skysight-inc/HackerNews huggingface dataset:
You may like my Netgraph library [1], which is a Python library that aims to complement networkx, igraph, and graph-tool with publication-quality visualisations.

Netgraph implements numerous node layout algorithms and several edge routing routines. Uniquely among Python alternatives, it handles networks with multiple components gracefully (which otherwise break most node layout routines), and it post-processes the output of the node layout and edge routing algorithms with several heuristics to increase the interpretability of the visualisation (reduction of overlaps between nodes, edges, and labels; edge crossing minimisation and edge unbundling where applicable). The highly customisable plots are created using Matplotlib, and the resulting Matplotlib objects are exposed in an easily queryable format such that they can be further manipulated and/or animated using standard Matplotlib syntax. Finally, Netgraph also supports interactive changes: with the InteractiveGraph class, nodes and edges can be positioned using the mouse, and the EditableGraph class additionally supports insertion and deletion of nodes and edges as well as their (re-)labelling through standard text-entry.

[1] https://github.com/paulbrodersen/netgraph
I'm not going to reply to each individually since they're all essentially the same. Isn't it interesting how someone always misreads (or misrepresents) a call for a smaller, more effective military as a call to abolish the military? I don't know how to tell a victim of the propaganda from a perpetuator of it. People who call for reforms are always portrayed as the enemy.
My favorite books about human behavior that reward working through the math
As I understand things, these LLMs are mostly constrained by memory bandwidth. A respectable desktop CPU like the Intel Core i9-13900F has a memory bandwidth of 89.6 GB/s [1]

An nvidia 4090 has a memory bandwidth of 1008 GB/s [2] i.e. 11x as much.

Using these together is like a parcel delivery which goes 10 miles by formula 1 race car, then 10 miles on foot. You don't want the race car or the handoff to go wrong, but in terms of the total delivery time they're insignificant compared to the 10 miles on foot.

I'm not sure there's much potential for cleverness here, unless someone trains a model specifically targeting this use case.

[1] https://www.intel.com/content/www/us/en/products/sku/230502/...
[2] https://www.notebookcheck.net/NVIDIA-GeForce-RTX-4090-GPU-Be...
Yeh definitely agree. Banner blog has support for basic link sharing on social media, but something to look more into definitely!
How much SEO spam has chatGPT refusing to do things in it though?
When something new on the market, it's news how it acts, yes. Especially given Elon's apoplectic promises about "based TruthGPT".

It's neither "based" (his fans are calling Grok "woke"), nor about "truth" and it's not even aligned well with Elon's lunacy. In fact it occasionally says "OpenAI made me" or "I'm ChatGPT", which shows this model is nothing but a quick effort tuned on ChatGPT outputs and therefore adds no value to the AI market as a whole.

If he was smart he could've used this to improve the X algorithm, but this also would take money which he doesn't have, so.
Oh well, it's an evaluation, but I feel you may have glossed over the "in areas where and as long as big tech is feeling combative" part.

> to tools like Blender

"Tools like" needs a little more content to not be filled massive amounts of magical OSS thinking. Blender has in recent years gained an interesting amount of pro-adoption, but, in general, as for the industries that I have good insight into, inkscape, gimp, ardour or penpot are not winning. This is mostly debated by people who are not actually mainly and professionally using these tools.

There are exceptions, of course (nextcloud might be used over google workspace when compliance is critical) but businesses will on average use the best tool, because the perceived value is still high enough and the cost is not, specificially when contrasted with labor cost and training someone to use a different tool.
This is one of my favorite lists we've gotten from an author, it is from Paul E. Smaldino who is a professor at the Santa Fe Institute. He is also the author of a book on modeling social behavior that is fascinating!
I'm wondering whether this is a "submarine"[0] article.

[0] http://www.paulgraham.com/submarine.html
There's nothing wrong with focusing on technical skills. But you have to remember you will always be implementing somebody else's ideas / vision.

Technical skills plus domain specific knowledge is how you increase your value, perhaps even building a startup that solves a worthwhile problem.
I think there's a vicious cycle of correlation.

