skysight-inc/HackerNews huggingface dataset:
I still have my SAW machine from Microsoft (quit, not laid off) and nobody has ever given me any indication what to do with it.
I wonder if the author is trying out GPT as a kind of auto-complete for ideas. I have not had a lot exposure to GPT, but it does seem to have something like an "accent". I was listening to This American Life, and they had a mini game show about accents and ages. So, maybe that's just on my mind.
I agree. I like pure JS, but it just does not scale by default. You need to have awesome architecture skills and you need to constantly observe your codebase, you need to write half of framework if you want to avoid frameworks. Of course it's possible, but it's not possible for vast majority of developers, including myself.

May be we need some education: how to write 100 kLoC pureJS WebApp and keep sanity. I didn't see that kind of articles. I know that my pureJS web apps can survive few hundreds LoC. Then it becomes a mess. With React it's much easier to structure an app so it's maintainable, different parts are separated, etc.
I see, thank you! That’s what I thought. So keep doing and showing good work, the rest will come.
I think gmail's spam filter is so close that it feels like a solved problem. But of course it has a lot of other indicators to look at than just the email body text and spam tends to revolve around a fairly predictable range of topics. None of that would apply in a "was this webpage written by a robot?" algorithm
The paper makes a valid point in general but I feel it makes unjustifiably definitive and general statements and puts up odd goalposts.

The section on emergence makes a very convincing point about how such systems might, at least in theory, be doing absolutely anything, including "real" cognition, internally and then goes right ahead and dismisses this entirely on the basis of the system not having conversational intent.
who cares if it has conversational intent? If it was shown to be doing "the real thing" (how ever you might want to define that) internally that would still be a big deal wether the part you interact with gives you direct access to that or not.

Then it goes on to argue that these systems can't possibly actually believe anything because they can't update believes.
Frankly I'm neither convinced that the general use of the word "believe" matches the narrow definition they seem to be using here nor that even their narrow definition could not in principle still be taking place internally for the reasons laid out in the emergence section.

I agree people should probably be mindful of overly anthropomorphic language but at the same time we really shouldn't be so sure that a thing is definitely not doing certain things that we can't even really define beyond "I know it when I see it" and that it sure looks like it's doing.

beyond that I'm not even really sure there is a good philosophical grounding for insisting that "what's really going on inside" matters, like, at all.
The core thing with the turing test isn't the silly and outdated test protocol but the notion that, if something is indistinguishable by observation from a conscious system, there is simply no meaningful basis to claim it isn't one.

all that said the current state of the art probably doesn't warrant a lot of anthropomorphizing but that might well change in the future without any change to the kinda of systems used that would be relevant to the arguments made in the paper
I dont even believe it was oversold. There were lots of independent reviews and analysis, even by Mozilla themselves that WebP wasn't even good. And yet people still uses it because they somehow hate JPEG.

It there was ever a "cult", it is "Anti JPEG cult" and "WebP Cult". Not JPEG XL.
I wont mention what company, but where I work we've spent about 6 months now with an entire dev team hammering their heads against a wall trying to port our extension to MV3, because the alternative was to lose it entirely at the deadline.

Hacks, workarounds, bad docs, and lately, Google pops up to tell us OSD is kinda sorta a thing you can use, but clearly it's at a basically alpha level of maturity. This latest announcement might seem like a reprieve, but it's even worse than before for us, because now it's clear that OSD is a temporary measure, and now we have promises to fix the actual issues in the future.

As a manager I have no idea how to proceed. Do we solider ahead with OSD like we planned? Wait for them to fix the core issues? We have so little trust in Google fixing things, and a great deal of confidence in them making things worse at this point. If we commit to OSD we might be looking at doing the same level of work again, when they fix the core issues and deprecate it. If we wait for core fixes, we might not get the work done before a nebulous future deadline that could drop on us at any moment.

Google has caused us to burn an absolutely incredible amount of time and money with this. Believe me, we're are footing the bill, and have been for some time now.
More info on this would be nice.

To me it makes sense that openai would store all input and output and could make something like a plagiarism checker page/API to search and see if openai generated that or very similar content... Another service they could sell to teachers and such.
Page 5: "The geo-server specification was by nature ambiguos and imprecise, thus leading to some variation in the functionalities of developed prototypes. (On the other hand, the specification is probably typical of that found in practice, especially during requirement acquisition.)"

Nevertheless, at Page 6 starts the chapter 3 which aptly named "Problem description".

The Haskell code for a problem solution is at Page 15. It is not complete, but it contains examples of what is called "combinators", from whose it is easy to deduce how authors approached the solution.

But, one needs to be aware of the notion of combinators and how they are usually constructed. For that, take a look at [1], a construction of parsing combinators. They start with a simple higher-order functional approach just like the solution exemplified in the paper we all discuss here.

