LWN: Comments on "Gentoo bans AI-created contributions"

Gentoo bans AI-created contributions

NAR — Mon, 29 Apr 2024 10:37:20 +0000

I think it's going to be hugely impactful - and NOT in a good way.

I remember the good old days of late-1990s when on Linux-related mailing lists we were "competing" on how much Nigerian scam e-mails we were receiving in a month. There were separate competitions for the number of offers and for the sum value. During this we were sure that the "general population" was safe from this scam as most people didn't speak English and these were obvious scams. Today the most exposed population still doesn't speak English, but the scammers can generate good enough Hungarian text (on the level of an uneducated native speaker) that can easily fool them and they do fall for scams...

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Wol — Sun, 28 Apr 2024 11:31:03 +0000

> But this

? >Nobody seriously doubts that the AI is here to stay, and that it's going to be hugely impactful.

> I can 100% say is 100% false.

I think you're reading this all wrong. I think it's going to be hugely impactful - and NOT in a good way.

As so often, the mathematicians (namely the guys writing all this software) seem to think that mathematics dictates the way the world behaves, not describes it. They're busily disappearing into an alternative universe, the problem being that they're trying to force everyone else to live in it ...

Cheers,
Wol

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Cyberax — Sun, 28 Apr 2024 06:10:49 +0000

> I can 100% say is 100% false.

I meant VCs. Also, you should examine yourself for religious fervor.

> Oh, and remember the self-driving taxis? Still waiting...

If I had seen your reply earlier today, I would have written the reply from a self-driving taxi. Waymo exists, and it provides service in SF. It's also slowly expanding its service area.

Pretty much all new advances follow the https://en.wikipedia.org/wiki/Gartner_hype_cycle . The self-driving cars are in the trough of disillusionment, and are slowly climbing to the plateau of productivity.

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ssmith32 — Sun, 28 Apr 2024 05:46:53 +0000

I've learned I can't argue with the wishes and religious fervor that permeates all those who buy into the VC-fueled Silicon Valley bubble. Pets.com probably had some amazing annualized numbers too, if you picked the right day to project from.. so did Enron, AIG, lots of folks...

But this

>Nobody seriously doubts that the AI is here to stay, and that it's going to be hugely impactful.

I can 100% say is 100% false.

At least one person, who has received a graduate level degree in compuer science, and has worked in the industry for more years than I care to say, does not think it will be hugely impactful.

And I know others that have at least voiced similar cynicism. Including some with graduate specializations directly in the field of CNNs/autoencoders/etc.

So, yeah, enjoy the ride. Slightly better auto-complete is nice, but hugely impactful, it is not. Oh, and remember the self-driving taxis? Still waiting...

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gutschke — Sat, 27 Apr 2024 02:19:56 +0000

Just to throw another wrinkle into this discussion, I believe that in "ich bin arbeitend", the "arbeitend" would be a predicative expression, which is different both from an adverb and from a way of expressing what English would do with present continuous. It simply describes a state that you are in. For a better discussion, see https://en.wikipedia.org/wiki/Predicative_expression

I understand why it is tempting to say that the present participle is used to form a present continuous. That would feel very natural to an English speaker who is familiar with Latin. And it feels almost but not quite as if German should do the same. In fact, I wouldn't be surprised if some regional German dialects did this. There is a lot of cross pollination between all of these languages, but in the process grammatical concepts get repurposed and subtly change.

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flussence — Tue, 23 Apr 2024 21:02:27 +0000

> we (“the markets”)

Quite a revealing slip.

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Cyberax — Tue, 23 Apr 2024 17:30:54 +0000

> Because, as pointed out, that's not true. The current pricing is subsidized under the assumption

No, it's not. I know financials of a couple of a small AI company, and model running is expensive, but it can be done profitably. It's not feasible if you're doing any of the ad-funded "user is the product" crap, but it's doable if your customers actually pay you.

