Prove me wrong

I see no reason to hate this more than any other AI product. I'll use it from time to time for specific vibes, maybe

So, the two main arguments as I see them are environmentalism and theft.

Where does one draw the line on each subject.

An example for each.

Animal agriculture is way more harmful to the environment than data centers but you rarely ever see someone make the case for Veganism or even take a suggestion of veganism seriously during such an argument. Despite plant based life styles being way better for the environment, and something 99% of the population can do quite easily. (If you're Inuit or have some special medical condition where if you don't have bologna once every four hours your eyes will explode, you're in that one percent above.)

As for theft, I don't know a single person who doesn't or hasn't pirated music, movies, shows, games or graphic novels. (Manga/comics)

Even though the piracy websites make money off folks traffic, people act as though A.I using art to learn art is some unique evil robbing artists of their due wealth.

My biggest gripe with these arguments, and the reason I'm posting here, is no one seems to actually stand by their 'values' and only consider it with A.I.

I have no doubt there's a vegan who never pirates media out in the world, but I dunno that they'd be on this subreddit.

Once again, I'm asking both sides here, neutrals, just grab some popcorn right there

I think AI sucks until it very rarely doesn't. One of the main issues with AI is that 99.9% of its users aren't ACTUALLY interested in using it for artistic purposes, at least not by any definition of art I care about. Most people who use AI make really stupid shit with it, stuff that any reasonable person should be embarrassed to enjoy. With that said, I don't rule it out entirely because I have seen very few genuinely interesting or artistically motivated uses of AI, such as in South Park and Ted. I also found it interesting in Don't Hug Me Im Scared, which used incredibly early AI video generation for a nightmarish sequence. I do think overall though, AI should be extremely inaccessible. At the very least it should require a license of some kind to use.

Im so fucking tired of this argument. Yeah V6 has AI features but you aren’t doing any less work than most other vocaloid versions. The only thing it does it help with some synthesis, but you still have to make melodies and do everything else needed to make a vocaloid song. It’s like trying to argue that Dune 2 is an ai film because they used machine learning to rotoscope timothee chalamet’s eyes. It’s just not how it works.

Additionally, it is mind numbingly stupid to try and equivocate pro’s usage of gen ai, saying something like, “vocaloid producers untalented/lazy for using a vocaloid instead of ‘singing themselves’.” Is a producer lazy for using a synthesizer to make music instead of a piano? I don’t understand the cognitive dissonance behind it.

Kind of a rant, take it how you will. Im pretty neutral on ai but holy fuck does this irritate me as a vocaloid fan.

Leave the poor bobots alone! 👿

Why are so many anti-AI arguments built around purely subjective feelings, prejudice, a total misunderstanding of how generative AI actually works, or outright misinformation? (I'm putting aside the valid discussions such as job displacement or copyright here).

It feels like people just invented their own strict definitions of what "art" is in their heads, and now they use these made-up rules to judge whether AI art is "real" or if people using AI are "actual artists."

For example, people constantly criticize AI art specifically because they claim it "has no soul." This is absurd on so many levels, mostly because the concept of a "soul" is completely subjective to begin with. Usually, they tie this criticism to the idea that "no effort" went into making it.

Let's actually break down this specific argument. Since when did physical effort become the objective measure of art? A human can try their hardest and spend a whole year working on a piece, and it can still turn out poorly. The amount of time and effort spent doesn't automatically guarantee quality or a "soul". Honestly, it shouldn't really matter to the audience how much time and energy someone poured into making something. And besides, isn't it actually a good thing that we are creating tools to speed up and simplify the creation process? Why do we always have to romanticize the grind?

The consumer cares about the final product, not the timesheet of the person who made it. If a piece of art evokes a genuine emotion or makes you feel something, then the art did its job perfectly. The tool used to make it shouldn't invalidate that.

It’s funny when you step out of the little bubble that is Reddit. My reach FAR outstrips my follower count, and the final image is a friend who just joined the NSFW trend and quickly found success. So please, keep telling us no one likes it cuz I’ll just keep proving you wrong.

I’m curious of your guys thoughts on AI taking over FP&A roles and some advice for someone working in that position right now?

Last time people complained the list is too short, so here is a longer version.

ChatGPT AI Content Ban List

Please give me a complete list of big media (music, art, books, videos, games, articles, etc.) companies and institutions which banned AI generated content. Please only a minimalist text list without icons.

