MurphyA/hacker-news huggingface dataset:
by const_cast | 2025-06-19 21:37:06+00:00
> Maybe I don't give people enough credit and you do, but I don't think most people care how you arrived at an opinion; they merely care about whether you're in their opinion-tribe or not.

Yes, most people don't care how you arrived at an opinion, they rather care about the practical impact of said opinion. IMO this is largely a good thing.

You can logically push yourself to just about any opinion, even absolutely horrific ones. Everyone has implicit biases and everyone is going to start at a different starting point. The problem with string of logic for real-world phenomena is that you HAVE to make assumptions. Like, thousands of them. Because real-world phenomena are complex and your model is simple. Which assumptions you choose to make and in which directions are completely unknown, even to you, the one making said assumptions.

Ultimately most people aren't going to sit here and try to psychoanalyze why you made the assumptions you made and if you were abused in childhood or deduce which country you grew up in or whatever. It's too much work and it's pointless - you yourself don't know, so how would we know?

So, instead, we just look at the end opinion. If it's crazy, people are just going to call you crazy. Which I think is fair.
by Johanx64 | 2025-06-19 21:37:07+00:00
>People in these communities are generally quite smart, and it’s seductive to reason in a purely logical, deductive way. There is real value in thinking rigorously and in making sure you’re not beholden to commonly held beliefs. But, like you said, reality is complex, and it’s really hard to pick initial premises that capture everything relevant. The insane conclusions they get to could be avoided by re-checking & revising premises, especially when the argument is going in a direction that clashes with history, real-world experience, or basic common sense.

They don't even do this.

If you're reasoning in purely logical and deductive way - it's blatantly obvious that living beings experience way more pain and suffering, than pleasure and joy. If you do the math, humanity getting wiped out in effect is the best thing that could happen.

Which is why accelerationism ignoring all the AGI risks is correct strategy presuming the AGI will either wipe us out (good outcome) or provide technologies that improve the human condition and reduce suffering (good outcome).

Logical and deductive reasoning based on completely baseless and obviously incorrect premises is flat out idiotic.

You can't deprive non-existent people out of anything.

And if you do, I hope you're ready for purely logical, deductive follow up - every droplet of sperm is sacred and should be used to impregnate.
by themgt | 2025-06-19 21:37:09+00:00
The problem Kubernetes solves is "how do I deploy this" ... so I go to Rivet (which does look cool) docs, and the options are:

* single container

* docker compose

* manual deployment (with docker run commands)

But erm, realistically how is this a viable way to deploy a "serverless infrastructure platform" at any real scale?

My gut response would be ... how can I deploy Rivet on Kubernetes, either in containers or something like kube-virt to run this serverless platform across a bunch of physical/virtual machines? How is docker compose a better more reliable/scalable alternative to Kubernetes? So alternately then you sell a cloud service, but ... that's not a Kubernetes 2.0. If I was going to self-host Rivet I'd convert your docs so I could run it on Kubernetes.
by alganet | 2025-06-19 21:37:12+00:00
> Karpathy [...]

I'm sure he's a great guy, but let's face it: He's there speaking those things because he made some popular videos in the past and they needed to renew their PR strategy.

Speaking of PR strategy...

> [...] augments [...]

Iron Man does not buy his metal suit at Costco. He builds it, in a cave, with a bunch of scraps. That's the magic of building things.

> I really don't think people understand how great things could be.

That's not the issue. I think it could be great, but they're being greedy and underestimating their best audience.

Instead, they're focusing on complete beginners, in the hopes that those beginners will generate enough monkey-bashing to train a model that can churn good quality "software 1.0" (which is the real deal, so far irreplaceable). I believe that's a mistake.
by baxtr | 2025-06-19 21:37:18+00:00
> Popper’s falsificationism – this is the old philosophy that the Bayesian revolution is currently dethroning.

https://www.yudkowsky.net/rational/bayes

These are the kind of statements I’m referring to. Happy to be falsified btw :) that’s how we learn.

