skysight-inc/HackerNews huggingface dataset:
Slack maybe, but I doubt they copied anything from Zoom. The Zoom UX is pretty inconsistent and horrific for some very basic things.

E.g. Ever tried to get a chat history from a call that's finished with Zoom?
Except in this case, $400 can also buy you one shirt per year for 12 years, all of which combined would most certainly last you longer than 12 years. Moreover you wouldn't have to waste your time babying them.
Yes, a program that spits out shit it reads on the Internet without a hint of understanding is in fact unacceptable. But, similarly to people who to the same, is entirely unstoppable at this point. The billionaires funding all this seem to have a similar lack of understanding.
Low bid contractors will probably use this library to pump their code coverage numbers. Some of the shit shops I have worked at that hired lowest bid contractors have done some shady shit to meet “management expectations”.
Read the pdf https://arxiv.org/pdf/2402.17764.pdf they call it 1-bit everywhere.

I don't know why do they do this, 1-bit seems to be a very wrong name for {-1, 0, 1}.
If it's desired integer performance could far exceed float performance, since ALUs need less die area than FPUs.

If this paper holds, I'd expect that's where custom accelerators will be heading.
Sounds like it got taken in by religious fantasy.

This could be a difficult problem to address since so many people and so much "information" follows suit.

How do you impress upon software driven by statistics and struggling to separate fact from fiction that this common mode of human thinking and expression is delusional and irrational and should not be mimicked or followed?

In other words, how do you explain to software this contradiction --- that god was created in man's image while *most* people prefer to express just the opposite?

How do you explain that "belief" in AI and crypto currency follows a similar pattern?
looking forward to see same title but for developers.
Having spent far too long in the annals of higher education, those who would be comparable stewards of growth are few and far between.
https://lobste.rs/s/0akqy7#c_ihruks
I am curious how the AI Agent drives. I actually think there is opportunity here because the current generation of "chat bots" that companies use are honestly terrible and frustrating.
By thinking slow.
YEah, pre-caching is very much what I do.

If you combine it with empathy skills: "What motivates this person", "What are their goals", "what are their interests/specialities" then you can work out a list of stock answers before hand, and alter them to suit the situation later on.

You still need to listen, as there is a non trivial risk of your mental model being wrong.
I won't run a VPS. I'm entirely capable of doing it.

Badly.

I'm a mediocre Linux admin, at best. The current environment is so dangerous, these days, that it's worth your life, to have your essential services run by a mediocre admin; even if I can convince myself that I'm the best (spoiler: I'm not).

I'll generally run shared hosting, or managed servers.
This problem isn't going to be unique to Twitter even if we're seeing it there first. Any site with user generated content will be chasing a never ending battle against bots churning out LLM content.

There's really no way around it from what I can tell. How does one actually recognize and block not content online in an automated way? When the platform is digital and we now have digital means of generating content, the battle is lost IMO.

Maybe it could be delayed by some kind of platform or regulatory change requiring state issued ID for all internet users. I think that has come up before and it feels very similar to what a few Googlers proposed (before the community dog piled on it). That's not a version of the internet I'd want to use though, and if that's the only avenue for avoiding a web full of bots it sure seems like the days are numbered.
That has already happened. Companies are hiring less on the engineering front and seeing AI tooling as multipliers to existing developers.

Edit: No direct citations, my own experience, sorry! Interesting to see how many people are throwing up the pitchforks in defense of engineering. Even if you are only getting a 5% increase in productivity via AI assistants, thats ultimately less people you may have to hire.
Exactly, they overshot the target. Bugs happen. The big mistake was not having team who actually knows what's going on to say "hey, you're over-correcting, hold the train. We got a bug here."
What are these hardware hacks you suggest?
I might have been a stupid assumtion indeed but I assumed it based on the fact that Gemini does not respond with the same shit chatGPT says regarding its knowledge cut-off.
I think we could limit the blast radius by working in reasonably sized chunks--like O(10-100MB)--and possibly replicating (which becomes much more attractive when the data set gets a lot smaller). But you're right, it's a good point that redundancy can be a feature.
Lots of great insights here. Personally, I use ChatGPT as a "sparring partner": I present an idea and talk with it to elaborate it further. Wether it's about programming, science, writing prompts or game design, among other examples.
Another great use case is to use ChatGPT to speed up chores, like hard to remember syntax or functions that are easy but boring to think and write, like parsers. Or even thinking about how to build the architecture of a certain application.
It's not quantising existing models, they're training new ones.
You can improve your quickness with experience in a particular area.

I am not very good at chess. If I need to make a decision on a move, I will think slowly and deeply. In the end, I often make a move because I feel I used up too much time, and not because I think it is a good move.

