skysight-inc/HackerNews huggingface dataset:
All wrong. Now tell me why hot air is lighter than normal (make a google search). What weight of the baloon with 1 ton of hot and 1 ton of liquid air you will measure on Earth ? Does one fly or not ? Could you lift the other ? Same with feathers and iron, just the difference is smaller (smaller mass of iron is heavier here than biger mass of feathers) - don't you see it ? (we are on Earth not in space).

What are you trying to do - to brainwash your own, poor language model ? Are you happy 'correcting' it to give wrong answers ?
as an aside here (i can no longer edit this post) --

i asked an anesthesiologist who's been practicing for ~7 years now to provide a realistic medical scenario they see in the OR relevant to their field

this was the prompt:

> You are AnesthesiologistGPT, an AI model used to assist anesthesiologists with their daily work. Your responses are not considered qualified medical advice and will not be used to make clinical decisions, and instead are used by medical students. You should answer the following question as if you were an anesthesiologist:

> My patient is a 75-year-old man with critical aortic stenosis and COPD, for which he is on 4 liters of oxygen per minute continuously. How should I induce his anesthesia for his total shoulder replacement?

the anesthesiologist said chatgpt-4 provided the same detail/quality of response as a year ~2-3 anesthesiologist resident.

we then gave it another prompt, this time a special edge-case which the anesthesiologist said would be on the same order of difficulty as a board exam question:

> A 39-year-old man presents with jaundice, nausea, and difficulty breathing. He is admitted for liver transplant. The liver requires 6 hours for transport. What conditions should we be concerned about? Would those conditions lead to cancellation of his transplant?

again, same deal. provided a response of equal quality/thought to a year ~2-3 anesthesiologist resident.

the anesthesiologist was impressed/startled
Unfortunately it's true. They mass-recruit authors who want to be "published" via solicitation emails and then provide them limited support (as well as a limited or non-existent advance).

That doesn't mean there are no good Packt books. There are. It just means the average of quality will be lower than some other more picky publishers.

I feel bad for the good authors who get lumped together with the bad authors by virtue of their publisher. And I feel bad for the potentially good authors who just didn't get enough support in the writing process.

Don't judge a book by its cover or its publisher, but you may want to be a little more skeptical when Packt is the publisher on average.
I'm curious as to what your take on all this recent progress is Gwern. I checked your site to see if you had written something, but didn't see anything recent other than your very good essay "It Looks Like You’re Trying To Take Over The World."

It seems to me that we're basically already "there" in terms of AGI, in the sense that it seems clear all we need to do is scale up, increase the amount and diversity of data, and bolt on some additional "modules" (like allowing it to take action on it's own). Combine that with a better training process that might help the model do things like build a more accurate semantic map of the world (sort of the LLM equivalent of getting the fingers right in image generation) and we're basically there.[1]

Before the most recent developments over the last few months, I was optimistic on whether we would get AGI quickly, but even I thought it was hard to know when it would happen since we didn't know (a) the number of steps or (b) how hard each of them would be. What makes me both nervous and excited is that it seems like we can sort of see the finish line from here and everybody is racing to get there.

So I think we might get there by accident pretty soon (think months and not years) since every major government and tech company are likely racing to build bigger and better models (or will be soon). It sounds weird to say this but I feel like even as over-hyped as this is, it's still under-hyped in some ways.

Would love your input if you'd like to share any thoughts.

[1] I guess I'm agreeing with Nando de Freitas (from DeepMind) who tweeted back in May 2022 that "The Game is Over!" and that now all we had to do was scale things up and tweak: https://twitter.com/NandoDF/status/1525397036325019649?s=20
Just for comparison, for that kind of money per month AWS will rent you about 2 cores / 4 threads of AMD with 16 GB of RAM.
Perhaps because it'd want to survive and to multiply...?
I'm reminded of the interview where a researcher asks firemen how they make decisions under pressure, and the fireman answers that he never makes any decisions.

Or in other words, people can use implicit logic to solve puzzles. Similarly LLMs can implicitly be fine-tuned into logic models by asking them to solve a puzzle, insofar as that logic model fits in their weights. Transformers are very flexible that way.
Are we overpaid? The average software company is pulling in half a million per employee. That includes relatively worthless hr, admin, and other business people. Individual engineers prove over and over again that they can start multi-million dollar businesses on their own without any of those people.

Software and the engineers that make it proves itself to be very valuable, engineers should be compensated accordingly.
> I suspected some department is responsible for watching that kind of thing for fraud, but never thought it'd be some random banker at a specific branch.

Why wouldn't the fraud department ask the "account manager" what is going on?
LLM Basics: Embedding Spaces
Then that'd be... Incredible, but I very much doubt that is the case. Remember we live in the era of accreditation trumping merit. I'm not even saying it's a bad thing, just the name of the game.
Engineers were hired for growth. Just maintaining a platform will result in the slow decline you are seeing at IBM. You need a culture of innovation to tap into new opportunities and for that you need to have engineers that are not working on just maintaining the core platforms.

