MurphyA/hacker-news huggingface dataset:
by pseudohadamard | 2026-02-15 06:49:50+00:00
It's worse than that, some of them are actually dangerous! Amazon seems to have removed this review but here's a copy of the original text:

1.0 out of 5 stars

Reviewed in the United States on November 15, 2010

We live underground. We speak with our hands. We wear the earplugs all our lives.

PLEASE! You must listen! We cannot maintain the link for long… I will type as fast as I can.

DO NOT USE THE CABLES!

We were fools, fools to develop such a thing! Sound was never meant to be this clear, this pure, this… accurate. For a few short days, we marvelled. Then the… whispers… began.

Were they Aramaic? Hyperborean? Some even more ancient tongue, first spoken by elder races under the red light of dying suns far from here? We do not know, but somehow, slowly… we began to UNDERSTAND.

No, no, please! I don’t want to remember! YOU WILL NOT MAKE ME REMEMBER! I saw brave men claw their own eyes out… oh, god, the screaming… the mobs of feral children feasting on corpses, the shadows MOVING, the fires burning in the air! The CHANTING!

WHY CAN’T I FORGET THE WORDS???

We live underground. We speak with our hands. We wear the earplugs all our lives.

Do not use the cables!

8,955 people found this helpful
by beloch | 2026-02-15 06:50:35+00:00
It's possible to put holes through things without a drill. People can get onto islands without boats. How do you define rope, and what else might cause similar wear? Are you certain you can distinguish them?

Archaeology has come a long way over the last couple of centuries. It used to be little better than grave robbing and crackpot (often racist) theories. Archaeologists made all sorts of assumptions that turned out to be ridiculously (and sometimes tragically) wrong. Excavations once involved dynamite and bulldozers. Things have changed. Techniques for re-analyzing and extracting new information from old finds are allowing archaeologists to make discoveries without digging at all. Even a careful, modern dig is a destructive act that can only be conducted once.

It's not frustrating. It's progress.
by victormy | 2026-02-15 06:51:43+00:00
I’m also maintaining an open-source project and have spent significant time drafting our CLA, so I completely understand the concerns surrounding them.

While DCO is excellent for tracking provenance, we opted for a CLA primarily to address explicit patent grants and sublicensing rights—areas where a standard DCO often lacks the comprehensive legal coverage that a formal agreement provides.

It’s a common and sustainable practice in the industry to keep the core code open-source while developing enterprise features. Without a solid CLA in place, a project faces massive legal hurdles later on—whether that’s for future commercialization or even the eventual donation of the project to an open-source foundation like the CNCF or Apache Foundation. We're just trying to ensure long-term legal clarity for everyone involved.
by valenterry | 2026-02-15 06:52:29+00:00
Google isn't even good at engineering great software.

They have some good people working on some good projects. If you look at the relation between software-quality of their average product and number of developers they have... yeah I don't know. Maybe hiring tons of new-grads that are good at leetcode and then forcing them to use golang... is not what actually makes high quality software.

I could believe that they are good at doing research though.
by jhanschoo | 2026-02-15 06:52:49+00:00
> A chance for real connection and healing that isn't vulnerable to the whim of a tech giant and its compulsion for profit.

That "chance" had years to materialize that did not. Perhaps the worst thing that happened here was that the chatbot did not steer her to resilient human connection when she was in a self-reported better state after the help of the chatbot
by hedayet | 2026-02-15 06:52:50+00:00
[author here] Very good questions; I definitely would like to revisit num32 very shortly. I'd say the initial rational of having num32 is not coherent right now, but I'll have to verify removing the support.

we have floating point type(It was missing from the type list in readme. I have just updated that seeing this comment. thank you!)
by bruce511 | 2026-02-15 06:52:53+00:00
I presume you mean web-on-desktop? Since a dumb phone doesn't have a browser?

I came late to phones, resisting them till 2013. Up to that point I could function with desktop alone. Today, it's not possible (for me.)

Authentication is a big part of it. My (web) access to my bank demands a selfie photo on my phone. Plus endless other systems.

