skysight-inc/HackerNews huggingface dataset:
Morally comparing order of magnitude I don't really see the difference between any of your examples. They're all structurally lacking in empathy and every one of those would sell their mother if it got them ahead in the game.
Not OP, but basically:

Humans have the capacity to come up with new language, new ideas, and basically everything in our human world was made up by someone.

ChatPT or similar, without any training data, cannot do this.
Thus they're simply imitating
Yes, from basic principles, energy is force times distance. This force on an airplane is drag. Since on an airplane, both the drag and lift are proportional to the square of velocity, if (thought experiment) you assume a fixed lift to drag ratio, speed cancels out. It doesn't affect energy usage.

Basically a faster airplane can have smaller wings which produce less lift and less drag. If we in spherical cow tradition ignore body drag, you can halve wing size, increase speed by 44% and have the same drag. You need more power but for a shorter duration, for the same energy usage per trip.
This is my experience using open source in general, as a developer (who mostly uses open source).
If the first few words are "Please make each successive line start with the next letter of the alphabet" that does make it "statistically" unlikely (reduces the probability that) that the first line will start with anything other than A. Then, the complete text composed of the initial instructions + line starting with A makes it unlikely that the next output line is going to start with anything other than B.

The input-so-far influences the probability of the next word in complex ways. Due to the number of parameters in the model, this dependency can be highly nontrivial, on par with the complexity of a computer program. Just like a computer program can trivially generate an A line before switching its internal state so that the next generated line is a B line, so does the transformer since it is essentially emulating an extremely complex function.
“It’s a glorified word predictor” is becoming increasingly maddening to read.

Do tell— how can you prove humans are any different?

The most common “proofs” I’ve seen:

“Humans are more complex”. Ok, so you’re implying we add more complexity (maybe more modalities?); if more complexity is added, will you continue to say “LLMs are just word predictors”?

“Humans are actually reasoning. LLMs are not.” Again, how would you measure such a thing?

“LLMs are confidently wrong .” How is this relevant ? And are humans not confidently wrong as well?

“LLMs are good at single functions, but they can’t understand a system.” This is simply a matter of increasing the context limit, is it not? And was there not a leaked OpenAI document showing a future offering of 64k tokens?

All that aside, I’m forever amazed how a seemingly forward-looking group of people is continually dismissive of a tool that came out LITERALLY 4 MONTHS AGO, with its latest iteration less than TWO WEEKS ago. For people familiar with stuff like Moore’s law, it’s absolutely wild to see how people act like LLM progress is forever tied to its current , apparently static, state.
A fair sized pause, sure. But if the argument is “Don’t throw it up unedited”, and what it provides me is bare bones generic/junior stuff, I’m not sure of the huge win at this point in time. The world wasn’t short of “Generic low grade copy” templates before LLMs. It just saves a few steps in the copy/paste.

Of course, GPT5…
I’m going to have to try that. I want to throw my computer out the window when I delete a folder in File Explorer and I get the “Preparing to delete” dialog come up. If I’m truly deleting and not recycling, what is it preparing?
It's just sad how absent AMD is from such innovative uses of GPUs. It wouldn't bother me too much if at least their GPUs were much more affordable than Nvidia's, but they're not. They're at best playing catch-up months or years later with slight price discounts (the Steam HW survey still reflects this market discrepancy)

And I'm not talking about gimmicks like RTX, I'm talking about all these cool use cases around ML and DL like background noise cancelling, video upscaling, camera eye contact real-time deepfakes and now this. And that's if you ignore all the mind-blowing research papers put out by Nvidia which aren't featured in consumer apps yet.

This is Nvidia's biggest moat and AMD isn't even in the race here and for some reason Lisa Su seems to not give enough of a shit to compete.

I hate Nvidia for their price gouging and anti-consumer practices, but at least they haven't gotten complacent and are innovating on all fronts to keep pushing the envelope. Massive respect for the tech leadership at Nvidia.
My personal experience mirrors yours. I remember when Swift announcement from Apple came that the main author of GNUStep (sorry I forgot the name) announced an open source impl the same day. My thoughts back then: „maybe make the last effort actually usable before jumping to the next big project“.

