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If the news reporter said "Someone at a park played this 4 minute copyrighted song, and today's top story is just us showing you the recording" I'd bet that would be illegal where you live.

I remarked upon distribution in a comment above

> however I might violate their copyright by reconstructing that poem and then distributing it

My argument is that the recording itself is not a copyright violation, not that distributing such a recording couldn't be construed as one (however I disagree on principle with that being illegal as well, as it puts an undue burden on the exercise of free speech, which should include the ability to accurately and entirely recite what I had experienced in a public place).


This reminds me of a stand up comedy routine about people being bad at hiding their porn collections because their brain doesn't work right when they are horny.

That’s harder hitting psychology in comedy than I’ve ever seen an example of the other way.

For me a basic test of A.I. creativity is give the A.I. chapter 1 of a novel it has not seen and ask it to write chapter 2, then compare the quality to the original author's chapter 2. The A.I. is always terrible at this in terms of matching the author's level of quality.

I would think that’s the opposite of creativity. Rather, I would label that as pattern matching and prediction capability.

Why box in creativity basically as the ability to mimic someone else who is creative? Why not choose something that better matches the definition of creativity (the ability to make new things, think of original ideas, or show imagination that is novel, useful, or pleasing)?

And even then, I am assuming the premise that the original novels are good and creative, especially chapter 2. Most novels are not very creative.

If it could make 5 different versions of chapter 2, all with different directions for the story, and all with novel and interesting developments, wouldn’t that be a better definition of creativity than “can it read chapter 1 and be able to copy style and deduce/predict what the author is going to do in chapter 2”?

And also, that’s only a subset of creativity (storytelling). I’ve met plenty of people who are terrible at writing and storytelling but can come up with the most impressive and novel solutions to a practical problem instantly.

Final thought: I have been following the development in the anime AI generation scene for a while now. It’s not even close to anything anyone would call creative or even OK quality. But it’s also massively impressive that it’s moving in that direction really fast. And if you watch enough, you are going to start to see some truly creative sparks. And some of the mainstream stuff that gets created and labeled as creative… really... How many isekai series with the same story have humans not made already?


> If it could make 5 different versions of chapter 2, all with different directions for the story, and all with novel and interesting developments, wouldn’t that be a better definition of creativity than “can it read chapter 1 and be able to copy style and deduce/predict what the author is going to do in chapter 2”?

If I like the novel, an alternative version where things happen differently would be fine.

The problem isn't that it's different. The problem is quality.

A lot of Isekai stories are crap but you can still rank them in terms of the author's ability or inability to have a creative POV that elevates the material.


I think “what I individually like” is a poor measurement of creativity, at least alone.

And yes you can rank quality. My point was that if you made two bell curves of the distribution quality and creativity of all new manga, The one for “AI slop manga” allready started overlapping with “normal human manga”.

That’s just a fancy way of saying the absolute best AI slop is at the level of the absolute worst human creation.

The interesting thing is that the AI slop curve clearly is moving to the right every month. Where it will stop tho, impossible to say.


Is chapter 1 of a novel really enough context to generate a chapter 2 of sufficient quality to match up to an author who spent a good amount of time planning out an entire story and whose manuscript probably went through a lot of revisions?

I don't necessarily just feed it chapter 1. (And chapter length varies between novels).

And no I don't think asking the A.I. to write the next 2000 words would require it to have the entire novel planned out. Not all writers even outline in advance.


Is anyone from 2016 still alive today?

If so I'm hoping we can track them down and have them tell us if they think this is AGI.


As someone who spent countless nights tweaking Edge Detectors (looking at you, Canny), morphology operators, etc., building models to recognize 10 handwritten digits, let me tell you: the current set of LLMs (even the smaller ones) seem like magic. I had never imagined a computer would do such things in my lifetime.

Exactly people can say whatever they want, but current level of LLM is AGI level to me. It is already on par with senior programmer if the instruction/prompt is right.

Once we have 1000 tps, i am sure robots etc.. will also start working like magic.


I don’t know, I am writing a modest 30 page paper with Fable and even after rounds and rounds of feedback and improvements there are so many things that are just plain wrong or weirdly out of place or just stupidly written that Fable 5.1 doesn’t seem to have any awareness of by itself that I don’t think it’s AGI, I think a human researcher can easily outclass it in writing and problem understanding. It definitely has super human capabilities but it lacks awareness or self reflection in my opinion.

