MurphyA/hacker-news huggingface dataset:
by westurner | 2025-08-21 22:51:58+00:00
TPUs are more efficient at LLMs because they do more TOPS/KWh.

"OpenTPU: Open-Source Reimplementation of Google Tensor Processing Unit (TPU)" (2025) https://news.ycombinator.com/item?id=44111452

"A Comparison of the Cerebras Wafer-Scale Integration Technology with Nvidia GPU-based Systems for Artificial Intelligence" (2025) https://arxiv.org/html/2503.11698v1

From https://news.ycombinator.com/item?id=44648575 :

> "Next-generation datacenters consume zero water for cooling" (2024) https://news.ycombinator.com/item?id=42376406

>> this design will avoid the need for more than 125 million liters of water per year per datacenter

"Microsoft’s Datacenter Community Pledge: To build and operate digital infrastructure that addresses societal challenges and creates benefits for communities" (2024-06) https://blogs.microsoft.com/blog/2024/06/02/microsofts-datac... :

> We will design and operate our datacenters to support society’s climate goals and become carbon negative, water positive and zero waste before 2030. [...]

> By 2025, we will procure 100% renewable energy on a global scale, both significantly expanding and decarbonizing local electricity grids.

> Our datacenter designs are more water efficient than traditional enterprise datacenters, and our plan by 2030 is to replenish more water than we consume locally.

Here's this about CNT cooling:

"Cyberpower begins selling desktop PCs with carbon nanotube CPU cooling" (2025) https://news.ycombinator.com/item?id=44899495

"A carbon-nanotube-based tensor processing unit" (2024) https://news.ycombinator.com/item?id=41322070

Graphene semiconductors should be at least 10X more energy efficient; but how much less water would graphene-based chips waste?
From GPT-4 to GPT-5: Measuring progress through MedHELM [pdf]
by fertrevino | 2025-08-21 22:52:14+00:00
I recently worked on running a thorough healthcare eval on GPT-5. The results show a (slight) regression in GPT-5 performance compared to GPT-4 era models.

I found this to be an interesting finding. Here are the detailed results: https://www.fertrevino.com/docs/gpt5_medhelm.pdf
by m00x | 2025-08-21 22:53:16+00:00
As a French, it's funny seeing references to the French revolution as some kind of rebellion against the rich.

Most people don't realize that the revolution was led by the nouvelle bourgeoisie ( new nobles) who were tired of paying taxes to the royals. They sacrificed thousands of commoners to reach their goals akin to how Russia is sending in soldiers into the meat grinder, and France was a much worse place afterwards for everyone.

The turning point was when Napoleon took over as a military dictator and ruled with an iron fist until the royalty took back the country yet again.

Merci d'avoir écouté un peu d'histoire Française, mes amis.
by jcranmer | 2025-08-21 22:53:59+00:00
When I worked at a water treatment plant, we produced about 160 million gallons/day of water in the summer time, and only about 80 million gallons/day in the winter time. Now ask yourself what water-consuming activities happen in summer that don't happen in winter.

Primarily, lawns. It's lawns. Most of the international difference in water consumption I would chalk up to lawns, given that the US has much larger average lot sizes and a much larger proportion of detached single-family houses (i.e., houses sitting in the middle of a lawn) than European countries have.
by CuriouslyC | 2025-08-21 22:54:23+00:00
Yes. Go on ChatGPT, explain what you're doing (claude code, trying to get it to be more rigorous with itself and reduce defects) then click deep research and tell it you'd like it to look up code review best practices, AI code review, smells/patterns to look out for in AI code, etc. Then have it take the result of that and generate a XML structured document with a flowchart of the code review best practices it discovered, cribbing from an established schema for element names/attributes when possible, and put it in fenced xml blocks in your subagent. You can also tell claude code to do deep research, you just have to be a little specific about what it should go after.
by johnecheck | 2025-08-21 22:54:47+00:00
While it's definitely possible to train a model for that, 'very easy' is nonsense.