[1] https://www.researchgate.net/publication/222837975_Combinato...
Why is it wrong or unethical? The letter typed with your own fingers isn’t any different than the one you wrote with a tool and tweaked. The essential element is that it reflects your feelings and you’re willing stand by the words. Surely being able to produce the same result with less human time and effort is a good in and of itself.

I have a friend who is using it to write donation thank you letters with it and they produce great results.
I’m happy to see new transit expansions but it’s pretty insane that four above ground train stations and a train yard costs over $3 billion dollars.
There's a difference between what you yourself believe is core to who you are, and what other people would say is core. They both get called identity, but I think Paul Graham is talking about the first, which is something you really are allowed to choose in the privacy of your own head.
You can definitely get pretty creative and interesting—for example, transmuting a pile of primed hand grenades into a handful of confetti and then tossing it over your enemy right before the spell wears off. That said, you're right, it's highly likely that boring strategies would dominate. However, the Harry Potter magic system is so fast and loose that you can always make up some new spell to cancel out whatever OP strategy; the author has almost unlimited leeway.
Keeping some stories out of the public domain forever is a pretty terrible way to fund something.
Is Japan even doing anything about this? The japanese people are going to disappear if this goes on for long enough. I always assumed the 98% ethnically homogeneous nation would want to prevent such an outcome.
inotify has pretty paltry limits. My ~/code is only 40-50GB but there's no way inotify can watch it all.

Thus, syncthing basically constantly has to rescan. It's not great.

And yes, rebasing linux+nixpkgs on even an hourly basis is absolutely devastating. lol
Isn't the main issue attribution? I mean you've got guys who put in hours a week over years to get rep and demonstrate their knowledge base then some script kiddy blows them out of the water. I'd be kind pissed. I think AI generated answers would be more acceptable if they were attributed to AI.
What is a SAW machine?
> Julia's threading macro is surprisingly brittle, only letting you chain single-argument functions

Julia's threading/piping is surprisingly limited, but the phrasing here (combined with the link) could make things confusing to a Julia beginner. So to make things clear:

* The linked page is talking about an external Julia package which provides a macro. And that macro lets you use the `_` syntax similar to what you describe Racket as having.

* Julia's default inbuilt piping syntax is the one with the single-argument limitation, and that's an operator, not a macro.

There's been a lot of discussion about bringing the `_` syntax or something like it to the base language, but there seem to be implementation difficulties. [1]

> +R :: https://r4ds.had.co.nz/pipes.html

This page is talking about magrittr piping (which is probably still the most popular), but base R also got inbuilt piping syntax with version 4.1. It automatically passes the piped-in value as the first argument to the subsequent function. [2] [3]

[1] https://github.com/JuliaLang/julia/pull/24990

[2] https://www.r-bloggers.com/2021/05/the-new-r-pipe/

[3] https://michaelbarrowman.co.uk/post/the-new-base-pipe/
Next.js also get into many of my govt's websites. It's the worst in any direction. I can explain why with bullets but so tired of these repetitive well-known reasons already.
Also misses out on fresh air and possible sunshine.
This reminds me a lot of frames [1]. I wonder if the creators are aware that at one time html did have a way to update different parts of a page independently, but due to various limitations, it fell out of favor and is now deprecated.

[1]: https://developer.mozilla.org/en-US/docs/Web/HTML/Element/fr...
That's something a robot would post.
It is the responsibility of the customer to enter correct number. I am sure there is a fine print in their terms to clarify exactly this. Also, if the booking is made and slot reserved, it can be said that the service was rendered even if the customer didn't make use of it.
Asians have a more positive image in Latin America because the overwhelming impression is that of Bruce Lee machismo, Peruvian Chinese and Japanese Brazilians and not Hollywood casting
What about a class action lawsuit? Surely there are some tech-oriented lawyers trawling HN/etc for class action ideas by now.
> The artist chooses what to keep identical [All of it], what to emphasize [None of it], what to remove [None of it], or what to add [Nothing]
There were several key insights that have made something like ChatGPT possible relative to traditional neural networks.

* A fixed (but large) vocabulary of sub-word like tokens as inputs.

* Attention mechanism for learning the correlation of words in a fixed sequence window.

* Implementing this attention mechanism in the form of matrix multiplies rather than some other complex math - it allows it to be parallelized and run on GPUs fast.

* Having enough layers of these encoders to have a huge amount of parameter space. ~175B parameters in the case of ChatGPT.

* Feed the model a lot of data - in this case, pretty much the entire internet as text.

* Self supervised learning: we take sentences from the internet and mask out some words and force the network to predict the missing word. Turns out this works extremely well. We don't use the traditional supervised learning inputs -> (prediction, label) paradigm that was the standard 10 years ago.