For example it should be easy to tell it to not write a paper in the style of a clickbait SEO article or use all of its stupid hallmark AI writing patterns “it’s A, not B!” And a smart human that would be told that would be easily able to comply with that but the model needs to be told in a very detailed way and it seems to lack even basic capabilities to reflect on this, when explicitly given a sentence it will be able to rewrite it but otherwise it’s mostly blind to it. That’s to me a hallmark of it being overtrained on the specific tasks or problems so it appears very smart but once you go off script it still shows that it’s not a “real” mind.

Of course it’s amazing and has super human capabilities in many areas but if you honestly think it’s better than Einstein like some people suggest why can’t it write a simple “good” academic paper even after giving it specific examples and instructions.

Maybe that’s what makes these things dangerous, they have super human capabilities in some areas but apparently lack self awareness, taste and meta reflection abilities. The only reason people aren’t afraid more is that they don’t act in the physical world yet, imagine giving it a body, superhuman strength and letting it care for your child when it has a strong “urge” to comply with your exact request and little to no self awareness and human basic instincts.


100%

"You're absolutely right to call me out on that. I shouldn't have stopped the baby crying by killing it, that's on me."


>It is already on par with senior programmer if the instruction/prompt is right.

It's magical to me as well, but I don't feel like it's AGI.

Because in my experience a Senior Programmer does not need the right prompts to deliver the right outcome! :-)


Doesn’t the G stand for “general”?

An AI model that’s human-level at programming is an incredible achievement. But it isn’t general intelligence. It’s highly specified intelligence.


Though what has a program that is really really good at edge detection have to do with AGI? The community just spent decades to perfect edge detection. That's great! But let your edge detector try to fry an egg and then tell me again that it's AGI.

I'm still here, nearly 50 years and counting. If you had asked me what I imagined AGI would look like back in the 90's, I would have told you "A system that can do everything we can: see, hear, think, do.". If you had shown me GPT-6 back then, I would have said "It looks like a really powerful program, but that's not really what I had in mind.". That's AI, but it's not quite general.

And then you'd ask it about an area you're knowledgeable in and realise it routinely makes stupid mistakes.

Or you'd ask it to add a new page to your website and shout at it to use your existing brand colours instead of inventing some and realise it's not AGI at all...


> And then you'd ask it about an area you're knowledgeable in and realise it routinely makes stupid mistakes.

This honestly doesn’t happen to me much anymore. In what areas do you find LLMs routinely make stupid mistakes?


Origami design will be my personal test bed for the coming years.

It's objectively very difficult and technical, it's spatiovisual, it's artistic, learning resources for it are sparse and most just learn by the FAFO method, current AI sucks terribly at it, and it's not likely to ever be specifically targeted by benchmaxxers.


In the last day of coding it has:

- Created useless pydantic schemas with all fields Optional[Any]

- Created a REST endpoint that silently mutated on GET (unsubscribed users from a mailing list)

- Failed to log costs in my app so users could have bankrupted me, etc, etc.

Good job I actually review its code.


It's really bad at game design

Scientifically useful physics simulations. Every model absolutely sucks at them.

Or, as someone else points out in another thread here, academic writing. It's one of the things newer models seem to have actually gotten worse at. Even when you give them detailed instructions on how to write and what to avoid, the "load-bearing", "A but not B" and journal-like writing make it in anyway, with the supposed AGI having no ability to reflect on how blatantly unacademic (and often unreadable) its writing is.


Likewise, it's very impressive and useful, but it is obviously not AGI to those of us from that era.

If anything, the fact that it is so powerful is almost a concern, because I think we are still way underestimating what these systems will be able to do when we give them more cognitive capabilities.

At the moment we are something like, having had great success with propellers and have promised we will fly to the stars.

People love to say 'this is the worse they will ever be', then extrapolate to conclusion that they will continue to accelerate at the same rate of progress of last few years .. it may, maybe, or we will hit a ceiling, might be a temporary one, could be 5 years or 50 years ..


Anyone that is not impressed by what ChatGPT or the likes are doing now is being either dishonest or is incapable of being impressed.

Only the translation and language understanding capabilities are enough to be impressed, and they are 2 year old already. Now, the AI do see, draw, speak, listen, think, work, etc.

Someone from the 90's would simply not believe that the AI would be a machine but would think for sure that a human is behind. The only odd thing would be that this human would both exhibit high intelligence and stupidity at the same time.