Unless you've got some superintelligence hidden somewhere, you'd choose a neural net. To train, you need a large supply of LABELED data. Seems like a challenge to build that dataset; after all, we have no scalable method for classifying as of yet.
by kstrauser | 2025-08-21 22:54:50+00:00
It really does sound like a bad idea, and now that I've used cargo a lot, I want a lot more of those bad ideas in my life.

Seriously, if uv becomes to Python what cargo is to Rust, the developer experience for Python is going to be vastly better than before. I've been writing Python professionally for more than 25 years, and getting paid to work around it's crummier parts, and I'm thrilled to be able to throw away all that knowledge and just use uv.
by wizzwizz4 | 2025-08-21 22:54:52+00:00
Not more: sooner (and, as clearly stated in my previous comment, less). By the time most countries were doing lockdowns, it was to prevent their local health systems from completely collapsing, not to contain and eliminate the disease in any real sense.

I think the comparison to plague is accurate, since quarantine and social distancing were effective in reducing mortality during the Black Death, as were plague vaccines.
by ants_everywhere | 2025-08-21 22:54:59+00:00
> • The use of AI tools to assist rather than stand in for human creativity does not affect the availability of copyright protection for the output.

> • Copyright protects the original expression in a work created by a human author, even if the work also includes AI-generated material

> • Human authors are entitled to copyright in their works of authorship that are perceptible in AI-generated outputs, as well as the creative selection, coordination, or arrangement of material in the outputs, or creative modifications of the outputs.
by matheusmoreira | 2025-08-21 22:55:30+00:00
> People around Desktop Linux could write a complete book about dismissing user's complaints.

On Linux we enjoy flexible systems that empower us to change the things we don't like all by ourselves without any need to involve any "project managers" at all.

And it's completely fine if Linux systems are built around the needs of programmers and power users. It's not like normal users are paying us. Linux users should focus exclusively on themselves and their own needs.
Show HN: I Was There, an iOS app for tracking your attended MLB games
by rylie | 2025-08-21 22:55:33+00:00
Hey HN, here to show off something for the baseball enthusiasts among us. I attend a lot of games, and I would always wonder things like "who have I seen hit the most homers?" and "who have I seen throw the most strikeouts?" and other questions along those lines. Instead of just making a spreadsheet or something just for myself, I decided it'd be a fun idea for an app, and now here we are.

You open the app and do two things: - Select your favorite team - Select the games you've attended from the Schedule and from there, you can start exploring your stats. You can see overall and team-specific stat rollups, which ballparks you have and have not attended, sortable player-level tables, and highlights for the most extraordinary moments you've witnessed.

It's my first app I've developed from scratch and taken all the way to launching, so I'm pretty excited! I'm trying to keep it simple and low overhead, so it's free with no ads or in-app purchases or anything, and no account is required or even supported. CloudKit integration is available for saving your data.

One caveat is that there's currently no data for the active MLB season. I am sourcing the data from Retrosheet, who updates with the previous season's data in January, so for now I will be following the same cadence.

Please give it a try and let me know how it goes!
by NitpickLawyer | 2025-08-21 22:56:08+00:00
> It's just not all that relevant today, and we don't prioritize memorization to the extent Plate and the ancient Greeks probably did.

Funny enough, that's kinda what we're seeing with LLMs. We're past the "regurgitate the training set" now, and we're more interested in mixing and matching stuff in the context window so we get to a desired goal (i.e. tool use, search, "thinking" and so on). How about that...
by FredPret | 2025-08-21 22:56:10+00:00
I don't think they're uneconomical. Fresh, clean water is astonishingly cheap; of course people are using it to grow almonds and alfalfa in the desert.

Just charge people what the water is worth and they'll stop, or water companies will be able to afford much more treatment capacity.

You have a point about sequestering CO2 molecules, but:

a) I'm sure this will get cheaper over time, just like every other technology

b) we should be using solar and nuclear for everything
by yAak | 2025-08-21 22:56:10+00:00
> Because they finally understood who was actually using our product.

Yes!!!

> The biggest problem with most engineers is actually over-engineering.

Err, wait, go back to step 1. Over-engineering is sometimes a byproduct of not understanding the customer use cases. That lack of understanding is the biggest problem.

