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To the rest of the world, US aggression is perceived as oppressive and unilateral primarily because it’s a political act meant to further domestic political goals. All US administrations act in their own self interest, as they should.

But the US being the world’s cop was never going to be sustainable indefinitely. It was partly because of hegemonic power and partly because of a reluctance of wealthy democratic countries to seriously invest in their military when they could just “pay” someone else.

I don’t think anyone wants the pre world war 2 order. So we are likely going to see otherwise reluctant states step up militarily to protect their neighborhoods.


those are some massive actuators on those joints


Brakes are being added to actuators but they're more useful for static holds / locking than dynamic balancing. Standing even in humans is a dynamic balancing activity.


It is, but you don't have to do it at every joint all the time. If you lock your knees your front and back thigh muscles don't have to work on balancing in that axis at all.


You evaluate the merits of the content? From a high-level systems pov, the article is largely correct, even if some details might be missed / simplified


How do you evaluate the merits of a graph of information? I usually read articles like this to learn something, not to grade someone else’s assignment.


Nobody is interested in correct information anymore. In 2026, trustworthy information is what people want.


Yes. This distinction is important.

As a lay person, I have limited knowledge of this field, yet am extremely interested. Unfortunately AI gen content is being used widely to spread spurious information/fake news etc. So my knee jerk reaction to AI gen content is - "this is going to be fake".

If the information you are trying to convey is true, and is technical/objective in nature, then why shy away from associating your identify to it?


I feel the same until I’m reminded I’m paying Anthropic $100 every month for something that’s indispensable to me now and would probably pay a lot more. Very inelastic demand as long as competition is low at the frontier.


I pay TMobile $100 a month but they aren't worth a trillion dollars.


Yes but Tmobile enterprise customers don't pay much more for plans. In fact, they may pay less because of volume.

However, Anthropic can and will charge much more for enterprise customers.


Why will Anthropic be able to do that? That assumes there won't be competition and switching costs will be high. That doesn't seem to be the case to me.


They're already doing it. There are reports of big companies like Meta spending hundreds of millions or billions on Claude tokens already.


Anthropic's market is global and the US is 4.5% of the worlds population. Telcos are regional.


TMobile is effectively a monopolist in many US regions.


Still not worth a trillion dollars.


There are no places in the US that Tmobile is the only wireless mobile network provider. While all 3 mobile network providers have weak coverage areas, Verizon is considered to have the most reach.


Would it still be indispensable to you if you weren't in this industry?


I think about this a lot - on HN and elsewhere online, there's an outsized portion of people who are likely to see use in AI. If you're online, you're on a computer and you're likely to also do office work that an AI can help with / do for you.

I don't think a majority of people will find it actually useful in the long run. I do game development as a hobby outside of work and every artist I know is outright hostile towards any sort of AI, to the point that they are dropping out of any community that so much as allows any mention of AI workflows.

I know that OpenAI is at least exploring "AI as entertainment" (Sora) but it has yet to be seen if that will be widely accepted or profitable. I've also been reading about teens talking to chatbots more and more rather than talking to real people, which seems like it will only end in mental health disasters.


Are you paying that, or is your work paying for it?

If you’re using it for personal work, why is $100 worth it?


$100/month isn't much for developer tooling. If you add up how much I spend on hardware upgrades, other SaaS products like backup services, software licenses, and other things it's easy to justify $100/month for a powerful tool.

I pay for my own AI provider subscriptions because keeping work and personal strictly separated is important for me. I do know some people who secretly pay $200/month for Claude and use it at their job even though it's not approved. I do not recommend doing that, but it shows that some people value this for their work.

For developers earning more than $10K per month, spending less than 1% of salary on tooling to make the job easier is easy to justify.


I too spend over $100 on drugs that make me feel productive but actually am not.


I’ve been a copilot and ChatGPT subscriber for probably close to two years now, give or take a couple of months, and I had a trusted friend telling me for months to give Claude a try.

It took about two weeks of really running it through its paces, and constantly slamming against the limit on it to convince me I had to upgrade to at least the 100/month sub, and at this point I wouldn’t blink to bump that to the 200/month if necessary.

