ianm218

Yeah who knows poor infrastructure might let India skip fiber in some areas entirely. Maybe it’s not that hard to launch a domestic Starlink if Blue Origin/ SpaceX will bring your satellites up cheaply .

> Ironically it couldn’t be further from the truth… and likewise the predictions of widespread labor obsolescence

Could you explain what you mean here?

It feels like there is one bucket of verifiable work - programming, math etc that AI will clearly excel at.

There is another large bucket of like law/ accounting/ financial analysis where I don’t have any reason to think AI won’t be super human at, but the work is more on bringing all the domain expertise into harnesses and software.

Is there aspects of knowledge work that you think AI wouldn’t excel at in the long run?

This does seem to validate the critique that models like GLM are benchmaxxed and not as close to the frontier as you’d think based on their numbers.

India is super super poor still I cannot imagine they would build out domestic Starlink for hypothetical wars before other actual critical infrastructure.

I would say I'm still in this mindset. Numbers are hard to come by but analysts optimistically put Chinese SaaS market at ~10% of the size of the US. Also I see that the gross margin for public Chinese SaaS is around 50% vs 80% for the US reflecting that SaaS in China is much more services and implementation heavy. So it feels like the direct to business SaaS's like Salesforce aren't really there and then then the selling to SaaS titans like Datadog have a much smaller flywheel to work in.

Happy to be wrong though if I'm missing something.

I came to the exact same conclusion recently. I am building something like lightspeed that can run on “pay per second” infra like fly.io sprites because I wanted to have an open claw style agent but not have to deal with paying for another VM.

> At least in China a lot of software developers are now struggling.

Do you think that Chinese software industry is that relevant to the kind of software market talked about on HN? I.e. lots of enterprise b2b and infra companies.

Chinese companies have always had a very low willingness to pay for software which kinda breaks the flywheel of B2B SaaS companies and companies to service those companies all the way down.

Inspired by this project I ported most of Valkey to Rust here valdr.dev .

The coolest outcome was being able to run a redis comparible store on an a cloudflare durable object so you do I.e. rate limiting for free with little infra.

Your comment doesn’t make it clear why supporting this party would interfere with making a point on mass surveillance. If there is a link could you describe it?

But there is also tons of actual corruption especially in the military [1] which is maybe by design so you never know if a purge is political or legitimate or both.

[1]. https://www.businessinsider.com/china-corruption-rocket-forc...

To be clear that was 5 of the top 7 in the military not the CCP as a whole. Leaves just Xi and the anti corruption officer.

But yes agreed. It’s very hard to parse what is going on from the outside.

My very uninformed read is that the people who were purged seemed already loyal allies to Xi but had more clout to disagree with him, while the new guys know they are replaceable. The PLA is notoriously corrupt as well so hard to say which of those purges were political control vs corruption based.

I kinda doubt the new guys are unambiguous though you need to be ambitious and risk taking to rise like that in the CCP.

5 of the 7 highest ranking officials have been purged in recent years [1].

It’s not totally clear what the consequences were for those purged or if their crimes were legit but seems like they are all in prison.

[1]. https://www.afpc.org/publications/articles/the-inevitability...

Could you flesh this out more? The Chinese surveillance state is pretty well documented by academics [1] I'd be curious to see what makes you think that is fake news or whatever.

[1]. https://www.technologyreview.com/2022/10/10/1060982/china-pa...

I'm not being intentionally disingenuous my model of the situation is the US does mass surveillance and China does it at a much larger scale with much less restrictions. For example, China and the US have roughly the same amount of cameras per capita... but the Chinese government generally owns all the cameras and can query across them while as far as I know it is relatively hard for US gov to get access to public cameras.

Could you point me towards something that corrects me where I'm wrong i.e. not that they both don't do it but that they are doing mass surveillance at similar scales?

Even then though at their scale - billions of DAU with pretty elite consumer distribution in terms of InstaGram and WhatsApp the future is hard to predict.

Like they have much lower cost of capital than OpenAI or Anthropic for example and far more direct to consumer muscle, if they could've gotten their models into a better position it's very possible they could've beaten out OpenAI on consumer AI. Probably a smaller prize to win than B2B AI but still huge.

And then if the case where AI is panning out but they are failing to execute (where we appear to be now) they have the option of becoming a SpaceX style NeoCloud that is pretty solid, even though most of their moves were pretty bad along the way.

It’s a hard thing to measure right? Google under bet on demand for their AI infra and left lots of money on the table with Anthropic/ has to buy computer from SpaceX for awhile, Meta over built.

Anecdotally I know several people who would fall in the camp of anti vax but openly use peptides.

And intuitively it makes sense we’re talking about groups of people who are skeptical of main stream institutional health recommendations but trust specific personal sources for medical advice.

I’m vibing but it feels like there is a pretty clear intersection of peptides and the fringe science health community no?

