skysight-inc/HackerNews huggingface dataset:
Sure, allow me to amend:

"If you're looking to understand the quality of a service, non-users are essentially worthless."

I'm suggesting that, in absence of some out-of-band signaling mechanism, the expectation value for usefulness of individual feedback is orders of magnitude greater for users than non-users.

Put differently, if I happened to be interested in this SFUSD school as well, is there some list of people like you I should interview?
No, but some of the data is licensed.

For example, my digital garden is under GFDL, and my blog is CC BY-NC-SA. IOW, They can't remix my digital garden with any other license than GFDL, and they have to credit me if they remix my blog, and can't use it for any commercial endeavor, which OpenAI certainly does now.

So, by scraping my webpages, they agree to my licensing of my data. So they're de-facto breaching my licenses, but they cry "fair-use".

If I tell that they're breaching the license terms, they'd laugh at me, and maybe give me 2 cents of API access to mock me further. When somebody allegedly uses their API with their unenforcable ToS, they scream like an agitated cuckatoo (which is an insult to the cuckatoo, BTW. They're devilishly intelligent birds).

Drinking their own poison was mildly painful, I guess...

BTW, I don't believe that Deepseek has copied/used OpenAI models' outputs or training data to train theirs, even if they did, "the cat is out of the bag", "they did something amazing so they needed no permissions", "they moved fast and broke things", and "all is fair-use because it's just research" regardless of how they did it.

Heh.
This doesn't look like a responsible disclosure, at all.

ed: I was wrong!
> for my NAS

What are you using for an OS? It seems like our NAS OS options are fewer than they were a decade ago - especially if you want ZFS.

For the 2 NAS I recently set up, one is running TrueNAS Core (last freeBSD) and the other is just minimal FreeBSD.
> If I could show the decompiler some output I liked and it edited the binary for me to make the output match, then the comparison would be closer.

That's fundamentally the same thing though - you run an optimization algorithm on a binary blob. I don't see why this couldn't work. Sure, a neural net is designed to be differentiable, while ELF and PE executables aren't, but then backprop isn't the be-all, end-all of optimization algorithms.

Off the top of my head, you could reframe the task as a special kind of genetic programming problem, one that starts with a large program instead of starting from scratch, and that works on an assembly instead of an abstract syntax tree. Hell, you could first decompile the executable and then have the genetic programming solver run on decompiled code.

I'd be really surprised if no one tried that before. Or, if such functionality isn't already available in some RE tools (or as a plugin for one). My own hands-on experience with reverse engineering is limited to a few attempts at adding extra UI and functionality to StarCraft by writing some assembly, turning it into object code, and injecting it straight into the running game process[0] - but that was me doing exactly what you described, just by hand. I imagine doing such things is common practice in RE that someone already automated finding the specific parts of the binary that produce the outputs you want to modify.

--

[0] - I sometimes miss the times before Data Execution Prevention became a thing.
Turing machines are typically described as having an infinite tape. It may not be able to access that tape in finite time, but the tape is not bound to a finite tape

But it doesn't matter, it is an abstract model of computation.

But it doesn't matter Church–Turing thesis states that a function on the natural numbers can be calculated by an effective method if and only if it is computable by a Turing machine.

It doesn't matter if you put the algorithm on paper, on 1 or k tapes etc...

Rice's theorem I mentioned above is like Scott–Curry theorem in Lambda calculus. Lambda calculus is Turing complete, that is, it is a universal model of computation that can be used to simulate any Turing machine.

The similar problems with 'trivial properties' in TMs end up being recursively inseparable sets in Lambda calculus.
The Supreme Couet has previously ruled that (in essence) that abortion is a right. It had previously ruled that fair share dues were legal. It had ruled previously that Chevron was the administrative standard. All of these were subsequently overruled.

Your point 3 is needlessly idiotic.
In the new American Kleptocracy, it just might
This whole argument by OpenAI suggests they never had much of a moat.

