skysight-inc/HackerNews huggingface dataset:
Why would anyone need a library when we could just do this?

arg=default
while [ -n "${1}" ]
do
case "${1}" in
--arg)
shift
arg="${1}"
shift
;;
*)
print_help_page
shift
;;
esac
done

The above is terse, readable, and doesn't rely on any dependencies other than POSIX compatibility.

Often the whole point of shell scripts is that they're dependency free; nothing is needed other than the shell. After all, why code rustup in sh if not for this reason?

People who make libraries like this for shell are, I think, missing the point of shell.
Making each webapp target & optimize ML for every possible device target sounds terrible.

The purpose of MLIR is that most of the optimization can be done at lower levels. Instead of everyone figuring out & deciding on their own how best to target & optimize for js, wasm, webgl, and/or webgpu, you just use the industry standard intermediate representation & let the browser figure out the tradeoffs. If there is inboard hardware, neural cores, they might just work!

Good to see WebML has OpenXLA on their radar... but also a bit afraid, expecting some half ass excuses why of course we're going to make some brand new other thing instead. The web & almost everyone else has such a bad NIH problem. WASI & web file apis being totally different is one example, where there's just no common cause, even though it'd make all the difference. And with ML, the cost of having your own tech versus being able to re-use the work everyone else puts on feels like a near suicidal decision to make an API that will never be good, never perform anywhere where near it could.
It's great that USCO is ending speculation with an official stance. Their rationale seems perfectly reasonable, and in step with the court rulings that they cited.
This didn't start with the Communists, it started with the Luddites. We don't think of them as the start of this sort of thing because wealthy Englishmen successfully slandered them as just hating technology for the sake of hating technology, so instead they're a by-word for "technophobe".
The city I live in recently passed a ban on "flavored tobacco," which includes (for some reason) vape products. While this ban has not taken effect yet, after it does, the net effect will be that full strength cigarettes like Marlboro Reds remain accessible at every gas station and corner store, while any vape product with a "flavor" is no longer legally saleable in the city limits.

I guess if flavor bans don't count for you, this wouldn't bother you. For me, this is a major "throwing the baby out with the bathwater" move that will remove access to a class of product with great effectiveness for smoking cessation and harm reduction. The reasoning, to my eye, seem to be largely moral panic bullshit, largely caused by the popularity of vaping among teenagers. (Why not impose harsher penalties for stores selling to underage kids? Seems to work fairly well for liquor in my experience.)

I'm also generally opposed to prohibition and think adults should be able to decide what goes into their bodies, so I'm opposed in principle.
That's precisely my question though, what are the possible risks? To me this seems less like a security exercise and more just like a fun way to get the bot the say things it normally wouldn't.
Grandpa? You know the rules about using the family computer after 8pm. You're supposed to be sleeping. It's for your health. Come on: back to bed.
From what I understand this seems useful if you have a model that will accept a large or unlimited number of tokens. I was looking into doing the same thing with ChatGPT and went with ada to find snippets related to the prompt and then to include those with a prompt to ChatGPT: https://bbarrows.com/posts/using-embeddings-ada-and-chatgpt-...

Does ChatGPT 4 now accept more tokens maybe?
A Dismal Guide to AWS Billing
How much text can you feed GPT-4?

Our codebase is 1 million lines of code.

Can we feed the documentation to it? What are the limits?

Is it possible to train it on our data without doing prompt engineering? How?

Otherwise are we supposed to use embeddings? Can someone explain how these all work and the tradeoffs?
>For example, if a user instructs a text-generating technology to “write a poem about copyright law in the style of William Shakespeare,” she can expect the system to generate text that is recognizable as a poem, mentions copyright, and resembles Shakespeare's style. [...] But the technology will decide the rhyming pattern, the words in each line, and the structure of the text.

