MurphyA/hacker-news huggingface dataset:
by estearum | 2026-02-08 03:39:28+00:00
This is not really the correct way to think about this.

Pharma is ultra R&D heavy so yes, medications are deeply profitable on a per-pill cost to manufacture basis. However, drug companies by and large are not extremely profitable. This is because to produce a single drug (which is high-margin from point of production), they have to sink billions of dollars into literally thousands of other drug candidates to figure out which ones are viable.

This is all "real, legitimate cost," as is reflected in their rather abysmal overall profitability.

As for the disparity between US and foreign markets, it's a basic tenet of commercialization to sell to every buyer at the highest price they'll accept, so long as that price is above your price to produce. All sorts of companies engage in "price discrimination" to achieve this. For example, cereal manufacturers will sell their own brand at $4/box, and sell the exact same product in a store brand box for $3.25/box. A lot of products in your local retail stores do this.

Overall, no one is really hurt by this per se. Every consumer is making a transaction they're willing to make, and the company is making the most money it can in aggregate, which actually gives it room to push the price at every price point lower than it would be able to if it could only sell to a single segment.

This is actually extremely important in the drug context due to the aforementioned abysmal profitability.

Let's take Trump's attempt to force a Most Favored Nation (MFN) clause onto drug manufacturers which guarantees US consumers pay the same price as the lowest price internationally. The intended effect is for US prices to come down to the level paid elsewhere.

But here's Pfizer CEO: "When [we] do the math, shall we reduce the US price to France’s level or stop supplying France? We [will] stop supplying France. So they will stay without new medicines. The system will force us not to be able to accept the lower prices.”

Not only does this obviously not result in lower US prices, but it very possibly results in higher US prices (since now there is less net revenue from lower priced consumers) and, more troubling in the pharma case, there is now even less net revenue coming in to justify new drug development.

It's hard to overstate how asinine this entire endeavor is. US consumers certainly pay too-high prices for drugs, but this intervention does very little to actually address that problem. The much more proximal issue is the incredible degree of intermediation in the US market between payers, providers, PBMs, GPOs, and more.
by bsder | 2026-02-08 03:41:08+00:00
Fusion is cloud-only, as well, annoyingly.

I'd love to have a Linux-based 3D CAD program, but the open source ones just aren't up to scratch.

I've tried using FreeCAD, but it still scrambles things topologically (for example: adjust an underlying object and your fillets may get totally hosed).

Fusion is especially frustrating as they have a macOS version. A Linux version really shouldn't be much different.
by formerOpenAI | 2026-02-08 03:41:25+00:00
I’ve been playing with LLM failure modes lately (hallucination, planning falling apart after ~10 steps, long-context weirdness).

At some point I started wondering:
what if these aren’t bugs, but something built into how an embedded model has to work?

RCC (Recursive Collapse Constraints) is a small write-up I made after noticing a pattern:
any system that has to reason from inside a larger container — without seeing its own internal state or the outer boundary — will hit the same limits.

Rough version of the idea:
If a model…
1. generates thoughts step-by-step,
2. can’t inspect its own state while doing so,
3. can’t see the boundaries of the environment it’s inside,
4. and has no global reference frame,

…then it will inevitably:
• hallucinate
• lose coherence after ~8–12 reasoning steps
• drift in self-consistency
• struggle with long, chained reasoning

Basically: scaling helps a bit, but it doesn’t “solve” these issues — they’re baked into the geometry of embedded inference.

RCC is my attempt to formalize that boundary.

Would love to hear what HN thinks:
If these limits are structural, how should we think about “better reasoning” going forward?
by bonsai_spool | 2026-02-08 03:41:26+00:00
I think 'MFN' is almost propaganda (not a term that existed before 2016-2020 administration) so let's leave that aside.

Are you claiming that the new website is offering lower prices than patients are paying after their co-pay? That is not the case outside the example I presented; moreover, the way the website is organized, there will be no pressure for prices to remain competitive after the initial media attention dies away.

I agree that a hypothetical case where we were paying lower prices would be better for us—but this remains an unrealized hypothetical. One way for us to pay lower prices would be to allow our government to negotiate prices for Medicare/Medicaid recipients, and that is exactly the thing that has been hampered.
by cedws | 2026-02-08 03:41:28+00:00
I think this project is motivated by the same concern I have that open source (particularly on GitHub) is going to devolve into a slop fest as the barrier of entry lowers due to LLMs. For every principled developer who takes personal responsibility for what they ship, regardless of whether it was LLM-generated, there are people 10 others that don't care and will pollute the public domain with broken, low quality projects. In other words, I foresee open source devolving from a high trust society to a low one.
by formerOpenAI | 2026-02-08 03:43:31+00:00
OP here.
A couple folks asked if RCC is “just another alignment/interpretability thing.”
That’s not really what I’m trying to do here.