So, I’m an “engineer” —- my most common frustration with other engineers is their lack of interest in understanding of the actual product being sold. In my experience, sometimes the reason is job-fit issues, sometimes it’s ego, but usually it’s a combination of culture and incentive.
by refulgentis | 2025-08-21 22:57:04+00:00
In the modes in APIs, the sampling code essentially "rejects and reinference" any token sampled that wouldn't create valid JSON under a grammar created from the schema. Generally, the training is doing 99% of the work, of course, it's just "strict" means "we'll check it's work to the point a GBNF grammar created from the schema will validate."

One of the funnier info scandals of 2025 has been that only Claude was even close to properly trained on JSON file edits until o3 was released, and even then it needed a bespoke format. Geminis have required using a non-formalized diff format by Aider. Wasn't until June Gemini could do diff-string-in-JSON better than 30% of the time and until GPT-5 that an OpenAI model could. (Though v4a, as OpenAI's bespoke edit format is called, is fine because it at least worked well in tool calls. Geminis was a clown show, you had to post process regular text completions to parse out any diffs)
by missedthecue | 2025-08-21 22:57:38+00:00
Good question. Options was casual nomenclature. He received PSRUs, which are Performance-based Restricted Stock Units. For him they vest through 2027 depending on if his hits the metrics or not. Failure to hit means no vesting at all.

Some of his metrics are about store renovations, revamping the rewards program, and hitting some internal financial operating ratios, and a couple other things.
Ask HN: If technology is so good for the world, why are we becoming less happy?
by cmcy | 2025-08-21 22:59:13+00:00
People are becoming less, not more, happy. Since the internet era began, every meaningful metric reflects this same picture - self reported happiness levels, mental health medication prescription rates, suicide rates at all ages, number of self reported close relationships, birth rates. Anything you can think of as a proxy for whether people are enjoying life is either stagnant or down.

Of course it's not as simple as saying technology is the cause of all of this unhappiness, but what is clear is that, at minimum, technology is not doing enough to counteract it. And if the technology isn't the cause, then what is it? A generation and a half of some of the smartest people in the world working on expanding the boundaries of what is possible and people are less happy than they were when it started. This is a huge indictment of the tech industry. What happened?
by gpm | 2025-08-21 23:00:24+00:00
I don't have numbers to quote at you, but I would assume not. Fundamentally coal, nuclear, and gas-boiler (but not gas-turbine) power plants work the same way - you heat up water until it boils, and run the steam through a turbine to turn that heat into mechanical energy. I.e. the "cooling" is also the electricity generation mechanism. As a result same amount of heat should result in the basically same amount of electricity for each process, and since the water is being used in the same way they should be pretty much equal in water (use or consumption)/electricity output efficiency assuming they were built with the same era of technology...
by slashdave | 2025-08-21 23:00:41+00:00
Inequity is a real thing, but I am confused about why the CEO of a company that consists primarily of low wage earners deserves a lower compensation for that reason alone. If you follow this logic to extremes, the compensation of a CEO of a company of a dozen people earning 100,000 should be higher than one with with tens of thousands of employees earning 30,000.

Not all businesses are the same.
by LargoLasskhyfv | 2025-08-21 23:00:43+00:00
I think they were mandatory for Doctors medical practices after some point in Germany.

There the Epsons were called the "Ärztedrucker" because Doctors they used them for "carbon copy" prescriptions. Even after Laser- or Inkjetprinters were common. No carbon copy possible there. And they had to be carbon copied, for legal reasons.
by ab2525 | 2025-08-21 23:01:32+00:00
I have had similar observations to you and tried to capture them here: https://www.linkedin.com/posts/alex-buie-35b488158_ai-neuros...

The gist being - language (text input) is actually the vehicle you have to transfer neural state to the engine. When you are working in a greenfield project or pure-vibe project, you can get away with most of that neural state being in the "default" probability mode. But in a legacy project, you need significantly more context to contrain the probability distributions a lot closer to the decisions which were made historically.
by missedthecue | 2025-08-21 23:01:50+00:00
But the buyback involves buying from sellers. Why don't the sellers of the shares owe tax? Don't see how that's a tax-dodge.