Neat example and convincing reasoning.
That's why, if you're going to pay someone 100 million dollars, you make sure they're the kind of person who won't quit first.
The thing is that it's super close to the migration of various streamers (some with a very high viewership) to a new platform. Though I also take it a bit at face value, in the sense of he was waiting for this and tired of all the shit that comes with Twitch.
Isn't that convenient, eh?
> In SVB's case, can't you cover depositors simply by holding their assets to maturity and waiting for them to be repaid?

If you're willing to lock the depositors up for 10 years and pay them back when those assets mature, sure. But that probably wouldn't be seen as an acceptable way of making those depositors whole.

Someone's got $100 of deposits with you today; you're holding a 10-year bond that will pay $102 over the 10 years but currently trades at $87. Yes you "can" "pay" "them" "back" eventually, but what if they want to pull their deposit today, perhaps to buy a bond like the one you were holding? If you do the accounting based on today, they're entitled to $100 and you only have $87; if you do the accounting based on 10 years' time, they're entitled to $115 and you only have $102; either way there's a shortfall.
For example: I can't punch a bear to death but give me and the other humans some time and we'll find a way to eradicate every single one of them.
Agreed, they basically launch Starlink satellites for free as they can reuse launch vehicles other customers already paid off.

Remains to be seen whether this is intentional or not. Given how a few of the satellites had a much sharper decay in orbit I would lean towards the latter. Doesn't seem to make sense that they would take them up only to bring them down again if they were setting them at a lower orbit.
It’s gotten so ridiculous I’ve started to see jobs… fully remote… that say will refuse to hire you if you use any nicotine products, explicitly including quitting aids like gums and patches.
If you're on a slowly-sinking ship, it'd be silly not to at least try to bring in someone with the full context of the ship's architecture to get it serviceable before going all-in on the decision to engineer and build an entirely new kind of ship while still aboard the sinking one.
They’re there, released Core ML Stable Diffusion a couple months ago.
This is all very sane and consistent with previous opinions on the matter.

But it doesn’t answer any tough questions either, like: if an AI model outputs something very close to a training input, does the result infringe on the copyrights of the input work?
Right… I hope this isn’t a situation where everyone has to be dishonest in order to compete at the highest level. Major League Baseball and cycling from the early 00s come to mind. I wonder if having correct rules that are unenforceable do more harm than good.
> its up to the tech community to educate ALL the casuals (best we can) so some idiot executive don't put it in full charge of mortgage underwriting or something

tech community are the idiots. Look at google autobanning based on AI

The inmates are running the asylum
Recipes are usually not copyrightable as they are just a list of ingredients and instructions with no room for expression. I wonder if the same argument could be applied to prompts.
I would love someone to clearly explain what makes a workplace culture toxic.
Asking for a friend who would love to know and understand all of the things that clearly contribute to workplace toxicity so that they can avoid them.
Not sure how you've landed on smoking (especially since it's not even mentioned in the article)

There are a multitude of other methods of consuming cannabis.
Does Swift has pattern matching and equivalent of Option/Result enums? I tried it casually but the documentation didn't feel great and things felt like they assumed familiarity with Apple's ecosystem.
Italy Revives Bridge-to-Sicily Plan That Eluded Ancient Romans
You bring up an excellent point, and it’s something we really should discuss in our explainer:
https://github.com/WICG/turtledove/blob/main/FLEDGE_k_anonym...

We’ve been calling this problem key consistency, basically the risk that Google (or any OHTTP gateway operator) gives out unique keys to different users and builds a {user -> request} mapping based on the keys used to encrypt requests. The OHTTP authors published a draft spec discussing exactly this problem.
https://datatracker.ietf.org/doc/draft-ietf-privacypass-key-...

Frankly, none of the technical solutions we considered were satisfying enough given the added complexity. It’s actually kind of tricky to form a convincing distribution model. The designs we looked at mostly involve multi-party schemes where there’s trust required either that parties don’t collude with each other or between the user and one party explicitly. Admittedly OHTTP is also premised on multiple parties not colluding, but we decided to punt on the key consistency problem for the sake of simplicity. We also recognize that it’s possible for savvy users to fetch the keys from the endpoints we’re serving them on, compare those keys with other users, and fact check our claims. We honestly have nothing to hide about this; everyone is receiving the same key.