I 100% believe we’re in a bubble, and that this level of compute isn’t sustainable at this price point, but for as long as I have it, I’m going to run it at the redline.

I’m a solo dev working on a project that I’ve just gone full-time on, after about 1.5 years of part time work. It’s a codebase that I laid the groundwork in, and has very well established systems, standards, and constraints.

The work I’m using Claude to do is the exact work I would be doing myself, but it does it at somewhere in the neighborhood of 5-10x the pace I could have. I don’t know that I could get the same rate of production if I managed a team of 2-3 programmers. Right now, it’s literally almost perfect at taking my iterative suggestions, and implementing them at that accelerated pace.

Honestly the hardest part is dealing with the fact that at the end of the day, I have to understand this codebase perfectly (solo dev and all that), so I have to take in changes to it that are also 5-10x the rate my normal intuition would. But, again, the plus side is that it’s implementing them essentially exactly as I would have, as it has ~20k lines of code that I wrote to use as an example.

If I were to hire even one other programmer, I’d be paying well north of 5k/month, and I’d not only be managing a super computer programmer tool, but an actual human being as well. $100/month might as well be free comparatively.


If it gets you so much value for $100/month and Anthropic still claims they have 50%+ gross margins, why do you think we are 100% in a bubble?

Doesn’t make any sense.


Because I don’t believe 50% gross margins at face value, as being discussed in this thread I think the economics of all of these things are far more complex than that.

For what it’s worth, I haven’t staked my investment portfolio on there being a bubble, I’m just preparing for the worst and doing as much work as I can with Claude before a potential massive rug pull happens.


Have you seen Dario's interview where he talks about gross margins and profitability for Anthropic?


>If you’re using it for personal work, why is $100 worth it?

I'm not who you were replying to, but:

My work pays for $100/mo Claude, I pay another $100 to bring it up to $200/mo level because:

    - Partly: I got in the habit back when work was only paying $20 and I was paying the $180.
    - It is not worth it to me to spend braincells trying to optimize my use to slip into the $100 plan, I give everything "Opus, effort max" and with the $200/mo plan I never run out ($100 I'll run out mid-morning).
    - I run a *lot* of experiments, including work-related and personal, to try to understand and improve my AI use skills.
    - I also use it for a lot of personal things, right now I'm using it to help me plan a backyard studio and ADU.
"ccusage" the past month says $1017.

edit: Formatting, ccusage


3/3.1 Pro appears to have knowledge about eccentric topics with no obvious sources that often turns out to be right.

It does hallucinate a lot though, and is the most affected by context rot in multi-turn conversations


Agreed on both, especially hallucination. That's what makes their chat app even worse, it's very opaque about web search and sources, so you can't tell whether it's a hallucination.


Acetaminophen (paracetamol) is the drug of first choice for addressing pain and fever, in India at least. To the extent that it's regularly abused, and I know people who have been hospitalized because of abuse.

Even then, doctors are usually disapproving of ibuprofen (or some combination of it with paracetamol) unless paracetamol is contraindicated for some reason, and I had always wondered why.


I did listen to this 99% Invisible story about the use of NSAIDs in India once[1]

What you describe in an interesting contrast to the situation in The Netherlands. Here, virtually no one is prescribing ibuprofen _without_ also prescribing a baseline of paracetamol.

[1]: https://99percentinvisible.org/episode/579-towers-of-silence...


Yeah it's weird, almost like we're seeing two cults form in real-time.

I imagine there's a benign explanation too - the intelligence of these models is very spiky and I have found tasks were one model was hilariously better than the other within the same codebase. People are also more vocal when they have something to complain about.

In my general experience, Opus is more well-rounded, is an excellent debugger in complex / unfamiliar codebases. And Codex is an excellent coder.



They have several levers for demand destruction. From Anthropic's POV, I suspect this is least to worst bad

- reducing the surface area of "acceptable use" (e.g., blocking third-party tools OpenClaw)

- tighter usage limits and more subscription tiers

- increasing existing subscription prices

- moving to usage based model completely

- taking away compute from training next gen models (future demand destruction)


Reduce quality? Like quantizing models or context cache


Or reducing default reasoning levels?


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