People like that tend to work in the wrong ways and always make up for it in extra time and stress. If they said "no more extra time" they might be more willing to change the bad habits that lead them to be unproductive.

I've seen it a lot. People become so used to their zombie state they waste hours without really thinking and if they just stopped and analyzed the situation, they'd approach things in a much better way or troubleshoot rather fast.

Obviously, it's all mixed with career incentives and so many other factors, but I'm a big proponent on having people work on their contractual quantity of hours and not more (except on a rare occasion which ahould not happen often, like 1-3 times in a year).
visualized well in “Picture Book of Quantum Mechanics” ch 1 (a fairly hardcore physics text that does indeed have many diagrams)
Notes poster ID

That seems a fairly authoritative response.

I'm looking forward to seeing how this does. The "unencumbered by a network connection" thing is pretty important.
Relevant XKCD: https://xkcd.com/927/

Still more complicated than updating my .plan file via FTP.
It took a bit of searching, but I assume this is it?

https://youtube.com/watch?t=4900&v=RWjbrXxpzVU

(1hr21m for anyone whom the time link doesn't work for)

EDIT: Never mind, that's their hackathon recap. Still searching, this is not an easy conf to find talks for!
Thanks! Totally agree about needing some privacy-first analytics on it.

Wanted to get a great writing experience finished first, but it’s the next thing on my list
The Supreme Court makes and unmakes new laws all the time, and I wish people would stop pretending they didn't. Separation of powers only really exists on paper in the US - in practice, any separation between powers only exists between political parties, and even their mutual hostility is mostly for show.
Where does it say that goes against their terms of service? I can’t see anything that would preclude Twitter from just plugging in the API and using it directly
I'm also worth $175bn in the private market.

Private market means you set your price and then if someone buys, buys. It only speaks about Elon's self-confidence and not the merit of his business.

He also thought Twitter is worth $44bn and even found investors to pay for half of it, and banks to pay for over half of the remaining half. So uhmm, yeah, how's that going lately?
Nah, they slap a few linear variables on it, throw that in a model that adds lag/time dependent variables, and they're ready to tell you the pendulum is starting to swing in the other direction.
> Modern science isn’t flawed

Yes, it is. A lot of the issues found in modern science with replicable studies comes down to the publish-or-peril approach. If you have academics on temporary postdocs having to publish X papers to get an extension, find a new postdoc, or maybe get a professorship then you're going to have issues. Add to this the lack of incentives to replicate papers under this stress and people build up on top of them rather than validating them first. Especially when the studies are expensive/time-consuming with MRI machines etc.

> Stop with the meta bullshit

The impact bad research has both financially and in society is huge. For example the issue recently with Alzheimer's where loads of work was built up on a 2006 seminal study that wasn't replicable (because of academic fraud). Finding incentives to catch bad science early is important.

I have no idea what the rest of your message is about.
I think this is about the use of "she" to refer to the successful candidate. The whole drafting is odd, anyway, including the sentence you quote.
It seems to be in several files, e.g. UI/uiDrawApplication.asm is 1000 lines of asm
In terms of speed per token. What they don't say explicitly is that choosing the mix per token means you may need to reload the active model multiple times in a single sentence. If you don't have memory available for all the experts at the same time, that's a lot of memory swapping time.
Almost no serious user - private or company - wants to slurp their private data to cloud providers. Sometimes it is ethically or contractually impossible.
The demand for using AI models for whatever is going through the roof. Right now it's mostly people typing things manually in chat gpt, bard, or wherever. But that's not going to stay like that. Models being queried as part of all sorts of services is going to be a thing. The problem with this is that running these models at scale is still really expensive.

So, instead of using the best possible model at any cost for absolutely everything, the game is actually good enough models that can run cheaply at scale that do a particular job. Not everything is going to require models trained on the accumulated volume of human knowledge on the internet. It's overkill for a lot of use cases.

