skysight-inc/HackerNews huggingface dataset:
most welcome.

i found it interesting too.

I had an uncle, an electrical engineer, who went there for higher studies, to stanford, got his PhD (typical common route for many talented Indians, at least up to MS, doctorate is less common), was mentioned in who's who in electrical engineering, worked there, married an American woman, and became a US citizen, and a hardware entrepreneur, in Sunnyvale, California, but I didn't hear about this from him, i just read it on the net.

cheers.
I meant to be referring to pulling kids out of school randomly .. nothing to do with speeding. My comment appears to have ended up under the wrong post :)
Exactly that. LLMs generate a lot of simple and dumb code fast. Then you need to refactor it and you can't because LLMs are still very bad at that. They can only refactor locally with a very limited scope, not globally.

Good luck to anyone having to maintain legacy LLM-generated codebases in the future, I won't.
Hiker discovers first trace of entire prehistoric ecosystem in Italian Alps
Final nail in the coffin for SO
Slightly off topic, but this was built using Avalonia, which I have never heard of. Has anyone used it? The promise sounds impressive (beautiful, cross-platform applications from a single .NET codebase), just wondering whether it actually delivers?

https://avaloniaui.net/
Nothing beats a clean windows 2000 install
Optimizing Vector Storage with halfvecs. A free lunch?
Coding with AI could easily be a new form of early software/developer tech debt. Taking leaps that are too big, or too small, can be unexpected.
> A lot of people pick dates

Yes, birth dates of themselves and family members, which are randomly distributed in the population, and which you can't possibly know, because you don't know the identity of other lottery buyers.

> or numbers that have won recently

Do people do this? I'd assume they do the opposite of this.

> or that form geometric patterns on the ticket, or that form interesting sequences, and so on.

This is all hand-waving. Please list the numbers that I shouldn't choose.

> those commonly picked sets of numbers

What are those numbers?

In any case, even if you eliminated several thousand numbers from the pool of possibilities, that doesn't really help you choose a specific set of numbers from the millions of possibilities, other than not those.
Complaint from engineering software company prompts two retractions
"I think the hardest problem at Vision is probably what does it do"
Ha. I had the exact same experience.

Thought wow cool! Quick flashlight! Instead the flashlight would frequently turn itself on while in my pocket.

And on the flip side; when I wanted the flashlight to come on the phone frequently wouldn’t recognize my tapping.

It just ended up being quicker and more convenient to turn on the flashlight from the lock screen.
I've been wanting to use an Inkplate 10 for my own mom, who doesn't have amnesia but is deaf. But, like the Boox that TFA uses, it has a 10" display which is too small imho. It would be great if they would finally start making bigger ones. 14" (A4 or letter size) is about as small as I'd want if I had my way.
It’s noticeably worse in Germany, to the point that the entire immigration industry is in a slump. My relocation consultant friends are really feeling it.

I also see it everywhere I look. I have never had this many unemployed friends. People spend a lot longer trying to find a job and don’t seem very successful at it.
You can just turn on low power mode and it stops autoplay videos.
> The idea that LLMs are going to advance software in any substantial way seems implausible to me

I disagree. They won't do that for existing developers. But they will make it so that tech-savy people will be able to do much more. And they might even make it so that one-off customization per person will become feasable.

Imagine you want to sort hackernews comments by number of character inline in your browser. Tell the AI to add this feature and maybe it will work (just for you). That's some ways I can see substantial changes happen in the future.
An implementation of the double ratchet in Javascript:

https://github.com/rongarret/ratchet-js

based on an earlier implementation I did in Common Lisp:

https://github.com/rongarret/tweetnacl/blob/master/ratchet.l...
Giving me flashbacks to the AOL punters and proggies scene. <3
These calculations read like an episode of Silicon Valley.

Sure the banners are a stupid idea and a little annoying, but these figures have no merit. There's no way 500m hours of productivity are going to materialize from removing the banners. Removing 'please subscribe' popups, and other ads, now that's altogether different...
Would you have any suggestions on how to play with the internals of these open models? I don't understand LLMs well, and would love to spend some experimenting, but I don't know where to start. Are any projects more appropriate for neophytes?
I'm not sure what point you're making. It's true that people, including myself, were dismissive of cryptocurrency a few years ago; I think it's clear at this point that we were wrong, and it's not actually the case that the industry is a Ponzi scheme propped up by scammers like FTX.
That's funny, because to me these headlines about how deep learning is over-hyped and hitting the wall remind me of headlines from ten years ago about how... deep learning is over-hyped and hitting the wall.
> Vision Pro is different. It has a finger gesture to "tap".