Outside of work, all communications is via WhatsApp. I pretty much don't even read SMS's anymore. They're 99% spam or scam. And it's not just person to person, all social activities from church to sport to band etc are all on WhatsApp.

I use maps only a couple times a year, but when I need it, I really need it (cause I'm not where I expected to be.)

I don't do social media, or email, on the phone. Both if which frankly lead to problems in some situations.

I'm traveling this year and the number of tickets (train and museum) that can only be used from a phone is impressive.

I applud your desire to remove the phone from your life, especially if you are distracted by it. But you may find that it's hard to do. I'm not interested in "work arounds", I want to get stuff done, not fight everything about my life.

So I recommend, get a dumb phone and use that. You'll quickly discover what's missing every time you have to reach for the smart phone.
by lelanthran | 2026-02-15 06:54:14+00:00
> However, the entire argument hinges on one assertion, buried about halfway through:

>> Robots are improving fast, but I do not believe that this cute fellow will be stuffing envelopes or affixing stamps anytime soon.

Okay, lets presume he is correct; the conclusion is still "We will do the unthinking manual work requirign physical dexterity while the computers will direct us".

That's not a positive outcome.
by quarkcarbon279 | 2026-02-15 06:55:42+00:00
Hey, we have various configurations available even in this very early preview: https://rover.rtrvr.ai/docs/configuration and you can turn off telemetry so we don't collect the data . As a website you can also configure to host the script on your preferred endpoint and our 'apiBase' helps with that pointing to custom domains. And based on project data needs we are also open to tighter data policy rules.
by lostlogin | 2026-02-15 06:56:24+00:00
Sorry, I edited my above comment to remove references to myself.

For clarity, I’m an MR tech and I can get scans of myself if I want to.

I generally don’t scan myself as it gets messy fast. If I had concerns and for some reason couldn’t get a proper imaging referral, I’d get a scan with small, good coils with high element counts (not body coils like whole body imaging uses) and scan individuals body regions.
by chiffaa | 2026-02-15 06:57:02+00:00
From this perspective - not sure, to be honest. For me an important factor was that Zed is getting way more love from its devs than my old editor of choice Helix. But also not being constrained to a cell grid is very nice in terms of readability to me.

One thing that Zed doesn't solve but likely will is that I found "jump to label" style of features (I think flash.nvim is the closest for neovim?) is almost unreadable to me with inlined labels, but that's so highly specific I'm almost willing to live with it
by rich_sasha | 2026-02-15 06:57:06+00:00
Can someone ELI5 why false positives on a MRI are so bad?

From a pure Bayesian PoV, you're better off with a noisy additional observation. At worst it doesn't get much weight.

At a pragmatic level, can't you say, hey here's something thats probably nothing, let's scan it again in 6 months? Why does an MRI necessarily lead to invasive follow ups?

I get that ideally we'd have a crystal ball with 0 type I / type II errors but short of that, why is a noisy predictor bad?
by themafia | 2026-02-15 06:57:35+00:00
The challenges I have were selected because I enjoy solving them and because very few, if any, people have taken the time to work on them already. As such I have no desire to "one-shot" a solution and I additionally have serious doubts that any model trained on any existing code could possibly output anything useful or anything that truly fits into the design of the system. These projects are written for style and are to explore ideas and gain experience. Inviting an LLM in out of laziness is completely the opposite of my intentions.

The only other code that I write is for a handful of industry specific products that are not challenging in any way to code but are fun to design for the specific needs of my users and are informed by their incredible feedback from the field. The time and effort to play games with an LLM prompt would have effectively zero value here and again is the opposite of what makes these products great enough to be sold by word of mouth alone.

Aside from all of this I have no desire to pay a subscription to a service that requires me to submit all of my code to their engine for output. Given their models apparent fondness for taking copyrighted code and passing it off as it's own I would not put it past them to play games behind my back with my work.