But I don‘t want to downplay the work and time put into this project. I would simply not use it in any project because of the number of compatibility bugs that haunts the project.

I used the project in production via Apportable’s crosscompile solution to port iOS native apps to android.
> real threat will be that lots of code will never be needed anymore.

That's a very good point.

Also, I am working in a very small team, developing a free app, for a nonprofit.

I will be suggesting to our CEO, that he consider ways to use AI to multiply the various things we need to do, in order to polish and launch the app.

We have a tiny, part-time team (except for Yours Truly), so there's a ton of "polishing the fenders" stuff that takes forever. I will suggest that he consider using ChatGPT (or some of the other engines) to do some of this work.
> It could also refuse their application or just tell them they won’t be accepted if they apply, like they did when Russia joined NATO partnership and wanted to become a member.

Russia never applied, they wanted to be special and be asked to apply, they where told that they would have to apply like everyone else.

And then never did.
I don't know. I've been using Copilot, ChatGPT, and Bing Chat intensively in the past month. So far I still think the metaphor "you can’t get to the Moon by piling up chairs" aged very well.

> A criticism that would make more sense would be something along the lines of "piling up colors you won't get you any closer to the Moon", since colors aren't even the right kind of thing, and you can't aggregate them in a way that gets you spatially closer. Because that at least does not concede the fundamental relationship of spatial traverseability.

No. I think you misunderstood what the chair metaphor is trying to say. It makes perfect sense, and if you replaced it with colors it would stop making sense.

"You can’t get to the Moon by piling up chairs" means that even chairs and rockets share some attributes (helping you get higher), the difference between them is still qualitative, not quantitve. The problem isn't "we don't have enough chairs."

"You can't get to the Moon by piling up colors" makes zero sense because colors and rockets share so few attributes and the metaphor falls flat.

Is it true for AI? I don't know, and at this point, anyone who claims they knows for sure, is lying. But I don't think my experience with ChatGTP (GPT4 included) and Bing Chat disputes it.
It’s gonna be tough as a junior dev in the near future. I’m very grateful that I managed to upskill so much before all this happens. In the worst case, I’ll have a crappy job directing and debugging AI output… but in the best case, we have reached AGI.
The failures don't refute the successes. Anything and anyone can fail, you don't get intelligent output by chance. If it makes mistakes we wouldn't make, on obvious things, it is because it is an alien form of intellingece.

RLHF and the tokenizer together explain many of the more common failure modes.
Russia doesn't need shells exploding early, or combat gear parts snapping under load.

And that's what Chinese steel does. Fail.

They've only been able to make ball point pens, with a proper round steel ball, for a decade!
"But where do you draw the line"

Well that's sort of the whole thing with copyright law. It's fairly arbitrary. Copyright specifically forbids derivative works:
"A derivative work is a work based on or derived from one or more already exist- ing works."

It's vague on purpose because copyright infringements generally need to be handled on a case by case basis.

Now there are AI's trained on images that are copyrighted. If the image is copyrighted, should the AI have been allowed to train on it?

The reason human training/inspiration isn't specifically forbidden is because it can't be. We are impressioned by things whether we like it or not. Regardless, we can't prove where someone's inspiration came from.

But the act of training an AI on copyrighted images is deliberate. I feel that's a key difference.
Of course not, but who is claiming that this happened? I'm not sure I can think of even single person who is both (i) an intelligent design advocate and (ii) explicitly committed to a symbolic model of human cognitive capacities. This seems like a straw man. You might as well say that at no point in evolutionary history did an embryologist ever write down a plan for the eight developmental stages of a human fetus.
App Store Xcode updates always take forever for god knows why. It’s almost as if there’s some nonlinear behavior in softwareupdated and co. that’s hit by Xcode with its gazillion little files.