That doesn't rescue it from being a poor control scheme.
I'm not sure how "liberal" the soda ban was. It was championed by Michael Bloomberg, who was at least nominally a Republican during his tenure. I know Bloomberg is trying to rub his nutsack all over the Democrat party now, but that's fairly recent and while he was mayor of NYC his administration was not considered "liberal" at the time.
Ask HN: Best place to find non-technical co-founder?
I've always had the entrepreneurial bug (selling websites on craigslist when I was 13), and feel I'm now in a good place financially, skillset wise (my last role was a tech-lead / cto with management experience, but many years as very fast generalist developer), and life to go in on a business idea.

My financial goals are to bootstrap something to 10's of millions and become financially independent.

It's my belief that the best / easiest way to accomplish this is to work with someone who has really deep industry experience and connections in a non-traditionally-technical field (construction, supply chains, healthcare, etc), and solve a niche problem that only someone with years of industry experience could identify.

My assumption, though, is that people with that sort of background do not traditionally hang out on reddit or HN -- does anyone have any experience or suggestions on where to find them?

I did check out YC's Co-Founder Match Maker, but so far most of the profiles have been either successful founders who are looking to go the fundraising route, or younger marketers / MBA's who don't necessarily have deep industry experience.

Thanks in advance!
you... are correct. Shame on me. Still a good book!
I also cut my teeth with BASIC. First was on the Apple ][s at school, then I got a Vic-20 at home. A lot of the cooler games for the Vic-20 were just a boatload of integer data you had to type in from magazines, not a very educational experience. Then I got access to an HP system with Rocky Mountain BASIC, which was a pretty sweet system. A few years later I got my first professional experience by working on the RM BASIC port to HP/UX as a tester. ~5 years later I came back to RMB working on a production test management system called Functional Test Manager, and I just had lunch with a guy I worked with on that a couple days ago.

BASIC was, I'm realizing as I write this, an integral part of my career. RIP Thomas.
I'm guessing this was posted due to "An analysis of the Keycloak authentication system" <https://news.ycombinator.com/item?id=42136000> getting some traction earlier; and I agree, most of their blog posts are awesome
I'm a parent. I've woken up in a panic just because I had a bad dream that something bad happened to my kid.

If I were one of the Sandy Hook families, I don't know if anything in life would ever bring me true joy again. But contributing to this would make me smile a little.
I guess this is somewhat expected? The current frontier models probably already have exhausted most of the entropy in the training data accumulated over decades and the new training data is very sparse. And the current mainstream architectures are not capable of sophisticated searching and planning, essential aspects for generating new entropy out of thin air. o1 was an interesting attempt to tackle this problem, but we probably still have a long way to go.
What “lies” is Bezos printing? AFAIK the only influence he had was pulling the endorsement for president.
I did a very unscientific test and it did seem to just play legal moves. Not only that, if I did an illegal move it would tell me that I couldn't do it.

I think said that I wanted to play with new rules, where a queen could jump over any pawn, and it let me make that rule change -- and we played with this new rule. Unfortunately, I was trying to play in my head and I got mixed up and ended up losing my queen. Then I changed the rule one more time -- if you take the queen you lose -- so I won!
To all the drive-by downvoters. Whatevs. If this is a low-quality environment, so be it.
But it also predicts moves where the text says "black won the game, [proceeds to show the game]". To minimize loss on that it would need to from context try and make it so white doesn't make critical mistakes.
Why do you feel like this will improve the dating experience?
Seems that you just don't believe the other side has done some investigation and therefore did not search for it. I'm not saying that either incident is fake but you've just proved my point of view.
Note that creating an arcade game at that time wasn't writing a computer program, it was designing a finite state machine out of discrete logic chips.
I mean, I’m amazed by LLMs.

But what you describe is basically done by any human on Earth : you are born not knowing how to read or how to talk and after years of learning, reading all the books may give you some understanding of the world.

Contrary to LLM though, human brains don’t have a virtually infinite energy supply, cannot be parallelized and have to dedicate their already scarce energy to do a lot of other things than reading books including moving in a 3D world, living in a society, feeding themselves, doing their own hardware maintenance (sleep …), pay attention not to die every single day etc etc.

So, for sure, LLMs _algorithms_ are really incredible, but they are also useful only if you throw a lot of hardware and energy into them. I’d be curious to see how long you’d need to train (not use) a useful LLM with only 20W of power (which is more or less the power we estimate the brain is using to function).

We can still be impressed by the results, but not really by the speed. And when you have to learn the entire written corpus in some weeks/months, speed is pretty useful.
Leader of Crypto Heist Worth Billions Gets 5-Year Sentence
Can you elaborate a little about your diet adaption in terms of food classes (carbohydrates, fat, proteins, ...) if it isn't only the coffeine intake you modify? Thanks!
Making satire today is really hard. This could even be some article title on The Onion.