Finally I see no new "AI billionaires" suddenly rising out of the field and I see no "AI heavy" companies suddenly increasing their profits, productivity or quality in any way. I hear what you are saying, and you're certainly not alone in saying it, but I see zero evidence that it's actually meaningful in the real world software market.
Which past applications you built can be migrated to Agentic architecture?
by sanatku | 2026-02-15 06:57:48+00:00
Recently I've been learning about [LLM-powered ReAct architecture](https://arxiv.org/pdf/2210.03629) for designing software solutions. I've also worked on a high-scale production implementation of this approach, which got me thinking about all the applications I've built in the past.

Theoretically, any of them could be implemented using the ReAct architecture, but I'm still grappling with when this makes sense and when it doesn't. Some applications clearly benefit from LLM-backed reasoning—particularly those with heavy business logic that changes frequently. In these cases, updating prompts could replace code changes, potentially enabling product teams to directly influence system behavior without engineering involvement.

On the other hand, static data processing pipelines seem like poor candidates for this architecture. When the logic is stable and deterministic, the overhead and unpredictability of LLM inference doesn't add value. The sweet spot appears to be applications where business rules evolve rapidly and the cost of maintaining traditional code outweighs the complexity of prompt engineering.

https://www.sanathkandikanti.com/meditations
by mmooss | 2026-02-15 06:58:08+00:00
> The Kamitakamori tools? Piltdown fossils? The pattern roughly seems to be "if you have physical artifacts that support a theory / fit a pattern they will be accepted (even if bogus)

Two examples from over a century is not evidence of unreliability.

> if you have a theory that explains facts (e.g. drilled holes) but no physical artifacts (in this case drills) it will be rejected".

Evidence is a requirement in all scholarship; the rest is speculation - which can be useful as a direction for searching for evidence, but is not sufficient to be accepted in any field. What field accepts claims without evidence?
by AlotOfReading | 2026-02-15 06:58:41+00:00
Piltdown was rejected 70 years ago, so hardly a current example. Kamitakamori was someone taking legitimately old artifacts and putting them in other places. You can detect that (as people did), but it's much less obvious than you're suggesting.

There are also numerous examples where physical artifacts haven't been immediately accepted. The white sands footprints. Monte Verde II. Others like Monte Verde I, Buttermilk Creek, and Cooper's ferry still aren't accepted despite physical evidence.

Consensus generally has high standards for anything that pushes boundaries. It's very easy to construct an "obvious" explanation that's totally wrong. We call these "just-so" stories. A narrative that's supported by physical evidence is a lot more verifiable.
Show HN: AI-optimized x86-64 assembly vs. GCC -O3 on three production kernels
by cod-e | 2026-02-15 06:58:46+00:00
Show HN: AI-generated assembly vs GCC -O3 on real codebases (300K fuzz, 0 failures)
Three kernels extracted from real open source projects, optimized with AI-generated x86-64 assembly, verified with 100K differential fuzz each:
KernelAI strategySpeedupVerdictBase64 decodeSSSE3 pshufb table-free lookup4.8–6.3xAI winsLZ4 fast decodeSSE 16-byte match copy~1.05xAI wins (marginal)Redis SipHashReordered SIPROUND scheduling0.97xGCC wins
The base64 win: GCC can't auto-vectorize a 256-byte lookup table (it's a gather pattern). The AI replaces it with a pshufb nibble trick — 16 parallel lookups in one instruction, zero table accesses. 1.8 GB/s → 11.6 GB/s.
The SipHash loss: on pure ALU kernels (adds, rotates, XORs), GCC's scheduler is already near-optimal.
300K total fuzz iterations, zero mismatches. Every result is one command to reproduce.
by microflash | 2026-02-15 06:59:59+00:00
I came to the same conclusion a while ago. You can get a lot of mileage by tweaking EQ. For me almost all headphones felt flat until I tried a bunch of studio monitors. They are not portable but I’ve been using a cheap AKG K72 pair at home and it has been great. Your experience may vary but do try a bunch of options, as suggested by parent.
by chmod775 | 2026-02-15 07:00:40+00:00
> I may have something to teach you about indicators, averages, and population samples/biases.