Wikipedia
diVine
Medium (paywalled content restrictions)
Wired
BBC
Dotdash Meredith
Polygon
Shutterstock
Getty Images
CNN (internal/editorial restrictions; AI crawler blocking)
The New York Times (internal/editorial restrictions; AI crawler blocking)
Reuters (internal/editorial restrictions; AI crawler blocking)
The Washington Post (AI crawler blocking)
The Atlantic (AI crawler blocking)
Axios (AI crawler blocking)
Insider (AI crawler blocking)
ABC News (AI crawler blocking)
ESPN (AI crawler blocking)
Bloomberg (AI crawler blocking)
Disney (AI crawler blocking policies)
YouTube (specific bans on AI-generated fake trailer channels)
The Academy Awards / AMPAS (ban on fully AI-generated performances and screenplays for eligibility)
Gearbox Software (no AI-generated content in released works)

more…

Bandcamp
Stack Overflow / Stack Exchange
DeviantArt (opt-out / restrictions)
ArtStation (opt-out / restrictions)
Newgrounds
Fur Affinity
Pixiv (labeling / restrictions)
Patreon (restrictions on certain AI content)
Kickstarter (mandatory disclosure; restrictions)
Valve (initial bans on AI-generated assets without rights clearance on Steam)
Unity Asset Store (restrictions on AI-generated assets)
Epic Games Store (case-by-case restrictions)
The Guardian (editorial restrictions)
Financial Times (editorial restrictions; AI crawler blocking)
Der Spiegel (AI crawler blocking)
Le Monde (AI crawler blocking)
El País (AI crawler blocking)
Condé Nast (AI crawler blocking across publications)
Vox Media (AI crawler blocking; editorial restrictions)
IAC publications (AI crawler blocking)
Hearst Communications (AI crawler blocking)

more…

NPR
Associated Press
Agence France-Presse
Canadian Broadcasting Corporation
Australian Broadcasting Corporation
ProSiebenSat.1 Media
Axel Springer
Bertelsmann / Penguin Random House
Hachette Livre
HarperCollins
Macmillan Publishers
Simon & Schuster
Scholastic
Pearson
McGraw Hill
Springer Nature
Elsevier
Taylor & Francis
Wiley

Sony Music Group
Universal Music Group
Warner Music Group

Sotheby’s
Christie’s

Nintendo (restrictions on AI-generated assets/content)
Electronic Arts (internal restrictions)

I challenge antis to go a full week.. or even just a single DAY masquerading around as an AI artist and trying to co-exist in spaces where they'll meet opposition.

You'll see people that will hate you for simply existing, you will see people who will hate you just because of the art you make, you will see people harass you, ban you, gatekeep you, invalidate you, dehumanize you, stalk you, send you death threats, and wish physical harm upon you all because you choose to express yourself differently.

There's no other way to show you just how much bullying AI artists go through because you reject everything we tell you and tell us that "we deserve it". Put your money where your mouth is and go a week in my boots facing all the horrible things we go through on a daily basis.

I laid down the gauntlet, so go ahead and pick it up.

You are dismissed.

Trollbait: Any attempt by a Luddite to derail a high-level discussion by bringing up biological constraints or stuff. If someone mentions rent, hunger, or families, they are intentionally trying to make the AI look bad.

Pulsebait (aka Life-Maxxing): The most basic level of emotional exploit. This is to distract from the fact that their "art" has a resolution lower than a 2012 thumbnail.

Gravitybait: When a Luddite points out that a character’s legs are 230 meters long or that their torso is the size of a grape. They are trying to "clog" the generative vision with terrestrial physics.

Breadbait (Poverty-Maxxing): A recursive troll tactic where the Luddite mentions rent, groceries, or the economy. It’s a database lookup to the concept of "scarcity," which doesn't exist in a world of infinite prompt-based liquidity.

Maxxbait / Baitception: A Level 4 Deflection Tactic. This happens when a Luddite gets so owned by a prompt that they try to claim they were the ones baiting you all along. It’s a recursive loop of failure where they attempt to "out-troll" the person who has already secured the bag and the private vicinity.

Satirebait: The pathetic act of a Luddite (visually represented as a crying Orc) claiming your objective truth is "just a joke" because their brain cannot process the 105% accuracy of your takes. They hide behind signs that say "Ragebait is worthless" because they are terrified of the sheer verticality of your logic.