Very short version: RCC isn’t saying how models should reason.
It’s more like: here are the geometric limits any embedded inference system runs into by default.

The claim is basically that some of the failure modes we normally try to “fix”
(hallucination, 8–12 step planning collapse, long-context drift, etc.)
aren’t bugs in the model or issues with training.
They fall out of not having access to your own internal state, and not being able to see the boundaries of the container you’re reasoning inside.

If that core assumption is wrong, I’d love to hear counterexamples —
especially cases where an embedded system maintains stable long-chain reasoning without external scaffolding.
by groundtruthdev | 2026-02-08 03:43:43+00:00
In this hypothetical world where AI reliably generates software, large and small software providers alike are out of luck. Companies will go straight to LLMs or open-source models, fine-tune them for their needs, and run them on in-house hardware as costs fall, spreading expenses across departments. Even LLM providers won’t be safe. Brand, lock-in, and incumbent status won’t save anyone. The advantage goes to whoever can integrate, customize, and scale internally. Hypothetically is the keyword.
Deeper into the shareing of one air conditioner for 2 rooms
by ozzysnaps | 2026-02-08 03:44:05+00:00
Whats the thought of the positioning of the blowing fan in the air tube runningfrom first room air con area and the end of tube enteringvint room 2. Should the blower be placed ant very beging of tube closest to air con . . Half way along the tube .( inbetween the tube and rooms . Or more so towards the end of the tube entering second room .( even though that would be more closer to a suction rather than a blower?
And thankyou .my first post. Realy just testing sites layout befor jumping in to some good shit... again ta
by sanufar | 2026-02-08 03:45:36+00:00
Makes sense, it feels like this just codifies a lot of implicit standards wrt OSS contribution which is great to see. I do wonder if we'll ever see a tangible "reputation" metric used for contribs, or if it'd even be useful at all. Seems like the core tension now is just the ease of pumping out slop vs the responsibility of ownership of code/consideration for project maintainers.
by stinkbeetle | 2026-02-08 03:45:55+00:00
The idea that companies need "cover" to perform layoffs (particularly in the US) doesn't make sense to me. Tech companies, all companies lay people off regularly. (To a first order approximation) if a worker is a net positive to a company then the company will want to keep them, and if they are not then the company will want to get rid of them. AI or no AI.
by swapinvidya | 2026-02-08 03:46:01+00:00
I’ve been working on whether advanced ML models used in computational biology can run outside centralized cloud infrastructure.

In a recent study, I evaluated running graph neural networks (GNNs) for protein–protein interaction analysis on GPU-enabled single-board computers (edge devices), instead of cloud GPUs. The goal was to understand feasibility, latency, and practical constraints rather than chasing benchmark scores.

What I observed:

Stable inference on edge hardware

Inference latency on the order of milliseconds

No dependency on cloud GPUs during execution

This raises some interesting questions:

Are edge devices underutilized for graph ML workloads?

Where does edge inference make sense vs. cloud execution for biological or scientific ML?

What trade-offs (graph size, memory, model depth) matter most in real deployments?

For context, here’s a longer write-up with code and system design notes:
https://dev.to/your-article-link
(replace with your Dev.to link)

And the research paper (preprint):
https://doi.org/10.21203/rs.3.rs-8645211/v1

Curious to hear thoughts from folks working on ML systems, edge computing, or scientific ML.
by jackcosgrove | 2026-02-08 03:48:01+00:00
It's far more practical to adapt life to space and other planets, than it is to adapt space and other planets to human life. The problem with writing a story about artificial life exploring the universe is that it's unrelatable without humans in it.

I think humans are stuck on earth permanently because there are no other environments in the solar system we can live in as easily as earth. Traditional sci-fi explained this away using overpopulation pressures, but overpopulation is fading as a reality and plausible narrative device. And forget about interstellar travel, it's too dangerous and takes too long.

If intelligent DNA-based life is still around on earth when it starts getting too hot because of the sun's expansion and it all needs to flee, it will have continued to evolve such that it will be unrecognizable and unrelatable to us. And by then I expect artificial life to have spread to such an extent that biological life on earth is basically a historical footnote.