You didn't sample. You filtered. You used a search engine to zero in on a couple dozen in a population of 8 billion, then try to suggest to me that the mere fact that there's at least some means it's some widely held opinion, when in fact it's clearly not even going by the references you selected yourself.
by Moto7451 | 2026-02-15 07:02:14+00:00
PET Scans feature areas with blood flow so tumors show up as hot spots for follow up. People who are maybe only feeling off or had one confirmed tumor can have a lot of small tumors spread across their body which will show up clearly on a PET scan.

When my brother was at the end of his run fighting cancer he felt a bit under the weather and managed to catch covid so everyone figured he was feeling bad due to that. The PET scan showed he had thousands of small masses converging into the large mass that eventually killed him by cutting off blood flow to his kidneys. His cancer was an aggressive blood cancer that had stood up to conventional and Trial Chemo drugs. There was no way to treat this but other cancers that are less aggressive can be treated at this point and would be treated differently than a single mass.

In a nutshell it’s that level of visibility that makes PET scans worth it.
by ssivark | 2026-02-15 07:02:15+00:00
Google Chat is definitely a product that could use more love, but it is situated in a specific internal landscape, and grows out of it. Slack is built for a very different context, and I doubt Google would build something like that. Google simply doesn't see the world the way someone who likes Slack would (and I also doubt a large co like Google could operate out of Slack).
by cod-e | 2026-02-15 07:02:35+00:00
Author here. Some context on how this works and what it doesn't do.
The system doesn't replace the compiler. It sits on top of it. The key insight (which took a few failed experiments to learn) is that AI-generated assembly is dangerous for code with error handling, state, and control flow — but strong on pure computational kernels.
We tried having the AI rewrite an entire packet parser. It shipped two bugs (flag clobbering, unsigned underflow) and was 1.23x slower than GCC. Then we split the architecture: compiler owns all structural code (validation, error paths, bounds checks, state management), AI only optimizes the inner kernel after all checks pass. Same parser, zero bugs on first try, clean performance win.
That's the design principle behind everything here. The compiler guarantees correctness by construction. The AI only touches pure load/transform/store kernels with no branches. Then we verify with 100K differential fuzz — run random inputs through both versions, compare output byte-by-byte.
What the AI is good at: spotting SIMD opportunities GCC misses. The base64 case is textbook — GCC sees a 256-byte lookup table and generates scalar loads. The AI recognizes that base64's alphabet can be decomposed into nibble ranges and uses pshufb to do 16 parallel lookups. That's not a novel technique (simdjson and others use it), but the point is the AI found and applied it automatically.
What the AI is bad at: pure ALU scheduling. SipHash is adds, rotates, and XORs with tight data dependencies. GCC's instruction scheduler already does this near-optimally. The AI tried and lost. The system reports that honestly.
The verification reports and build scripts are in the repo — every number is one shell command to reproduce. Happy to answer questions about the architecture, the failure cases, or where this goes next.

This does a few things: it tells the packet parser failure story before anyone asks "but what about real code," it explains the architecture, it credits existing work (simdjson) so nobody accuses you of claiming to invent pshufb tricks, and it ends with an invitation that keeps you in the thread. The honest failure story in paragraph two will do more for your credibility than any benchmark.
by SilverElfin | 2026-02-15 07:03:52+00:00
I generally agree with the article. We can debate timing, but whether it is 1 year away or 10 years away, a major rise in employment is not something America is prepared for. No politicians even talk about this threat seriously, let alone come up with solutions for it. But in a world of higher automation and reduced need for labor, the only practical solution is to redistribute wealth and power in the country. Otherwise, those who enter this new era with wealth or power will be in a permanent ruling class while others suffer.
by andrewflnr | 2026-02-15 07:04:41+00:00
They didn't say things should be accepted without evidence. That's a laughably bad-faith reading. They proposed a different standard of evidence that they think is less infeasibly high while still not accepting nonsense. I don't totally agree but it's a reasonable direction to argue.

As for the examples, when they start with "swings over the years" they're clearly taking a long-term perspective, and not trying to claim that modern archaeology will "believe anything" (especially not when their more prominent claim is that modern archaeology believes too little).
by hedayet | 2026-02-15 07:05:48+00:00
[author here] ROX avoids implicit structural sharing and persistent data structures. Allocation and mutation are explicit - if I want a modified container, I construct one.