Even if they win the legal case, it means weights can be inferred and improved upon simply by using the output that is also your core value add (e.g. the very output you need to sell to the world).

Their moat is about as strong as KFC's eleven herbs and spices. Maybe less...
> What I am doing is clarifying that this is unlikely to become a 1st Amendment fight.

It is 100% going to become a First Amendment fight.
Thanks for the answer. Was there an email that went out or something? If I recall I didn't back on Kickstarter, but directly with the company. (Also is it ever going to leave Early Access? Are they asking for more money?)
SEO, marketing, and content generation are fundamentally parasitic bullshit. Unlike the initial .com wave, there is value to some companies, but basically no value to end consumers or (ultimately) humanity.
I worked for a startup that used Kotlin. The language itself is not that bad (if you ignore the engineers that want to use every single time all the features the language has to offer), but the ecosystem was awful. We were using Gradle, and Spring Boot: just too much magic for my taste. Gradle itself is a beast I never fully understood, and I don't comfortable working with such tools (the Gradle userguide has over 1000 pages https://docs.gradle.org/current/userguide/userguide.pdf)

On the other hand, Go is a breath of fresh air; the tooling is simple and one can actually learn them in no time. There's less magic, and so a bit more of repetition, but I can live with that.

I don't see the advantage of having the JVM to be honest. I just don't see why it would be needed in 2025 (the "Write once, run anywhere" is not relevant anymore).
I wonder if it's analagous to spread spectrum[1] with radio comms.

[1] https://en.wikipedia.org/wiki/Spread_spectrum
Why is that bad? If a powerful entity can scrape every piece of media humanity has to offer and ignore copyright then why should society let then profit unrestricted from it? It's only fair that such models have no legal protection around their usage and can be used and analyzed by anyone as they see fit. The only reason this hasn't been codified into laws is because those same powerful entities have been busy trying to do regulatory capture.
I completely agree with you and apologize for cheapening both the nuance and complexity where I did.

My personal take is this. What deepseek is offering is table scraps for the CCP's actual ambitions with what we call AI. China's economy is huge on industrial automation, and they care a lot about raw materials and manufacturing efficiently than say the US's interests.
One of the rare times when the slow pace of open source innovation is actually a benefit, because all innovation that's occurring is making things worse.
If their OS is open to the internet and you can scrape it and copy it off while they’re gone, then that would be about the right analogy. And OpenAi and DeepSeek have done the same thing in that case.
I think the point was more to contrast STC as a certifying and publishing body, versus WTD as more of a peer/user group.
And C++ should have just been Objective-C with saner invocation syntax.
$313 thousand not million which seems reasonable enough.
The official stance in the US is currently that there is no copyright on AI output.
What does 55:55 mean? I know ifkyk but idk and would like to k.
I stopped using Lyft after two close calls with drivers who must have faked their papers. One Lyft drive ran a red light into a postal truck at an otherwise empty intersection causing the front to fall off, like that Australian ship: https://www.youtube.com/watch?v=3m5qxZm_JqM
How hard can it be to wrap it in a loop and apply some off-the-shelf good old fashioned AI^H^H optimization technique?

"Given specific inputs X and outputs Y, have a computer automatically find modifications to F so that F(X) gives Y" is a problem that's been studied for nearly a century now (longer, if relax the meaning of "computer"), with plenty of well-known solutions, most of which don't require F to be differentiable.

Isn't "operational research" a standard part of undergrad CS curriculum? It was at my alma mater.
It is apples to apples.

Microsoft didn't want to compete with Sun so much as have an application development language with a garbage collector that wasn't owned by Sun.

You don't make much money off programming languages inherently.

