiFi, so I assume my PiHole is blocking something there. That being said, if anyone at Anthropic is reading this, I'm primarily an Android dev but if you'd like to hire me to write a simple static HTML page just like I taught myself back when I was in elementary school, I think it could significantly improve your conversion rates or whatever, and I've been unable to even get an interview anywhere for the past 7 months so I really think we'd be helping each other out.
(Suffice to say I passed on Claude/Claude Code for the time being.)
On Android it more or less just uses the accessibility APIs to grab the actual text, you can do it without using Google Assistant even by selecting text inside an app's thumbnail window from the Recent Apps screen.
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.