The fundamental purpose of a buyback is not to raise the stock price. The purpose of a buyback is to reduce the amount of outstanding shares, which makes every existing owner own an increased percentage. If a company buys back 10% of its stock, each long term shareholder now owns 10% more of the company. Over the long term, steady buybacks increase shareholder value this way, but the purpose of it isn't to slam the order book and juice the price. That's counterproductive, because you'll buy fewer shares at higher prices, and within a trading day, the market will push the price back to normal anyway.
by diggan | 2025-08-21 23:01:51+00:00
> It became evident to me while playing with Stable Diffusion that it's basically a slot machine.

It can be, and usually is by default. If you set the seeds to deterministic numbers, and everything else remains the same, you'll get deterministic output. A slot machine implies you keep putting in the same thing and get random good/bad outcomes, that's not really true for Stable Diffusion.
by bruceb | 2025-08-21 23:02:06+00:00
"Immigration’s impact on wages, especially in the long term, is not as straightforward as “less supply → higher pay.”

"Restricting immigration might reduce competition in some low-skill job markets, but it can also harm industries that rely on labor shortages being filled"

So restricting immigration of low wage workers, would push up wages in low wage industries. Seems pretty clear.
by dragonwriter | 2025-08-21 23:02:08+00:00
> In the modes in APIs, the sampling code essentially "rejects and reinference" any token sampled that wouldn't create valid JSON under a grammar created from the schema.

I thought the APIs in use generally interface with backend systems supporting logit manipulation, so there is no need to reject and reinference anything; its guaranteed right the first time because any token that would be invalid has a 0% chance of being produced.

I guess for the closed commercial systems that's speculative, but all the discussion of the internals of the open source systems I’ve seen has indicated that and I don't know why the closed systems would be less sophisticated.
by simoncion | 2025-08-21 23:02:10+00:00
So, I'm not sure what your claim is. Is it something like "bonus pay is totally incomparable to regular wage pay and does not enter your bank account"? That's the most charitable interpretation I can make out of

> ...awarding him a pile of [RSUs] if he hits certain metrics is not pay, is not comparable to W2 income, does not hit his bank account...
by ants_everywhere | 2025-08-21 23:02:15+00:00
If you don't disclose the use of

- books

- search engines

- stack overflow

- talking to a coworker

then it's not clear why you would have to disclose talking to an AI.

Generally speaking, when someone uses the word "slop" when talking about AI it's a signal to me that they've been sucked into a culture war and to discount what they say about AI.

It's of course the maintainer's right to take part in a culture war, but it's a useful way to filter out who's paying attention vs who's playing for a team. Like when you meet someone at a party and they bring up some politician you've barely heard of but who their team has vilified.
by ab2525 | 2025-08-21 23:02:58+00:00
Well said - language (text input) is actually the vehicle you have to transfer neural state to the engine. When you are working in a greenfield project or pure-vibe project, you can get away with most of that neural state being in the "default" probability mode. But in a legacy project, you need significantly more context to contrain the probability distributions a lot closer to the decisions which were made historically otherwise you quickly get into spaghetti-ville as the AI tries to drag the codebase towards its natural ruts.
by stetrain | 2025-08-21 23:03:25+00:00
Yes, my point is just that the financial feasibility is related to the policy decisions.

For example you could say that most people who live in Manhattan would choose to live in a 2000sqft+ detached home if it was financially feasible to do so.

But because there is limited space, high demand, and city policy allows high density, such a home is not financially feasible for almost anyone in Manhattan.

And of course that applies in sprawling metro areas like Houston as well. Forcing large swaths of single-family zoning despite the market forces means that housing supply can’t grow with demand, so cost of housing increases.
by uberduper | 2025-08-21 23:03:27+00:00
> If a user holds an ice cream cone upside-down and their ice cream falls to the floor, do you blame the user for not holding their ice cream cone upright or the creator of the ice cream cone for a stupid design that allows the ice cream to so easily fall out of the ice cream holding device and onto the floor?

