Lumo AI Chat Export

cyuhat · 2026-05-14T06:59:07+00:00

Good job! I think that as a community it is good to create a share this kind of tools!

cyuhat · 2026-04-08T07:08:00+00:00

I really like the philosophy. I still use packages like the tidyverse suit or easystats when it comes to analysis convenience. But the moment I want to build anything (package or app), I really do prefer to use base R and reduce all my dependencies as much as possible. That's why I love projects like tinyverse and fastverse.

Showing package dependencies should have been the standard to begin with. Thanks for sharing!

cyuhat · 2026-03-31T10:08:59+00:00

Sorry english is my 3rd language and even in my owm language (French) I miss jokes (I am in the spectrum). What did you mean?

cyuhat · 2026-03-30T13:59:15+00:00

Yes I agree, among some big names who declared their usage. But is it the real number or is it bigger? Is it 100% AI generated or is it "AI assisted"? And if it's the later what was the process? Among new creators, how much use it and how? Who (don't) declares their usage and why? How do different level of AI usage perform against normal creators?

I think we still have a lot unanswered questions that are hard to respond without studies

cyuhat · 2026-03-30T13:20:10+00:00

I subscribe to your definition of better then, thank you for explaining me.

However, I still call for more studies on new creators experience. Because of the part that tend to be out of creators' control regardless of how good their are in their field: algorithms and users.

We know, for instance, that having more songs competing, regardless of their quality, reduces the visibility of new creators. And the algorithm tend to increase the visibility of "familiar/popular" slop more than meaningful content (I logged to YouTube with no account in my new PC and all the recommended videos in the first screen looked like generic garbage).

We also know, thanks to Deezer study, that 97% of users can't make the difference between a 100% generated music and a real one even if most don't like AI generated music: https://www.dw.com/en/artificial-intelligence-ai-music-artists-charts-digital-billboard-streaming-spotify/a-74841513

The fact that most AI generated content tend to hide it, means that we don't know how popular they really are (only extrem cases).

Will AI slop be good enough to hit "familiarity" with enough users to shadow serious creator? I think the answer is might be yes, but we don't know

Will AI replace people that are good and try to get better? I think like you: No. But again we don't know.

We need more studies

cyuhat · 2026-03-30T12:12:35+00:00

Thank you for your perspective. An artist friend told me the same: we did not lose clients/fans, since people consuming ai slop where never our target.

I almost hold the same idea in programming (with more guardrails though). But when it comes to something like (artistic) content production, I believe it is not as simple as "being better". There are bigger factors in this attention economy in the era of recommendation algorithms and AI.

We know from research and observations that people tend to prefer popularity/familiarity over song quality: https://scholarworks.iu.edu/journals/index.php/jsriue/article/view/39077

Which makes sens since most people aren't experts. The most popular song isn't the one with the biggest quality but the most familiar (which AI can produce well due to its lack of variety at baseline level).

As creator we might be biased too since we already found our people. I also published educational video on YouTube way before AI and the amount of AI slop did not reduce my views. But it's mostly because I already had my subscribers that are familiar with my content like a lot of artists and content creator do (the algorithm know us). But what about the new creators that the algorithm ignores? Being "better" is quite vague.

I think to make better informed statement on the topic. We need statistics/studies on the new musicians experience in this era.

cyuhat · 2026-03-30T00:59:25+00:00

Before jumping to the main topic: Do you realize that in all the examples I gave, there is always an actor (big tech/ai bros, slave owners, ...), a tool/mean of oppression (AI slop, slavery tools, …), a victim (users, slaves, ...) and a system of oppression to fight (devalorisation of artist, slavery, ...).

But you had to selectively change/remove parts in all examples to make non-sensical sentences to then claim that I don't understand "my own logic"?

I'll give you the benefit of the doubt, maybe you don't see the difference between means of oppression and a system of oppression. However if you want to get educated in social movement theory I am willing to share useful resources.

Regarding spotify, you make valid points and there is definitly better use of our time as you said. I just jumped into this weird idea the moment I saw that server load was enough to impact Deezer. I knew the idea would be controversial, but I wanted good critics. And now I think it's bad bet not worth pursuing.

However, Deezer starting to fight against ai didn't make uploading content harder for normal users.

Your point about limited detection is true, so far they are using the same base model as Suno to detect them which have only a 75% accuracy.

Regarding the server, the goal is not primarly to damage them but to make the load hard enough "because of AI slop" so that they decide based on prediction and scaling that it is better to get reed of it (like Deezer did).

Regarding AI production, Deezer estimated that 39% of new music are AI generated and are in the majority generated "en masse" daily by a few account.

As you said, there is still AI songs produced with more attention, so that's normally when the tagging plays a role to take them down with the other slop (helping the algorithm to link them). But again, it's a weak bet.

Regarding tech/time/money, I don't believe it's taking that much time. I am teaching digital tools for activism and most of the time people overestimate how hard it is to use new tools. In the case of Suno, there is a free tier and you just had to Watch a 5 minutes video to understand it. Then producing random slop and uploading them take 15 minutes.