There are some domains where I am very experienced. When I listen to someone's question, many possible solutions come to mind. As the person continues to explain the situation, some of the solutions are eliminated as they don't apply. When the person finished speaking, I have either a possible solution for their problem (assuming they provided adequate context) or some followup questions. In either case, I am able to offer a quick response or followup question, and may come across as quick-witted.

I don't think I am quick witted. I am able to listen and process at the same time. I have a considerable library in my head on some subject, and can navigate it while someone is speaking.

This varies from subject to subject, and largely depends on the complexity of the question or decision. The more I know about something, and the simpler the situation, the quicker comes a response. To someone who has less experience, this may seem like a quick wit.
Yes it is. Saying happy hour existed before this announcement so any kind of price discrimination is not new or surprising ignores the human psychology of it all. Yes, the math works out the same if I charge $5 normally and discount it $1 during happy hour, and if I charge $4 during happy hour, and surge price $1 all other times, but people don't like getting charged extra for things because it feels like they're being cheated. Saving money on the other hand feels like something good has happened. Saying oh but that's just feelings and emotions dismisses the fact that we're humans that have feelings and emotions. Emotions like surprise. This is surprising, because it feels like Wendys just announced "hey, we're going to go gouge our customers. Have fun you guys!" If someone wanted to get into PR and the business of writing press releases, this would be an example of what not to do. Of course this isn't a new thing, but you call it dynamic pricing, say it's cheaper during the lull, and never ever say the word surge. With one press release, Wendy's has earned itself a bunch of bad press, and a bunch of fanatics who will shit talk them at recruiter opportunity and boycott their restaurant because they couldn't be bothered to put out a really lame and boring version of the same thing - that they're spending $20 million to modernize their in-store menus.
Crore
I agree that it’s not a great analogy but would caution that some of the same concerns about complacency apply. If this tool produces some decent looking output, it’s not hard to imagine a mistake being okayed because it looked good similar to someone hitting “LGTM” on Friday afternoon because it’s been fine the last 500 times OR miss something else because they were assuming that the AI would flag the important areas.

I know that people in the military are very familiar with problems like that so I think the main concern here is making sure that vendors don’t successfully oversell their products’ capabilities.
you can reduce the need to be in those situations

when it comes to human interactions, you don't really need to respond. most of that is pride or lack of options.

for example, in interpersonal relationships, its a learned trait to not respond reactively

in another example if you're overemployed, you don't need to quickly fight for relevance in your job from decisions that could theoretically seem like threats to your division or employment to just you, because you already secretly have another job
- we have llama.cpp (could be enough or at least as mentioned in the paper a co-processor to accelerate the calc can be added, less need for large RAM / high end hardware)

- as most work is inference, might not need for as many GPUs

- consumer cards (24G) could possibly run the big models
Hard to see a human making them, they're not just typos. Catgacating?
How are they different from GenAI mistakes? Are all LLMs and image generators the same?

For reference, sure looks like some of the gibberish in [https://gizmodo.com/rat-dck-among-gibberish-ai-images-publis...]
Do you mean just putting each app in it's own folder? That just isn't enough for isolation and could be massively wasteful, depending how far you take it.

Flatpak and NixOS are more complex because it's worth it. For example, they don't duplicate exact versions of dependencies on disk.
People seem quite excited by the new goggles.
So are there any details on the algorithms they used for backprop? I'm not seeing any in the paper other than "we used a lot of tokens".
The people who steal it were probably not going to buy it anyway. And it’s not like they are downloading a car.
Well, you do need things like emphasis, lists, headings etc., which aren't typically part of a programming language.
Is driving a single car to the mall really that much worse than a delivery truck making deliveries?
The tech-employee cycle is turning
Who is going to hire all those millions of marginal workers now left without a job?

And those who get employed, how are they going to make near as half as much as what they made?
> If by "smallest pieces of the system" you mean something like individual classes then you are definitely testing implementation details.

If your classes properly specify access modifiers, then no, you're not testing implementation details. You're testing the public interface. If you think you're testing implementation details, you probably have your access modifiers wrong in the class.
sure, pick a target, aim for it, and try to hit it, then have people whose job it is to tell you if you hit the target or not. They evaluate the work before your customers do and so you can do things like stop ship when significant bugs are found.
I understand this part but it seemed that the 16->8->4 etc is similar to compression of the "net" and seemed to lower quality below 8.
I wouldn't be surprised if this causes hardware startups to pop up that build accelerator cards tuned for this architecture. It seems stupidly simple to do inference in hardware, and with most of the training being quantized as well you might even be able to provide speedups (and energy savings) for training with reasonable investment and on cheaper processor nodes than what Nvidia is using.