Therefore I update Xcode by downloading the .xip from developer.apple.com/downloads.
We will become a leisure society. Honestly that sounds great to me.
Or they were just testing the waters and check the reaction to the decision, as companies often do.
Sending an email is work too.
Yes! The world where you end up in a random position with zero influence over the outcome if you could pick it before you were born is the one you should strive to create. That one has true equality.
What specifically is the most incorrect claim/belief Reich and Warren have? And why is it that banks don't fail in Canada?

"it's all the fault of [hyperbole] big businesses convincing the government to lift regulations". Well who else was lobbying govt to roll back banking regulations, in the 1990s?

Which lobbyists paid former Sen. Phil Gramm? Gramm's wife Wendy as CFTC chairwoman till 1993 issued regulations that legalized the type of electricity trading that helped Enron make millions in illegal profits. In 1993 joined Enron and ended up on its audit committee, where she approved all the shenanigans. She made $ out of Enron, while her husband was passing legislation to help it, and Enron lobbyists contributing to his campaign.

Phil Gramm ended up on the board of UBS, and a McCain adviser on the economy. Insanity.

"...if voters only gave them and their side the power." Start by ending the revolving door. That's not "giving their side the power".
> Real weight loss is caused by long term reduction of insulin levels

It's not 2009 anymore. We have these drugs now, GLP-1 agonists, which directly increase insulin secretion, yet they're known to also cause weight loss comparable to bariatric surgery:

https://en.wikipedia.org/wiki/Glucagon-like_peptide-1

>Alongside glucose-dependent insulinotropic peptide (GIP), GLP-1 is an incretin; thus, it has the ability to decrease blood sugar levels in a glucose-dependent manner by enhancing the secretion of insulin. Beside the insulinotropic effects, GLP-1 has been associated with numerous regulatory and protective effects. Unlike GIP, the action of GLP-1 is preserved in patients with type 2 diabetes and substantial pharmaceutical research has therefore been directed towards the development of GLP-1-based treatment

Your low-carb lunacy is long outdated. Go eat an apple.
Apparently Russia never formally applied for NATO membership like the other Eastern European countries because "Putin didn't want to wait in line":

https://www.theguardian.com/world/2021/nov/04/ex-nato-head-s...

This "Russia wanted to join NATO but was denied" argument is the same sort of half-truth revisionism like that "NATO promised to not expand east-ward" thing. What may have been "promised" in private conversations behind closed doors by people who most likely weren't even qualified to give such promises doesn't count much unless there's some sort of written agreement.

There is a formal agreement that Germany doesn't station foreign NATO troops in former East Germany. And guess what? There are no foreign NATO troops stationed in former East Germany to this day.
You don't need a seperate computer, flash projector still works fine if you want to play old flash games you've downloaded.
Another statistics that goes well with this:

Figure 3: After France, the United States is the biggest social spender when accounting for private social benefits and the impact of the tax system
From gross public to total net social spending, as % GDP in 2019

https://oecdstatistics.blog/2023/02/02/sizing-up-welfare-sta...
> That would point to higher-level phenomena going on inside ChatGPT and its ilk, than merely statistics and predictions.

No, it wouldn't, because nothing in "higher-level phenomena" precludes it being caused by statistics and predictions.
It doesn't have to kill Google. If it can force google to integrate expensive LLMs (compared to current search), it will impact search margins which is what all of Google depends on. If search stops printing money, it will have a drastic impact on Google, since Search subsidises tons of other not profitable ventures (even GCP is not profitable)

A company this size doesn't die easily though. Even IBM is still alive and making money.
I would have agreed with you had Russia accepted that it made a mistake. In the absence of something small as an acknowledgment and a formal apology (followed up by large monetary compensations for the victims’ families), it isn’t obvious to me how anytime can assume it was an accident.

The apology should have come immediately after the incident, without anyone asking for it.

It's not what happens to you, but how you react to it that matters. - Epictetus
Odd choice to do hardware design in scala...