Reality is their biggest competitor.
I don't know if I need a documentary of the times I'm living through.
This is why I exclusively use the API to 'chat' with GPT -- complete control over the context presented.
We will see how the confirmation goes.
It's simple: no one. Americans can enjoy 4 (or more) years of nasty, unusable toilets, and will probably just take a dump behind a tree if they're in a national park, so popular parks will be full of human waste lying around. Maybe they can just close the parks altogether.
It occurs to me to say injection molding of any plastic has gotten better probably due to numerical simulations of molten plastic. Injection molding parts of any type of polymer used to be a black art, requiring a lot of trial and error. Parts had simpler shapes and thicker walls in the 1990s than they do now. That's very important to making quadcopters light enough to fly, but still durable.
My money is on a fluke inclusion of more chess data in that models training.

All the other models do vaguely similarly well in other tasks and are in many cases architecturally similar so training data is the most likely explanation
This is so great, I love it. I don't have amnesia but I have lots of trouble remembering what I was going to work on next and used an e-paper display[1] to help with that. My code is a lot simpler (as the display only has an ESP32 and that isn't particularly powerful) but it can fetch a PNG image and it can display it, so my "protocol" (which I'm hesitant to call it that) is it opens a URL named 'inkstatus.html' and looks for a link of the form "http://example.com/image.png" (sadly I can't code quote that here but you get the idea, a URL pointing to image.png from the same server. It then reads that image and displays it, if the image is the same one it displayed the previous time it just does nothing and goes back to sleep for 10 seconds.

That way, all of the rendering is done on the web server (by a cron script in my case and LaTex) and display doesn't have any fiddly html/css issues it is just putting up a full size png image which was part of the library that the Soldered guys provided.

Based on the referenced article I'm going to see if I can replicate this for my Dad who is at the age where he doesn't remember things.

[1] https://soldered.com/product/inkplate-10-9-7-e-paper-board-c...
Chess does not clearly require that. Various purely ML/statistical based model approaches are doing pretty well. It's almost certainly best to incorporate some kind of search into an overall system, but it's not absolutely required to play just decent amateur level.

The problem here is the specific model architecture, training data, vocabulary/tokenization method (if you were going to even represent a game this way... which you wouldn't), loss function and probably decoding strategy.... basically everything is wrong here.
> chess is an excellent metric for testing logical thought and internal modeling

Is it, though? Apparently nobody else cared to use it to benchmark LLMs until this article.
> Yes, birth dates of themselves and family members, which are randomly distributed in the population

Nope - not uniformally random, there's literally a non uniform age distribution, a specific set of months, a capped number of days, and various "peak" birth seasons.

>> > those commonly picked sets of numbers
> What are those numbers?

One way to find out is to get a math degree and moonlight as a consultant for, say, the local uni math department and perform quasi regular spot checks on the state lottery games.

There are many lottery variations and differing games show interesting patterns of choice - although more and more people these days simply get machine generated tickets .. this expands the surface of interest as not only the game results themselves need to be checked for bias but also the various networked game terminals for their random generation and for local tampering.

It's probable that anyone who has done such work is bound by NDA's and agreements not to dump mass data aquired through work.
LLMs like GPT aren’t built to play chess, and here’s why: they’re made for handling language, not playing games with strict rules and strategies. Chess engines, like Stockfish, are designed specifically for analyzing board positions and making the best moves, but LLMs don’t even "see" the board. They’re just guessing moves based on text patterns, without understanding the game itself.

Plus, LLMs have limited memory, so they struggle to remember previous moves in a long game. It’s like trying to play blindfolded! They’re great at explaining chess concepts or moves but not actually competing in a match.
Self-replicating probes aren't closed systems. They exist within the universe, consume matter (which is how they replicate) and emit waste heat (as all physical systems must,) and are bound to the laws of physics which, yes, include the second law of thermodynamics. There may be short term local reductions in entropy, but eventually, inevitably, entropy must increase.

>Resilient, error-checking, self-healing systems are possible.

You cannot have such systems be perfectly efficient. That isn't physics, it's magic.
I don't think that Obama was a liar, crook, incompetent, or evil. So I think you're a bit over-pessimistic.

The last couple cycles have pretty well fit your opinion, though. I'll give you that.
How can this be a good thing? Tether doesnt have any legitimate backing for their pegged crypto. This is just an amplified ball and cup game.
> Yes we do. We know how neurons communicate, we know how they are formed, we have great evidence and clues as to how this evolved and how our various neurological symptoms are able to interact with the world. Is it a fully solved problem? no.

