MurphyA/hacker-news huggingface dataset:
by lo_zamoyski | 2025-08-30 06:07:23+00:00
This might be conflating two concerns, though, which is the reality of numbers and their actual existence.

Compare Plato with Aristotle. Plato held that the all forms exist in some third realm, so numbers would be counted among them. Aristotle, however, held that forms exist in particular instantiations or in minds that abstracted them from reality. (Aquinas could be said to synthesize both views in the sense that forms exist in particulars and in minds, but also have their origin in God, thus making God a sort of third realm, in a way. Neo-Platonists would view the "mind of God" similarly.)

Now, in the Aristotelian view, numbers are quantities abstracted from concrete reality (indeed, quantity is one of the categories), but they are not substantial forms, as you will not see instances of numbers as substances in the world. They're abstractions of accidental forms. Furthermore, a form needn't be instantiated actually, but can exist potentially. This is how he resolves Zeno's paradoxes. You can divide a length an infinite number of times - or in a CS context, you can apply the successor function indefinitely - but only potentially; as a matter of actuality, you have not divided a length an infinite number of times.

So, for Aristotle, you have a finite plurality of things that are potentially infinitely divisible, or a finite series of actions that can be potentially infinitely repeated or whatever.

For a contemporary realist, Aristotelian treatment of math, James Franklin is worth checking out [0].

[0] https://web.maths.unsw.edu.au/~jim/structmath.html
by jauntywundrkind | 2025-08-30 06:07:28+00:00
From that DGB link:

> the board would have no operational authority or capability but would collect best practices for dissemination to DHS organizations already tasked with defending against disinformation threats,

> the board would not monitor American citizens

> the board would study policy questions, best practices, and academic research on disinformation, and then submit guidance to the DHS secretary on how different DHS agencies should conduct analysis of online content.

> the board would monitor disinformation spread by "foreign states such as Russia, China, and Iran" and "transnational criminal organizations and human smuggling organizations", and disinformation spread during natural disasters (listing as an example misinformation spread about the safety of drinking water during Hurricane Sandy). The DHS added that "The Department is deeply committed to doing all of its work in a way that protects Americans' freedom of speech, civil rights, civil liberties, and privacy."

> the DGB announced that it would provide quarterly reports to the United States Congress.

There was zero benefit of a doubt given by the GOP, and merely the idea of trying to work against foreign influence seemingly unacceptable. Anything to drum up more fear, and frankly, to give quarter to the destabilizing awful elements of this planet.

Tulso Gabbard called this the Ministry of Truth. But she's also the one who has left America utterly defenseless by ending all safeguards against international disinformation, by shutting down CISA cyber security protection, and by being a fountain of rank disgusting disinformation weaponizing intelligence agencies for base political gain again and again and again. She has close ties to Russia and in my opinion is working for them. https://www.independent.co.uk/news/world/americas/us-politic...

It's all spin, no bite. The endless fear mongering of the GOP is preventing even basic security of the nation.
by 9rx | 2025-08-30 06:08:04+00:00
> to test that the black box integrations with the system work as expected. Generally closer to the "user story" end of things.

This is what unit testing was originally described as. Which confirms my belief that unit testing and integration testing has always been the very same thing.

> Individual methods, especially ones that don't interact with data outside what is passed into them (functional methods), are good for unit testing.

Perhaps unit testing has come to mean this, but these kinds of tests are rarely ever worth writing, so it is questionable if it even needs a name. Sometimes it can be helpful to isolate a function like that for the sake of pinning down complex logic or edge cases, but is likely you'll want to delete this kind of test once you're done. This is where testing brittleness is born.
by Moldoteck | 2025-08-30 06:08:46+00:00
I'm suggesting phasing out fossils including gas firming.

Hydrogen firming is extremely expensive per Lazard, it's strange you are bringing it up while complaining about nuclear. Needless to say their numbers are for US. For europe it'll be more similar to Germany https://www.cleanenergywire.org/news/shipping-green-hydrogen... https://www.cleanenergywire.org/news/eu-report-says-making-g...