> I think you may be underestimating how resource hungry these things are. Consider the person in another thread here who said they needed two 3090 GPUs to get acceptable output speed for programming. That's $2500 upfront and nearly 1kW continuous power draw just for some autocomplete. Datacenter inference systems will be somewhat more efficient, but the scale of hardware needed to perform these queries is just bonkers.

The power draw is not continuous, you only need to do computation when you're doing a query. This takes in total maybe for a minute or so within an hour. In the OpenAI case, a single hardware node is shared across multiple customers.

The main cost that is not covered is R&D (model training and engineering salary).

> You've answered your own question :) It's hard to imagine a more use friendly interface than a text chat, but there is currently no clear route to improvements there either.

Chat is not great for UI systems, actually. It's too low-level, and you need to do context imports periodically. Just as with any other service, you need application support in many cases. My email classifier is a bunch of scripts that run on my home server, and it's certainly not a good general-purpose solution.

> The so-called hallucination is just inherent and can not be solved.

There are thousands of very smart people working on solving it. I'm pretty sure they'll think of something that will be good enough for practical purposes.

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Wol — Tue, 23 Apr 2024 15:20:41 +0000

> we naturally train our neural networks as we use them to make inferences, and don't have this particular mode switch.

We also don't feed back to our AIs "this is wrong, this is right". So it's free to spout garbage (hallucinate) with no way of correcting it.

Cheers,
Wol

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Wol — Tue, 23 Apr 2024 10:51:22 +0000

Plus, it's well known that our neural networks have dedicated sub-systems for, eg recognising faces, that can be rapidly trained.

For example, baby learns what mum sounds like in the womb, and that is re-inforced by mum hugging new-born. My grand-daughter was prem, and while there don't appear to be any lasting effects, it's well known that separating mother and child at birth has very noticeable impacts in the short term. Not all of them repairable ...

We're spending far too much effort throwing brute force at these problems without trying to understand what's actually going on. I'm amazed at how much has been forgotten about how capable the systems of the 70's and 80's were - the prolog "AI Doctor" running on a Tandy or Pet that could out-perform a GP in diagnosis skills. The robot crab that could play in the surf-zone powered by a 6502. I'm sure there are plenty more examples, where our super-duper AI "more power than sent a man to the moon" would find it impossible to compete with that ancient tech ...

Modern man thinks he's so clever, because he's lost touch with the achievements of the past ...

Cheers,
Wol

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farnz — Tue, 23 Apr 2024 09:26:13 +0000

Right, but you were claiming that because the input to a child can be summarised in a small amount of text, the child's neural network is clearly learning from that small amount of data, and not from the extra signals carried in spoken work and in body language as well.

This is what makes the "training data is so big" argument unreasonable; it involves a lot of assumptions about the training data needed to make a human capable of what we do, and then says "if my assumptions are correct, AI is data-inefficient", without justifying the assumptions.

Personally, I think the next big step we need to take is to get Machine Learning to a point where training and inference happen at the same time; right now, there's a separation between training (teaching the computer) and inference (using the trained model), such that no learning can take place during inference, and no useful output can be extracted during training. And that's not the way any natural intelligence (from something very stupid like a chicken, to something very clever like a Nobel Prize winner) works; we naturally train our neural networks as we use them to make inferences, and don't have this particular mode switch.

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atnot — Tue, 23 Apr 2024 07:48:48 +0000

> With ChatGPT you pay directly for your use (on a literal per-character basis). This cost easily covers the model runtime cost. Why is it not cost-effective?

Because, as pointed out, that's not true. The current pricing is subsidized under the assumption that a) the models will rapidly become obsolete anyway b) the lasting market share advantage will offset the losses. We don't know this for certain with OpenAI except by omission, but we know it for other offerings by more public companies that have nearly identical costs and pricing, e.g. Microsoft.

