MurphyA/hacker-news huggingface dataset:
by ath3nd | 2025-08-08 18:08:27+00:00
> but just have a look what countries around Israel are doing about Gaza. Nothing.

It's hard to help Palestinians when Israel is actively bombing you them as well, like they did with Iran. And like they did with Lebanon.

> Looking the other way after their own negative experiences with Palestinians.

They have all called out the genocide that's happening. Here are some examples: https://www.aljazeera.com/news/2025/2/9/saudi-arabia-slams-n...

And the other ones are being bombed by Israel anyway (Iran and Lebanon).

Also, whatever differences the Arab states had with Palestine, only one country is actually doing a genocide to the Palestinians, and that's Israel.

Israelis themselves call it out: https://www.theguardian.com/world/2025/jul/28/israel-committ...

Starving the population (war crime) https://www.ohchr.org/en/press-releases/2025/08/gaza-israel-...

Killing civilians looking for aid (war crime) https://edition.cnn.com/2025/07/20/middleeast/israel-gaza-ai...

Bombing hospitals (war crime) https://www.bbc.com/news/articles/cx2jvx3yjg3o

Killing Journalists (war crime) https://www.bbc.com/news/articles/ckgnp154eeko

So all kind of what-about-ism can't distract us from the fact that Israel is doing a genocide in Gaza.
by j_timberlake | 2025-08-08 18:08:44+00:00
"You would need ~30 years of continuously beating the market to be able to claim that you are statistically likely to be better than random chance."

You use the word statistically as if you didn't just pull "~30 years" out of nowhere with no statistics. And people become billionaires by making longshot bets on industry changes, not by playing the market while they work a 9-5.

"Does your average speculator have 30 years of experience beating the market, or were they just lucky?"

The average speculator isn't even allowed to invest in OpenAI or these other AI companies. If they bought Google stock, they'd mostly be buying into Google's other revenue streams.

You could just cut to the chase and invoke the Efficient Market Hypothesis, but that's easily rebuked here because the AI industry is not in an efficient market with information symmetry and open investing.
by vasa_ | 2025-08-08 18:09:08+00:00
The usual benchmarks for language models—Exact Match, F1, and even multi-hop QA datasets—weren’t designed to measure what matters most about persistent AI memory: connecting concepts across time, documents, and contexts.

We just completed our most extensive internal evaluation of cognee to date, using HotPotQA as a baseline. While the results showed strong gains, they also reinforced a growing realization: we need better ways to evaluate how AI memory systems actually perform.

We ran Cognee through 45 evaluation cycles on 24 questions from HotPotQA, using ChatGPT 4o for the analysis. Each part of the evaluation process is affected by the inherent variance in GPT’s output: cognification, answer generation, and answer evaluation. We especially noticed significant variance across different metrics on small runs, which is why we chose the repeated, end-to-end approach.

We compared results using the same questions and setup with:

Mem0 Lightrag Graphiti

While they are standard in QA, EM and F1 scores reward surface-level overlap and miss the core value proposition of AI memory systems. For example, a syntactically perfect answer can be factually wrong, and a fuzzy-but-correct response can be penalized for missing the reference phrasing.

LLMs are inconsistent, that is another issue.

Even HotPotQA assumes all relevant information sits neatly in two paragraphs. That’s not how memory works. Real-world AI memory systems need to link information across documents, conversations, and knowledge domains that traditional QA benchmarks just can’t capture.

Consider the difference:

Traditional QA:

“What year was the company that acquired X founded?”

Memory Challenge:

“How do the concerns raised in last month’s security review relate to the authentication changes discussed in the architecture meeting three weeks ago?”

Only one of these tests long-term knowledge, reasoning across sources, and organizational memory—care to guess which one?

We are working on a new dataset and benchmarks to measure memory, and would love feedback!
by 9rx | 2025-08-08 18:09:26+00:00
> Has anyone with decent (5+ years) experience built a non-trivial new feature in a production codebase quicker by letting AI write it?