To specifically address the two proposals you made:

1) Shipping the key with the client: it’s not clear this is any better than fetching it right from Google. Chrome updates and our experiment framework (known as Chrome Variations) are both Google-managed distribution mechanisms, not terribly different from fetching the key at a Google API endpoint.

2) Having the relay serve the keys: these keys are actually designed to protect data from the relay. If the relay could change the public key Chrome uses to something the relay knows the private key for it would undermine the purpose of HPKE encryption. You suggested the relay could serve a key signed by Google. The issue with that is it complicates the process of key revocation. We expect to rotate the key we use, and we want to maintain the ability to revoke keys if needed (say the relay learned of a private key). Sure we could serve a signing key revocation list, but then we’re back in into the world of complicating the multi-party relationships.

All this being said, addressing key consistency issue is on our radar, and we hope to improve the distribution model in the future. We welcome feedback of course; and we’ll take it into consideration as we continue to evolve the designs used here. There is a general blog post on Privacy Sandbox feedback at [1] and you can take a look at specifically how Chrome is fetching keys in [2]. In case you're curious the key we’re serving today has a cipher suite of (DHKEM_X25519_HKDF_SHA256, HKDF_SHA256, AES_256_GCM) and at the moment we have two gateways (one for read traffic and one for write traffic) each using their own single keypair.

[1]: https://developer.chrome.com/docs/privacy-sandbox/feedback/

[2]: https://source.chromium.org/chromium/chromium/src/+/main:chr....
The point is that whatever the role, the LLM is supposed to be "safe", and it won't be safe if it is injectable.

Let's say you are generating contracts with it and those contracts take a bunch of input from all parties involved. If you are able to then inject input that causes the LLM to generate a contract that is subtly changed to your favor, the other parties may still assume it is safe and sign it. Even it they catch it and don't sign it, you have broken the system. The point is as long as these exploits are possible, the LLMs in question are not suitable for any task where the output needs to be trustworthy within any kind of parameters. Which is pretty much anything you'd use then for other than toys.
> However, with LLMs coming, I could see data center energy usage jump 10x over the next decade.

Just a note: we are probably right now at peak inefficiency for LLMs. There are obvious improvements available but they will only be explored by organizations which have different time vs resources trade-off calculations compared to OpenAI and Google.

Right now OpenAi and Google are racing to ship products. A working training framework is more important than saving $X (where X is a very large number) because capturing marketshare is seen as vital and they have no shortage of capital.

But the massive and rapid progress seen by projects like llama-cpp show how much performance they are leaving on the table. (And yes this also applies at training time).
Hi! Creator of the library here. If you change the generation parameters to be greedy (i.e., sample=no and top_k=0), you will get "Bonjour, comment êtes-vous?"

The top_k and sample generation parameters are just there to show that they are supported :), and is sometimes useful for the other tasks (like text generation w/gpt2, to get more variety)
Tsoding is a really impressive (though cranky in an almost stereotypically Russian way ) coding livestreamer. I've really enjoyed his voyages around Haskell, Rust, and other esoteric pursuits over the years: https://tsoding.github.io/
Something else streamers mention is that on twitch there are way better/more moderating features than on youtube. Shared ban lists, automod bots, annottions like "likely avoiding ban" etcpp
To prove you can run a marketplace with lower commissions since the Epic Store was shown to be running at a loss, which hurt their case against Apple. Or so I’ve read.
A buddy of mine works for Pepsi maintaining outside equipment and says how people go from place to place throughout the day just spending everything they have on slots. Harder to feel sorry for someone that eats and leaves a few minutes a day, every day than someone that sits at one place all day wasting everything they have.
The issue is, much of the performance of Pytorch, JAX, et al comes from running a JIT that is tuned to the underlying HW, and come with support for high level intrinsic operations that were either hand-tuned or have extra hardware support, especially ops dealing with parallelizing computation across multiple cores.