Also note that Popper never called his theory falsificationism.
by bilbo0s | 2025-06-19 21:38:08+00:00
Sorry, what do you guys mean by "been there, done that"?

Do you mean that you're slave descended black americans, and, in the case of HN User mistrial9, therefore speak for most of the slave descended black americans in coastal California?

Or do you guys mean that you celebrate Juneteenth. Thus, "been there, done that"?

The former I would challenge you on, despite obviously not being "black american coastal Californian?". The latter I would never challenge you on as that's your business.
by simba-k | 2025-06-19 21:38:43+00:00
So one big difference is that we aren't doing text2sql here, and the framework requires clear descriptions on all fields, entities, and relationships (it literally won't run otherwise).

We also generate a few tools for the LLM specifically to explain the data model to it. It works quite well, even on complex schemas.

The use case is more transactional than analytical, though we've seen it used for both.

I recommend running the openai_chat_agent in examples/ (also supports ollama for local run) and connect it to the shop_api server and ask it a question like : "Find and explain fraud transactions"
by tasuki | 2025-06-19 21:39:09+00:00
> The smallest unit of software ownership and delivery is the engineering team. It doesn’t matter how fast an individual engineer can write software, what matters is how fast the team can collectively write, test, review, ship, maintain, refactor, extend, architect, and revise the software that they own.

Yes, and there are often teams of one. I am currently in such a team. Even though I work on a different problem than other "teams", I think it's reasonably easy to eyeball the relative productivity (not in my favour, in my current circumstances; though, to the credit of my superiors, they're being very patient with me).
by josephcsible | 2025-06-19 21:39:14+00:00
On x86 it's debatable, but on ARM it absolutely is. When ARM PCs first started coming out, Microsoft jumped on the opportunity by forbidding OEMs from letting you disable Secure Boot on them or add your own keys to them. (And when Microsoft signs third-party things like shim, they do so with a different key than they sign Windows with, which isn't one they allow ARM OEMs to trust.)
by simba-k | 2025-06-19 21:40:01+00:00
Yes but the agent reasoning is going to use an LLM, I sometimes run our openai_chat_agent example just to test things out. Try giving it a shot, ask it to do something then ask it to explain its tool use.

Obviously, it can (and sometimes will) hallucinate and make up why its using a tool. The thing is, we don't really have true LLM explainability so this is the best we can really do.
by aduwah | 2025-06-19 21:40:30+00:00
Issue is that you do not want a dev learning hcl. Same as you don't want your SRE team learning next and react out of necessity.

The ideal solution would be to have an abstraction that is easy to use and does not require learning a whole new concept (especially an ugly one as hcl). Also learning hcl is simply just the tip of the iceberg, with sinking into the dependencies between components and outputs read from a bunch of workspaces etc. It is simply wasted time to have the devs keeping up with all the terraform heap that SREs manage and keep evolving under the hood. The same dev time better spent creating features.
by muppetman | 2025-06-19 21:40:32+00:00
I don't read that reply as them saying we should hasten deployment of DNSSEC. If that was the intention of the comment then no, I don't agree with that aspect of it.

I saying say I agree with the statement "I am saying it is dishonest to discount the real security threat of not having DNSSEC."

I believe we do need some way to secure/harden DNS against attacks, we can't pretend that DNS as it stands is OK. DNSSEC is trying to solve a real problem - I do think we need to go back to the drawing board on how we solve it though.
by fideloper | 2025-06-19 21:40:35+00:00
"Low maintenance", welp.

I suppose that's true in one sense - in that I'm using EKS heavily, and don't maintain cluster health myself (other than all the creative ways I find to fuck up a node). And perhaps in another sense: It'll try its hardest to run some containers so matter how many times I make it OOMkill itself.

Buttttttttt Kubernetes is almost pure maintenance in reality. Don't get me wrong, it's amazing to just submit some yaml and get my software out into the world. But the trade off is pure maintenance.

The workflows to setup a cluster, decide which chicken-egg trade-off you want to get ArgoCD running, register other clusters if you're doing a hub-and-spoke model ... is just, like, one single act in the circus.