The US government is no saint in terms of mass surveillance but there is a gigantic gulf between US governments mass surveillance and China, I think to act otherwise is a bit disingenuous.

Hmm yeah I really think that the US government doesn’t have access to my Claude chats and wouldn’t be able to without jumping through actual legal hoops like a subpoena or other legal order. More than happy to be wrong if you have a source that points in that direction.

I think it’s a real concern. Chinese companies are much more closely tied to the state, as in if you decide to go to China one day they might already have all the data on how you have interacted with their models.

The US is certainly inching in that direction but it’s not like someone from the US government sits at Anthropic’s HQ reading chats from state people of interest.

I feel like the topic has been discussed ad nausiem but:

* Software security - I.e. Mozilla blog post on using Mythos for software security [1]

* Algorithms - AlphaEvolve makes real progress on matrix multiplication [2]

* Open source - Backlog crushing in openvpn [3]

* Corporate - CloudFlare Oauth workers [4]

People are clearly using AI to ship real work that people end up using directly or indirectly. Projects like Godot are also in a weird spot though.

[1]. https://blog.mozilla.org/en/privacy-security/ai-security-zer...

[2] https://arxiv.org/abs/2506.13131

[3] https://stanislas.blog/2025/12/claude-code-opus-open-source-...

[4] https://github.com/cloudflare/workers-oauth-provider

I think this is a false dichotomy. We’re getting lots of new productive output in some areas and in other areas it is too much slop.

Hmm but isn't your point moot if the GLM 5.2 type models are good enough to do these large scale port to Rust projects? Like maybe Anthropic goes bust but doesn't really matter for this case.

I feel like your conflating some general skepticism around the trillion dollar valuation of the US majors and their business model with the topic at hand - large scale C to Rust conversions and similar.

Could you explain your mental model of the situation a bit more?

Let's take something like GML 5.2 that is open source - anyone can run it on NVIDIA or AMD chips. People are currently making money by running GLM 5.2 Nvidia and AMD chips and selling inference on aggregators like openRouter.

So the cost to serve is like cost of Chip or financing for Chip + power and rackspace somewhere. We basically know that each year you will be able to server exponentially more inference per $ on Nvidia and AMD hardware as it gets to newer generations, so why would you expect the cost of inference on open models to also increase?

Like let's say not through a Chinese subsidized provider but like BaseTen https://www.baseten.co/pricing/ why would that get more expensive year over year?

So your prior is that token costs are only going to go up. Doesn't stuff like GLM 5.2 and Deepseek change this? I.e. something close to Opus 4.5 that runs 10X + more performantly.

I have been experimenting in this general area myself. I started by doing a port of Lua to Rust, then did Valkey to Rust using my Rust Lua for scripting, and now I've been working nginx in Rust.

I was thinking for all of these that the end goal is to take some existing technology and add some novel features rather than just X in Rust so what I have so far.

1. The Lua project bundles Lua 5.1 - 5.5 in one binary and one npm package so it's easy to run in the browser or CloudFlare Worker etc.

2. The Valkey (Redis) port builds something called EdgeStash - lets you run Valkey with Lua scripting in a CloudFlare Durable Object programmable with Lua scripting.

https://edgestash-valdr.ianmclaughlin1398.workers.dev/ that's a demo of the Edge Valkey node running.

I've been meaning to take take it and do something like yours that is sweet!

This thread is about a product based on fully reproducible research though so I feel like we should stay grounded. Claude science is meant to be used in the context of reproducible science research, there is a decent reason to not be cynical on future research being reproducible.

> if AI can reproduce such research it would be capable of doing such research itself

Well there is a big distinction between research validation and research generation, it is generally much easier to verify that a math proof is true or false than to find a truly novel proof.

But yes in the long run I’d think AI will be doing tons of research and it will by default reproducible. So maybe we’re aligned after all?

You can imagine using AI agents to tag papers that don’t have code or similar work attached and just filtering them out.

The Chinese open source community has made a lot of incentive to make research reproducible for example. The most reproducible works from I.e. deepseek get widely cited and adopted.

I don’t think we can just say “AI” and it’s fixed but with deliberate effort there’s reason to be optimistic.

Just as a counterpoint ML and AI research has become much more reproducible over time. I feel like this is relevant because ML / AI researchers are huge power users of AI tools.

Between 2016 and 2021 the share of ML/ robotics/ AI researchers being reproducible (ie contianing code and similar instructions to reproduce) doubled [1].

The major US labs have gone largely closed source (I.e. they no longer publish frontier research) but the Chinese ecosystem has incredibly reproducible code.

This is field dependent obviously but I think it atleast gives reason to be optimistic.

Yes people will churn out fake slop research, but it feels like that can be categorized and then ignored.

[1] https://arxiv.org/pdf/2308.10008

Isn't this just blanket cynicism?

In the long run conceivable we could use AI to hold papers to a much higher standard, audit all the data and code that is associated etc.