It's not even close to fully solved. We're still figuring out basic things like the purpose of dreams. We don't understand how memories are encoded or even things like how we process basic emotions like happiness. We're way closer to understanding LLMs than we are the brain, and we don't understand LLMs all that well still either. For example, look at the Golden Gate Bridge work for LLMs -- we have no equivalent for brains today. We've done much more advanced introspection work on LLMs in this short amount of time than we've done on the human brain.
Words vs characters is a similar problem, since tokens can be less one word, multiple words, or multiple words and a partial word, or words with non-word punctuation like a sentence ending period.
> lawfare is the most effective tool

You knew precisely what the word meant when you used it.
You're right! I still agree with the policy, though.
I don't agree with your "/s". You make a lot valid points. Why soften it by saying it's sarcasm?
The gap from the virtual world of software and the brutally uncompromising nature of physical reality is wider than most people seem to accept.

It's almost like saying "we've already visited every place on Earth, surely Mars is just around the corner now"
It’s about time the hype starts to die down. LLMs are brilliant for small bits of grunt work in software. It is not however doing any actual reasoning.
The new Gemini just hit some good benchmarks.

This smells like it’s mostly based on OAI having a bit of bad luck with next model rather than a fundamental slowdown / barrier.

They literally just made a decent sized leap with o1
Fight AI scams with AI assistants and just let them have the conversation themselves
I’m not a Trump supporter but clearly inflation was worse during Biden than Trump, that’s just a fact. So your claim that it’s on “any measure” is wrong.
If it was trained with moves and 100s of thousands of entire games of various level, I do see it generating good moves and beat most players except he high Elo players
I can't tell if you're being facetious or not, but the fact is that, when Boomers and Gen Xers entered the workforce, formal training was provided for many entry-level professional positions, and even for higher junior-level ones. This was particularly so when the company was using unusual or uncommon technology. GP was complaining that "no one has any experience in our technologies." That speaks to an underlying entitlement, not just to employees' time, but to prospective employees' time. It's part of a broader shift of the cost of doing business onto everyone but the business (labor, customers, vendors, government).

Companies should pay what it costs to get people to give up a significant portion of their lives working towards their business mission, or else get out of the business.
You can rip a rootfs from a docker image using skopeo[1] and undocker[2] then you can puppeteer it with bwrap[3].

This works for most linux distributions (they behave well as fakeroot puppets).
Package managers from Debian-based distros tend to misbehave in bwrap in my experience.

I use this method to obtain software from various distro repositories or when RPM packages are distributed by vendors.

[1] <https://github.com/containers/skopeo>

[2] <https://git.jakstys.lt/motiejus/undocker>

[3] <https://github.com/containers/bubblewrap>
No, don't close the park. Just open them for business. You want a clean, well-light, comfortable toilet in a national park? NP Toilet Inc will provide one for a small fee.
Perhaps something like Cobol? (Shudder.)
I don't necessarily believe this for a second but I'm going to suggest it because I'm feeling spicy.

OpenAI clearly downgrades some of their APIs from their maximal theoretic capability, for the purposes of response time/alignment/efficiency/whatever.

Multiple comments in this thread also say they couldn't reproduce the results for gpt3.5-turbo-instruct.

So what if the OP just happened to test at a time, or be IP bound to an instance, where the model was not nerfed? What if 3.5 and all subsequent OpenAI models can perform at this level but it's not strategic or cost effective for OpenAI to expose that consistently?

For the record, I don't actually believe this. But given the data it's a logical possibility.
The physical switch on my old iPhone to toggle silent mode stopped working and sometimes it will toggle itself. I had to setup the triple tap to toggle silent mode because the alternative is like 20 clicks deep in settings.
I'm curious, did you consider hiring a CEO to run the company? Or is the company too small for that?
So sad, he helped lots of us kids learn something that would later turn into a productive career.
He made 100s millions specifically from libeling the SH families?

Or his entire lifetime earnings were 100s millions?

The point is the law has been used (imho totally disproportionately) to bankrupt someone for things they said, and therefore censor them.

The same as with Thiel and Gawker.

Whether or not you agree with what they say, they should be able to say it.
There's a more insidious effect of cookie banners, which is that they make it annoying to follow external links, especially to websites that you haven't visited before. This disadvantages websites built for external links, like HN.
Start digging your own holes and kindly fill it back before you leave
heh, I've been using neom online for over 20 years, when they announced the city people I knew from the early 2000s emailed me ha. mine is from my original irc name neomonk.
Who comes up with this shit?
It's the year 2035. 80% of all energy is consumed by AI scammers talking on the phone with AI Grammas.
> Rhetorical question: ...

I've not seen any evidence that US voters in the US electoral system have much say in the choices they are given on the ballot.

My major criticism of the US electoral system, as an outsider, isn't of the candidates on ballots but rather the system that has devolved into non representative party politics where very small groups have an outsized weighting on the choices put forward and the system that works against alternative proportional choices.
Is not even funny
> who is paying the salaries for them?

Per the other comments, no one.
New York Doesn't Have Enough Housing. Why Is It So Expensive to Build?