Then there's installing all the operators of choice from https://landscape.cncf.io/. I mean that page is a meme, but how many of us run k8s clusters without at least 30 pods running "ancillary" tooling? (Is "ancillary" the right word? It's stuff we need, but it's not our primary workloads).

A repeat circus is spending hours figuring out just the right values.yaml (or, more likely, hours templating it, since we're ArgoCD'ing it all, right?)

> As an side, I once spent HORUS figuring out to (incorrectly) pass boolean values around from a Secrets Manager Secret, to a k8s secret - via External Secrets, another operator! - to an ArgoCD ApplicationSet definition, to another values.yaml file.

And then you have to operationalize updating your clusters - and all the operators you installed/painstakingly configured. Given the pace of releases, this is literally, pure maintenance that is always present.

Finally, if you're autoscaling (Karpenter in our case), there's a whole other act in the circus (wait, am I still using that analogy?) of replacing your nodes "often" without downtime, which gets fun in a myriad of interesting ways (running apps with state is fun in kubernetes!)

So anyway, there's my rant. Low fucking maintenance!
by Johanx64 | 2025-06-19 21:41:04+00:00
> Being 100% rigorous and rational, reasoning from first principles

It really annoys me when people say that those religious cultists do that.

They derive their bullshit from faulty, poorly thought out premises.

If you fuck up the very firsts calculations of the algorithm, it doesn't matter how rigorous all the subsequent steps are. There results are going to be all wrong.
by hellovai | 2025-06-19 21:41:18+00:00
have you tried schema-aligned parsing yet?

the idea is that instead of using JSON.parse, we create a custom Type.parse for each type you define.

so if you want a:

class Job { company: string[] }

And the LLM happens to output:

{ "company": "Amazon" }

We can upcast "Amazon" -> ["Amazon"] since you indicated that in your schema.

https://www.boundaryml.com/blog/schema-aligned-parsing

and since its only post processing, the technique will work on every model :)

for example, on BFCL benchmarks, we got SAP + GPT3.5 to beat out GPT4o ( https://www.boundaryml.com/blog/sota-function-calling )
by OhNotAPaper | 2025-06-19 21:41:21+00:00
Out of curiosity, why x86? Is it the preponderance of resources? The weird instruction format? The complexity of the boot sequence? Are you specifically trying to mimic DOS?

> A support for the ARM architecture (aarch) is coming soon too.

Wow! How do you support a DOS-like OS across multiple architectures when DOS itself is tightly tied to interactions among the program, the system code, and the architecture?
by SvenL | 2025-06-19 21:41:29+00:00
Well, about the public transport being always under construction, yes, it is. But I think it’s a good thing.

First there is quite some money put into public transportation which is great.

Second, it has to be modernized all the time to accommodate for the growing passenger numbers and city growth.

Last but not least, for a long time there was no investment done into public transportation in Munich, so now they have to do more to keep up.

I like it and I would not like to live in a city which doesn’t invest in its public transportation system.
by MondayGravity | 2025-06-19 21:41:44+00:00
Perhaps this is an insensitive question/comment, but do trans women feel like they have the wrong body or the wrong wholesale gender? In my experience with trans women I know, they still seem to relate primarily to men (they still gravitate towards male dominated interests) whereas many gay men I know seem to relate primarily with women, and gravitate towards women interests.

So this reconciliation is hard, and the topic too sensitive for me to dare asking people I know in real life.
by southernplaces7 | 2025-06-19 21:41:51+00:00
>I just cannot believe people can just fly the confederate flag and not be thrown into prison or worse. Same with Nazis.

Yeah, this is how things like freedom of expression and free speech clauses to the constitution work, they prohibit imprisoning ("or worse") people for displaying symbols of their preference, just because you don't like them, even if they're racist, as long as they're not actually committing violence against others.

Does your "or worse" refer to torturing people for these things perhaps? Congratulations, you're about as shitty as any garden variety authoritarian, racist or not.