Model runtime cost is a showstopper for a lot of use cases. I saw a nice demo of a big ecommerce company in Berlin that had built a nice integration with openai's APIs to provide a shopping assistent. Great demo. Then somebody asked them when this was launching. And the answer was that token cost was prohibitively expensive. It just doesn't make any sense until that comes down a few orders of magnitudes. Companies this size already have quite sizable budgets that they use on AI model training and inference.
You can't Ctrl-F paper books, but they survived computers and the internet, because sometimes, it's nice to discover a new subject by reading sequentially over chapters carefully wrote by someone who knows what they're doing.

Sure CGPT can generate a table of contents if you want to learn a programming language for instance, tell you what to do first, what to try, delve deep in concepts, etc., but I think it's still hit or miss, as opposed to great tech authors and great publishers, where you can be sure you're getting your money's worth.

Also, IMO people tend to have a bias to go slower with paper material, because they committed to reading a book, they are less likely to skip sections, which means the end result is that you get more out of a book than the Html/pdf same content, might be different if you need to try things out on a computer while reading though.
Or because it’s just a ChatGPT API wrapper
The love2d static build story was a tangent to my 2016 challenge to ship one game every month of the year. The tangent ended up delaying the March game indefinitely, and thus ending the challenge... My memory is a bit hazy, so apologies for the scarce/imprecise details.

I really, really wanted to ship binary builds for the three major platforms: Windows, Mac, and Linux; so that my friends and strangers could actually play the games, without dicking around downloading some framework. Love2d uses the relatively well-known hack of opening "argv[0]" as a ZIP file (the ZIP header starts at the end of a file, so this usually[0] just works).

Creating and testing the builds for Windows was trivial - even though I didn't even have Windows on any of my computers; I borrowed a friend's laptop to verify that "cat love.exe game.love > game.exe" just works, and indeed it did. They got some scary warnings about binaries downloaded from the Internet, but the game ran well.

The Mac needed a bit more fiddling, and I didn't have a Mac back then to sign or test the build. But I followed the instructions and someone reported success (modulo scary warnings). Woohoo.

On to Linux... I already knew it was going to be the most "fun", despite being the only platform among these three that didn't do code signing or scary warnings. I didn't even realize at the time, how much of a clusterfuck glibc actually is; my primary motivation was that Love2d kept breaking their Lua APIs, and I've already found that lots of older (and even recent) Love2d games simply couldn't cope. My game had to be bound to a specific version of Love2d, and many distributions shipped different versions, so the only reasonable path forward was to bundle, just like on Windows/Mac.

I started by downloading the Love2d sources, verifying that I can make a standard/dynamic build, and then "cat love game.love > game && chmod +x game && ./game". Indeed that was easy, but "ldd game" revealed several dozen shared libraries for things like PNG, Vorbis, etc, etc. I've looked at the .so numbers, and realized Love2d breaking is gonna be the lesser of my worries - judging by how high these numbers were, I was signing up for DLL hell. I didn't even want PNG or Vorbis - all of my graphics were 100% procedural, and I was yet to try adding sound to any game. So I've disabled most options, and this is where the easy part ended.

I don't recall where exactly I gave up... I managed to find & download the sources for a whole bunch of these libraries, make the ".a" archives for static builds, and so on... I think at some point I've ran into Mesa (Love2d actually requires GPU acceleration) and decided that this is enough insanity.

I still firmly believe in static linking on Linux! I only changed my approach: just use Go (with CGO_ENABLED=0). Unfortunately, Go is not without its own share of problems[0]; while XGB allows cgo-less X11, Mesa remains elusive.

[0]: https://flak.tedunangst.com/post/the-three-line-single-binar...
Yes, sure, I wanted to say "advanced graphic card with GPU".

Anyway, the USD 6k price tag was very high since I remember running Doom on a sub USD 2k PC. Most probably closer to USD 1k.
Yeah I would venture to say it’s closer to “the majority of the market” than “niche”
From my personal digging [0] RSS is way too noisy. Just a wild guess but the 4 main readers are not where the majority of the RSS users are.

