Yep, lots of opportunities for insiders to make money [1]. Particularly on things like product launch dates, when will it announce its IPO, which banks, etc.
> Juicing some streaming numbers hurt who? Spotify's margin?
You don't seem to understand how the streaming revenue model works, and why this is an egregious fraud against the public interest. You believe that stream fraud is someone simply stealing from Spotify/YouTube/etc, so who cares.
In reality, all musicians share a pool of revenue across ads + subscriptions on each platform (typically two-thirds of the total, although each platform has a different rev share model).
This fraud only marginally impacts Spotify financials, as their cut is fixed and taken from the topline [1]. But someone abusing the system like this guy breaks the model for everyone. Not only you're stealing money from millions of musicians, but you're undermining the confidence in the whole industry.
I don't have an opinion if this merits jail time or not, but yes, this is pretty bad. Like money counterfeiting-bad.
[1] ps: of course, if this becomes rampant, musicians get screwed and turn against Spotify, so it's in their best interest to do whatever it take down the fraudsters. It's a never-ending cat-and-mouse game.
As already discussed in other places in this article Spotify chose this model and could well choose one that cannot be abused this way. Why does it need protection by the criminal justice system.
What does it have to do with the crime at hand? Spotify is not asking for special protection. Someone defrauded thousands of musicians; it's the justice's job to step in and ensure markets operate fairly. This is working as intended.
Also, this is not (just) about Spotify; all streaming platforms have some sort of subscription and/or ad revshare, and were abused by the same fraudster.
Per the original case: "Music can be streamed through platforms such as Amazon Music, Apple Music, Spotify, and YouTube Music... SMITH created thousands of fraudulent accounts on the Streaming Platforms that he could use to stream songs".
In my opinion using an AI system to judge an AI system is perpetuating slop.
If you read the article and thought it was superficial, then say so. Constructive criticism is helpful for others, including the author. But simply copying and pasting from LLMs (including Pangram) is not much better than the the alleged slop you're implying in OP's submission.
More specifically, I read the article and felt it was a bit shallow, but still appropriate quick intro to Dr. Gruber and his work at Project CETI. A better link would be to Project CETI [1] directly.
I've seen a talk by Dr. Gruber and briefly spoke with him, and was mind-blown by what they're trying to accomplish. If they continue making progress, may be a decade or two away from achieving inter-species communication. Just think about it for a minute: if we manage to communicate with whales (or any other non-human species for that matter), we'd have massive philosophical, ethical, and even legal implications.
> using an AI system to judge an AI system is perpetuating slop
Yeah, this is just ignorance. I'm not against using AI systems.
https://rfd.shared.oxide.computer/rfd/0576 does a good job of summarizing the problem with AI writing specifically this part: "If, however, prose is LLM-generated, this social contract becomes ripped up: a reader cannot assume that the writer understands their ideas because they might not so much have read the product of the LLM that they tasked to write it. If one is lucky, these are LLM hallucinations: obviously wrong and quickly discarded. If one is unlucky, however, it will be a kind of LLM-induced cognitive dissonance: a puzzle in which pieces don’t fit because there is in fact no puzzle at all. This can leave a reader frustrated: why should they spend more time reading prose than the writer spent writing it?"
This is pretty sad. Seeing this a couple of years ago would be mind blowing. An impressive technical feat by someone with grit and resilience to painstakingly build this from scratch.
I had the exact same thought. I vibecoded a MOS6502 emulator a few months back in Rust. My Rust skill is weak, and I learned absolutely nothing about the 6502 or CPU design. Had I done it manually, there's also no way to prove I created it without LLM help making the whole exercise less appealing overall.
> there's also no way to prove I created it without LLM help
You don't need to prove it, that was never a requirement. You can simply say it. The only complication is that there's a fair number of people who, for some reason, really want to pass LLM output as their own. They are present on HN too. But here's another ancient trick to overcome that: reputation. Either the reputation you already have, or reputation you build over time. If you have a reputation as an honest person with genuine interest in software, you really don't have to worry, and you will have audience for your work.
I'm very grateful I have public pre-LLM projects I can point at (including a 6502 emulator!), and I have absolutely no idea how I'd go about bootstrapping the same kind of reputation starting from scratch.
Unfortunately few of us have such reputation to truck with. I think the reality is there is no point in showing off manually coded work any more. All that stuff is really left for self-edification, and increasingly so as AI becomes more capable.
> I think the reality is there is no point in showing off manually coded work any more
What was the point before? To have fun, build a community, and to get attention of hiring managers. The first two reasons are still there. The third is more questionable, but there's still plenty of companies that hire based on what you know, not how well you prompt.