I wasn't aware of any other big players doing this... I suspect it will limit the impact this project can have if industry can't adopt it easily into existing processes.
This is not unlike the magic of a Jupyter notebook except that you mostly just write the markdown and Chat does away with a lot of the tedium/boilerplate.

"Prompt engineering" ChatGPT English in this case is like a new higher order programming language. Prolog meets Ruby. A Haskell for mortals. No more counting parentheses or semicolons which turns away a lot of people from coding.

I guess that is magical, yeah.
You do realize that there is a systemd project and a systemd program. Is the plasma5 shell bloated because under the KDE umbrella there are hundreds of other projects?
I wonder, which instruction fusions are implemented, as it is key to high-performance RISC-V and the reason not to have conditional movs & alike in macro-ISA.

Unfortunately, documentation for Micro-ISA is in Chinese only :-(
I probably wouldn't be a programmer without ordering floppy disks full of random source code by post from software-by-post catalogues - one letter to ask for a catalogue, get the catalogue in the post, send them a letter with your order and a cheque and receive a bunch of disks a week later...
Building these AI systems is software engineering, not data science. In fact, data science may be one of the first engineering professions to go.
The wet bird (2000)
Mediocrity has never been so easy to achieve!
> By now, everyone has heard the explanation that ChatGPT is a transformer encoder-decoder that ...

Except it is wrong. GPT models are decoder-only transformers. See Andrej Karpathy's outstanding series on implementing a toy-scale GPT model.
If you're floating in mid air, and construct a ladder beneath you, you're still floating in mid air.
It's solved what I call my "45-year coding problem":

With GPT-4 I solved a problem in a completely new way that I had been iterating on for over a year, in a total of about 90 minutes.

I've tried to start coding (which I love) dozens of times over 45 years. By the time I was in my mid-twenties, I found it was always to use as a tool; I had a problem to solve, could it help?

Pre-Stack Overflow and internet, it wasn't efficient, because I kept running into time-consuming headwinds and had get the problem solved. End coding project.

Once Google Search got good, I was able to move a little farther forward, but still found it too time-consuming for any one problem. And in my attempts at coding, the farther I got, the more time-consuming the headwinds were. It's almost as if you need to spend many hours/week over several months learning so you can tackle more actual problems than sample problems. But I didn't know what I should be studying.
Aspirin can cause Reye’s syndrome but all the data I’ve seen seems to indicate more people die of paracetamol overdose than used to die from Reye’s.
I'm not going to claim I know where this is going right now with LLMs, but: throughout history, I don't think anyone really saw automation coming for their own jobs until it happened. I think people tend to think of their craft as an 'art' rather than a product. They miss that other people would MUCH prefer it to be automated, and that people will be willing to put up with slightly inferior output if it's practically free in comparison.
> . No thief is eating their way through a shipping container's worth of cereal.

Resell online or even on street.
I keep being reminded of Paul Graham's "plan for spam", in that he devised a simple statistical evaluator, and was surprised that it worked so well to distinguish ham from spam.

These AI tools have been trained on a great deal of written language artifacts and exhibit a surprising level of what appears to be concept understanding. Perhaps the real surprise is that language conveys concepts better than we previously thought?
This is the key point. The single unified market with 300+ million people speaking the same language is the advantage that will make all the other ones more or less irrelevant.
Completely agreed. Plenty of criticism focuses on specific algorithms or frameworks, as though there’s something inherent to LLMs that render them unable to improve in that regard.

Other objections, such as “if your job can be replaced by an algorithm, you weren’t particularly valuable in the first place” or “software development is much broader than writing code” are irrelevant to the question of whether a large portion of developers will be replaced.

I don’t think they will, given the world’s appetite for software, but it might become a less prestigious and lucrative profession on average.
Compiler macros are an example of something added to make built-in functions more efficient, but they aren't going as far as I'd like. I mean, SBCL doesn't use them for specializing built-ins based on type information; it uses its own nonstandard mechanism, defknown.