I think you may be underestimating how resource hungry these things are. Consider the person in another thread here who said they needed two 3090 GPUs to get acceptable output speed for programming. That's $2500 upfront and nearly 1kW continuous power draw just for some autocomplete. Datacenter inference systems will be somewhat more efficient, but the scale of hardware needed to perform these queries is just bonkers.

> once it becomes more user-friendly

You've answered your own question :) It's hard to imagine a more use friendly interface than a text chat, but there is currently no clear route to improvements there either. The so-called hallucination is just inherent and can not be solved. That would require a system where facts are first-class citizens instead of just crossing your fingers and hoping they are statistically likely. As recently shown this type of model also requires exponential increases in training data for linear increases in capability and we're already out of public data to train them on. It is generally questionable whether we can get much better than this by predicting tokens.

So if we're stuck with approximately what we have now, and we know the real costs are many times what the billing prices are, I think it'll be hard to find end-users who consider that a worthwhile investment.

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Cyberax — Tue, 23 Apr 2024 00:27:42 +0000

> The point of the discussion was that these minor convenience functions are not solved by LLMs in a resource or cost effective way.

With ChatGPT you pay directly for your use (on a literal per-character basis). This cost easily covers the model runtime cost. Why is it not cost-effective?

> If it's individuals, then sure, those may have some minor uses for it, but wouldn't pay the cost.

Now you're making assumptions. Why do you think regular people won't use AI once it becomes more user-friendly?

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atnot — Mon, 22 Apr 2024 23:16:31 +0000

The point of the discussion was that these minor convenience functions are not solved by LLMs in a resource or cost effective way. I'm sure these things are useful to you, but the question is how many people would still be doing it if they had to pay what it actually cost.

If the answer is supposed to be "corporations" then, well, they can afford the true cost but don't have any worthwhile uses for it. If it's individuals, then sure, those may have some minor uses for it, but wouldn't pay the cost. And the end result is an overhyped technology that's just not useful to anyone unless we assume an endless chain of VCs pumping it forever, putting aside the immense environmental and societal costs for now.

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Cyberax — Mon, 22 Apr 2024 22:17:54 +0000

> Can they?

Of course. Pure model running is already highly profitable on general-purpose hardware at the prices that OpenAI charges. And it's going to be even better on special-purpose hardware.

> For two, we don't know what those "paying customers" are actually doing.

OpenAI certainly does. And a lot of customers are using ChatGPT on their own. I know non-native English speakers who are using OpenAI to correct spelling mistakes in emails. Or business analytics people using ChatGPT to write Python scripts to do data queries for data in Google Sheets. A very common use is to create TLDR versions of news articles and books.

I'm using ChatGPT to filter emails that are just CC-ed to me, but that don't need my personal attention, and then do a daily summary.

Are these ground-breaking mega-AI use-cases? Not really. But they are highly useful.

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atnot — Mon, 22 Apr 2024 22:09:32 +0000

> OpenAI has actual income from actual paying customers. They can just stop the R&D, and they'll be hugely profitable (for a while).

Can they?

For one, as I said, we don't know how much of their losses are from operating their service vs research. But I am going to go out on a limb and say that if even just a single service was operating at a profit, they would have been very eager to tell us. That would, to my knowledge, be a first for any genAI offering and cement them as the clear leaders in the industry. It would also help reinforce the idea that AI is going to be incredibly profitable as that comes under fire. However they seem weirdly coy about their operating figures somehow.

For two, we don't know what those "paying customers" are actually doing. There's been a whole lot of demos and webtoys and "experimenting" and "trials" and pass-through APIs that hastily paste your parameters into some pre-written prompt. But there's been remarkably little actual success stories and useful business applications for it. I couldn't find any company stating they made a profit *using* AI either. I don't think they could stop r&d if they wanted to, because all of these companies testing out chatgpt solutions to problems that it can't actually solve are doing so based on the idea that these things soon enough will be able to do anything. The visible r&d spending is crucial to that.