Compared to what we had in 2016 with RNNs, this is effectively “AGI”

OK, so its way better. that doesn't make it AGI.

If I can't give it an arbitrary task and have it solve that task eventually, it's not a general intelligence.


Are you guaranteed to solve an arbitrary task eventually?

I believe so. AIs are shockingly good at a lot of domains, but there's still a lot of pretty basic stuff they don't really "understand" at a conceptual level and (currently) they can't learn to get better at them.

(obviously it might take years for me to get good enough at something, or if you set the "arbitrary" task as something ridiculous, but lets work in good faith here and think of something the average human could do after learning about it)

If we progress to the point where an LLM instance can meaningfully learn to get better at something overtime without retraining, then I will accept that is basically AGI. Right now, they still seem to be pretty boxed into their training, even if you can prompt them to act differently.


Compared to 2016, it can do a lot of things, but it still fails for example with recommending a setup for my Raspberry Pi to have a 4G connection with some parameters (I want to use as a gateway between VoLTE calls and SMS, and my SIP server somewhere else). It failed miserably. I bought stuff according to its recommendation which was more or less a waste of money, twice. With miniscule knowledge compared to theirs, or even hobbyists', I could figure out all the details at the end, and order something which really works, but only after I sit down for 4 hours, and dig through exactly what I needed, because LLM lied flat out what Sixfab 3G/4G HAT can do. (Of course, not just LLMs lie, SixFab lied about something else too)

Of course, it's a moving goal post, because we have no clue what general intelligence is exactly. But it's definitely not general yet. Now the goalpost is to achieve that kind of level of thinking which I did in that 4 hours. When it reaches it, we will find something else it clearly lacks. Until we can't. Then, and only then we reached AGI. Until you see comments, reviews, etc about things which it cannot do, until then it's not general.


You are worried about bias but judge an author on whether they use X or Bluesky?


You can find the full picture elsewhere.

Futurism is a known source of easy to correct misinformation


The U.S. government wouldn't need to use bombs they could just send in the police.


Or ICE.

Half of the employees deported and a few shot dead just for good measures should be enough to bring Dario to the negotiations table.


From what I recall Zune had a much bigger screen for videos so I bought one for that reason you can see the side by side here:

https://electronics.howstuffworks.com/zune-ipod.htm


I had to hunt this, but the classic design perspective of the ipod vs zune by Joel

https://youtu.be/e-blUcmpW1s?list=PLcIkt5s7w8D0ywp0CBmNFWRTF...

At the end of the day Apple got design and Microsoft didn't and it showed in their sales.


> Their doctor should be qualified to make that judgment without a government bureaucracy

This is like saying AI developers should be qualified to evaluate the effacy of a model without testing the model.


This is funny because the stock Market has been ahistorically high. My portfolio went up over 20 percent in the last 12 months.

A major correction would be a bummer but we were never entitled to these abnormal gains in the first place.


It’s not as bad as dot.com of course since all purely AI companies are private and the ones on the market have pretty decent cash flow outside of AI. But the stock market pattern is not that dissimilar, the largest increases are usually just before the crash.


Yeah the last year has been astonishing, my portfolio is kicking ass. But I'm 10 years out from retirement and I am pretty confident a correction is coming; I hope the correction happens soon.


This comment thread was started with discussions of AI doing a bad job at a task (communication).

Doesn't the Chinese Room posit an AI good at the task of communication?


AIs are better communicators that most of people I have worked with in my life.

They are infinitely patient, don't mind going into more detail if I ask, not too bad at summary, have no ego and don't boast. They are also not too afraid of hurting my feelings, they will tell me my code sux if it does.

I'd don't care if they fit a definition intelligent, they are good colleagues. They have strengths and weaknesses sure, but so do people.


> have no ego and don't boast

Yes they do, and they famously do it quite a lot.

> they will tell me my code sux if it does

If they knew when code sux, someone should write an agentic loop around that.


The Chinese Room mainly just posits a room that passes the Turing Test, which LLMs do pretty well outside of outright adversarial situations.


Do they? https://longbets.org/1/ has yet to be settled. Either way, I doubt an LLM could fool anyone here who who knows how LLMs work into thinking it is human, at least not for an extended period of time (think about context length/compression, prompt injections, …).


You'll notice those goalposts are substantially stretched from the original test.


How so?


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