Agreed. In the pre-LLM days, students always asked me how to "maximize" their hirability. The standard response was "have a passion project" and yeah, that did help people get hired in some ways. But the project was almost never the point of the demonstration. It was more to show that you are _the kind of person_ who sweats the details, who likes taking deep dives. For many of the best jobs, that's _still_ what they want; it's just now, a Github repository is no longer sufficient. That should not stop a passionate person from pursuing their passions.
LLM output should be credited to whoever prompted it. I don't get this hysteria. Llms are tools like compilers or chain saws. We don't say a cabinet made from milled wood is some how less authentic than a cabinet made with flint tools. We don't deny people who write compiled programs in a high level language without understanding every branch of the AST and every transistor setting authorship of their programs. Just because something is somewhat non deterministic and draws from the wealth of previously curated human knowledge does not make it an independent agent and not a tool. The people who find AI generated work 'sad' are implicitly sad about the democratization of knowledge and the lowering of barriers to entry to producing things. The thing produced is still a human product. Rather than saying it is an ai creation we can say it was author prompted and compiled of the combination of the author's intent and the store of human knowledge and reasoning trained into an LLM. What is there to be sad about a new tool existing to make things?
I used to think this, but I can ask an LLM to design me a CPU at this point while knowing absolutely nothing about how it works. Literally nothing. This is not the same as writing a program and handing it to a compiler. This is more like asking youtube to give you a video, then pretending you are Mr. Beast.
Thanks for making my point for me, although probably not in the way you intended.
The credit for the Doordash meal should be given to the person placing the order. If it weren't for their amazing prompting^Wordering skills, which can make food materialize out of thin air, we would not be eating today.
Yes an usually it is easy to tell one shot ai attempts vs careful or interatively regimes designs. Just because ai was used to execute and help generate the design in detail does not mean the human in the loop is not essential to the product.
"LLM output should be credited to whoever prompted it" promptly falls apart when you convert it to its pre-LLM equivalent "worker output should be credited to the manager who supervised it." These LLM bros are like bad managers trying to pretend the creativity, reasoning, and effort of their subordinates is actually their own just because they had the idea.
> Had I done it manually, there's also no way to prove I created it without LLM help
Of course there is -- ask you about it.
The coolest interview process i ever participated in (at MIT Lincoln Lab) was structured this way, and seems 100% LLM-proof. The interview was: give a talk about a cool/impressive technical thing you did for an hour and then answer questions from the interviewers about it for an hour. No way to succeed there without actually understanding.
>My Rust skill is weak, and I learned absolutely nothing about the 6502 or CPU design.
But you could have if you had have chosen to. Did you ask the AI what the slow parts were, and why?
Why did you want to emulate a 6502 in the first place? If you just wanted to run some 6502 code then that's ok, you didn't really need to know much about the 6502. If you wanted to know how much better it could be if it had an single register that was the high byte of zero page address accesses then you probably would have to be engaged enough to find out, and the AI would help you answer questions. You could try rearranging the lookup table at the bottom of the die to see if you could make your own instruction set that would perform better overall. AI would help with that too, but to direct it to do so you would have to be learning something.
Ok, I did learn a little bit about the 6502. I would have learned far more by implementing the emulator itself.
My actual goal was to understand if it was possible to build the equivalent of a rudimentary CPU inside of a living cell. At a high level, the 6502 shows me that most of the circuitry of the chip is not concerned with arithmetic, but rather orchestration and moving data.
Same problem actually exists when trying to map this concept to a cell... the lack of wiring makes this more difficult.
Yeah, the microcode ops are a pretty good demostration on how it is all just a sequence of connect-this-to-that with a bus for the this and fixed functions on all of the that.
I've build a similar project in university in two weeks with lisp, spending 30 minutes before bed on it. The difference being that it started with analogue voltages in the transistors.
I'm starting to think people impressed by LLMs are for the first time in their life not using a hammer on fastening screws and deeply impressed by tools that font fight them every step of the way.
Yup. I got excited for a bit, until I loaded the page and saw it was slop. I still would be impressed if someone actually took the time to learn about and implement it for themselves.
Yeah, and it seems they didn't even physically build it (which is most of the point of these retro projects), else where are the photos? So this is an emulation of a vibe coded processor. Couldn't they at least have added a three.js animation of bits flying around or something?!
Game console dev kits are typically _more_ expensive than the consoles they're for. So "full price" isn't a good argument. (The fact that they were available to the public is a stronger argument.)
Game console dev kits usually cost more than the consoles they're for, not less. They're not mass produced at the scale that the consoles are, and they're sold or leased to companies expecting to make several orders of magnitude more back off the products they create with the dev kits.
There isn't a very direct comparison of Oculus products to game consoles like PlayStation, Nintendo, XBox, or those in the distant past. It is interesting, and they have a lot of the same market forces at play, but I don't think they behave by the same rules.
[1] https://kalshi.com/search?q=openai
reply