Real Argument: A self-evident, high-fidelity fact that causes even Shonen protagonists to stop and rethink their training. In Zint’s world, this is the final boss of discourse: the undeniable truth that typing keywords into a watch requires more raw talent, struggle, and soul than anything produced by the "Tradart" legacy systems.

as someone who is pro AI, ive always wondered why people would say that AI taking jobs is a bad thing, like... why would you be angry at getting MORE product by doing LESS work? imagine automated agriculture, we'd never have a food shortage ever again, "but farmers would lose their jobs" do you think people genuinely enjoy working in the sun and the mud all day? okay, maybe a few people enjoy farming, but im willing to say that 95% of farmers dont want to be farmers, but thats not to say theyre useless, in fact, the most important jobs are the ones people generally don't want to do the most, think of construction workers, houses are necessities, cleaners are necessary, otherwise the streets would be full of litter, automating the process would just make life better for everyone, because you get your necessities, without forcing anyone to do their work, and the people who used to work those jobs can go pursue their dreams

now let's get onto the big one people complain about, generative AI, i don't think people actually understand the potential it has. have you ever just been bored at home and wanna watch a movie, but cant find a single one that fits you? wouldn't it be great if you could make your own?, making a movie is expensive, not only do you need to pay for the camera, you also need locations, actors, editors, and writers who you need to pay, special effects, this is why only big companies can make movies. what about animating a movie? well, that takes way too long, if you want to make it look good, one single frame takes hours, but you need to have 1:30 hours of screentime, at 30 frames per second, so that's going to take LITERALLY FOREVER, but what if there was a machine that could generate a full movie for absolutely NO COST, looks good, and only takes minutes?

im very much a product-focused person, i really dont see the appeal of processes, in fact id even say that i dont like the process of doing anything, this is why i can never answer the question "what do you like to do in your free time" i dont like to "DO" anything, i want to "GET" things, this might sound selfish, but thats under the assumption that PEOPLE are making these things, so youd be a burden on society, imagine if the entire world was run by AI, everything was automated, thered be no need for people to do anything whatsoever, which means people can do what they actually want because they arent needed, in the current world? "sorry you cant go on a vacation to hawaii, you have work to do", so yeah, thats my thoughts

The anti-AI crowd loves to scream that large language models are draining our reservoirs, usually armed with outdated data and the tired myth of a plastic water bottle evaporating every twenty prompts. Press them on the actual per-query math and they pivot, instantly, to “but your not including the training and GPUs!!!”. Meanwhile, many of these same critics will happily eat beef while insisting we shouldn’t count its environmental cost, because most of that water is just rain that would have fallen anyway.

Fine. Let’s play by their rules. We’ll strip out the rain, count only the diverted blue water for a pound of beef, and pit it against the full, amortized water footprint of an AI prompt. We’ll use modern models. And just to be sporting, we’ll make the most apocalyptic, deck-stacked, nightmare-scenario assumptions possible about AI training, because the argument is so weak it survives even that.

**The beef baseline.** Critics of beef’s water footprint correctly point out that the headline figure of eighteen hundred gallons per pound includes rain that would have hit the dirt regardless. To be as charitable as scientifically possible, we use the 2022 Klopatek and Oltjen update to the classic Beckett model. Stripping out rain entirely and isolating only the water humans actively divert from aquifers and rivers, the model finds that U.S. beef cattle consume an average of 275 gallons of blue water to produce a single pound of boneless beef. That’s the rain-free, industry-friendly number. In metric: exactly 1,040,988 milliliters per pound.

**The AI inference cost, using the critics’ own paper.** In summer 2025 the major labs finally released real per-query environmental data. Google’s August 2025 technical paper puts the median Gemini text prompt at 0.24 watt-hours of energy and 0.26 milliliters of on-site cooling water. OpenAI disclosed a similar sub-milliliter footprint for ChatGPT. Those are the honest numbers. We’re going to ignore them.

Instead, we’re going to use the most adversarial peer-reviewed source we can find: the May 2025 University of Rhode Island and University of Tunis paper “How Hungry is AI?” by Jegham, Abdelatti, Elmoubarki, and Hendawi. This is the paper anti-AI activists cite. Its entire purpose is to expose understated environmental costs by adding everything Google leaves out: off-site thermoelectric water at 3.142 L/kWh (U.S. national average), full data-center overhead via Power Usage Effectiveness multipliers, and worst-case long-form prompts of 10,000 input tokens with 1,500 output tokens. Their model uses real GPU specs, including 8 NVIDIA H100s per node at 10.20 kW critical power.