I would say yes. I have been blown away a couple of times. But find it is like playing a slot machine. Occasionally you win — most of the time you lose. As long as my employer is willing to continue to cover the bet, I may as well pull the handle. I think it would be pretty hard to convince myself to pay for it myself, though.
by prasadjoglekar | 2025-08-08 18:09:26+00:00
Au contraire, that is much closer to the definition of insurance. We don't want people to get bankrupt with an unforseen medical issue like cancer. Insurance should cover that.

Routine care, including shit that's a little unlucky should be paid for out of pocket.

In the US, health care and health insurance have become synonymous such that all the good bits of insurance are out the door and all the bad ones have stayed. And polluted the true cost of getting simple, routine care.
by Someone | 2025-08-08 18:09:40+00:00
> Users often talk about how certain models "feel" smarter on their particular tasks, and we won't know if the same is true for GPT-5 until people use it for a while.

The idea that models “feel” smarter may be 100% human psychology. If you invest in a new product, admitting that it isn’t better than what you had is hard for humans. So, if users say a model “feels” smarter, we won’t know that it really is smarter.

Also, if users manage to improve quality of responses after using it for a while, who says they couldn’t have reached similar results if they stayed using the old tool, tweaking their prompts to make that model perform better?
by Quarrelsome | 2025-08-08 18:10:15+00:00
I would argue that the money is short termism though. It just assumes short term returns are the correct choice because it lacks the technical understanding of the long term benefits of a good job.

In my experience many acquisitions set the peak of a given software product. The money then makes the argument that its "good enough" and flogs the horse until its dead and a younger more agile team of developers eventually build a new product that makes it irrelevant. The only explanation I have for why so many applications fail to adapt is because of a cultural issue between the software and the money, that always gets resolved by the money winning.

For example I would suggest that the vast majority of desktop apps, especially those made by SMEs, originally in MFC or something fail to make the transition to online services that they need today because of this conflict. The company ends up dying and the money never works out what it did wrong because its much harder to appreciate those long term effects than the short term ones that gave them more money at the start.
by svachalek | 2025-08-08 18:10:16+00:00
Prompt: "Spell blueberry and count the letter b".

They're not claiming AGI yet, so human intelligence is required to operate an LLM optimally. It's well known that LLMs process tokens rather than characters s, so without space for "reasoning" there's no representation of the letter b in the prompt. Telling it to spell or think about it gives it room to spell it out, and from there it can "see" the letters and it's trivial to count.
by NitpickLawyer | 2025-08-08 18:10:17+00:00
Yeah, I agree. And prices are slowly coming down. Gemini 2.5 was cheaper than claude4, and (again depending on task) either on par or slightly below in quality. Now gpt5 is cheaper still (I think their -main is 10$/M?) and they also have -mini and -nano versions. The more choices we have the better it will be. As you said, without a clear winner we're about to get spoiled for choice, and there's no clear way for them to just sit on stuff and increase prices (yet). Plus there's some pressure coming from the open source releases. Not there in quality, but they are runnable "on prem", pretty cheap and keep getting better.
by ChadNauseam | 2025-08-08 18:10:25+00:00
Yeah, Jazz is amazing. The DX is unmatched. My issue when I used it was, they mainly supported passkey-based encryption, which was poorly implemented on windows. That made it kind of a non-starter for me, although I'm sure they'll support traditional auth methods soon. But I love that it's end-to-end encrypted and it's super fun to use.
by epolanski | 2025-08-08 18:11:51+00:00
I will also state another semi-obvious thing that people seem to consistently forget: models are non deterministic.

You are not going to get the same output from GPT5 or Sonnet every time.

And this obviously compounds across many different steps.

E.g. give GPT5 the code to a feature (by pointing some files and tests) and tell it to review it and find improvement opportunities and write them down: depending on the size of the code, etc, the answers will slightly different.

I often do it in Cursor by having multiple agents review a PR and each of them: - has to write down their pr-number-review-model.md (e.g. pr-15-review-sonnet4.md) - has to review the reviews of the other files

Then I review it myself and try to decide what's valuable in there and what not. And to my disappointment (towards myself): - often they do point to valid flaws I would've not thought about - miss the "end-to-end" or general view of how the code fits in a program/process/business. What do I mean: sometimes the real feedback would be that we don't need it at all. But you need to have these conversations with AI earlier.
by ivape | 2025-08-08 18:11:59+00:00
It’s also one of the most bipartisan political things ever, in a weird way.