This also elides an obvious riposte (so you mean they should have just used Mono? how did all that work out?) and a metric ton of differences between what C# targets and what Dart targets.
You would probably say the same thing about Amazon when it was founded in 1994. Personally, I don’t agree with the article if for no other reason than we’re too early in the cycle to know the outcomes. I also don’t think cheaper models will sink the AI market because really models are just infrastructure. It’s what you build on top of the models that’s useful. For example, ChatGPT is actually an agent built on top of models.
The Dev options have a setting to not apply updates on reboot. I'm hoping that'll work if I forget.
Yep.

Kinda like how your comment was grey within 1 minute, despite stating an objective truth.

Sure, this is to be expected given the billions and billions of dollars at stake but like - that money is gone lol. DeepSeek isn't going back in the bottle, nor is open source AI in general.
Apple's macOS Unix certification is a lie
In all seriousness your world view is pretty dark, maybe get outside more?
Alternatives exist, especially for mature and simple models. The point isn't that Nvidia has 100% market share, but rather that they command the most lucrative segment and none of these big spenders have found a way to quit their Nvidia addiction, despite concerted efforts to do so.

For instance, we experimented with AWS Inferentia briefly, but the value prop wasn't sufficient even for ~2022 computer vision models.

The calculus is even worse for SOTA LLMs.

The more you need to eke out performance gains and ship quickly, the more you depend on CUDA and the deeper the moat becomes.
Except we have thousands of competing Soviets keeping the system healthy.
> This kinda does support the 'DeepSeek is the side project of a bunch of quants' angle

Can we stop with this nonsense ?

The list of author of the paper is public, you can just go look it up. There are ~130 people on the ML team, they have regular ML background just like you would find at any other large ML labs.

Their infra cost multiple millions of dollar per month to run, and the salary of such a big team is somewhere in the $20-50M per year (not very au fait of the market rate in china hence the spread).

This is not a sideproject.

Edit: Apparently my comment is confusing some people. Am not arguing that ML people are good at security. Just that DS is not the side project of a bunch of quant bros.
I am an actual trans person, you know. Unlike religion or higher powers, there is a great body of evidence that a model of gender which treats people like me as honest conveyors of our experiences is a much better description of reality than a model like yours.

The difference is that scientific models of gender are naturalistic (they follow typical scientific principles), and religious models are not. I think the naturalistic view of the world is objectively the best view of the world.
I really wish Apple and Google would run VPNs. Then, given their markets are so large, they couldn't be blocked by anyone that wanted customers/eyeballs.

You'd think "Privacy First" Apple would do this.

HN blocks (ghost blocks) VPNs. Make a new account from a VPN. Post. Open a private/incognito window. Load up the thread. Your comment won't appear. Give it few days. It never appears. It only appears for you when you're logged in.
LLM finetuned for generating symbolic music
Is there any evidence for this story?
> Still really early on and wanted to get some thoughts / feedback on the idea or just thoughts on AI trading in general.

My feeling is that trying to use an AI agent to trade against market participants that are also using AI to trade except with nanosecond latency and single digit millisecond pings sounds like a losing battle, but I’m a skeptic at heart.
> "DeepSeek trained on our outputs, and so their claims of replicating o1-level performance from scratch are not really true"

Someone has to correct me if I'm wrong, but I believe in ML research you always have a dataset and a model. They are distinct entities. It is plausible that output from OpenAI's model improved the quality of DeepSeek's dataset. Just like everyone publishing their code on GitHub improved the quality of OpenAI's dataset. What has been the thinking so far is that the dataset is not "part of" or "in" the model any more than the GPUs used to train the model are. It seems strange that that thinking should now change just because Chinese researchers did it better.
Numpy can use the chipmaker’s BLAS (Intel MKL or AMD’s Blis fork). Trying to replace it could be a good academic exercise but I think most people wisely leave that to the vendors.
I noticed several people mentioned Karpathy already, but I wanted to include that his tiny "Micrograd" project (see Youtube Video and GitHub) is a great introduction to Neural Nets (Multilayer Peceptron), which is at the core of [most] machine learning of course.
This looks very nice, and obviously needed in hindsight.