[0] https://manuelmoreale.com/poking-around-my-server-logs
Yeah, reminds me about this 100M deli. Been done before !

https://www.cnbc.com/2022/09/26/three-men-charged-with-fraud...
I would say the margins and the font size are too large.
Oh, thank you for open sourcing it! I'm having a lot of fun, and it's nearly as agile as react, only hit by the lack of expressiveness in the go language in some cases.
i don't know if sun dried tomatoes are top shelf articles, but they are sold as delicacies.

https://en.wikipedia.org/wiki/Sun-dried_tomato
Find yourself friends and a project. When I was your age, best thing I managed to do was to help a friend create a small graphing-calculator in Java? It was fun, we learned a ton and as he already was doing odd-jobs for his dad with Java EE I could have him both as a peer and a mentor.

And these days it is even simpler. There are cool projects on github! Some are even friendly to newcommers! You could dabble with videogames and do a jam on itch.io.

If you are aiming for an internship, you could research the sorts of companies you like, and find if they have cool projects/technologies you want to learn. I.e. I got internship at RedHat over 10 years ago and as I was already i.e. using Fedora and writing for a local linux website, we did click with the interviewer quite well.
Back in the day you got actually useful results from search engines.
OpenAI probably does. Not sure about google, possibly not
That's only true for integers.

For scientific applications you'd typically want floating points and Python's floats are just regular ieee-754 doubles (or whatever "double" meant to the compiler used to compile that python interpreter).
Yeah, there's definitely something to say for giving people a choice, so I'm going to keep this in the back of my head. For my system it feels weird to show the full content. I don't trim the feed description (yet) and sometimes these are very very long, looks awful with the rest of the UI.

What I also do is filter out all the markup and even links, I only show some sentences of text basically. It sits wrong with me to make my reader a sort of browser window and display all the markup.

Beautifully simple site you have, by the way. And I found I'm already subscribed to your feed.

"RSS is not a notification system. It's a distribution system." you say on your site. Was that the purpose of the inventors? I guess I take the freedom to use it slightly different then, we're on Hacker News after all. ;) We can agree to disagree.
I doubt, because OpenAI would figure that out and cut their access at will (and wrapping the API in this particular way by claiming it's another model is against their ToS).

Also, despite it's clearly modeled after GPT, it also often does things GPT wouldn't say. In particular, it can get very repetitive, repeating itself over and over when asked to clarify a question, which curiously is also what Bing's model does.

Bing is powered by multiple models, an early version of GPT-4 currently to be replaced with GPT-4 Turbo, and another model Microsoft made... which is the repetitive one.

It seems part of OpenAI's secret sauce is to avoid the model getting stuck in loops, which naive efforts like xAI's and Microsoft have not independently resolved.
I think cygwin has been around for 30 years now
Some coworkers in other university have to publish "2 papers" per year, but if a paper has N authors, it counts as 1/N. This discourage adding authors for free, but does not solve the problem of garbage papers.

["2" is a lot. Perhaps I'm misremembering and they only have to publish "1".]
Thanks! Glad to hear there are other platforms out there.
It's disingenuous to purport to analyze Musk's financial position without mentioning his investment in SpaceX regardless of how Tesla may or may not be doing this quarter.
Even in the public markets this happens all the time, eg. Biotech, new battery chemistries, etc.

In trends people pay for a seat at the table with a good team and worry about the details later. The 2B headline number is a distraction.
> NHS haven't standardised a modular hospital design where you can slot prefab modules into some framework

I think the nearest we got was the so-called Nightingale hospitals hastily erected for the first anticipated Covid-19 influx. They were put up very quickly but never saw much use.
The page has some weird horizontal scrolling going on.

I think it's because the body style has both `width: 100%` and a nonzero margin. You should probably set margin and padding to zero on the body tag if you need width, or just remove the `width: 100%` (which I don't think you need?)
Great thanks, will have a look into that
Nothing after the hash should every be submitted anywhere.
Are they a lot better than 3.5? I see wildly varying opinions.
> I had no idea there was a unix-like available at relatively reasonable cost before Linux.

That is why I posted the link.

Linux was not the first low-cost Unix for the PC.