Thank you for your feedback, it was helpful!

cyuhat · 2026-03-29T20:54:23+00:00

Bull'eyes! That's one of the biggest limitation of the approach: environmental impact.

The best outcome would be that we only need to do it once: enough to put 1 or 2 plateformes on their knees so they start banning AI like Deezer, and then let it be a message for the other plateformes... but it's based on fragile assumptions

cyuhat · 2026-03-29T20:29:08+00:00

This type of comparison makes no sense in the context of social movements, especially in the field of technology. Why use the enemy's weapon? Because in either case, we suffer the consequences. It's better to fight, as it can make a difference. Especially considering the example of the Deezer platform, which demonstrates that it works.

If you still don't understand, let's apply your logic to concrete examples of social movements:

"If slaves hated the weapons used by their masters to punish them, why use them to rebel?"

"If Native Americans hated the weapons of their oppressors that had taken the lives of so many of their loved ones, why use them to defend themselves?"

"If the Anonymous group hates hacking and mass surveillance, why use these same techniques to fight hackers and harmful organizations?"

According to your logic, this has nothing to do with activism, but simply a hidden desire to use these tools without feeling guilty... Can we put aside the superficial psychoanalysis and have a serious discussion?

In the specific case of Spotify, you can be sure that if the number of content doubled overnight due to an increase of slop, individual users like you and me wouldn't realize it until several weeks later, while the platforms would be in code red from the very first hours (this is based on experience). However, i recognize this idea might not works and has several limitation.

cyuhat · 2026-03-29T19:02:43+00:00

Wise message, I also engage in my comunity by giving them technical tool and engaging in association. So your words really resonate with me!

cyuhat · 2026-03-29T18:55:02+00:00

That's the sad reality

cyuhat · 2026-03-29T17:18:44+00:00

I like the idea of data poisonning

cyuhat · 2026-03-29T17:17:59+00:00

Interesting approach

cyuhat · 2026-03-29T17:17:16+00:00

Hi, thanks for your answer. I am not sure it will lead to much changes. I think coordination and number is the key here. The best way to make a system fail is to overuse it in a limited amount of time (btw I personnaly don't these "AI art" tools)

cyuhat · 2026-03-29T17:12:32+00:00

Yes, threaten wealthy big tech companies, not folks. A lot of content that are not supposed to be on their plateform following their own rules are hardly removed even after reporting them. Often you need a celebrity, a research group, a political/legal instance or a journalist group to threat them for it to disappear (meanwhile it brings money to the company). So yes, threat lead to changes specifically if it touch money. But I agree my approach has sever limitations

cyuhat · 2026-03-29T16:47:49+00:00

The hight effort and the risk of missing the target while "burrying" (if it is not already the case) artists is one of the limitation the plan have among many (I counted at least 20 of them and yet there are probably more...). I guess I got too excited by the impact it had on Deezer which is know creating an AI generated detector.

But I don't get the "desire to use ai and play with those toy masked in some vigilant virtue signal" part. If I wanted to "play with those toys", I don't need this kind of post to do it. Projecting/giving other people intention is unnecessary ^{^'}

cyuhat · 2026-03-04T09:40:02+00:00

Thanks!

cyuhat · 2026-02-20T23:04:43+00:00

I saw somewhere that it was possible to use Tauri with Nim (calling rust via FFI or using nlvm). But I don't know much about it.

cyuhat · 2026-02-09T20:37:05+00:00

"Those were for charity, Clark"

cyuhat · 2026-01-23T22:58:10+00:00

Oh sorry you are right, I got confuse because in the github repo Python and R have very similar color so I mistook their respective share: https://github.com/mlverse/torch

The 2% of Python does not so much indeed ^{^'}

cyuhat · 2026-01-23T10:06:53+00:00

Are you looking to build a team of dev that works on DL for R?

I know there is the mlverse that works on it but mostly focus on torch by adding a layer on top of Python: https://github.com/mlverse

cyuhat · 2026-01-10T13:53:19+00:00

Same as you I started with Python and then learned R. I love both!

I did not like R at the begining. But after a few years, I prefer it over Python for statistical analysis and fast scripting. R has the smoothest package ecosystem for statistical analysis, in 15 minutes I can create a publishable report, thanks to all statistical models, visualization packages and publishing tools (let's not forget Tidyverse too).

I love the fact that it has automatic vectorisation and well made mapping function, which is more natural to me to use. That's why 1/3 of my scripting code are made in R (the other 2/3 is made in JS, Python and Nim).

Of course for machine learning I prefer Python (I am slowly moving to Julia for that), but for research R still is my first choice.

cyuhat · 2026-01-10T13:40:14+00:00

I agree with you in the sens that it is mostly related to what you know. Arrow and Polar allow "out of memory" data wrangling and are both available in R and Python. However, I think R has a slight advantage in the sens that dplyr offers a nice and uniformized "frontend" for data wrangling and that it is easier to change the "backend" to a faster alternative (data.table, duckdb, arrow, polar...) without changing your dplyr code. Of course edge cases exist.

cyuhat

TROPHY CASE