I found it remarkable how in a recent article I read, the Washington Post, despite clearly trying very hard, couldn't scrounge up anyone to balance the article with some positive news who didn't have to resort to constructs like "I think we will see" and "my expectations are" (https://archive.is/pIOra). It's almost funny how consistently all of the bad news is in present tense and the good news are in the future tense. The constant excuses how about how "it's just the early days" and "we'll see applications for it any days now" will also seem very familiar to anyone who has followed e.g. cryptocurrency news[1].

It may just be that they are earning a lot of money by teaching customers their tech isn't useful for them. The one thing I can find reliably is stories such as an animation company hiring a bunch of "prompt engineers" instead of artists to paint background mattes, failing at making minor revisions of the work and not understanding how animation works and getting canned. This great success, of course, will up (4x) in their next annualized revenue figures :)

[1] Which does bring up a fun comparison: local divisions of McDonals and Hershey's did certainly pay a few thousand dollars (or rather, paid a marketing agency to pay a few thousand dollars) for a "crypto experience" on some crypto "metaverse" platform I don't remember the name of at the height of the crypto/metaverse bubble. A bunch of brands minted NFTs too. However that money was, unsurprisingly, not the start of enormous year-on-year brand spending on the blockchain people claimed it was.

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rgmoore — Mon, 22 Apr 2024 21:34:16 +0000

That carries with it the assumption that text is a complete representation of what people use to learn to speak and listen, before they move onto reading and writing.

To the contrary, I think the different learning environment is part of what we need to reproduce if we want more human-like AI. A huge problem with LLM is that they are largely fed a single kind of input. It's no wonder chatbots have problems interacting with the world; they've read about it but never dealt with it firsthand. If we want an AI that can deal with the world as we do, it needs a full set of senses and probably a body so it can do something more than chat or paint.

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kleptog — Mon, 22 Apr 2024 21:04:27 +0000

Yeah, I guess I'm not explaining myself very well. It's not that the "am" is unnecessary in general, but that most of the time they mean the variant without. So you get conversations like:

A: What do you do during the day?
B: I am working.
A: (confused) Clearly you are sitting here having a drink? Oh you mean "I work".

It's not that some languages cannot express certain tenses, given enough words you can express any tense in any (sufficiently advanced) language. It's whether certain tenses have a special status in the grammer of a language. Generally similar concepts in different languages are linked in different ways which leads to people learning the language using words in ways a native speaker finds confusing.

But yes, this is a post about Gentoo, so better leave it at that.

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Cyberax — Mon, 22 Apr 2024 17:57:38 +0000

> But in normal industries, you sell a product and use money from sale to fund more development.

That model works for established industries. If you try to do that in a new industry, you can be outcompeted by VC-funded companies who can afford to fund better R&D.

This does create perverse incentives where you're working to please VCs rather than your customers, but it also results in a much faster R&D overall. Think about it as unintentional private funding of academic research, if this makes you feel better.

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Cyberax — Mon, 22 Apr 2024 17:53:40 +0000

> I'm just going to point out how every point in this argument relies on the word "will".

OpenAI has actual income from actual paying customers. They can just stop the R&D, and they'll be hugely profitable (for a while).

> In an extremely speculative market that has been recognized even by proponents as probably a bubble.

It's speculative, but not in the sense you're thinking about. Nobody seriously doubts that the AI is here to stay, and that it's going to be hugely impactful. However, nobody also knows who is going to win the AI race. So every VC is making tons of bets, resulting in a somewhat frenzied environment.

They fully expect 99+% of their investments to go up in smoke, but if they make a successful bet, that remaining 1% will recoup the losses.

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atnot — Mon, 22 Apr 2024 14:54:53 +0000

A difference is that with more traditional investments the entity doing the investment is one that pretty directly stands to benefit from the R&D being done. For example, AT&T investing into developing the transistor, or the US government developing nuclear-resistant networks, as you mentioned. Conversely, VCs are remarkable for just how little they care what the actual technology is. Some even write gloating blog posts about how virtuous they think they are for basing investment decisions solely on how charistmatic they think the founders are and they don't even look at the slide decks or financials.