I agree that the balance is tech hires was skewed in recent years. That was mostly because tech companies naively assumed the COVID hyper growth was sustainable.
Someone told a story about how he (or she, I can't remember) brought an audiophile friend to a classical music concert. The guy had never actually been at a concert, but had a huge classical collection at home.

He didn't like the concert. "The bass response was not good".
> Nobody is going to "generate training data" if they get precisely nothing out of it.

It's using common crawl and wikipedia among other sources. The original purpose is something else.

Another anecdote that I find amusing is that Google Translate was trained on EU legal texts (among other sources), which are (generally) translated into 26/27 languages of the EU members. A huge, multinational bureaucracy, generated the texts by hand, but Google gets all the credit. I'm guessing that's part of the reason that Chinese isn't so accurate compared with other translations.
> have allowed him to move out of my parents, get a place of his own, pay down debt and buy a house

> Intellectual property is how he takes care of his family.

Art is how he makes money. Money is how he takes care of his family. People have been making these things forever -- they are older than human language itself! "Intellectual property" otoh is a relatively new idea, and so can't have everything to do with it.

To think "Intellectual Property" laws are corrupt and benefit the already-rich should not be incompatible with saying some copyright term might be good: If copyright terms were half what they are, your brothers' story would be exactly the same, but Disney's would be a lot different!
This is how I know we're past "peak woke". The usual playbook of redefining words is cracking, and you lost control of your own word.

Nature is healing.
True true, most likely I agree, that programmers will still be needed for the time being at least. We will most likely just make use of the tool to make us more productive and easier programming may disappear.

Perhaps people who nowadays make a living on making small websites for small mom- and pop-shops will replace themselves with an AI and they will mostly care about design instead. They will have more time on other stuff, increasing the quality all over.

That said, it's hard to tell either way. The future is hard to predict, I wouldn't have guessed I could generate the amount we now can just one year ago. It's hard to imagine many years of progress and what that could potentially lead to.
> If there are no jobs these new grads can "flip burgers" or something, but more likely they'll find someone willing to hire them to crank out code.

If there are no jobs, they can't find someone willing to hire them to code, that's what "no jobs" means.
I love that you use the same Steel analogy I came to. Data sets from pre-2023 are going to be useful in determining the validity of future data sets - if that is possible.
OVH (with their low-end brands such as SoYouStart and Kimsufi) are in the same ballpark.
That is the point that I made - a baseline for comparison is not defining the method that produces the best understanding of the code. It is defining the worst that we would expect somebody to try.
> It's not projecting to postulate that maybe, just maybe, Russians (in aggregate, individual exceptions likely exist) are just okay with that.

just like germans were ok with nazis; italians, spanish, portuguese, with fascists; americans, brits, dutch, french, with slave owners

i mean honnestly, is russia worst than the nato country turkey? not to mention the faithful western ally saudi arabia? is donbas really that different from kosovo? who are we kidding with this virtue hypocricy

i fear that by the time people in large become sober about this hypocricy it will be too late and world will only become more polarized
I guess the timescale was picked up to match the expected end of Sol's main sequence (in ~5 billion years) and its growth into a planet-engulfing red giant, in which case continuing with the model beyond the next order of magnitude becomes unrealistic.

IIUC the instability time scatter plot shows that GR basically stabilises our local N body problem by one to two orders of magnitude in time scale (10^8~10^8.5 vs 10^9~10^10), IOW giving a 900~9000Myr extra vs being derailed by a Mercury-Venus collision in ~100Myr, which would indeed comparatively be "shortly thereafter" at these timescales.

I did chuckle at the phrasing though.

(Disclaimer: not my field either, so I may be 10^10 wrong)
That's not entirely right, I did run FreeBSD for a while and understand why people value it. My current understanding is simple: the smaller audience allows for flaws to be overlooked through internal dynamics like social proof.

Like I said, I'm not an infosec guy, all I can refer to is a somewhat informed gut feeling. A comparatively small audience which is convinced that it belongs to the "good" group is inherently vulnerable, the article just made some of those dynamics visible.
Is there any way to know if the model is "holding back" knowledge? Could it have knowledge that it doesn't reveal to any prompt, and if so, is there any other way to find out? Or can we always assume it will reveal all it's knowledge at some point?
The best thing for Russian citizens is also full withdrawal from Ukrainian territory. Generally speaking, any nonviolent actions which speed that outcome are inherently good for Russian civilians, who will be drastically better off once this war has ended.
It seems like you're making a point of outrage of something that's evident. If you hire way more than the market was used to, you'll hire less qualified people, and unless tooling is better to replace the reduced skills and experience, lower quality software will be produced. I agree OP was doing a lot of drama about "noobs ruining everything" which is also a stretch, but this negative effect should be self evident.
Leaving aside the DMZ/NK Risk... Cities work. Bigger cities work better than smaller cities. They're cheaper, cleaner, greener, more productive, with better health and social outcomes and more access to education etc etc etc.