A) Both Biden and Trump provided rhetorical cover, but never tried to stop it in anyway.

and

B) People on both sides of the political spectrum see it for what it is and are against it.

So if we had to get Sherlock Holmes with it, I think you’ll see that both A and B have one thing in common, and that is neither A or B has any avenue to stop the Israeli government.

B doesn’t have the power because the representatives are beholden to something. A won’t stop it because, I guess they are beholden to the same thing?

So, the powerful have no way of stopping it. Which bring us to C, the people in Gaza. They had no fucking chance of stopping it if A and B couldn’t.
by jauntywundrkind | 2025-08-08 18:12:04+00:00
I sympathize so much with the failure of personal computing to manifest!

> My point is that if all knowledge were stored in a structured way with rich semantic linking, then very primitive natural language processing algorithms could parse question like the example at the beginning of the article, and could find the answer using orders of magnitude fewer computational resources. And most importantly: the knowledge and the connections would remain accessible and comprehensible, not hidden within impenetrable AI models.

It's a pocket hope of mine that AI brings us back to the Semantic Web, or something very like it. In many ways these embeddings are giant non-human lexicons already. Distilling this information out seems so possible.

Even just making an AI to go markup (or uhh perhaps refine) a page with microdata seems conceptually very doable!

More broadly, looking at personal computing: my personal belief is that failure is hugely because of apps. Instead of a broader personal computing that aggregates, that allows constructivism, that enables personal growth & development (barefoot developers & home-cooked software style), computing has been defined by massificstion, by big tech software. The dominant computing paradigm has been mainframe pattern: we the user have an app that acts as a terminal to some far off cloud-y data center. Whatever agency we get is hewn out for us apriori by product teams, and any behavior not explicitly built in is a "Felony Contempt of Business Model" (an oh so accurate Doctorow-ism)! https://maggieappleton.com/home-cooked-software https://news.ycombinator.com/item?id=40633029 https://pluralistic.net/2022/10/20/benevolent-dictators/#fel... https://news.ycombinator.com/item?id=33279274

It is so so sad to see computing squandered so!

The good news is AI is changing this relationship with software. I'm sure we will have no end of AI models built in to our software, that companies will maintain the strict control (tyrant's grip) over software as long as they can! But for AI to flourish, it's going to need to work across systems. And that means tearing down some of the walls, walls that have forcibly kept computing (ardently) anti-personal.

I can go look at https://github.com/punkpeye/awesome-mcp-servers and take such great hope from it. Hundreds of ways that we have eeked out a way to talk interface with systems that, before, people had no say and no control over.
by m463 | 2025-08-08 18:12:07+00:00
lol.

don't spend your time cooking food, pay for others to prepare it for you.

don't spend your time maintainig a house, rent and let someone else do the maintenance.

just lease a car and get a new one automatically every 3 years.

honestly, everyone has their own setpoint for things. and there are degrees of solutions for every point you make.

I think most people would benefit from being just a little bit self-sovereign.

Personally, "majority of people" could use one low power fanless server with 1tb for the few things most people need continuously online.

And separately a server you turn on occasionally with lots of storage, like maybe

https://www.amazon.com/dp/B09TV1XPDD

I'm reminded of jwz's backups info www.jwz.org/doc/backups.html

"RAID is a goddamn waste of your time and money"
by lurking_swe | 2025-08-08 18:12:15+00:00
My company deploys everything in the cloud, but we can still do some meaningful work locally for a few hours if needed in a pinch. Out gitlab is self hosted because that’s extra critical.

I continue writing code and unit tests while i wait for the cloud to work again. If the outage is a long time, I may even spin up “DynamoDB Local” via docker for some of our simpler services that only interact with DynamoDB. Our apache flink services that read from kafka are a lost cause obviously lol.

It’s also a good opportunity to tackle any minor refactoring that you’ve been hoping to do. Also possible without the cloud.