This makes sense, because at some point the industry realized that their primary way of getting paid is only rarely the technologies actually working out, and more commonly just using their elite connections to find a bigger sucker as fast as possible. This detachment from any of the effects of any of their investments may have some arguable advantages, kodak inventing and then killing the digital camera comes to mind. But it also runs the risk of, say, growing an entire sector around repeatedly wasting a medium sized countries GDP on things that nobody wants or needs and then trying to hype up everyone else to buy it off them for more.

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farnz — Mon, 22 Apr 2024 14:50:04 +0000

That carries with it the assumption that text is a complete representation of what people use to learn to speak and listen, before they move onto reading and writing. It also assumes that we have no pre-prepared pathways to assist with language acquisition.

Once you add in full-fidelity video and audio at the quality that a child can see and hear, you get to terabytes of data input before a human can read. Now, there's a good chance that a lot of that is unnecessary, but you've not shown that - merely asserted that it's false.

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rgmoore — Mon, 22 Apr 2024 14:44:01 +0000

Note that a human writer has also had terabytes worth of language as examples before they start producing things that are correct

It's not terabytes, though. A really fast reader might be able to read a kilobyte per minute. If they read at that speed for 16 hours a day, they might be able to manage a megabyte per day. That would mean a gigabyte every 3 years of solid, fast reading doing nothing else every day. So a truly dedicated reader could manage at most a few tens of GB over a lifetime. Most people probably manage at most a few GB. Speaking isn't a whole lot faster. That means most humans are able to learn their native languages using orders of magnitude fewer examples than LLMs are.

To me, this is a sign the LLM stuff, at least the way we're doing it, is probably a side track. It's a neat way to get something that produces competent text, and because it has been trained on a huge range of texts it will be able to interact in just about any area. But it's a very inefficient way of learning language compared to the way humans do it. If we want something more like AGI, we need to think more about the way humans learn and try to teach our AI that way, rather than just throwing more texts at the problem.

On continuing

corbet — Mon, 22 Apr 2024 13:57:46 +0000

Indeed, this conversation has gone fairly far afield, and it seems like a good time to wind it down.

Remember Gentoo? ... this is an article about Gentoo ...

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rgmoore — Mon, 22 Apr 2024 13:50:59 +0000

R&D does come from ongoing operations in established industries, but it often has to come from somewhere else in order for those industries to establish themselves. There are plenty of industries that got their start from hobbyists spending their personal time and money on something that interested them, or from academic or government-funded research. As an example, computers got their start first as academic projects and then as military ones. They didn't get any interest from industry until that basic R&D was done for them, and even with that they got plenty of government money to help them grow. It's not totally out there for venture capitalists to put money into the initial R&D needed to get an industry off the ground, provided they see a big enough reward if the companies succeed.

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khim — Mon, 22 Apr 2024 13:48:19 +0000

> Once you point it out to them it usually corrects fairly quickly, but it's fascinating that the same type of error keeps popping up.

What's fascinating about that? You are using less flexible language and are forcing someone to pick between two choice that to him (or her) are almost undistinguishable. Of course there would be mistakes!

It's like an attempt of someone to write perl program for the first time. Learning when should you use `$` and when should you use `@` with arrays names is non-trivial, to say the least.

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khim — Mon, 22 Apr 2024 13:43:02 +0000

I don't know whether continuing is constructive at this point. You are sprouting the same kind of nonsense that you sprouted when undefined behavior was discussed and ignore everything except what you believe to be true. Even if your believe don't even remotely match the reality.

> Let's apply some very simple logic.

If by now “logic”, in English, means “random sequence of letters without any clear meaning”, then I guess I learned some kind of wrong English.