I would love to see a Typescript/node port of this.
Plenty of popular games still do p2p
August 9th 2038. 11:42am.

Zulu time.
since your reply died - your absolutely wrong about massive oversampling, you can get 95% with basic assumptions about 60% white, 40% minority (matching actual proportions in the population - and actually an underestimate when you consider that new hires are young) and the retiring fortune 500 population (70-90% white).

as i said, just basic innumeracy on your part
There really needs to be a price-per-1M-tokens with these announcements. In the case of DeepSeek R1 it's all over the place.
Yeah, mine did the same and later died completely, and only now I found that the LG was refunding the full price of phones or fixing them for free if they had this specific HW issue...
The number of Starlink satellites and the rapidity of their replenishment vastly outnumbers the number of ASAT interceptors, and launchers, that any nation could produce.

Shooting-down Starlink satellites is economically infeasible, never mind the fratricide it would cause to the aggressor's own LEO assets.
My favorite is Russian Borodinsky bread with caraway seed. You can find a standard GOST recipe for it online, but be warned that it's a 48 hour process that includes scalding the dough.
Is a person running an exit node responsible for the requests coming out of that node? Or will it just make for a very awkward conversations with the authorities if someone requests CP or terrorist paraphernalia via your exit node?
I think we will have to move with pre-training and post-training efforts in parallel. What DeepSeek showed is that you first need to have a strong enough pretrained model. For that, we have to continue the acquisition of high quality, multilingual datasets. Then, when we have a stronger pretrained model, we can apply pure RL to get a reasoning model that we use only to generate synthetic reasoning data. We then use those synthetic reasoning data to fine-tune the original pretrained model and make it even stronger. https://transitions.substack.com/p/the-laymans-introduction-...
One obvious business case is customer service chatbots, which all of a sudden do seem to have got loads better, ie, they work for the first time and can at least interact and understand what your problem is (before passing you on to a human) which has been 30 years coming.
They do, sort of; iCloud Private Relay. Details: https://support.apple.com/en-gb/102602
I wonder why making those sort of tools is so difficult
Plus Volkswagen and Subaru in the last few weeks ...
"You have discovered ENGINEERING"
No unintended consequences will occur for those places, like being overrun with not just influencers but hoi polloi.
[Flutter founder here.]

I'm pretty sure we did look at C# (and certainly a whole bunch of other languages). I don't actually recall why we didn't use C# at the time. I remember Go binaries were waaay to big, JS (what we originally wrote Flutter in) startup time was way too slow on iOS, Swift was too deeply tied to Apple (the standard library was closed source at that time), etc. It's possible that C# was too verbose or didn't have a path to hot reload? But that's just a guess. I'm not a C# expert, and Adam Barth drove most of the language evals at the time.

That said, I'm also not sure Miguel (creator of Xamarin) would agree. He's a Flutter fan now (and backer of Shorebird, my company).

Past discussions:
https://x.com/migueldeicaza/status/1778759403451081159
https://x.com/migueldeicaza/status/1559898665350832128
Because it's arguably syntactic sugar and, IMHO, it's worked out better for developers for Dart to model it as a 3rd party library problem. i.e. have a JSONSerializable protocol, and enable easy code generation by libraries.

i.e. I annotate my models with @freezed, which also affords you config of the N different things people differ on with json (are fields snake case? camel case? pascal case?) and if a new N+1 became critical, I could hack it in myself in 2-4 hours.

I'm interested to see how this'd integrate with the language while affording the same functionality. Or maybe that's the point: it won't, but you can always continue using the 3rd party libraries. But now it's built into the language, so it is easier to get from 0 to 1.
You are right, part of every dollar must be paid back. If there is any interest on a loan then you need to pay back more than 100% the original cost.

