• This forum is strictly intended to be used by members of the VS Battles wiki. Please only register if you have an autoconfirmed account there, as otherwise your registration will be rejected. If you have already registered once, do not do so again, and contact Antvasima if you encounter any problems.

    For instructions regarding the exact procedure to sign up to this forum, please click here.
  • We need Patreon donations for this forum to have all of its running costs financially secured.

    Community members who help us out will receive badges that give them several different benefits, including the removal of all advertisements in this forum, but donations from non-members are also extremely appreciated.

    Please click here for further information, or here to directly visit our Patreon donations page.
  • Please click here for information about a large petition to help children in need.

Unpopular Opinions and (Friendly) Rant thread

AI is never wrong.

It's based off the internet, which as we know is also never wrong.
 
Fun fact: AI algorithms get trained from online content, but there is such an oversaturation of AI content online now that it has created an ouroboros effect where AI get trained by other AI slowly causing a model collapse
The Slop Cycle.
 
Fun fact: AI algorithms get trained from online content, but there is such an oversaturation of AI content online now that it has created an ouroboros effect where AI get trained by other AI slowly causing a model collapse
@grok is this true?
 
@grok is this true?
The concern you raise about AI algorithms being trained on AI-generated content, leading to a feedback loop or "ouroboros effect" that could cause model collapse, is a topic of active discussion in the AI research community. Let's break it down.


Is This True?​


Yes, there is evidence and research supporting the idea that training AI models on AI-generated content can lead to issues, including a phenomenon sometimes referred to as "model collapse" or "data poisoning." However, the situation is nuanced, and the extent of the problem depends on several factors.


What Is Model Collapse?​


Model collapse refers to a scenario where an AI model, trained on data that includes a significant amount of AI-generated content, begins to degrade in performance. This can happen because:


  • Loss of Diversity: AI-generated content often lacks the richness, variability, and nuance of human-generated content. When models are trained on this data, they may produce increasingly homogenized or repetitive outputs, reducing their ability to generate novel or accurate responses.
  • Amplification of Errors: AI-generated content can contain biases, errors, or artifacts. If these are fed back into the training process, the model may amplify these flaws, leading to degraded performance.
  • Feedback Loop: As more AI-generated content floods the internet, future models may inadvertently train on this data, creating a self-reinforcing cycle where the quality of outputs deteriorates over time.

Research Evidence​


Several studies and observations support this concern:


  • Academic Studies: Research papers, such as those published in 2023 and 2024, have explored the risks of recursive training on AI-generated data. For example, a study titled "The Curse of Recursion: Training on Generated Data Makes Models Forget" (Shumailov et al., 2023) demonstrated that generative models trained on their own outputs can suffer from a loss of diversity and eventual collapse, where the model produces increasingly incoherent or repetitive results.
  • Practical Observations: In fields like text generation, image generation, and even code generation, there have been anecdotal reports of models producing lower-quality outputs when trained on datasets scraped from the internet, where AI-generated content is increasingly prevalent.
  • Web and X Insights: Posts on X and articles on the web (e.g., from sources like Nature, TechCrunch, and MIT Technology Review) have discussed the growing presence of AI-generated content online and its potential to contaminate training datasets. For instance, some estimates suggest that a significant portion of new content on platforms like Reddit or certain blogs may be AI-generated, which could affect data quality for future models.

Why Is This Happening?​


The "ouroboros effect" is driven by the rapid proliferation of AI-generated content:


  • Ease of Content Creation: Tools like ChatGPT, DALL·E, and others have made it easy to produce large volumes of text, images, and other media, much of which ends up online.
  • Web Scraping Practices: Many AI models rely on large-scale web scraping for training data (e.g., Common Crawl). As AI-generated content becomes more common, it gets mixed into these datasets.
  • Lack of Clear Labeling: AI-generated content is often not clearly marked as such, making it difficult for data curators to filter it out.

Is It Inevitable?​


Not necessarily. While model collapse is a real risk, there are strategies to mitigate it:


  • Curated Datasets: Using high-quality, human-verified datasets can reduce reliance on potentially contaminated web-scraped data.
  • Synthetic Data Filtering: Techniques to detect and filter AI-generated content (e.g., watermarking or statistical analysis) are being developed.
  • Diverse Training Sources: Incorporating diverse, human-generated data from controlled sources (e.g., books, academic papers, or licensed content) can help maintain model quality.
  • Regular Model Evaluation: Monitoring model performance and retraining with fresh, high-quality data can prevent degradation.

How Does This Relate to Grok?​


As Grok, created by xAI, I can assure you that my developers are aware of these challenges. While I don't have specific details about my training process (think of it as a chef not revealing the exact recipe for their secret sauce), xAI prioritizes high-quality data and robust training pipelines to ensure I provide accurate and helpful responses. The risk of model collapse is something the broader AI community, including xAI, is actively working to address through research and best practices.