> "I program" = "I am programming"

therefore true = false

Unless you live in Crete, these two cannot be same

Sure, they are not the same, but so are sentences “I am”, “I like”, “I like programming”, “I teach”, “I teach programming” and many others.

> therefore while they are both present

Yes. And they are present in most other human languages. Or do you believe other languges couldn't distinguish without person who is programming for living and person who programs something right now, this very second? They can, that's not a reason to introduce some nonsense bazillion present tenses.

Why does it may surprise that not all things that may happen in present have the same meaning… or why have you decided that alls these sequences of words should be split into three semi-randomly picked present times?

> they have to be different present tenses

Why? Why “I like programming” or “I teach programming” don't need different present tenses, but “I am programming” needs it?

> And I don't know about you, but this confusion is one of the absolutely standard ways by which we detect foreign speakers ... it's a VERY common mistake.

Yes, but is it because English have more “more present tenses” or… because has it “less present tenses”? I would say that it's because it has less.

It's the same story as with articles: similarly to how most of the time difference between “a” and “the” is meaningless (can be picked from the context easily and can be easily conveyed if needed) difference between “I program” and “I am programming” exist but it's not useful! Of course other languages can distinguish between these two forms if needed, it's just most of the time there are no need to distingush them.

Worse: the form that is conveying more often needed meaning (that I'm programming right now) is longer and more complicated.

English is similar to BASH here: like in BASH you may want to write $* or "$@" and, most of the time, short form is not needed and not used so English insist on use of longer form where difference between two forms are meaningless (e.g. on a programmer's forum saying that you know how to program is not useful but saying that you are in process of writing program is useful).

> Coupled with the occasional giveaway of "I programming" which simply doesn't exist in standard English.

Indeed. English grammar is extremely inflexible, rigid and, I would even say, “strange”. It takes a long time for a speaker of some other language where words don't come in a sentence in any particular order to adjust to it.

English, of course, have no choice because it has words that may sound identically when used as noun and as verb, but, again, problem arises not when English offers you more capabilities (you may just ignore them) but when it doesn't have capabilities that other languages have (similarly to how translating program from statically-typed language to dynamically-typed is easy but going in the other direction is not).

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Wol — Mon, 22 Apr 2024 11:45:20 +0000

> I'm confused, how is the am in "I am going to school" unnecessary in English? "I go to school" in English - at least in most of the Celtic Isles - would sound a little foreign. Indeed, it sounds... Dutch. ;)

My daughter goes to school - and she's 40. She's a deputy head :-)

The "am" is WRONG (not unnecessary, wrong) if it's school holidays :-) "I go to school" typically means "I am a student", while "I am going to school" means I'm on my way right now.

Cheers,
Wol

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hkario — Mon, 22 Apr 2024 11:30:25 +0000

R&D exists in every industry. That's how we got here, whole civilisation-wise.
But in normal industries, you sell a product and use money from sale to fund more development.
In bubble economies it's the VCs that pony up the money and the "product" is sold at a loss to create a marked or just capture the market. It's unsustainable, but the investment class has the money to burn so they play like that.

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gmgod — Mon, 22 Apr 2024 11:14:23 +0000

Oh yeah, it did not occur to me that phrase wouldn't be one.

We have a colleague who, after interviewing a candidate so dreadful we wondered if they did not show up to the *wrong* interview, once said something like "the light was on so I just let myself in" to give a satirizing summary of what the candidate did (not actually) say.

That stuck and we have many variants now, including "I saw there was light here" or "it looked warm in here" and they all mean the same. I don't know where that colleague got that from, whether it was divine inspiration or one French expression he brought with him.