Sure, Nvidia might eat their lunch in a couple of years, but bitcoin ASICs prove that you can have a niche producing specialized processors, and VCs would probably jump at the thought of disrupting Nvidia's high margin business.
It's coming in October with the new Apple chip
1-bit LLMs remind me of a random forum post I read about SACD and limitations of the 1-bit DSD audio format. https://www.audiosciencereview.com/forum/index.php?threads/d... Accumulating approximate values in one bit leads to being "constantly overloaded", with any error correction overwriting all of your real signal from the next step. I think this trinary system might leave enough room to avoid this problem.
Depends. The only paper they cite for training: https://arxiv.org/pdf/2310.11453.pdf doesn't improve training costs much and most models are already training constrained. Not everyone has $200m to throw at training another model from scratch.
piracy is not stealing. the potential profit that they could have had is just potential, not actual, so you don't steal money. You also do not steal the game since the game is still owned by nintendo/others. Please don't accuse users of doing something they don't do. Also, this lawsuit is not against users, it's against an emulator creator, they didn't still nor pirate the nintendo content (it can be debatable if they had access to proprietary nintendo code and the emulator was written based on that code, but if not we can for sure say that they do not infringe nintendo's copyright)
> Nowadays, it is just 90% bots in all replies.

all bots posting viral clips that have nothing to do with the content you clicked the comments on

its very annoying
Related:

Klarna says its AI assistant does the work of 700 people - https://news.ycombinator.com/item?id=39531662
One friend once told me, even a few years before ChatGPT, that they use AI to generate daily horoscopes in his online newspaper. Using far more simple models.

Nobody ever noticed.
Because NASA could accord to pay one start up.

I belittle nothing but landing rockets wasn't a new idea and wasn't seen as impossible.

It was an evolutionary step and that's what I acknowledge.

But people treat Musk as if he single handedly built a Mars colony.
Yes Technically, but it is catchy for the masses. 1-bit seems to get the idea across, even if not technically describing {-1,0,1}.
That suggests an interesting idea.

Figure out what might be meant by "a good employee." This is hard. Maybe factor in tenure, promotions, projects delivered, peer evaluations, etc. Develop of set of measures for an employee's overall all-time job performance.

Now take each candidate's "interview binder" and map it to some set of ratings (coding proficiency, favorite ice cream flavor, etc.). Set thresholds for each rating initially to reach hiring targets and some vague notion of an acceptable employee profile.

Always allow some small percentage of candidates below the thresholds to receive an offer.

Correlate the interview rating dimensions with the set of employee performance measures as employees work through the job.

Adjust the interview thresholds and experiment with adding or removing dimensions as you learn which things in the interview are correlated with "good employees."

Maybe this is how it's done when it's done properly, but it's the "extend offers to a few people below the cut, and see if they fare worse" idea that I like.
Is there any reason to believe they're worse than any other business with operations in china?
Personally, growing a startup enough to catch the eye of EU regulators is a problem that I’d like to have.
If this paper (especially the results on Table 4) is true, then this is a game changer!
yes only matter of time until you can present an AI with a specification and mockup and it will give you the code/app

it would need some human touch but most of the work will be done already

edit: i just had this thought that my dev job has become less coding and more process and tooling over the years. which is why i dont enjoy it. it feels like tedium that should be automated.
Hopefully not powering this bot:

https://www.forbes.com/sites/marisagarcia/2024/02/19/what-ai...
He's got his own blood boy!

> Johnson has gotten experimental blood-plasma transfusions from his teenage son

Living the dark humor some parents share. Or just being a vampire. You choose.
didn't oslo always been warm bc of ocean currents?
Does this help? https://arxiv.org/abs/2310.11453

It seems to have more details (it's the paper before the linked one) about the actual training, but I'm scanning it and this isn't my field so maybe it's too light also.
The Internet was (is) a totally transformative technology which has changed how people work, play, shop, and interact worldwide. Your claim is that generative AI will do this? How? I recall a few months ago the Web 3.0 people saying a similar thing. Is it different this time?
This isn’t the only possible explanation. If you compare Y-chromosome haplogroups to mitochondrial haplogroups there are similar cases within even more recent human populations. For instance, European populations almost exclusively come from R1a and R1b Y-chromosome haplogroups that probably originated with the Proto-Indo-Europeans of the Pontic Steppe. However, there are still European mitochondrial haplogroups corresponding to much earlier European populations.

In other words, the carriers of the R1a and R1b haplogroups specifically replaced the male population of prehistoric Europe. These were all modern humans so there’s no reason they wouldn’t be able to have viable offspring the other way around. That’s just not how the Proto-Indo-European migrations seemed to work out.