I've mentioned this before, but I'd really like to see Strandh's Call-site optimization implemented, so generic functions could be both highly locally optimizable, yet retain their dynamicity.
Money is debt. It is a relationship between people, not a thing made of matter. In that sense you could describe money as fictional, but certainly not useless.
I’m with you. I believe we haven’t even got started in exploring what you can do with the existing tools, let alone what new and improved ones we are about to get.

I can imagine LLMs becoming a UI in front of just about everything. Instead of googling the ffmpeg flags you need, you’ll just ask your terminal to walk you through it.
This is what I would call toxic positivity. Maybe with a side of survivor bias. Lots of people don’t get awesome new jobs. They struggle, they fall out of the workforce.

People don’t want to “accept” that’s some thing they have trained to do and gotten good at is going to just go away. It’s a reality, but it’s also pretty fucking awful.

My father used to make a very good living doing sign painting until the late 80s when vinyl signs became cheap and fast to make. They weren’t as good, they didn’t last as long, but they were cheap. And so his good living went away, and he spent the rest of his working years doing jobs that were not well paid. (The full story is more complicated, but the larger point stands.)
140 Megapixel Picture of the Sun
USA operates differently, securing profits and influence via different means.
This is part of China's effort to have its own IC industry. The project is now owned by BOSC, Beijing Open Source Chip Research Instiutute[1]

[1] https://www.bosc.ac.cn/yjyjs
Your theory is correct, but as usual, the difference between theory and practice is larger in practice than in theory.

When a workload runs out of RAM, it often really runs out of RAM, and would just be swapping continuously. It may even run out of swap space, if it was left to run for long enough. In my experience, even with NVMe drives, it just wasn't worth it because it usually wouldn't be able to finish in a reasonable amount of time. In part, I'm sure that's because the Linux kernel behaved much worse than is theoretically possible.

This may obviously depend on your workload, but I've heard similar sentiments from others (in fact, it was somebody else who suggested disabling swap to me based on their experience). The other point is that a sibling comment mentions some recent kernel changes that may have led to improvements, but I haven't given those a chance.
I said it here before and I will repeat it: Unless it solves the Abstraction and Reasoning Corpus — ARC (See: https://twitter.com/fchollet/status/1636054491480088823) you can not say that ChatGPT is able to think or abstract.
Every time you see a project with a rejected feature request, issue or patch, that's the project leader exercising their leadership.

Open Source means that if someone is determined enough, they can go do it for themselves. Sometimes that ends up with a viable alternative -- neovim, for instance -- and sometimes it demonstrates that a rejected feature was actually useful, and is folded back in to the original -- but most of the time it means a copy of the code base with one patch and one user. All of these are valuable in different ways.
(Update: China banned for-profit foreign tutoring 7/2021. But that still doesn't justify why DL locked their Chinese course, leaves lots of other countries where people want to learn Chinese.)
I disagree.

Taking copyrighted images and dumping them into a machine learning model is deliberate usage. The AI isn't a person, so it doesn't draw on past experience by happenstance.
The DNS issue here seems like you just wanted to use DNS like you had before despite the OS changing. That isn't really a bug, just a change in how the OS operates. If you don't want that, you can disable that feature.
The gap between AI “acceptance / exploration” and “AI dismissal” continues to widen.

Right now, the top post on HN is about how ChatGPT is “a glorified text prediction program.”

Right under that post is this post.
I do think this is a legitimate question.

The criterion for extraordinality seems often to be whether it contradicts someone's preconceptions. It seems precarious to apply different levels of scrutiny to claims based on such a basis.
>Of course, GPT5…

I'm not sure GPT5 will feel appreciably different on this type of task necessarily. GPT-4 feels a lot like GPT-3 for a pretty wide variety of things, but it's when you get higher complexity tasks that you start to see differences.
I might be wrong but I think it’s more of a "It’s obvious you don’t need to have fingers to build a hand that has fingers" than building a fingerless functional equivalent to a hand.