This is intentionally more resource-intensive. ROX trades some efficiency for simplicity and predictability.

The goal is clarity of logic and clarity of behavior, even at slightly higher cost. And future optimizations should preserve that model rather than hide it.
by rsynnott | 2026-02-15 07:06:24+00:00
So, first of all “but it’ll get better” has been the AI refrain since the 1950s. Voice recognition rapidly went from “doesn’t work at all” to “kinda works” in the 80s-90s, say, and in recent years has reached the heady heights of ‘somewhat useful’, though you still wouldn’t necessarily trust your life to it.

But also… okay, so maybe AI programming tools get good enough at some point. In which case, I suppose I’ll use them then! Why would I use a bad solution preemptively on the promise of jam tomorrow? Waiting for the jam surely makes more sense.
by canucker2016 | 2026-02-15 07:09:07+00:00
Yes, MS Mail for PC Networks used a shared file system for email.

The Workgroup Apps (WGA) divison ran MS Mail for PC Networks since they produced MS Mail. Gotta dogfood your product. The WGA email system used a Xenix gateway to connect with the rest of Microsoft.

The rest of Microsoft ran MS Mail for Windows with a Xenix email backend and address book, since MS was already using Xenix before MS Mail for PC Networks existed.

Windows for Workgroups 3.11 contained a one postoffice-version of MSMail, (which could be upgraded to the full version).

Some more Microsoft email-related history at https://en.wikipedia.org/wiki/History_of_Microsoft_Exchange_...
by somenameforme | 2026-02-15 07:09:27+00:00
No agreement is necessary under law, only knowledge of an illegal activity and an intent to help it succeed. Agreements just tack on new charges like criminal conspiracy. This is why the peer comment about Waze is interesting. They likely have a fairly strong argument that it's simply sharing publicly available information - which is of course 100% legal, while I think ICEBlock will likely lose a very open and shut case because it's entire purpose is to facilitate the evasion or disruption of law enforcement.

I expect the government is probably thrilled to get sued by ICEBlock precisely because of this. It's probably about as favorable a case as they could ever find, and ICEBlock losing will set a highly useful (from the government's perspective) legal precedent which will then probably be weaponized to go after stuff like Waze.
by alexey-salmin | 2026-02-15 07:10:17+00:00
There's a theory that the first-stage cancer is way more common than we think, it's just doesn't develop further most of the time, cause no symptoms and remains undiagnosed throughout the lifetime.

There's some support for this view because agressive screening for thyroid and prostate cancers increases the number of surgeries a lot but doesn't seem affect the mortality rates.

Risks from a surgery are non-negligible, if you perform it to treat a low-risk condition it may be a net loss in the end.

So you're technically right about the "early-detecting" part, but the "much easier to treat" step is problematic because it's unclear what a net-positive treatment looks like for low-risk cases. Probably it comes down to yearly monitoring of whatever was detected, not the actual treatment.
by mediumsmart | 2026-02-15 07:12:02+00:00
Maybe try something new. Lift the embargo and let the regime fail by itself after 66 years of this. 66 Years.

A 2023 study by the Cuban Observatory of Human Rights estimated that 88% of the population lives in extreme poverty.[28] According to the World Food Programme of the United Nations, rationed food meets only a fraction of daily nutritional needs for many Cubans, leading to health issues.[29] Ongoing since 1960, the United States embargo against Cuba stands as one of the longest-running trade and economic measures in bilateral relations in history.[30]

The U.S. government influences extraterritorial trade with Cuba. The embargo has faced international criticism for its adverse impact on Cubans, including by the United Nations who have formally condemned it intermittently since 1992.
by tomjen3 | 2026-02-15 07:12:51+00:00
I hope I don't suffer from early onset Alzheimer's, but I seem to recall the joke pre the pandemic was that Google would constantly make new chat apps.

Google Dou, Google Chat, Google Wave, Google this, Google that. Seemingly because someone needed a promotion and the way to do that was to create a new chat app or lead the effort for the same.