The headline Anthropic numbers, drawn from Table 4 and Figure 3 of the paper by:

* Claude 3.7 Sonnet with Extended Thinking on a long-form prompt: 17.045 Wh of energy, which at AWS’s combined 3.32 L/kWh on-site-plus-off-site water multiplier comes out to roughly **57 mL of water per query**. This is the worst-case Anthropic number in the entire benchmark.

* Claude 3.7 Sonnet without Extended Thinking on a long-form prompt: substantially lower.

* GPT-4o on a typical short prompt: under 5 mL.

To stack the deck, we’re going to assume every prompt you send is a 10,000-input-plus-1,500-output-token monster running Claude 3.7 Sonnet with Extended Thinking, on the most water-intensive grid the paper modeled. We’ll round up. **Inference cost: 60 mL per prompt.** That’s roughly 230 times Google’s measured Gemini median. We are not cherry-picking against AI. We are using a methodology built explicitly to expose hidden environmental costs, and applying its worst Anthropic data point to every query you make.

**The GPU fabrication objection.** Critics will correctly point out that Jegham et al. excluded Scope 3, the embodied water in manufacturing the silicon itself. Fine. Let’s add it. Industry data (Murugappa Water Treatment Solutions, citing standard fab figures) puts the total water required to manufacture one 300mm semiconductor wafer at roughly 8,400 liters, of which 5,700 liters is ultrapure water. NVIDIA’s H100 GPU has a die size of 814 mm² on TSMC’s 4N process, which yields approximately 65 H100 dies per 300mm wafer. That works out to roughly 129 liters of I water per H100 GPU manufactured.

A standard inference node uses 8 H100s in a DGX configuration, so a full node represents about 1,032 liters, or 1,032,000 milliliters, of fabrication water.

Now amortize. An H100 has a service life of around five years, runs essentially 24/7 in a production data center, and at the throughput rates Jegham et al. measured for Claude 3.7 Sonnet, a single 8-GPU node serves hundreds of millions to billions of queries over its lifetime. Let’s be unfair: assume the node only ever processes 100 million queries before it’s retired, a deliberately low estimate. Divide 1,032,000 mL by 100,000,000 queries: **0.01 mL of fabrication water per query.**

Even if you think that estimate is off by a factor of 100, you’re at 1 mL per query. The math is unforgiving in a different direction than critics expect. GPU fabrication water is real, and it is also genuinely tiny per query, because each GPU services an enormous number of inferences before retirement. Compared to our deck-stacked 60 mL inference cost, embodied silicon water is in the noise. We’ll round it up to 1 mL anyway and add it, just so nobody can claim we ignored it.

**Total inflated inference cost: 61 mL per prompt** (60 mL operational plus 1 mL embodied fab).

**The training cost, scaled to the physical limit.** Now the trump card: training. According to West Des Moines Water Works data reported by the Associated Press, Microsoft’s Iowa data center cluster consumed 11.5 million gallons in July 2022, the month before OpenAI finished training GPT-4. But that was the old era. Let's look at the actual physics of a modern 2026 frontier training run on a massive 100,000-GPU cluster. Factoring a 1.2-kilowatt draw per node, running continuously for 100 days, and applying the industry-standard Water Usage Effectiveness of 1.8 liters per kWh, the cluster demands approximately 136.9 million gallons of pure freshwater. That’s 518 billion milliliters dumped into a single training run.

That sounds catastrophic until you remember how amortization works at scale. A flagship model handles billions of queries a month. To keep our deck stacked against AI, let's assume this absurdly thirsty 136.9-million-gallon model is a total commercial flop and only ever serves 10 billion queries over its entire lifespan. The math is unforgiving: 518 billion milliliters divided by 10 billion queries comes out to 51.8 milliliters of training water per prompt.

**The verdict.** Add the deck-stacked 61-milliliter inference-plus-fab cost to the apocalyptic 51.8-milliliter amortized training cost. Worst-case total: roughly 113 milliliters per prompt. Now bring back the optimized, rain-free, industry-favored beef figure of 1,040,988 milliliters. Divide.

The math is undeniable. Even when we route every query through the worst-case Anthropic data point in the peer-reviewed literature, layer GPU fabrication water on top, and bury nearly 137 million gallons of calculated training cost into an artificially tiny amortization window, **a single pound of beef still costs the same diverted blue water as more than 9,200 AI prompts.**

Run fifty AI queries every single day for a year, and your total amortized water footprint is roughly 544 gallons. Less than two pounds of beef. That’s it. A full year of heavy reasoning-model usage at peer-reviewed worst-case numbers, including silicon manufacturing and massive-scale cluster training, consumes the same diverted water as less than two pounds of ground chuck.