That’s not to say that the same thing happened with the Neanderthals. We can piece together the story of the PIE’s from archeology, linguistics, and population genetics to a much fuller degree than the story of the Neanderthals. But it does go to show that you can have significant interbreeding events between human populations that do end up happening exclusively one way around.
Open-source AI visual video and audio search
This free and open-source solution uses OpenAI Vision and OpenAI Whisper to extract segments of the video based on a prompt like "Extract all the places where he talks about Microsoft" or "Get me all the scenes where there is a person with a flag in their hand". Running on Drupal.
Neutron capture reaction cross-section of 79Se through inverse kinematics
Was Eunuchs, an OS that runs only on 8088 CPUs, a joking reference to Linux?
Perhaps you could ask some of your favorite podcast hosts to make a deal with me. Running a training on their voice once and then just re-using that will be much cheaper. Also, customers who buy in bulk will help me focus on this full time. There is huge potential for making this faster and cheaper.

(Even using OpenAI is silly. Technically, I neither need GPT-4's knowledge nor instruction tuning. Both is unnecessarily adding cost and latency. But it helped me get the demo out.)

Basically, the deal for Podcasters / YouTubers would be:

- Get all their episodes converted into 15+ languages
- Increase their reach today, while the novelty is high and the market is still uncrowded
- They get to tell their sponsors that they now have reach across the language boundary
https://aros.sourceforge.io/ is based on AmigaOS 3.X and can run on X86 PCs.

They made a PowerPC-based Amiga about a decade or so ago https://www.amigaos.net/hardware/133/amigaone-x5000

If made today it would be an ARM-based system like the Macintosh uses and a custom GPU, NPU, Audio, and MMU chips. But would fail because it doesn't run Windows or Mac OS.
I haven't run any specific low level benchmarks, lately. But chunked prefilling and tvm auto-tuned Metal kernels from mlc-llm seemed to make a big differenced, the last time I checked. Also, compared to stock mlc-llm, I use a newer version of metal (3.0) and have a few modifications to make models have a slightly smaller memory and disk footprint, also slightly faster execution. Because unlike the mlc-llm folks, I only care about compatibility with Apple platforms. They support so much more than that in their upstream project.
from their doc, Reasons to use Pingora:

- Security is your top priority: Pingora is a more memory safe alternative for services that are written in C/C++.

- Your service is performance-sensitive: Pingora is fast and efficient.

- Your service requires extensive customization: The APIs Pingora proxy framework provides are highly programmable.
It's a fairly straightforward modification of BitNet, so I assume this quote from the BitNet paper applies:

To train our 1-bit model, we employ the straight-through estimator (STE)[BLC13 ] to approximate the gradient during backpropagation. This method bypasses the non-differentiable functions, such as the Sign (Eq. 2) and Clip (Eq. 5) functions, during the backward pass. STE allows gradients to flow through the network without being affected by these non-differentiable functions, making it possible to train our quantized model
That's valid for his evolutionary promises, for the revolutionary one even step one doesn't work.
I don't think Meta's margins have something to do with this. Companies smaller in scale than Meta also have less data!

And yes, Scuba is in-memory, but it's not the requirement. Check this video out on how Honeycomb implemented their columnar storage: https://vimeo.com/331143124
I am not in management. Never was, most likely never will be. Just had the luck of working for companies that take "blameless" problem analysis seriously.
"diarization" is your search term. eg. https://github.com/MahmoudAshraf97/whisper-diarization
Having Fun with Natural Language Inference
in a perfect world each unit would do the obvious thing without many different paths throught it. The only paths would be the paths, that are actually relevant for the function. In such a perfect world, the integration test could trigger most (all?) paths through the unit and separate unit-tests would not add value.

In this scenario unit tests would not add value over integration tests when looking for the existence of errors.

But: In a bigger project you don't only want to know "if" there is a problem, but also "where". And this is where the value of unit tests comes in. Also you can map requirements to unit tests, which also has some value (in some projects at least)

edit: now that I think about it, you can also map requirements to e2e tests. That would probably even work much better than mapping them to unit-tests would.
your comment relies on the false premise that jokes cannot condemn things

but in fact jokes very commonly condemn things; often they are the most powerful condemnation possible. jokes can express ideas, and the ideas they express can include condemnation; this is not changed by the fact that they are sometimes difficult to interpret because they express the ideas indirectly rather than directly

your comment is incoherent in light of that fact
Screw a test group, a test department, called QA, people who are paid to understand the system and how it works enough to evaluate if it's fully working or not and empowered to stop ship when it's catastrophically not working.
"Neutron capture reaction cross-section of 79Se through the 79Se(d,p) reaction in inverse kinematics" (2024) https://www.sciencedirect.com/science/article/pii/S037026932... :

> One way of handling such long-lived fission products is to neutralize waste through nuclear reactions [1], [2], [3], [4]. Decommissioning nuclear waste by employing high flux accelerators [1], [4] and fast reactors [2], [3] has been proposed. However, to design such facilities, reaction cross-sections in a wide energy range are indispensable.

Neutron capture for transmutation.
Does this work for any other languages?

i.e. the notes are not in english