We have a president doing his best to winnow down the 1st amendment against his particular brand of dislike, and on the other hand idiocies like what you demand doing it from another end. In both cases, emotionally claiming that what they want to restrict is "dangerous".

>If a house divided will inevitably fall, then certainly, a house that tolerates people advocating destruction of the house will also fall.

If your notion of a house divided means anyone not sharing your worldview then being imprisoned ("or worse"), it's you, or people like you who are really the problem in a country where it's exactly the kind of authoritarian bullshit you vomit that has been largely rejected by centuries of constitutional protections.
by DoctorOW | 2025-06-19 21:42:35+00:00
I haven't studied gender dysphoria but I've been diagnosed with it. In my experience, it's an incongruence between your idea of yourself and your perceptible form. In some ways it could be argued your body is "craving" it but not in the same way it may crave a specific nutrient. Instead, you're sort of surprised and often upset by the way that you are.
by gherkinnn | 2025-06-19 21:42:51+00:00
What an interesting read. I wonder, are these reports a reliable way to begin to understand what it feels like to be of the other sex? Insofar as such a thing is possible, of course. The anecdotes of smell and the sensation of powering up a hill are fascinating.

On a different note,

> At smoothbrains.net, we hold as self-evident the right to put whatever one likes inside one’s body;

I never thought of it that way, but I agree.
by abusayedopu22 | 2025-06-19 21:42:57+00:00
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by flakiness | 2025-06-19 21:43:04+00:00
This project is from CMU. Hazy Research at Stanford talked about the megakernel too: https://hazyresearch.stanford.edu/blog/2025-05-27-no-bubbles

Good to see the competition in this area.

(Edited): Related paper covering the larger "mirage" project, but this doesn't cover the "megakernel" approach: https://arxiv.org/abs/2405.05751
by varjag | 2025-06-19 21:43:22+00:00
Computers in Apollo programme controlled most of the function with minimal human involvement in the loop. The dynamic systems were orders of magnitude more complex than what you find in a modern vehicle.

Also I can assure you no-one at Cariad had to write an MP3 decoder. And speaking of sensor control, my car (on its 4th year now) still fails to unfold the mirrors once in a while.

We also have huge, orders of magnitude advances in tooling and process since mid-1960s. For starters you don't have to weave your program into magnetic core fabric by hand.
by geysersam | 2025-06-19 21:43:25+00:00
The other techniques you mentioned also suffer from some drawbacks. Cameras are relatively easy to avoid if you don't want to be recognized. Phone tracking is not very effective if the target is security minded and you're not a state actor. And I want to reiterate that you don't know how prone this new technology is to false positives, you don't know how cheap it can be made. Just to illustrate, instead of figuring out how to put concealed cameras in the entries of a building, could it be enough to place a small device near the ventilation exhaust fan?
by rebeccaskinner | 2025-06-19 21:43:58+00:00
I’ve been lucky enough to work on a number of teams in my career that are full of brilliant high performing people who are also kind, empathetic, and focused working together to deliver something to customers. These days I’m lucky enough to lead a team like that.

Counter to the article, in my experience these are the hardest teams to manage well because organizations typically aren’t set up to deal with them. Larger companies tend to lean into standardization and making things accessible to average engineers in ways that make high performing teams less effective and often demotivated.

I think this is an overly cynical approach that assumes that you can’t invest and grow people into exceptional engineers. In my experience you can if you are willing to invest in it, and the long term benefit of having more high performing engineers who aren’t being restricted from doing good work outweighs the cost of training and growing people.
by SoftTalker | 2025-06-19 21:44:16+00:00
Yes, I think there is a difference between being kidnapped from your home, shipped across the ocean and sold into a life of servitude (with any children you have being born into the same condition, or yourself being born into such a situation) vs. doing labor as part of a sentence for a crime of which you have been duly convicted (and will someday be released from). That is my opinion.
by conductr | 2025-06-19 21:44:35+00:00
I don't quite get the available tasks section with per task pricing. Can't I just rent it for the day and let it do my gardening, housecleaning, .... as much as it can get done in the time I have it? Or are you actually charging me based on the services I want performed?