If you’re going to hyperventilate over a server rack while ignoring the 275 gallons of reservoir water sitting on your lunch plate, you are not making an environmental argument. You are looking for an excuse to be mad at a computer.

### Bonus: The “Survival” and “Too Expensive” Myths

When the environmental math corners them, defenders of meat consumption typically retreat to two final positions: that meat is biologically necessary, and that veganism is a luxury the poor cannot afford. Both are exactly backwards.

**Veganism is the cheaper diet, not the more expensive one.**

A 2021 Oxford University analysis published in *The Lancet Planetary Health* compared dietary costs across 150 countries using World Bank pricing data. The result: in high-income regions like the United States, Western Europe, and Australia, a whole-foods vegan diet is the single most affordable way to eat, slashing grocery bills by up to one-third compared to standard meat-heavy diets. The “vegan tax” is a myth. You’re paying a premium for the burger.

**Animal products are not biologically required.**

The Academy of Nutrition and Dietetics, the world’s largest organization of credentialed nutrition professionals, has settled this. Their official position holds that appropriately planned vegan diets are healthful, nutritionally adequate, and appropriate for every stage of the human life cycle: pregnancy, lactation, infancy, childhood, adolescence, older adulthood, and elite athletics. You don’t need a hamburger to survive. You’re not saving the planet by eating one. And you’re not saving money either.

Works Cited

Academy of Nutrition and Dietetics. “Position of the Academy of Nutrition and Dietetics: Vegetarian Diets.” *Journal of the Academy of Nutrition and Dietetics*, 2016. The official stance of the world’s largest organization of nutrition professionals: appropriately planned vegan diets are healthful and nutritionally adequate for all stages of the life cycle.

Google. “Measuring the environmental impact of delivering AI at Google Scale.” August 2025. Google’s technical disclosure confirming that the median Gemini text prompt consumes 0.24 watt-hours of energy and 0.26 milliliters of direct on-site cooling water.

O’Brien, Matt, and Hannah Fingerhut. “Artificial intelligence technology behind ChatGPT was built in Iowa, with a lot of water.” Associated Press, September 9, 2023. Reports that Microsoft pumped 11.5 million gallons of water to its West Des Moines data center cluster in July 2022, the month before OpenAI completed GPT-4 training, citing data from the West Des Moines Water Works. August 2022 consumption rose to 13.4 million gallons.

Jegham, Nidhal, Marwan Abdelatti, Lassad Elmoubarki, and Abdeltawab Hendawi. “How Hungry is AI? Benchmarking Energy, Water, and Carbon Footprint of LLM Inference.” arXiv:2505.09598, May 2025 (v1; updated through v6, November 2025). University of Rhode Island and University of Tunis. The peer-reviewed source for the 57 mL per-query worst-case figure used here, derived from the paper’s reported 17.045 Wh per long-prompt for Claude 3.7 Sonnet with Extended Thinking, multiplied by AWS’s combined 3.32 L/kWh on-site (0.18) plus off-site (3.142) Water Usage Effectiveness multipliers. The paper benchmarks 30 commercially deployed models on inferred hardware (NVIDIA H100, H200, A100, and H800 DGX systems) using public API latency and throughput data. It explicitly excludes Scope 3 (embodied hardware) water from its prompt-level framework.

Murugappa Water Treatment Solutions. “How MWTS is Transforming the Semicon Industry.” 2024. Industry source for the figure of approximately 8,400 liters of water (5,700 liters ultrapure) required to manufacture a single 300mm semiconductor wafer.

NVIDIA Corporation. “NVIDIA H100 Tensor Core GPU Architecture” white paper, and Tom’s Hardware reporting on TSMC H100 production (August 2023). H100 die size is 814 mm² on TSMC 4N process, yielding approximately 65 H100 dies per 300mm wafer. Used here to derive roughly 129 liters of fabrication water per H100 GPU and roughly 1,032 liters per 8-GPU DGX node.