Our FED operates the same way, the government must pay back the FED's loans, and these loans have interest. When the US was printing greenbacks without the FED there was no one to "pay them back to". This is how the USA operated before 1913.
Seems to be significantly slower than on the official deepseek API. But at least it's the full model!
> That said, if you zoom out to the overall conduct, it's fair to argue that the companies are doing something unethical, the same as if they paid an army of humans to memorize other people's work and then regurgitate slightly-reworded copies.

I would use the analogy of those humans learning from the material. Like reading books in the library

"regurgitate slightly-reworded copies" in my experience using LLMs (not insubstantial) that is an unfairly pejorative take on what they do
I had it extract the data from the page directly and actually calculate it:

https://chatgpt.com/share/679aafa9-7ac8-800a-8f4c-3ba67f4502...

It claims it's ~47 (only natural causes). I'm too lazy to verify it of course...
I think Go would have been the most logical choice, given that it's Google.
Like Nokia, Samsung and Huawei, among others, before DeepSeek.
The US (firms and government) are just acting as a bully, as always...
I'm not super familiar with this project, so forgive a bit of ignorance on this; what does this buy you over vanilla Clojure and native-image compiling with GraalVM.

This is a genuine question, not meant to dismiss the project!

ETA:

Sorry, further down the article answered my question:

> “jank is also a good fit for any Clojure devs who want a lighter runtime without sacrificing JIT compilation, as they would if they used a Graal native image, or if they want easy access to native libraries for whatever reason.”
Who's going to go after them? Heck, they may get an award for this.
I think this sort of stuff implies a switch to new APIs that understand that the app is inside a sandbox, instead of "just trying to do things". For example, XDG Portals for opening/saving documents, instead of open(2) syscall.
Do you also comment like that on every man’s channel that you watch?
It does? The article goes through a number of specific examples, including screenshots of actual results, and repeatedly links the dataset in different forms.

You do have to click into the link though.

https://huggingface.co/datasets/promptfoo/CCP-sensitive-prom...

https://docs.google.com/spreadsheets/d/1gkCuApXHaMO5C8d9abYJ...

https://www.promptfoo.app/eval/eval-0l1-2025-01-28T19:28:13
Yeah I could maybe highlight how good that library is in here
I keep seeing similar aesthetics for landing pages and startup sites. Is there some common template that’s become popular for this purpose?
Astral has consistently surprised the python community with amazing tooling. It was a matter of time before they jumped into type checking. I think ruff and uv were good first MVPs for a small company with a highly talented team. I can't help but wonder if someday they'll attempt to build their own Python interpreter in Rust, or if that's overkill.
Can't fault hackers for taking a look at a website that goes from "virtually unknown" to "extremely popular and headline news globally" practically over night. If nothing else, the probability of low-hanging fruit in something that is barely battle-tested is high.

You can fault them for disclosure practices though :-)
Which AMD GPU gives you 50 tok/s on a 30b model? My 3090 does 30 tok/s with a 4 bit quant.
On the contrary with cheap LLMs this practice will be more prevalent. If you lift the cost barrier the McKinseys will be attaching all sorts of AI to everything.

All the AI bust means is that for engineers working at companies that invested too far into AI they're going to be looking for jobs. ML departments will be culled too. Just like the dot-com bust.
One of their drives was famously so unreliable that it has its own wikipedia page [1].

Guess who had two of these fail almost at the same time in his NAS a couple of years back.

1 - https://en.m.wikipedia.org/wiki/ST3000DM001
You know, I personally would love that too. TypeScript is my favorite language and tons of infra is built on Node now. Would you like to collaborate on building an mcp-agent.js? I think it can be done within a week or so. Let me know!
I might be missing something here, don't records already exist? https://dart.dev/language/records
I, for one, think this is a valuable piece of information and somewhat interesting analysis. You can take the cynical point of view that this was released just to tarnish their reputation or you can assume that it's security researchers publishing an important discovery just like they've always done whether it's for OpenAI, Microsoft Copilot, or any other AI or non AI product.