Playing along with this analogy, what I think we see a lot of in product development is the customer going to the PM and saying they need the cone to have a cover. The PM and the customer iterate over the specifics of the cover. PM goes to the engineer and tells them the cone needs a cover that meets x, y, and z requirements. Engineer, knowing how you're supposed to use the ice cream cone, objects. PM, knowing what the customer needs, insists.
by gdubs | 2025-08-21 23:04:05+00:00
I think the water-usage stuff regarding data centers is really lacking context in online discourse – and yet, I still believe that freshwater usage really needs to be more of a concern for people, generally. I'm not 'anti-AI' but, I cringe a bit every time someone dismissively says "water cycle" to dismiss concerns around freshwater because, some aquifers are not going to recharge in a meaningful timeframe. That water isn't 'destroyed' – but if a town is tight on water already, it's not necessarily coming back, practically speaking.
by FredPret | 2025-08-21 23:04:34+00:00
Doesn't pass the sniff test:

From what I can glean from Google, the sun moves 1500 cubic kilometers of water from the ocean into the air every day, around 500,000 cubic kilometers a year (ie, a stupendous amount).

Apparently around 10% of that makes it up the various mountains and comes back down as rivers - that's 50,000 cubic kilometers.

And for scale, human "consumption" is 5000 cubic kilometers.

I agree we should be careful and intelligent about how we use water and where we get it from, but I fail to be alarmed.
by hermitcrab | 2025-08-21 23:04:45+00:00
I waded through some of this:

https://www.youtube.com/watch?v=5m7LnLgvMnM

Carroll comes across as very reasonable. Weinstein comes across _very_ badly. The only positive thing I can think to say about him, is that he kept the equally awful Peirs Morgan quiet for a while.
by TheAlchemist | 2025-08-21 23:06:01+00:00
Technology is just a tool. It can be great, it can be very bad. What can of technology are we investing in ?

If you look at top US companies, half of top 10 is investing tens of billions $ trying to get people addicted to screens. That's reflected in the metrics you're seeing. It's an unfair game. Hell, even the richest guy in the world got his brain rotten recently (arguably with a solid help from drugs) and is spending his days posting soft anime porn AI generated images and videos.

It's just really all about the incentives. Everybody would like the world to be a better place, but who among top technologist, which are in big numbers here, are willing to work for 1/10 of what he can make at a big co, to make it happen ?
by beezle | 2025-08-21 23:06:10+00:00
Until the mid-80s they were illegal except in a handful of unique cases. This is not just about div vs buyback taxes. Though there is no immediate mathematical economical benefit to the shareholders who remain, the markets have proven that the stock price will rise (and likely executive compensation) as a result of reduced sharecount vs the same demand (though possibly more demand as other companies engage in the same behavior).

Much of the gains in the stock market the past decade or so are simply the result of a greatly reduced number of shares available to purchase - as a result of buybacks, takeovers and going private (there are roughly 1/2 the number of listed companies today as in the 1990s).
by godelski | 2025-08-21 23:06:18+00:00
What's the old Rockefeller clique? When your shoe shiner is giving you stock advice it is time to sell (may have heard the taxicab driver version).

It depends on how risk adverse you are and how much money you have there.

If you're happy with those returns, sell. FOMO is dumb. You can't time the market, the information just isn't available. If those shares are worth a meaningful amount of money, sell. Take your wins and walk away. A bird in your hand is worth more than two in the bush, right? That money isn't worth anything until it is realized[0].

Think about it this way: how much more would you need to make to risk making nothing? Or losing money? This is probably the most important question when investing.

If you're a little risk adverse or a good chunk of your profile is in it, sell 50-80% of it and then diversify. You're taking wins and restructuring.

If you wanna YOLO, then YOLO.

My advice? Don't let hindsight get in the way of foresight.

[0] I had some Nvidia stocks at 450 and sold at 900 (before the split, so would be $90 today). I definitely would have made more money if I kept them. Almost double if I sold today! But I don't look back for a second. I sold those shares and was able to pay off my student debt. Having this debt paid off is still a better decision in my mind because I can't predict the future. I could have sold 2 weeks later and made less! Or even in April of this year and made the same amount of money.