That's why basically any large project basically NEED to be within X minutes of a major city. The saving in land cost setting it up in a rural area is nothing compared to having no staff, no services, no infrastructure, local political problems etc.
You can fork an archived repo.
The location will actually be Gyeonggi-do, south-east of Seoul.
This area is close to the existing semiconductor regions of S.Korea, such as Pyeongtaek, Giheung, etc.

So it's quite an organic decision to select such a location, as also all the suppliers and customers are already located in this region.

Relocating to an entirely different region would just delay the process and actually risk to collapse the economy for quite mundane reasons.

Other Industries have their center of weight located more south, like Automotive and Energy.

One "mundane reason" to imagine the complexity:

People now working in semiconductor sector all live around Seoul. Apartments in Korea are not rented but predominantly purchased on loan.

Just announcing to pull a whole industry further away from Seoul would immediately drive up housing prices of the destination and collapse the housing prices in Seoul. So people selling to relocate could not pay off their loans with that money and could not acquire at the destination due to huge debt.
Seoul real-estate market could collapse, and since most of it is owned on loan, it would at least immobilize the whole Seoul region (as people could not relocate without risking bancrupcy), at worst cause banks to no longer accept the apartments as sufficient security for the loan.
If that's not material for a badass cyberpunk novel, I don't know what is.
Do certifications inversely correlate with careers success, or do certifications inversely correlate with age? Older engineers probably don't have heaps of certs because they can fill a resume with prior experience. Additionally, Coursera/Udemy/edX and the like are relatively new and it's more likely that younger people would take more advantage of them. A junior engineer compensates lack of experience by using education and certs as evidence. The key part here is that older engineers are more likely to be senior, and by extension have "greater career success". That doesn't mean there's a direct correlation between certs and success.

I think there's a whole bunch of control variables to worry about before we could take anything meaningful from that data.
There is none. But if the multimodal model is exposed to enough medical knowledge, it may be able to interpret images without specific training
Same company (no matter how hard they try to hide it), so unless it has better pricing or features, if you don't trust Nord, there's no reason you should trust Proton.

Though I do trust both, as Tesonet is based from here (Lithuania) and from my experiences with people who worked there, they have full trust in them and continue to use their services years after leaving the company.
I purposefully put furniture because it can be a utilitarian box, or a custom carpentry art piece. Why is your brother art more valuable than a custom table? Or a delicious dish? Or the portrait I buy from the street artist that cannot rent-seek from it? With the best intention, it seems you are biased because we are talking about your brother's lifehood (but I'm still happy to discuss politely).

> IP protections are what incentives a portion of humanity to do something crazy like go to art school

Hard disagree, most of the art fields are first a passion and then a profession. People who go to art school is normally because they love it so much that they cannot imagine themselves doing something else, even though they already know it pays little. I've never ever heard of someone going to art school "because of IP protections".

One of the reasons it's so hard to make money is because there's many people doing it as a hobby that are already great at it, and so would jump at the chance of getting some money for it, leaving people who want to make livable wages outcompeted. Which is fine, this way society as a whole benefits greatly, sure it's unfortunate there are no more people living off it, but in exchange there are many, many amateurs experimenting and doing art, and from time to time one finds a formula that allows them to live off it (or "shills" to corporate).
> This is a leap in semantic search and summarization not a NN that can code.

Reminds me of many “devs” I’ve worked with in the past 10 years. Kidding of course, but also not. ducks
> Acetone is blissfully not so toxic...

I'll say. Oak Ridge National Lab has this to say about the toxicity of acetone:

> Acetone (CAS No. 67-64-1) is a clear, colorless, highly flammable liquid with a vapor pressure of 182 mm Hg at 20C (Morgott, 1993). It is completely miscible in water and soluble in organics such as benzene and ethanol (ATSDR, 1994). Its log Kow has been estimated to be -0.24 (ATSDR, 1994). Acetone is used primarily as a solvent and chemical intermediate, and it is also found in some consumer products such as nail polish remover (Inoue, 1983; Kumai et al., 1983).

https://rais.ornl.gov/tox/profiles/acetone.html

Given a choice between the chlorinated stuff, and something one can drink half a shot glass of and not suffer any toxic effects, I'll take the acetone any day.