* RLHF (Reinforcement learning from human feedback). Take generated text from GPT-3 (the underlying generative model) and ask humans to rate different completions. Retrain the model from those ratings.

* A massive compute infrastructure that is able to train this model in a reasonable amount of time, allowing for iteration on hyperparameters. For example, what's the optimal attention head-size? How many encoder layers are good? What should the sequence length be? What should the embedding dimension be? etc. In OpenAI's case, they used thousands of GPUs and thousands of CPUs provided by Microsoft/Azure.

In summary, relatively simple model, parallelizable on GPUs, trained on a lot of data.
The immediate feelings you had before you read the second sentence are not good conversational material.
The need to document your changes would help with copy-paste, in my opinion. You would be forced to extensively document why do you repeat these 70 lines here in your code instead of using the same 70 lines elsewhere.
Don’t worry, Pan never wanted to grow up.
I asked ChatGPT and here is its answer:

Sure, I'd be happy to help. An artificial neural network (ANN) is a type of machine learning algorithm that is designed to mimic the way the human brain processes information. At its core, an ANN is composed of a large number of interconnected processing nodes, called neurons, which are organized into multiple layers. These layers are interconnected in a way that allows them to pass information back and forth, with each layer building on the information provided by the previous layer to make a decision or generate a response.

Transformers are a type of ANN that was introduced in 2017 by a team of researchers at Google. They are called "transformers" because they use a technique called "self-attention" to transform the input data before passing it through the network. This allows them to better capture the underlying relationships in the data, which makes them particularly well-suited for tasks like natural language processing and machine translation.

ChatGPT is a type of transformer that has been specifically designed for use in chatbots and other conversational AI systems. It is an extension of the GPT-3 model, which was developed by the same team of researchers at OpenAI. GPT-3 is a large language model that has been trained on a massive amount of text data and is able to generate human-like responses to a wide range of questions. By building on the capabilities of GPT-3, ChatGPT is able to provide even more sophisticated and natural-sounding responses in a conversational setting.

As for the size of the network, GPT-3 is a very large model, with 175 billion parameters. This means that it has a massive amount of interconnected neurons, which allows it to capture a wide range of knowledge and generate responses to a wide variety of questions. Of course, having a large network also requires a lot of computational power, which is why GPT-3 and other large language models are typically run on powerful servers or specialized hardware.
When I mentioned de-duping and append-only logs, I had this in mind. It's hard to imagine implementing a backup system with those two properties that don't include snapshotting nearly by design-necessity.

(Beyond even the fact that ~/code is also on a ZFS volume that is snapshotted and replicated off-site, which I argue can be used in all of the same important ways any other "backup" is used.)

Hence the comment! After all this blockchain hoopla and everyone's understanding of how "cool" Git is, we really, really deserve better in our backup tools.
At 4% a year, it will be roughly 70 years before 10000 euros have become 600 euros of today (which is still above the size of a typical cash transaction).
Is any country really doing anything of substance like fixing structural problems in their societies?
I want to know if it will ever be possible to run this kind of AI at home once its training is complete. I dont need all the knowledge just subset that I'm interested in.

Actually I'm more interested in its ability to transform things. For example I can ask it to convert docker-compose to docker run command, it can manipulate JSON, it can sort numbers in table when prompted. I'm more interested in these abilities rather than just getting answers for which I already have Google
There are no known boundaries of the universe. The universe expands everywhere continuously. I think of it as though a little bit of extra volume is injected in between everything on a regular basis. Also when we look out as far back in time as we can, everything looks very similar, and there's no "boundary". Each year we can see a little bit farther out into the universe because those photons from billions of years ago finally got to us and so far things keep looking the same the farther out we can see. So as far as we know the universe is far larger than what we can see (what has had enough time to send us photons). I also don't understand enough about this.

https://en.wikipedia.org/wiki/Expansion_of_the_universe
https://en.wikipedia.org/wiki/Observable_universe
Waaay easier than external AI and technology interventions, which don't even fully exist yet and without side effects.

I mean, think of it as bodybuilding: there are plenty of good ol' ways of building strength and stimulating hypertrophy on purely natural processes, and that shouldn't be disheartening as compared to, say, injecting yourself with steroids.
We can calculate the force exerted on an object by a photon of light of a given frequency. I'm guessing it is not sufficient to produce the effect you envisage, although I have not done the calculation. Interestingly this photon pressure does put an upper limit on the mass of a star; the Eddington Limit [1]. If a star is too large (and therefore luminous) its photon pressure pushes away other material and stops is from growing larger!