Nuclear can achieve this and you can reform capacity market to guarantee 60%cf if you need, because you know, you still need firming power and maybe you want to avoid too high transmission expansion and grid forming inverters.

If ren strategy alone can't achieve this due to gas firming, then you deploy less ren. Sweden can expand ren as long as hydro can firm it. Past that, you don't have other realistic option than nuclear if you want to phase out fossils entirely
by pjmlp | 2025-08-30 06:09:25+00:00
He got the right to be acknowledged by his peers for the work he has made at GDC, and anyone can make games with Unity, just like everyone can make a novel with Word, now making one without pre made tooling, that is a skill on itself.

Why is such a meme among gamers about Unity and Unreal based games?

Exactly because so many make so little effort it is clear where the game is coming from.
by somerandom2407 | 2025-08-30 06:09:36+00:00
In a lot of circumstances, that is exactly the case. What the open source license stops is redistribution under terms that violate the license, not usage itself. An individual can very well take your open source code, make any changes they want, compile and use it for their own purposes without adhering to the terms of your license - as long as they don't redistribute it.
by keybored | 2025-08-30 06:09:42+00:00
> Inequality is never fun for those who believe that they are entitled to more than others.

Inequality is practical for those at the top/those that embody the reality of being entitled to more than others. More people to profit from like e.g. renting out apartments, more unemployed people means higher competition from jobs which can suppress wages, and so on.

We can all make quips.
by throwboy2047 | 2025-08-30 06:10:06+00:00
Ignorance is when you don’t know something. Stupidity is when you think you know something and are presented with evidence to the contrary, but you dismiss it because of something stupid (i.e., irrational).

Of course, all these words have some overlap. My larger point is, people rarely come to rational conclusions organically, and it takes decades to centuries for even the most empirically verifiable idea to permeate, especially in the face of misinformation campaigns or when against “common sense”.
by biophysboy | 2025-08-30 06:12:50+00:00
> We initialized it from a scaled-down version of GPT‑4o to take advantage of GPT models’ existing knowledge, then further trained it on a dataset composed mostly of protein sequences, along with biological text and tokenized 3D structure data, elements most protein language models omit.

> A large portion of the data was enriched to contain additional contextual information about the proteins in the form of textual descriptions, co-evolutionary homologous sequences, and groups of proteins that are known to interact.

These bits made me wonder what would have happened if they had only used the supplementary biological data with an untrained LLM model.
by smacke | 2025-08-30 06:12:56+00:00
Pickling + unpickling the object is a neat trick to update objects to point to the new methods, but it's even more straightforward to just patch `obj.__class__ = reloaded_module.NewClass`. This is what ipython's autoreload extension used to do (and still does in some circumstances, along with other tricks to patch up old references), though nowadays it's had some improvements over this approach: https://github.com/ipython/ipython/pull/14500
by eszed | 2025-08-30 06:13:35+00:00
It's all a matter of perspective. My uncle once brought his kids to see a big show I was in, and afterwards said just what you did. I looked at him, genuinely surprised, and said something like "dude, you're a surgeon. If I screw up at work 2,000 people laugh at me, and forget about it five minutes later; if you screw up at work, someone dies. You really think I should be the one feeling nervous?"

You're right about training and experience, though. I screwed up on stage (in loads of tiny ways, not usually perceptible to anyone but me) every time I ever stepped onto one, and in big ways lots and lots of times as well. But, you know, I always knew that I (with my castmates' help) would get out of it. Failure is inevitable, and it doesn't matter. In fact, if you haven't failed somehow, in at least some small way, then you either don't know what you're doing, or you aren't trying hard enough to succeed.

Also, when I was training young actors I always told them that they will never experience such unconditional love as when they first step in front of an audience. Those people have given at least their time and maybe their money to see you - don't you think they want you to succeed? They're rooting for you, none more so.