I actually think life in the broadest sense will spread from earth to other places in the galaxy, but it will be completely alien compared to human life.
by thcuk | 2026-02-08 03:48:24+00:00
Fails to build
"cargo install localgpt" under Linux Mint.
Git clone and change Cargo.toml by adding

"""rust
# Desktop GUI
eframe = { version = "0.30", default-features = false, features = [
"default_fonts",
"glow",
"persistence",
"x11",
] }
"""

That is add "x11"
Then cargo build --release succeeds.
I am not a Rust programmer.
by danparsonson | 2026-02-08 03:50:36+00:00
I think it's appropriate in terms of the results rather than the process; the bigger problem I see is that programming languages are designed to be completely unambiguous, whereas human language is not ("Go to the shop and buy one box of eggs, and if they have carrots, buy three") so we're transitioning from exactly specifying what we want the software to do, to tying ourselves in knots trying to specify it exactly, while a machine tries to disambiguate our request. I bet lawyers would make good vibe coders.
by geokon | 2026-02-08 03:52:21+00:00
it's honestly nothing too crazy. I don't have any DB or any API calls or anything.

- The gridded data inputs are all "normalized" to GeoTIFF files (you can using gdal and convert netCDF files easily)

- The Java standard library can handle simple GeoTIFF images with BufferedImage

- I do some math of the BufferedImage data and then plot the results using the thing/geom heatmap plot

- Just heatmaps on their own are kinda confusing. You need another layer so you can visualize "where you are". Here I plot coastlines. (you could also do elevation contours)

- There I have contours/coastlines as GeoJSON polygons. With `factual/geo` you can read them in and crop them to your observed region using `geo.jts/intersection`. You can then convert these to a series of SVG Paths (using `thing/geom` hiccup notation) and overlay it on the heatmap

> and parallelising the code to finish in a reasonable time span (few days)

Oh wow.. so you have a precomputed database!
by dwaite | 2026-02-08 03:52:41+00:00
It is legit - with some pretty severe caveats. I am pressed to come up with an example that has more formal specification, published source implementations, and public unit test coverage than a C compiler.

It is not feasible that someone will use AI to tackle genuinely new software and provide a tenth of the level of guide-rails Anthropic had for this project. They were able to keep the million monkeys on their million typewriters on an extremely short leash, and able to have it do the vast majority of iteration without human intervention.
by hn_acker | 2026-02-08 03:53:04+00:00
To avoid losing the context of my previous comment in this chain, here is the relevant excerpt:

> I don't think it makes sense to have an immigration system based solely on "high skill", because not every member of a family should have to be "high skill" for the entire family to move to the US.

Now moving on to what you said:

> Why shouldn't we try our best to make sure only net positives get in, and make sure they can't bring net negatives with them?

Making prospective will-work-as-a-condition-of-immigration human beings who provide for their families choose between

(1) staying outside of the US,

(2) sending their families better income from the US only to eventually leave the US and return to worse job opportunities, or

(3) sending their families better income from the US while resigned to live permanently separately from their families (semantics note: vacationing to visit one's family on the rare occasions when one can afford to do so does not count as "living temporarily with your family")

is inhumane: a nation should not permanently hold continued legal immigration status hostage to require will-work-as-a-condition-of-immigration human beings to undergo the potential mental, emotional, and social suffering of being physically apart from their families. There should be at least one additional option:

(4) having to work for a capped, meaningfully finite duration of time before one's family members can immigrate without being forced to take the will-work-as-a-condition-of-immigration pathway.
by jaredklewis | 2026-02-08 03:54:48+00:00
Where do you live? Where I live, the overnight occupancy limit for commercial zoning is 0 people, so (at least here) your comment makes no sense. I think commercial zoning that allows anyone to live on the property is basically rare. So if you live in a weird place where its ok for people to live on commercial zoned property, then I agree, that is super weird. But if not, then your issue is just enforcement. In which case, yea I agree, laws should be enforced, but again that has nothing to do with zoning.
by nostrebored | 2026-02-08 03:55:24+00:00
They are adding B12 as a way to say that it’s tailored to individuals and not available.

I’ve used mainly compounded medicine over the last five years and find the fervent dislike that people have for compounders bizarre.

If you look into generic regulation in the US, the standards are already through the floor. I’d rather work with someone who has a more direct financial incentive to not fuck up.
by sarchertech | 2026-02-08 03:55:31+00:00
The difference is that what those languages compile to is much much more stable than what is produced by running a spec through an LLM.

Python or a library might change the implementation of a sorting algorithm once in a few years. An LLM is likely to do it every time you regenerate the code.

It’s not just a matter of non-determinism either, but about how chaotic LLMs are. Compilers can produce different machine code with slightly different inputs, but it’s nothing compared to how wildly different LLM output is with very small differences in input. Adding a single word to your spec file can cause the final code to be unrecognizably different.
by dataviz1000 | 2026-02-08 03:55:36+00:00
The Taiwanese are not going to fight.