You can also work on _designing_ new features (whiteboarding, creating a design document, etc). Often when doing so you need to look at the source to see how the current implementation works. That’s much easier with code comments.
by muzani | 2025-08-08 18:12:18+00:00
They nerfed free too. Just yesterday, it felt like I had 50 gpt4o messages and had a 2 hour long conversation with it. Now I'm out with far less use at about 30 min.

I'm guessing they'll just announce massive tier generosity later considering how GPT-5 input tokens are half the price of 4.1 on the API. It's probably a way to keep the servers from being overloaded and to encourage people to buy Plus while the hype is hot.
by porridgeraisin | 2025-08-08 18:12:20+00:00
Same. I have two small UPS. The first I connect to my computers and it lasts about 15 minutes. Enough for me to save/checkpoint whatever in a restorable way. The second I connect to the wifi router. This lasts for a while longer and it's pretty useful. In those 15 minutes local network still works. And if the power comes back in a minute or two (which happens more often than outages that last hours where I am), then I don't have to wait for the wifi routers painfully slow boot time.

Speaking of... does anyone know how to speed up wifi router boot time? Stupid thing takes 5 minutes almost.
by cyberax | 2025-08-08 18:12:40+00:00
It's a bit trickier than you think. And can be dangerous.

The discharging circuitry is fine, but the _charger_ might overheat because a larger battery can draw more current while charging for longer periods. I discovered that when I tried to attach a "lead-acid compatible" LFP battery to an UPS.

These days, it's just easier to buy a dedicated rack-mountable LFP battery originally meant for solar installations, an inverter/charger controller, and a rectifier. The rectifier output will serve as a "solar panel" input for the battery. You get a double-conversion UPS with days-long holdover time for a fraction of a lead-acid UPS.
by dahart | 2025-08-08 18:13:00+00:00
It was a loose analogy, but it is thought Neanderthals may have hibernated (or gone into a state of torpor). Your comment offers no reasoning nor evidence; is something wrong with it, and if so what, exactly? Food scarcity in winter time is something humans have historically been exposed to and evolved with in much of the world. And clearly over-eating in humans corellates somewhat with food insecurity. Regardless of the mechanism, my point was that it’s not hard to imagine why obesity and hunger might go together.
by nullc | 2025-08-08 18:14:34+00:00
> I asked GPT5 directly about fake system prompts.

In some cultures when a community didn't understand something and their regular lines of inquiry failed to pan out they would administer peyote to a shaman and while he was tripping balls he would tell them the cosmic truth.

Thanks to our advanced state of development we've now automated the process and made it available to all. This is also know as TBAAS (Tripping Balls As A Service).
by physix | 2025-08-08 18:14:37+00:00
About 1: Indeed. The moderator remarked at the end that once the interview was over, Dario's expression sort of sagged and it felt like you could see the weight on his shoulders. But you never know if that's part of the act.

About 2: Ah, yes. So if one vendor gains sufficient momentum, their advantage may accelerate, which will be very hard to catch up with.
by runningmike | 2025-08-08 18:14:37+00:00
This wheel has been reinvented again and again. The $$$ seems very attractive. But simple is a scam… https://news.ycombinator.com/item?id=44838059 Make an existing Foss wheel better. This is a hard crowded market with many many tools and solutions. But the problems are seldom solved with a tool alone.
by klardotsh | 2025-08-08 18:15:01+00:00
Well, sure, age is part of it. I would hope languages coming out 40-50 years after their predecessors (in the case of Rust following C/C++) would have improved upon those predecessors and learned from the ideas of computer science in the intermediate years.

(Coincidentally this is one of my chief complaints about Go: despite being about the same age as Rust, it took the avenue of discarding quite a lot of advancements in programming language theory and ergonomics since C)
by andy99 | 2025-08-08 18:15:04+00:00
Edit to add: according to Sam Altman in the reddit AMA they un-deprecated it based on popular demand. https://old.reddit.com/r/ChatGPT/comments/1mkae1l/gpt5_ama_w...

I wonder how much of the '5 release was about cutting costs vs making it outwardly better. I'm speculating that one reason they'd deprecate older models is because 5 materially cheaper to run?