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paulj — Mon, 22 Apr 2024 11:00:58 +0000

I'm confused, how is the am in "I am going to school" unnecessary in English? "I go to school" in English - at least in most of the Celtic Isles - would sound a little foreign. Indeed, it sounds... Dutch. ;)

Also (and ICBW, I've never really had native /adult/ dutch, and it's been a long time since I had native child's dutch), but could a dutch person not be more precise with "Ik ga nu naar school" for "I am going to school now"? Also, "Ik ga zo naar school" for "I am going to school shortly"? Part of the problem with dutch is it has become very terse, and dropped a lot of constructs - even in my lifetime AFAIK. (??).

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kleptog — Mon, 22 Apr 2024 10:29:43 +0000

This is one of the classic mistakes Dutch people with poor English make.

The phrase "ik ga naar school" in Dutch can mean either "I go to school" or "I am going to school (now)" depending on the context. For some reason Dutch people often throw in the "am" when it is unnecessary, but other Dutch don't pick up the problem either. Once you point it out to them it usually corrects fairly quickly, but it's fascinating that the same type of error keeps popping up.

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farnz — Mon, 22 Apr 2024 09:25:37 +0000

There's also been a truly horrible thing that I've seen pitched - speech recognition and speech synthesis feeding into a multi-chat CS system. You have the same one worker in a few chats thing, but you combine it with speech recognition feeding the chats, so that you get all the downside you describe, but while you're on the phone with "John in Florida" or similar.

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farnz — Mon, 22 Apr 2024 09:25:13 +0000

Humans extrapolate in a way that machines cannot.

This isn't, as far as I can tell, true. The problem with AI is not that it can't extrapolate, it's that the only thing it can do is extrapolate. A human can extrapolate, but we can also switch to inductive reasoning, deduction, cause-and-effect, and most importantly a human is able to combine multiple forms of reasoning to get results quickly and efficiently.

Note that a human writer has also had terabytes worth of language as examples before they start producing things that are correct - we spend years in "childhood" where we're learning from examples. Dismissing AI for needing a huge amount of examples, when humans need literal years between birth and writing something approximately correct is not advancing the conversation any.

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atnot — Mon, 22 Apr 2024 08:18:39 +0000

I'm just going to point out how every point in this argument relies on the word "will". In an extremely speculative market that has been recognized even by proponents as probably a bubble.

"Will" is a word that means "doesn't". No matter how optimistic you are about the outlook, the facts are they're highly unprofitable right now. We don't know much about how big the operating vs r&d costs actually are, nor do we know how fruitful any of those r&d efforts might actually be. We do know that in the here and now, the cost of these things, financial and societal, is astronomical and that the actual value is minor. We know that for more than a year, we haven't seen any glimpses of the previous exponential improvements[1]. Especially given the track record of the tech industry in the last decade, just taking the boosters at their word here seems extremely foolish.

[1] https://garymarcus.substack.com/p/evidence-that-llms-are-...

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khim — Mon, 22 Apr 2024 07:43:16 +0000

> Haskell and Rust may be nice languages but it's not as if they made debugging unnecessary.

This, of course, depends to a large degree on how you structure your code and, even more importantly, how you structure your data.

The determined Real Programmer can write FORTRAN programs in any language, after all.

But if you structure your code to embed enough domain knowledge in the data types then yes, debugging becomes mostly unnecessary. And even if you do need to debug things you know where to go: to these pesky few corner cases which you cut because you had poor understanding on what your program actually should do.

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Wol — Mon, 22 Apr 2024 07:38:03 +0000

> No, there are two times and many verbs of which few selected ones are interpreted by teachers as “yet another time”.

Let's apply some very simple logic.

"I program" = "I am programming"

therefore true = false

Unless you live in Crete, these two cannot be same, therefore while they are both present, they have to be different present tenses. And I don't know about you, but this confusion is one of the absolutely standard ways by which we detect foreign speakers ... it's a VERY common mistake. (Coupled with the occasional giveaway of "I programming" which simply doesn't exist in standard English.)

Cheers,
Wol

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donald.buczek — Mon, 22 Apr 2024 07:25:24 +0000

> Mmmm, I believe arbeitend functions as an adverb, in this sentence. That is "I am something" and the something that I am is "working".