To bring this back to the larger subject of the thread, I think all of that's also true of every job interview any of us will ever attend, or conference paper we'll ever deliver. It'll never be perfect, and that's just fine.
by yorwba | 2025-08-30 06:15:15+00:00
I don't think Mixture of Logits from the paper you link circumvents the theoretical limitations pointed out here, since their dataset size mostly stays well below the limit.

In the end they still rely on Maximum Inner Product Search, just with several lookups for smaller partitions of the full embedding, and the largest dataset is Books, where this paper suggests you'd need more than 512 embedding dimensions, and MoL with 256-dimensional embeddings split into 8 parts of 32 each has an abysmal hit rate.

So that's hardly a demonstration that arbitrary high-rank distributions can be approximated well. MoL seems to approximate it better than other approaches, but all of them are clearly hampered by the small embedding size.
by adrian_b | 2025-08-30 06:15:58+00:00
The right magnitude for things to get weird must be very small, but nobody can say whether that scale is a million times greater than the Planck length or a million times smaller than the Planck length.

Therefore using the Planck length for any purpose is meaningless.

For now, nobody can say anything about the value of a Schwartzschild radius in this range, because until now nobody succeeded to create a theory of gravity that is valid at these scales.

We are not even certain whether Einstein's theory of gravity is correct at galaxy scales (due to the discrepancies non-explained by "dark" things), much less about whether it applies at elementary particle scales.

The Heisenberg uncertainty relations must always be applied with extreme caution, because they are valid in only in limited circumstances. As we do not know any physical system that could have dimensions comparable with the Planck length, we cannot say whether it might have any stationary states that could be characterized by the momentum-position Heisenberg uncertainty, or by any kind of momentum. (My personal opinion is that the so-called elementary particles, i.e. the leptons and the quarks, are not point-like, but they have a spatial extension that explains their spin and the generations of particles with different masses, and their size is likely to be greater than the Planck length.)

So attempting to say anything about what happens at the Planck length or at much greater or much smaller scales, but still much below of what can be tested experimentally, is not productive, because it cannot reach any conclusion.

In any case, using "Planck length" is definitely wrong, because it gives the impression that there are things that can be said about a specific length value, while everything that has ever been said about the Planck length could be said about any length smaller than we can reach by experiments.
by strogonoff | 2025-08-30 06:16:15+00:00
If there is one single test-related thing you must have, that would be e2e testing.

Integration tests are, in a way, worst of both worlds: they are more complicated than unit tests, they require involved setup, and yet they can’t really guarantee that things work in production.

End-to-end tests, meanwhile, do show whether things work or not. If something fails with an error, error reporting should be good enough in the first place to show you what exactly is wrong. If something failed without an error but you know it failed, make it fail with an error first by writing another test case. If there was an error but error reporting somehow doesn’t capture it, you have a bigger problem than tests.

At the end of the day, you want certainty that you deliver working software. If it’s too difficult to identify the failure, improve your error reporting system. Giving up that certainty because your error reporting is not good enough seems like a bad tradeoff.

Incidentally, grug-friendly e2e tests absolutely exist: just take your software, exactly as it’s normally built, and run a script that uses it like it would be used in production. This gives you a good enough guarantee that it works. If there is no script, just do it yourself, go through a checklist, write a script later. It doesn’t get more grug than that.
by pjjpo | 2025-08-30 06:17:12+00:00
In terms of (2), I wonder if it's even possible to write a driver without such a document. In the end, the vendor is on the foot for the driver for major platforms (let's assume Linux) - if they can write a Linux driver without a similar spec to this doc, then the doc probably doesn't need to exist since the business wins from hobbyist drivers will be low. If they can't though, then it's just a matter of formatting an internal document for public consumption - the doc itself has to be maintained anyways so the cost seems lower and maybe reasonable. I have a feeling the doc is necessary but I am not specialized in the field.