You'd probably end up representing these as external library function calls in WASM, but then the WASM JIT would have to be taught that these are magic functions that are potentially treated specially, so at that point you're just embedding HLO ops as library func, and them embedding an HLO translator into the WASM runtime, I'm not sure that's any better.

By analogy would be be better to eliminate fragment and vertex shaders and just use WASM for sending shaders to the GPU, or is the domain specific language and its constraints beneficial to the GPU drivers?
> if all content is recycled / mixed from the past, when did innovation and creativity stop?

Your question contains the answer. Remixing begets innovation / creativity begets remixing.
Yeah, I'm aware there are some legitimate uses for crypto, apologies that I came off overly dismissive.

My point is mainly that the use cases for GPT/LLMs are pretty glaringly obvious to anyone with an imagination and should be proportionally more difficult to dismiss as seems to be a somewhat popular minority opinion here on HN.
Hi, Vaibhav here, the creator of the token smuggling attack. They have just banned the variation of this particular prompt, please change the words/smuggling technique and it will work accurately.
Just train it on tic tac toe and it will figure out the only winning move is not to play
The difference being AI is likely going to massively change the world we live in within the next few decades, just like the internet did. AI's abilities have increased exponentially in the past decade, and are improving vastly right in front of our eyes.
Maybe excuse is the wrong word.

It’s like saying: “It only affected 2% of our users, therefore we figured it wouldn’t be a big deal. Nobody cares about 2%.”

It’s those two percent they’re aiming to apologize to isn’t it?

Then of course they missed the fact it would impact the entire OS community…
There’s this gold rush going on, you’re right, any B without RLHF is meh.

The things getting published as “on device LLM” focus on bitcrushing the lowest B model with minimal RLHF and then pronouncing we have on device LLMs. We’ll definitely get there but signal >>> noise currently.

First person to admit this and write their blog post with A / B tests vs. a Markov chain deserves the gold.
Yes, it was on SyFy, but was a CAD co-production so aired on CBC here.
Why are you trying to minimize his lived experience (or in English, just "experience")?
Fraud has existed for a long time.

For the most part society is designed with the assumption that most people will tell the truth.

You could create a different kind of society, where the default assumption is everyone lies, but I suspect no one would be able to live under those conditions.

Note this is not the same as taking steps to check for lying, it's just a question of what's the default assumption.
"Based on the Office's understanding of the generative AI technologies currently available, users do not exercise ultimate creative control over how such systems interpret prompts and generate material."

As an artist and a musician I use various degrees of randomness in my work - from feedback and "noise" in a composition to abstract splatters in my paintings.

Plenty of art, writing, and music is the result of partially or completely random techniques, over which the artist has little to no control, and AI generated works are just another tool in the hands of a creator.

The copyright office understands neither art nor creativity.
There is huge variation in how well people can prompt LLMs, prompt-engineering has many tricks that aren't obvious, that's why there's prompt engineers,
This works for now. However, I can imagine a spectrum of input parameter specificity that could eventually blur the line this draws and undermine this strategy.

On one side you have these general prompts.

On the other side you have, say, autotune, where the final output is still created by a machine but the human's input (voice in this case) greatly constrains the output.
I don't think we can quite know yet really, but whatever it will be, this will be a solid avenue to at least not be caught by surprise.

And just, we are already starting to be like "ok lets start teaching people with this" or "maybe we don't need lawyers or doctors anymore." Maybe we don't see the full implications yet, but there is a lot of potential for undesirable externalities already! That seems reason enough to be constantly trying to break it to find whatever out from this practice.