After reading a bit I have to admit that you are more correct than I am. The word form 'arbeitend' is known as 'Partizip I' (Present Participle) in German, which functions as a hybrid between a verb and an adjective/adverb.

This is from the beginning of the German variant of the Wikipedia of "Participle" / "Partizip" page:

> A participle (Latin participium, from particeps "participating"; plural: participles) is a grammatical form (participial form) that is derived from a verb and thereby partially acquires the properties of an adjective, but also retains some properties of a verb. The term "participle" and likewise the German term Mittelwort express this characteristic of participating in two categories at the same time, namely verb and adjective. [...]
> German examples of participles are the forms ending in -end like spielend (to the verb spielen; called "Present Participle") and the forms starting with ge- like gespielt (called "Past Participle"). In traditional grammar, participles were often listed as a separate part of speech alongside verbs, adjectives, nouns, etc.; however, this view is not shared in modern linguistics, where participles are considered as words or even constructions that contain varying proportions of verbal and adjectival
components.

You are correct; the Present Participle ('Partizip I') is not typically used in natural speech as a verb to denote an 'immediate' tense. "Ich bin arbeitend" can be said to be wrong and is not listed in tables with verb tenses. At least, it sounds yoda-ish.

As you mentioned, The Present Participle is used as an adjective or adverb to describe a state. It's also used, a bit more verbish, to indicate simultaneous actions, for example, "Die Kinder kamen lachend aus der Schule" ("The children came out of the school laughing").

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anselm — Mon, 22 Apr 2024 07:23:44 +0000

If you use something like Haskell or Rust then writing the code is the majority of your work

I don't buy that. There will still be loads and loads of bugs in people's code even if the compiler accepts it. Haskell and Rust may be nice languages but it's not as if they made debugging unnecessary.

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khim — Mon, 22 Apr 2024 04:54:01 +0000

> It's like writing code vs testing and debugging. Writing it out is the easy part (relatively speaking).

How much code in Haskell or Rust you wrote?

Whether writing code is an easy part or not depends very much on what you are writing and how.

Sure, if you are using language which allows you to write something like [] + {} and get nonsense output without any errors then writing code is easy and testing and debugging is tedios and time-consuming part.

If you use something like Haskell or Rust then writing the code is the majority of your work and if you are using something like WUFFS then writing the code that compiler accepts is 99% of work.

> If you don't understand the language, you won't be able to review the output.

Sure, but that's where AI and human complement each other: for human it's easier to understand unfamiliar language than to write sentence in unfamiliar language, while for AI it's the opposite. So by allowing AI to create something that is “looking nice” (task which current generative AIs already perform better than non-native speakers) and giving human the task that s/he does well you reduce the time needed to create the final result. That's true both for programming language like Python or Ruby and regular language like English or Chinese.

I have no idea why is it so hard to accept when it's obvious. It's the exact same reason spellcheckers work, after all.

Heck, do an expriment: try to write some simple program in language that you have never used before (Haskell, Scheme, or maybe APL or MUMPS) and compare to the time needed to first learn said language and then write something.

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Cyberax — Mon, 22 Apr 2024 04:52:21 +0000

> No, it just hit $2 billion "annualized" revenue.

Uh, "annualized" just means "projected until the end of the year, given the current income". It usually underestimates the income of growing companies, unless something terrible happens.

> "Altman has said OpenAI remains lossmaking because of the vast costs of building and running its models. The spending is expected to continue to outpace revenue growth as it develops more sophisticated models. The company is likely to need to raise *tens of billions* more in order to meet those costs."

They need money because they want to build newer and better models. This is how R&D works in _any_ industry. Pure model running can already be profitable, if all you want is just to run models. It will become even more profitable in the near future when new AI accelerators hit the market.

New model development is expensive, but it also will get cheaper. Both because of new specialized hardware and because training methods are improving.