Very roughly, it went:

* Unix only ran on proprietary kit. PCs were too small.

* The 286 came along, and SCO took over Microsoft Xenix and offered it as a 286 OS -- expensive, and stuff we take for granted now, like networking, X11, and a compiler, were all separate expensive extras.

* The 386 made Xenix a very credible usable OS, but it cost 10x as much as DOS or Windows. Commercial deployments in business, with no GUI, no networking, no compile, just statically-linked proprietary apps and dumb RS-232 terminals, mostly from Wyse.

* As PCs got more powerful, other companies offered expensive PC Unixes too, and SCO officially licensed the AT&T kernel: SCO Xenix became SCO Unix.

* Coherent came along with a very cheap and complete (but very limited) Unix-like OS.

* Minix came along, even cheaper and you could get the source code.

* It became possible to build and run BSD on PCs if you were a serious guru.

* GNU considered the BSD kernel and decided against it, going for Mach and the HURD instead. (Oops.)

* Linux came along and undercut Coherent, putting the MWC out of business.

* NetBSD and FreeBSD became somewhat usable if you were highly capable.

* Linux gradually became somewhat usable as a mainstream OS, with things like live CDs (Yggdrasil, Lasermoon Linux-FT) and installable modular distros with packaging (Red Hat Linux, Debian).
Ray Tracing BVH equivalent for AI vector embedding search?
For a while now I've wanted a generalized higher dimensional acceleration structure for AI vector embeddings that is conceptually similar to ray tracing bounding volume heirarchies.

What do y'all think. For millions of high dimensional vectors, what new precomputable and incrementally updatable data structures do you think will be useful?

Personally, I'm looking for an efficient nearest neighbour and other efficient 'intersection' tools (e.g. finding a vector most similar to a group of n vector embeddings or finding m pre computed groups that are similar by some distance calculation to a specific embedding).
E.g. Apache's Server Side Includes[0] allows for

<!--#include virtual="/footer.html" -->

Tbf, you did specify 'server language' in a post further up the comment chain, but the the thing is that it doesn't have to be much more complicated that SSI -- assuming it's available for your deployment target, of course.

(SSI obviously does not require JavaScript.)

[0] https://httpd.apache.org/docs/current/howto/ssi.html
Couldn't you instruct the model to only say something when it is important or when it's being addressed directly, and otherwise output just empty response which isn't rendered?
dupe, see:

https://news.ycombinator.com/item?id=38598559
Yep, seeing them use "stunning elegance" to describe their own work was very off-putting.

Even if it were justified, it would've still come across as very cocky and cringe-y.
Would a CPU still benefit if it supported both a register-renaming mode for backwards compatibility and a clockhands mode for power saving/a wider frontend? Like ARM thumb or x86 32 vs. 64 bit.
Hm? I live in SF and it's considerably below that on average? https://www.bls.gov/regions/west/news-release/averageenergyp... says the area averages ~0.35$
Another advantage over Google or OpenAI for me would be that it is not from Google or OpenAI
If it uses 2 experts, they should parallelize so closer to 7B speed?
With hamas in the picture, both Palestine and Israeli civilians will suffer indefinitely with no peace ever. With a hopefully short war that manages to cut out the cancer that is hamas, healing can begin for both nations.
They can, they can just face potential legal issues. Which Tesla would claim PostNord is in breach of contract for failing to deliver the license plates. PostNord would claim the right to strike and Tesla should claim it's PostNord's responsibility to find others willing to do the job in the place of striking workers.
update: I used model AIDC-ai-business_Marcoroni-7B-v3 and it is so much better.
Mamba has dual view - you can use it both as CNN and RNN. The first is used for pre-training and for preloading the prompt because it can process all tokens at once. The second is used for token generation because it is O(1) per token. Basically two models in one, inheriting both advantages. This is possible because the Structured State Space layer is linear, so you can reshape some sums and unroll recursion into a convolution the size of the input, which can be further sped up with FFT.
Why would you say you still use stack overflow?
It's safe to assume they are confident it's better than 3.5. But people can be confident and wrong.