If I rent a car, I don't pay different rates for mileage or where I take the car (tolls aside)
by bdbenton5255 | 2025-06-19 21:44:43+00:00
Strangely enough, I work with AI models as a programmer and do not use any AI tools to code. The creation of "cognitive debt" as AI researchers describe it means that crucial components of my code are offloaded into a black box understanding.

https://arxiv.org/abs/2506.08872

"Across groups, NERs, n-gram patterns, and topic ontology showed within-group homogeneity. EEG revealed significant differences in brain connectivity: Brain-only participants exhibited the strongest, most distributed networks; Search Engine users showed moderate engagement; and LLM users displayed the weakest connectivity."

In other words, working with LLMs reduces the level of engagement in our brains and offloads much of our cognitive activity.

When working with models that require a high level of abstraction and optimization, offloading these tasks to LLMs that essentially scrape and combine code from various sources can lead to disaster. For something like a basic CRUD app such factors are not nearly as important.

I can see the future convergence of two clear trends in software: No-code tools and AI tools. The development of AI agents which handle not only the generation of code but the full development cycle of creating, testing, and deploying projects with a limited level of programming knowledge required.

As an additional note:

Both of these software trends aim to automate and replace many responsibilities of the programmer in a commercial sense. I believe that future programmers will need to become familiar with these emerging technologies in order to remain competitive in the job market.

Namely, math skills. Linear regression, multivariable calculus, the sort of math applied by scientists and researchers. If you do not understand the mathematics at the core of neural networks, now is the time to learn.
by const_cast | 2025-06-19 21:45:12+00:00
> Well, the rational thing is obviously to be scared of what ideas sound like.

Yes, actually. If an idea sounds like it can be used to commit crimes against humanity, you should pause. You should reassess said idea multiple times. You should be skeptical. You shouldn't ignore that feeling.

What a lot of people are missing is intent - the human element. Why were these studies conducted? Who conducted them?

If someone insane conducts a study then yes - that is absolutely grounds to be skeptical of said study. It's perfectly rationale. If extremely racist people produce studies which just so happen to be racist, we should take a step back and go "hmm".

Being right or being correct is one thing, but it's not absolutely valuable. The end-result and how "bad" it is also matters, and often times it matters more. And, elephant in the room, nobody actually knows if they're right. Making logical conclusions isn't so, because you are forced to make thousands of assumptions.

You might be right, you might not be. Let's all have some humility.
by orionsbelt | 2025-06-19 21:45:59+00:00
So can humans? I can ask a human to draw Mickey Mouse or Superman, and they can! Or recite a poem. Some humans have much better memories and can do this with a far greater degree of fidelity too, just like an LLM vs an average human.

If you ask OpenAI to generate an image of your dog as Superman, it will often start to do so, and then it will realize it is copyrighted, and stop. This seems sensible to me.

Isn’t it the ultimate creative result that is copyright infringement, and not merely that a model was trained to understand something very well?
by abdullin | 2025-06-19 21:46:13+00:00
Here is another way to look at the problem.

There is a team of 5 people that are passionate about their indigenous language and want to preserve it from disappearing. They are using AI+Coding tools to:

(1) Process and prepare a ton of various datasets for training custom text-to-speech, speech-to-text models and wake word models (because foundational models don't know this language), along with the pipelines and tooling for the contributors.

(2) design and develop an embedded device (running ESP32-S3) to act as a smart speaker running on the edge

(3) design and develop backend in golang to orchestrate hundreds of these speakers

(4) a whole bunch of Python agents (essentially glorified RAGs over folklore, stories)

(5) a set of websites for teachers to create course content and exercises, making them available to these edge devices

All that, just so that kids in a few hundred kindergartens and schools would be able to practice their own native language, listen to fairy tales, songs or ask questions.

This project was acknowledged by the UN (AI for Good programme). They are now extending their help to more disappearing languages.

None of that was possible before. This sounds like a good progress to me.

Edit: added newlines.