The day we stop hacking and trying to break and/or coerce things is the day we lose everything. Isn't this how we all got into this computer stuff to begin with?
32k tokens is the limit, so you won't be able to load the whole thing into the context.
If someone build a software that would be able to attend a meeting instead of you - it will become as popular as Zoom. Combine LLM with voice and video recognition and synthesis, and voila - an immense chunk of wasted time in every corporation is gone.
And how close is too close?
You misspelled RRDTools.

And it took absolute ages for industry to get to the level where those graphs could be recreated easily in something else.

Even now it's pretty hard to recreate something like what https://oss.oetiker.ch/smokeping/ does with it.
I used to be very much the same and have started to reconsider too. I think I’m shocked at just how prevalent it becomes when it’s legal and advertising is permitted. It’s like gambling becomes a double digit percentage of the economy.

In the future I think the ability to resist addiction is going to become a massive factor affecting life outcome, possibly even larger than intelligence or education or appearance.
It is possible that it will hit a dead end. But I believe nobody expected the current architecture to be anywhere near this good.

I can literally tell it, in plain text with a single example, to become a home assistant to control the lights and output JSON, then prompt it with natural language like "make it look like a submarine on battle stations" and it will output a setting where all the lights are red. In the exact format I asked it to use.

That's a bit more than "appearing to solve a problem". That, right there, is a directly usable application. I could literally plug a speech to text -> ChatGPT -> something that filters invalid JSON -> light controls together, teach it a few more commands, and have a much better home assistant than anything I've seen commercially available, limited mainly by the speech recognizer.

The incredible thing about this is that it can't just do that with ONE problem, it can do that with MOST simple problems that don't require really extensive background knowledge, and it is clearly able to encode knowledge (battlestations -> red), so it seems plausible to me that more data will let it handle more knowledge.
Dungeons and Dragons Could Prevent the AI Apocalypse–Or Kick It Off
> Which entirely depends on how it is trained. ChatGPT has a centre-left political bias

Would an AI trained purely on objective facts be perfectly politically neutral?

Of all benchmarks to asseess AI, this is the worst. I would rather have clever, compassionate, and accurate but biased AI.

Then one that is callous and erronous but is neutral
“Not going to know” can apply to most laws.

Most people especially enterprises abide.
Not possible to reliably tell apart. The Image generation scene is one thing. For a lot of output, there are still some tells. Text generation though...well good luck ever finding that out.
It's like they know something is up. Got 2 random texts today after not getting any for a few months.
Rather than prompting GPT into implementing a solution, can we prompt it to try to preemptively find issues with the codebase or missing-functionality?

Also, do we know what languages GPT-4 "understands" at a sufficient level? What knowledge does it have of post-2021 language features, like in C23?
Have seen this destroy families as well. Once people use up their own funds they will absolutely find ways to extract from others, including elderly parents. It can be ruinous.
Project Daedalus could reach 10% speed of light. But that didn’t use thermonuclear bombs but laser-pumped inertial confinement fusion. It also didn’t use physical pusher but magnetic nozzle. We don’t know how to do them with our technology but should be possible. There are followons that are more doable but slower.

I have seen Wikipedia quote 10% for regular Orion but not finding any sources. I find that speed unlikely with all the trouble that Daedalus and others went through to get interstellar pulse rockets. I see 6ksec impulse for could-build-now Orion, 100ksec for theoretical improvements, and Daedalus would be 1Msec. Regular Orion probably maxes out at 1%.

Fission Orion is infeasible for interstellar because need huge quantities of fissionables, maybe 10-100x weight of ship. Fusion has advantage of using cheap elements.
> If an author chooses not to credit an AI, how are they going to know?

USCO doesn't generally proactively investigate (it would take too long), but a copyright claim could be invalidated if it is proven that the applicant didn't disclose required information. As of today, the USCO has explicitly say that AI-assistance needs to be disclosed.
Sounds reasonable and like good code and design, perhaps we "engineers" think hard enough already. I just started reading A Philosophy of Software Design and it talks about "deep" modules (they give the example of UNIX's open creat close lseek and read vs java's I/O interfaces).