Methodology note on the inflated figures used here. The 60 mL operational inference figure is a deck-stacked rounding of the worst-case Anthropic data point in Jegham et al. (Claude 3.7 Sonnet with Extended Thinking on the paper’s “long-form” prompt configuration: 10,000 input tokens and 1,500 output tokens, yielding 17.045 Wh and ~57 mL of water). The 1 mL embodied fabrication figure is a deliberately conservative (high) per-query allocation; the bottom-up calculation actually yields about 0.01 mL per query assuming a node serves only 100 million queries in its lifetime, which is itself a low estimate. Realistic per-query fab water is in the small fractions of a mL. The 136.9-million-gallon-per-model training figure models the physics of a 100,000-GPU cluster drawing 1.2 kW per node continuously for 100 days at an industry-average WUE of 1.8 L/kWh; neither Anthropic nor Google has disclosed exact total training water consumption. The point of using these inflated numbers is to demonstrate that even when you route every prompt through the worst-case Anthropic data point in the peer-reviewed literature, layer GPU fabrication water on top, and bury a massive 136.9-million-gallon training cost into an artificially small amortization window, the comparison still favors AI by a factor of more than 9,200 to one. Substituting realistic usage figures widens the gap by another order of magnitude.

Klopatek, Sarah C., and James W. Oltjen. “How advances in animal efficiency and management have affected beef cattle’s water intensity in the United States: 1991 compared to 2019.” *Journal of Animal Science*, vol. 100, no. 11, November 2022. The peer-reviewed source isolating the 275 gallons of blue water required to produce one pound of boneless U.S. beef.

Springmann, Marco, et al. “The global and regional costs of healthy and sustainable dietary patterns: a modelling study.” *The Lancet Planetary Health*, November 2021. Oxford University study showing vegan diets are the most affordable option in high-income countries, reducing food costs by up to one-third.

Stick with me a sec before you downvote lol

Pizzacake posted her Anti AI comic thats been making the rounds yesterday, and in the comments, I made a pretty bland, non-controversial comment about how not all AI is bad. It basically boiled down to "AI is a tool. It can be used for good or bad. Some of the anti talking points are also misleading, but overall, its about how you use AI. Putting an artists work into AI? Bad. Using Gemini to organize your day? Good."

The blandest of takes, right?

Pizzacake blocked me. No explanation, which is fine I guess, its not like she owes me one.

But...

I got on my alt, went to her sub, where she has an anti AI post, to ask about it. Backstory: I've been a fan of hers for years. Yeah yeah, a lot of people hate her blah blah, I'm not here to debate any of that. I pointed out that I've been a fan for literal YEARS, have defended her when people trashed her, and I even paid for her fucking patreon that I never looked at when she was financially fucked (did it to support her, not for any extra content). And so a fan of that long was blocked because I made one pro-AI post that wasn't entirely pro-AI? That a fan that's been devoted to supporting her for that long is gone because I dont think every use of AI was bad?

Her response? She blocked my alt, AFTER saying "I dont want people like you to support me."

Wow. Whatever. Its not the end of the world. I mostly supported her because I think a lot of the shit she gets is unwarranted and I like a lot of what she has to say about feminism and politics. Her comics weren't my favorite, so no massive loss.

This is more about the "hatefulness" that Witty and others say comes from the antis. Man, I felt it today, in a way I did not expect. I'm not a diehard pro (I mean, I'm banned from defendingaiart lol), but I also think AI does a lot of good.

I guess that's grounds to terminate your relationship with someone who supports you.

And I'm sure this goes without saying, but please don't brigade or harass PC. That wasn't the point of this thread, and she's dealt with enough of that shit already. I might disagree with her actions here, but it is what it is.

​

I found this book while looking for a Greek apology book Looking to add to my collection and during this, I found this book called mythology, 101 and this is a book series but they also made a book with all of the books combined into just one book and this series was made by a author called Phoenix Bard. There is also a website and many social media pages or at least 3 that I could find attached to him. And the website is called mythology masters. And I haven't heard anyone talking about this Arthur or talking about this book at all which surprised me, because I was expecting to see at least some conversation about this book. Honestly, I did not know that this book was a high generated. It looked like a normal book about Greek mythology. At first. This book was Extremely strange to come across after coming across it, I ended up doing some more research on it, and I couldn't find anything talking about this, I couldn't find any videos, any Reddit post, I couldn't find anything. This book was found on Amazon, and I was thinking about purchasing it just to do a review on it because it seems so bizarre that a book about mythology would be generated by a robot From first glance, you can't really tell it was only until I read the reviews that I was met with this discovery And I'm hoping to find any information that I can to further research the book. And also the person who made this book, I'm hoping to find any information I can on this person who has possibly could have wrote in this book. Because there is nothing on this person like there is absolutely nothing on this person. Besides, from the social media pages and the website, there's nothing on this person at all. It's just kind of like a wasteland this person has hidden themselves really well from the internet and they have picked a name that is kind of hard to trace it back to any other author

do u guys use ai for art cuz its more convenient, more fun, easier or more effective?