Would have been better to just jack up the price on the others. For companies that extensively test the apps they're building (which should be everyone) swapping out a model is a lot of work.
by CodingJeebus | 2025-08-08 18:15:05+00:00
How is the database migration support for these tools?

Needing to support clients that don’t phone home for an extended period and therefore need to be rolled forward from a really old schema state seems like a major hassle, but maybe I’m missing something. Trying to troubleshoot one-off front end bugs for a single product user can be real a pain, I’d hate to see what it’s like when you have to factor in the state of their schema as well
Ask HN: How would you build second brain in the AI era?
by divan | 2025-08-08 18:15:08+00:00
A lot of people use 'second brain' software and are now trying to connect/integrate them with LLMs.

But if you were starting with a new 'second brain' from scratch, how would you do it, given the current state (and trends) in AI/LLMs?
by lupusreal | 2025-08-08 18:15:10+00:00
> I'm assuming reckless joyriding isn't what you're referring to as "violent crime"

It is, and worse. There have been numerous cases of scumbag teenager stealing cars and then crashing them into people, mostly by accident but often enough on purpose. They also use the cars for gangbanging shit since they know the car can't be traced back to them.

A lot of this stuff wouldn't be happening if cars weren't so easy to steal. There is a casual accessibility to stealing certain cars which makes it an easier crime to commit than carjacking (parked cars aren't witnesses, parked cars won't fight back or pull a gun of their own, parked cars won't try to run you over, etc.) Once the car is stolen, other impromptu violence seems and becomes easier.
by jandrese | 2025-08-08 18:15:24+00:00
The semantic web was theoretically great for data scientists and metadata scrapers, but offered close to zero value for ordinary humans, both on the publishing side an the consumption side. Also, nobody did the hard work of defining all of the categories and protocols in a way that was actually usable.

The whole concept was too high minded and they never got the implementation details down. Even if they did it would have been horrendously complex and close to impossible to manage. Asking every single publisher to neatly categories their data into this necessarily enormous scheme would have resulted in countless errors all over the web that would have seriously undercut the utility of the project anyway. Ultimately the semantic web doesn't scale very well. It failed for the same reason command economies fail: It's too overwhelming for the people in control to manage and drowns in its own bureaucracy.
by prepend | 2025-08-08 18:15:24+00:00
In my experience 99% of consulting is fully in the business of telling whatever emperor or micro emperor with budget authority that their clothes are just beautiful the way they are. Very few billable hours are people like GP. But maybe Im unlucky.

I consulted for about 10 years and enjoyed building stuff, but I didn’t like how the key metric was “is the client happy? will they extend?” And frequently the client is happy with what is not best.

Now I strive to work in organizations that don’t use or rely on consultants very much. I actually think a health metric for organizations is having low levels of consultants.
by aurelb | 2025-08-08 18:15:38+00:00
We run a small open-source project (Intlayer) and recently saw a 10x traffic spike from suspicious IPs, mimicking Googlebot and hitting random pages every few seconds.

It looked like someone was trying to get us penalized by Google. We wrote a post explaining what happened and how we responded.

Curious if others have seen something similar and what tools or strategies you use to detect/prevent this?
by tropicalfruit | 2025-08-08 18:15:46+00:00
reading all the shilling of Claude and GPT i see here often I feel like i'm being gaslighted

i've been using premium tiers of both for a long time and i really felt like they've been getting worse

especially Claude I find super frustrating and maddening, misunderstanding basic requests or taking liberties by making unrequested additions and changes

i really had this sense of enshittification, almost as if they are no longer trying to serve my requests but do something else instead like i'm victim of some kind of LLM a/b testing to see how far I can tolerate or how much mental load can be transferred back onto me
by surfaceofthesun | 2025-08-08 18:15:49+00:00
This completely ignores Friedman's concept of the velocity of money (MV = PY). If that $15k is being saved by someone versus immediately spent, that has a different effect. A transfer isn’t neutral if the two parties have different propensities to consume (marginal propensity to consume). Similarly how quickly and what the money is being spent on will have an effect. Most money (M2) is not created directly by the treasury but rather indirectly from large banks lending against fractional deposits. This is money created on the balance sheets of banks but has real effect on the economy.