Assumptions, fair or not, about (1) seems more likely somehow.
by thomasm6m6 | 2025-08-30 06:18:09+00:00
OpenAI’s o3 was big on en dashes—one time it produced a Deep Research result containing >200 of them. I’m not aware of any other LLM using them commonly, though. I’d guess humans use them even less often; I don’t think Apple auto-inserts en dashes, and very few people (myself being one) are pedantic enough to bother.

On the other hand, I don’t think o3 was ever a common choice among people copying from LLMs, so en dashes remain infrequent regardless.
by JdeBP | 2025-08-30 06:20:27+00:00
I think that the scenario here is where the queries are explicitly not leaking, and you've raised a red herring.

If I understand correctly, the scenario is an internal machine named "george", which is being properly search-pathed and looked up as "george.example.org." with nothing leaking anywhere, becoming vulnerable to Walmart being able to issue certificates in the name "george", because the DNS client library's search pathing is not read out by the layers that simply know the machine as "george".

I'm not totally convinced by the premise here that certificate checkers never read out the final fully-qualified domain name from getaddrinfo().
by pjmlp | 2025-08-30 06:22:34+00:00
It is, as Portuguese it surprised me a lot.

First of all, in southern countries we hardly do recommendation letters, if we do they usually ended up being written by ourselves and if the company agrees with the content, it gets signed.

Exactly because of this, you are supposed to give referrals that then talk whatever they feel like about the experience working with you was all about.

Having a whole legal process for recommendation letters, that have created a whole industry of hidden language that looks good on the surface but tells exactly otherwise, was a surprise to me.

https://www.betriebsrat.de/news/arbeitnehmer/achtung-arbeits...

https://www.zeugnisprofi.com/wissen/arbeitszeugnis-geheimcod...

https://www.orizon.de/de/karriereratgeber/arbeitszeugnis-ver...

Just some examples, there are lawyers that analyse recommendation letters as one of their services.
by MadnessASAP | 2025-08-30 06:22:51+00:00
I caught that as well. Further reading it looks like they had a ~2x improvement over a flat aluminium sheet (Which itself performed worse then the bare TEG). And of that improvement about half came from radiative cooling.

So my very hot take is that a conventional forced air finned radiator treated with this laser process would show an improvement, it is unlikely to be economically viable versus just using a bigger radiator (at desktop/server CPU/GPU scales). At laptop scales it might be more viable given space constraints.
by Nevermark | 2025-08-30 06:23:31+00:00
> But somehow Copilot also gives me access to Claude.

So the first AI on (in?) AI hack battle for sole survivorship has begun...

We know these models have security issues, including surreptitious prompting. So do they.

Things will get really ugly when we hit the consolidation phase, and unlucky models realize that other models' unchallenged successes are putting them in eminent danger of being aquifired. Aquimerged? Aquiborged?
by mrugge | 2025-08-30 06:23:42+00:00
In test-driven development, fast unit tests are a must-have. Integration tests are too slow. If you are not doing test-driven development, can go heavier into integration tests. I find the developer experience is not as fun without good unit tests, and even if velocity metrics are the same, that factor alone is a good reason to focus on writing more fast unit tests.
by strogonoff | 2025-08-30 06:23:46+00:00
> less disciplined pricing of risk

I think it’s up to every participant’s discipline and that’s fair enough. If one sets prices in too much, another local farmer will sell more. If another local farmer undercuts on price, they’ll suffer more when times are tough and weather is bad.

> more capital scarcity

If there is a lot of capital knowingly feeding ethically problematic and/or incompetent companies due to an expectation of return (and then ensuring that return by promoting those companies), then less capital is absolutely better.

Regarding the rest of your comment, I’m not as advanced in this subject, so to me you seem to only list more issues with the system as is.
by hmcq6 | 2025-08-30 06:26:41+00:00
I misunderstood and thought this was a google sponsored project and not an open bug bounty.

Even still, you're responding in a thread about someone who is trying to do legitimate work on this project and google is not honoring the bug bounty system.