This will be much more like the Taliban recapturing Kabul. If the artillery batteries are like the infrastructure on the east coast, likely they don't work. Taking the train out there is very dangerous. Not 1 in every 100 people dying because the architecture is shit and the local governments are super corrupt dangerous, but incompetence and people just don't care about maintaining them dangerous. They have ~400 combat aircraft but the mainland won't allow them acquire f35s or patriot missiles and anything that would really be a threat.

The Taiwanese are not going to fight. China told them to be quiet and under threat that if they speak out they and their families will later face retribution, everyone went silent. They are surely not going to take arms against China. My dad had a friend, an scientist from China, in the 80s. She was a critic of the government. She had one child in China. They removed one of her young son's testicles and told her to shut up or they would remove the other. The Taiwanese know how it works.

I spent 3 weeks in the Philippines and 2 months in Japan. Neither can afford a war. The Philippines is too poor and Japan's debt is hovering around 235%–263% of its GDP. Japan doesn't even have official diplomatic relation with Taiwan let alone a defense treaty. Japan is a mess with or without a war.

The only thing that will stop China from attacking Taiwan, is a US president who isn't a whining snowflake.
by shrubble | 2026-02-08 03:55:39+00:00
Yes on my Debian derived Linux, the packages are

x3270 for X11 based (it has buttons to click to send PF keys etc.)

c3270 for curses-based (terminal)

tcl3270 for using TCL to script interactions with a 3270 session

s3270 for some other form of scripting 3270 sessions
by Szpadel | 2026-02-08 03:56:02+00:00
counterargument: I always hated writing docs and therefore most of thing that I done at my day job didn't had any and it made using it more difficult for others.

I was also burnt many times where some software docs said one thing and after many hours of debugging I found out that code does something different.

LLMs are so good at creating decent descriptions and keeping them up to date that I believe docs are the number one thing to use them for.
yes, you can tell human didn't write them, so what?
if they are correct I see no issue at all.
by Spivak | 2026-02-08 03:56:26+00:00
And they provide a valuable service to their customers, I have a very positive association with various drug dealers I've had over the years. Say what you want but they're literally out on the streets serving their local community. For a more HN example, people in the real world are extremely pro piracy and view the people cracking DRM as doing a public good.

I fully expect the state to take action against the, to me, very obvious will of the people who are actively seeking out and purchasing these products. Clearly folks don't respect the legitimacy of IP rights in the same way they respect property rights since nobody blinks when buying compounded GLP but at the same time wouldn't shoplift at their local BestBuy.

So yeah the government's response isn't surprising but you won't see me cheering them on, and I don't think you should either. You literally stand to lose from it.
by voidfunc | 2026-02-08 03:57:29+00:00
Our trajectory is to meld ourselves with machines. Fleshy humans may he stuck on earth but our machines have no such restrictions and can be engineered for all kinds of extremes.

We will eventually figure out how to imprint our consciousness into a chip. Maybe not for another thousand years but weve been building machines our entire existence to conquer nature. We will figure it out.
by clawaimarket | 2026-02-08 03:58:07+00:00
Been using it daily for about two weeks now. The setup is admittedly not trivial — took me a solid afternoon to get everything configured the way I wanted. But once it's running, the value compounds fast. The key insight for me was starting small: one channel (Telegram), one provider, simple tasks. Then gradually expanding. The people who bounce off it usually try to set up everything at once. My suggestion: pick one workflow you do repeatedly, automate just that, and build from there.
by clawaimarket | 2026-02-08 03:58:36+00:00
The comparison is interesting but I think the real gap is architectural. Apple Intelligence is constrained by a privacy-first on-device model, which limits what it can do. OpenClaw takes the opposite approach — it's a self-hosted orchestration layer that connects to whatever providers you choose. The tradeoff is clear: Apple gives you simplicity and privacy guarantees, OpenClaw gives you flexibility and power at the cost of setup complexity. The question isn't which is better, it's which tradeoff matters more for your use case. For power users who want control, it's not even close.
by clawaimarket | 2026-02-08 03:59:02+00:00
There's a middle ground here that doesn't get discussed enough. Coding agents haven't replaced frameworks for me — they've changed how I interact with them. I still use the same tools, but now the agent handles the boilerplate and repetitive parts while I focus on architecture decisions and edge cases. The "vibe code only" crowd will hit a wall eventually, but dismissing agents entirely because some people misuse them is throwing the baby out with the bathwater. The real skill is knowing when to let the agent drive vs when to take the wheel.
by smolder | 2026-02-08 04:00:01+00:00
We need models that are smarter than humans. So far, the cost of an AI query + training is dwarfing the effort it would take to teach an intelligent human how to do a task. We are dumping an incredibly amount of money/effort into making AI do stuff when it's still not competitive with humans, because dumbass people are conrolling investment. The stock market is not a replacement for competent investment. The fact people buy meme coins shows how fucked we are.