[1] https://en.wikipedia.org/wiki/Eddington_luminosity
Trying and failing to use ChatGPT to write Python to parse a PDF
> Here we make some great progress, but ultimately fail to correctly parse a PDF invoice vendor file using ChatGPT. Still shows a ton of promise and interesting results!

I thought it would be interesting for you all to see an actual workflow and see ChatGPT in action. It was not all bad, but it's at least intermediate level in his opinion.

I think the joke about "prompt engineers" might not be that far off the mark.

He had got ChatGPT working for a simpler workflow - download and extract text from a PDF file[1], so it was not all useless.

BTW, here is how the programmer did this process manually[2], just in case you were curious

----

[1]:(https://www.youtube.com/watch?v=DoyRTMlVFTU)

[2]:(https://www.youtube.com/watch?v=eTz3VZmNPSE)
Unseen Photos from the Set of the Shining
Same for macOS, Chrome. CPU sometimes jumps to 3%, but that's about it (and I guess that's because it uses slow core).

I have very clean mailbox, though.
What do they do with the vulnerabilities instead of going to pwn2own? If they report vulnerabilities to the manufacturer directly, how does the pay compare to the pay from pwn2own?
Yes, to be fair, that's still a marginal improvement, assuming you aren't forced to validate your email address at any point, which might be the case for lower security stuff. On the other hand, either way, you can often use an existing session to do the same thing without needing to reauthenticate.
I find lots of arguments about who was actually more arrogant. But lets look at it from objective perspective. Looking at neovim[1] vs vim[2] contribution

Bram is top contributor for vim. 16,211 commit right now. Second top most contributor has 194 commits only.
Neovim top contributor has 2285 commits, followed by 21,66 commits for second.

It looks to me that neovim is more open to community contribution.

Then look at commit graph over period of time. It looks like Neovim is more actively developed. There development activity level around vim also increased in 2016. Perhaps that was the time when bram realized that he need to do more with vim, to compete with neovim.

I myself was a longtime vim user, who switched to neovim 2 years ago, and am happy with it.

[1] https://github.com/vim/vim/graphs/contributors
[2] https://github.com/vim/vim/graphs/contributors
It's a bit expensive to get started, but a rack and weights will pay for itself in saved gym fees after a couple years, or a few months for 2 people somewhere expensive like SF. We managed to fit one back when my wife and I lived in 1 bedroom apartments.
One could make the same argument for 30, but 20 shows up repeatedly ("four score and seven", «quatrevingt-treize», 'Jiggit') and I can't think of any 30's. Months?
Yeah, I have no ability whatsoever to write in corporate business speak. My boss who is a wizard at it does me a service and takes what I write and translates it.

I am shocked every time at how polite yet firm he can make things sound. I swear he could tell someone to go fuck themselves and they would nod and say that seems like the best course of action going forward.
Everyone says their favorite library "is becoming standard". The rest depends on marketing budgets.
Just get a treadmill. Not as pleasant as walking in nature, among trees, or by a lake.

But beats walking in a crowded city or having to cross roads anyday.

I live in a place where it is too hot, and only time people can go on walks is dawn/pre-morning. As a night owl, I cannot do that. So I bought a treadmill.

It has been great for me and has served me really well.

The cognitive benefits mentioned in the article and what many of us know, you can derive that from treadmill walking. I can attest to that.
You can search by date ranges (though the date picker is kind of weird tbh):

https://hn.algolia.com/?dateEnd=1543795200&dateRange=custom&...
Precisely. There was someone here bemoaning how difficult it was to follow generic advice of using profilers to optimise hotspots in the application code.

He started off with something like: "Why don't you try your 'simple' techniques in a tangled web of hundreds of microservices written in different languages and running on different platforms?"

It's like some people can't see the forest for the trees.

In the last few years, I've come across about half a dozen existing web sites with hideous performance problems, all of which should have been vanilla HTML but were written as Angular monstrosities. The same teams -- against repeated advice -- have started new Angular projects for sites showing static data, anonymously, to the general public.

They start off conversations with "We'll need a web app, an API app, a mid-tier, a service bus, and then this, and then that..."

It's madness.
Ask HN: How can I sell my app?
I’ve built a pretty polished cross platform desktop app as a side project. It it small (has a few hundred users) and is new. Since I want to focus on other projects and schoolwork, is there anywhere I can go to sell this? Or find partners to handle growth while I focus on tech?

If it helps, the app in question is at https://parallelsocial.net. Thank you for your help & advice!
The AI generated AI response sounds way worse than the AI generated "human" response. That sympathy angle is so hollow even if it were coming from an actual human.
If you wanna gamble on this solution, that's definitely your prerogative. I think it's unreasonable to assume that any function of your account will continue to work if it becomes locked, inaccessible, or possibly compromised. A better backup is a custom domain. Which, of course, is not really great with Gmail.