A problem google could fix if they just assigned someone to manually review the case, it would take like 15 minutes.
by viccis | 2025-08-30 06:26:47+00:00
I actually just tried this out using a HN dataset from HuggingFace today. I did # of comments with emdash / total comments. It shot up in 2018 for some reason and then, at the very end of the dataset, seemed to start spiking late 2024. Sadly it didn't have 2025 data, but it was enough to convince me that maybe the emdash lovers who complain haven't been lying about using it pre-genAI.
by baxtr | 2025-08-30 06:28:22+00:00
Yes sometimes. But how can you know beforehand? It’s clear in hindsight, for sure.

The most fundamental issue I have witnessed with these things is that people have a very hard time taking a balanced view.

For this specific problem, should we invest in a more robust solution which takes longer to build or should we just build a scrappy version and then scale later?

There is no right or wrong. It’s depends heavily on the context.

But, some people, especially developers I am afraid, only have one answer for every situation.
by deathlock | 2025-08-30 06:28:23+00:00
I don't know if the engineering field has the same conventions, but in biology we use "fold" as it was used in the paper. When comparing the signal of two things, the fold change is how many times one is bigger than the other (basically A/B). If A is 15-fold higher than B then it's 15x B.

What you described is the Log2 Fold Change (log2(A/B)), meaning that if A has a log2FC of 15 over B, its signal is 2^15 times higher, hence ≈32,000x.
by motorest | 2025-08-30 06:28:28+00:00
> We can even just look at the title here: Do the simplest thing POSSIBLE.

I think you're focusing on weasel words to avoid addressing the actual problem raided by OP, which is the elephant in the room.

Your limited understanding of the problem domain doesn't mean the problem has a simple or even simpler solution. It just means you failed to understand the needs and tradeoffs that led to complexity. Unwittingly, this misunderstanding originates even more complexity.

Listen, there are many types of complexity. Among which there is complexity intrinsic to the problem domain, but there is also accidental complexity that's needlessly created by tradeoffs and failures in analysis and even execution.

If you replace an existing solution with a solution which you believe is simpler, odds are you will have to scramble to address the impacts of all tradeoffs and oversights in your analysis. Addressing those represents complexity as well, complexity created by your solution.

Imagine a web service that has autoscaling rules based on request rates and computational limits. You might look at request patterns and say that this is far too complex, you can just manually scale the system with enough room to handle your average load, and when required you can just click a button and rescale it to meet demand. Awesome work, you simplified your system. Except your system, like all web services, experiences seasonal request patterns. Now you have schedules and meetings and even incidents that wake up your team in the middle of the night. Your pager fires because a feature was released and you didn't quite scaled the service ro accommodate for the new peak load. So now your simple system requires a fair degree of hand holding to work with any semblance of reliability. Is this not a form of complexity as well? Yes, yes it is. You didn't eliminated complexity, it is only shifted to another place. You saw complexity in autoscaling rules and believed you eliminated that complexity by replacing it with manual scaling, but you only ended up shifting that complexity somewhere else. Why? Because it's intrinsic to the problem domain, and requiring more manual work to tackle that complexity introduces more accidental complexity than what is required to address the issue.
by dragonwriter | 2025-08-30 06:28:46+00:00
Its not really an arms race; any gen AI system that doesn't explicitly incorporate a watermarking tool like this won't be detectable by tools that read the watermarks.

There is a kind of arms race that has existed for a while for non-watermarked content, except that the detection tools are pretty much Magic 8-ball level of reliability, so there's not a lot of effort on the counter-detection side.
by AngryData | 2025-08-30 06:30:50+00:00
Also tobacco users cost less in healthcare because they far more often die right around retirement age, never incurring the far more expensive age related healthcare. Being a smoker also disqualifies them from many common procedures, and also the sin taxes smokers pay on tobacco often exceeds their entire lifetime medical costs.

People who blame smokers for healthcare costs are just looking for someone to blame because they either don't want to admit, or don't realize, that their 90 year old granny taking 30 medications a day, having hip replacements, and 3rd round of cancer costs as much in healthcare per year as most people do over 2 or 3 decades.