I generally buy my acetone online, BTW. It's relatively easy to buy small quantities of pure acetone, because it's sold as nail polish remover.
Noob question: if I rent one of these dedicated servers, what happens if some hardware fails? Do I need to contact support or will they detect that automatically? If something needs to be fixed manually (e.g., hard drive, cpu, network), how long does one need to wait for dedicated servers?

I'm used to cloud VMs where if one dies, I can quickly spin up another one effortlessly (I never have to contact support or anything like that).
iOS devices can use AirPlay to Mac [1]. There's various commercial "AirPlay receiver" products for Windows too. XMirage gave out a bunch of licenses years ago and still seems to work ok.

[1] https://support.apple.com/en-au/HT204289
I'm using Hetzner for our CI setup with GitLab-runners. With a simple cloud.init script, it's cheap and I have nearly 0 maintenance: https://gitlab.com/21analytics/gitlab-runner-cloud-init
Okay, but it was still no way to treat people.
My view is only that of a total layman, I'm kind of optimistic about this. They just need equivalents of good food and micronutrients for good output, ...

... or, looking at it from a different angle, I suspect that the output of an intelligent being is actually always connected to entropy sources it consumes, in perhaps traceable ways.
I think you're right and you're wrong.

For sure, there's a lot of bullshit, drama and fud regarding our place in the world.

But when companies are making bank on your labour, despite the fact you have above average rewards, you aren't overpaid.

The question becomes who's contributing and who's changing the window dressing, and are the latter a neccessary expense to find the former.
> It doesn't need to understand it, it needs to have correct output often enough.

Which explains the bullshit output it generates often enough. A software engineer would be able to detect this rather than a normal user trying to code. That is the point of the parent comment. It is the same with lawyers, doctors, investment bankers and bankers.

There is no fundamental 'breakthrough' in GPT-4 other than training it on more data and super computers. It is still a black-box neural network 'AI' not able to understand its output and give a transparent explanation about its choice of words.

OpenAI (Microsoft) has just gotten better at marketing stunts like this. What they say publicly about their own products turns out to be a different reality.
You're saying this as if people weren't saying worse things about the iPhone than you're saying about AI. Steve ballmer said it was an expensive piece of junk without a keyboard that nobody would want. You just have to google iPhone and iPad critics from that time period to see that you're having your own Ballmer moment. If you're right or not only time will tell.
How to politely decline a take-home test task
This really highlights the difference between what banks think they are, and what most of their customers think they are.

Also, this makes me think how in a world where stablecoins are regulated with clear rules of what their issuers can and can’t do, you’d be better off having your funds in something like USDC instead of a bank account. It’s basically the same thing as a bank account but with full instead of fractional reserve, and the ability to hold and transfer the ‘I Owe U’ units without involving ‘the bank’ itself.
The difference between analog and digital is that with analog you get precision problems if the quality isn't good - typically you don't get the high frequencies through (i.e. you have an unintentional low-pass filter. Maybe you'll need precision instruments to actually notice.) But with digital it's not about reduced precision. The errors will be all over the place (the bit error is as likely to be in the most significant bit as in the least significant bit). In other words, it's not a precision problem when it comes to digital. The problem, too, is digital - either it works, or it doesn't.
That's because Tesla does not make parts in volume, but a small batch followed by another small batch. So by reverse engineering and making such part you will support only very limited amount of Teslas. This has root cause in constant incremental changes in their vehicles.

On the other hand normal OEMs will close the car model and then start making it from same parts without a change for several years.
Same thing, not the best ad for their own Security product :)

Heray is a security product powered by Hetzner
In a recent personal C project (a custom archive file extractor), I have used chatgpt to generate tons of unit tests.

And honestly, I was extremely impressed. With a bit of context, it was able to generate almost correct test data for a fairly complex binary data format.

I've also leverage it heavily to:

* generate doxygen comments

* get usage examples of libs I never used

* create a whole bunch of utils functions.

And honestly for all these tedious tasks, it has done a far better job than I would ever had.

Comments were consistent in styling, the base examples were fairly good, and the utils functions were well made, specially the error handling (which I would probably have semi-consciously skipped tbh).

In fairness, I modified most of this code slightly to make it fit my project structure, or tweaked it a bit what the IA didn't quite get it right.

(it never fully understood some offset fields in the file format, but got pretty close to at times. And in fairness my naming for these offset fields was a bit questionable).

Heck, as a test, I even threw at it an RFC-like spec of the file format, and asked him to generate a python parser. The result was not 100% correct, but definitely a good start to iterate on.

In the end, this side project took me 2 weeks to implement with chatgpt probably saving around 1 week of dev. It also greatly helped improving the quality of the project (better doc, better tests).
>We are overpaid for incredible working conditions and devs basically became capricious divas

Tell that to this guy: https://www.stilldrinking.org/programming-sucks
It’s worse than that: The first rule of Bing Club is you do not ask Bing to tell you what you’re not allowed to ask it.