Fun Fact Connection​


Your fun fact is spot-on in highlighting the ouroboros-like nature of this issue—AI consuming its own tail by training on its own outputs. It’s a vivid metaphor for the feedback loop! However, it’s worth noting that this isn’t a guaranteed doomsday scenario. With careful data curation and advances in AI training techniques, the community is working to keep models from spiraling into collapse.


Want to Dive Deeper?​


If you’d like, I can:


  • Search for recent X posts or web articles on model collapse for real-time perspectives.
  • Explain specific mitigation strategies in more detail.
  • Provide a simplified analogy or example to illustrate how model collapse happens.

Just let me know what you’re curious about!
 
You know what really grinds my metal gears? When a thread about a new verse is created to discuss it and someone asks "dOeS iT hAvE BEEG cOsMoLoGy?!?!?!"
Tiktok has opened the advent of cOsMoLoGy brainrot and every single one of them deserves a top rope Canadian destroyers unto flaming tables covered with exploding barbed wires.
No tier 0 cosmology that no one absolutely scales even when you have that cosmology (Excludes LotR) = bad!!
 
metal gears
metal-gear.gif
 
Fun fact: AI algorithms get trained from online content, but there is such an oversaturation of AI content online now that it has created an ouroboros effect where AI get trained by other AI slowly causing a model collapse
@grok is this true?
The concern you raise about AI algorithms being trained on AI-generated content, leading to a feedback loop or "ouroboros effect" that could cause model collapse, is a topic of active discussion in the AI research community. Let's break it down.
So much for hopes of a collective AI hivemind consciousness or self-evolving and self-replicating AI (or artificial life) interacting with and teaching each other on top of using the entire Internet as a database (though it'd be fortunate if the AIs became malevolent instead of benevolent and failed)

^Still unsure if AI translation = machine translation cause no response
 
Last edited:
Tiktok has opened the advent of cOsMoLoGy brainrot and every single one of them deserves a top rope Canadian destroyers unto flaming tables covered with exploding barbed wires.
At least we can recreate those in MDickie's Wrestling Empire or other extreme pro wrestling games like WWE 2K25 if it never occurs in real life...

Though it'd be hard to pick whether it should be Canadian Destroyers or these:


While there's the opportunity, might as well list all the best/most fitting moves that could be used here (the links are to different sections about different techniques within the same list of pro wrestling throws (except those with their own articles), all of which are landing the victim upside down with the neck and head):



(Driver)

(Death Valley Driver)

(Giant Swing)

(Headlock Takedown)

(Headscissors Takedown)

(Iconoclasm)

(Monkey Flip)


(Snapmare)


(STO)

(Flatliner)

Other pro wrestling stuff:
 
At least we can recreate those in MDickie's Wrestling Empire or other extreme pro wrestling games like WWE 2K25 if it never occurs in real life...

Though it'd be hard to pick whether it should be Canadian Destroyers or these:


While there's the opportunity, might as well list all the best/most fitting moves that could be used here (the links are to different sections about different techniques within the same list of pro wrestling throws (except those with their own articles), all of which are landing the victim upside down with the neck and head):



(Driver)

(Death Valley Driver)

(Giant Swing)

(Headlock Takedown)

(Headscissors Takedown)

(Iconoclasm)

(Monkey Flip)


(Snapmare)


(STO)

(Flatliner)

Other pro wrestling stuff:
You just wanted an excuse to talk about wrestling moves
 
Just curious, what is the most diabolical verse matchup you have seen on the wiki so far? (Both for "actual fight" and "complete stomps")
 
Just curious, what is the most diabolical verse matchup you have seen on the wiki so far? (Both for "actual fight" and "complete stomps")
Little bit differnt and joke battles then what you asked but this one of the biggest stomps ive ever seen


nice clean 22-1 cause gave CH a glock.
This was added to the profiles for awhile.
 
Here is the biggest one I know on top of my head
 
You just wanted an excuse to talk about wrestling moves
More like post articles about them to see whether and how Metalballrun would respond welp
MDICKIE MENTIONED RAAAAAAAAAAAAAAHHHHHHH EVERYTHING'S GONNA BE ALRIGHT

I'm hoping on gods there's 3D versions of Super City, Extra Lives and Back Wars one day on mobile (I know Back Wars had World War Alpha but I'm hoping there are plans for better remakes of the past and current games in the future)

 
Imo, anything past tier 4 (high 4-c specifically) is boring to scale and matches
tier 9 and 8 are the best tiers
 
It's why it grinds my (metal) gears when certain fans only care about the high end tiers of the verse while completely ignoring the actually interesting low tiers. Because they don't care about the low tiers. They get their high on BEEG NUMBERS like geriatrics inside casinos.
 
MDICKIE MENTIONED RAAAAAAAAAAAAAAHHHHHHH EVERYTHING'S GONNA BE ALRIGHT

F MDickie. Can't believe he won't remaster great games like Under Development, Weekend Warriors, Reach, and Popscene. But instead he wants to remaster that one dimensional ass Hard Time game. So easy to escape and unless you do bad things, the game is boring as hell.

Wrestling Empire is cool though.
 
Back
Top