AI on Air #02: The Rise of AI Influencers

Episode Transcript

Speaker 1 (00:03):
Broadcasting live from somewhere inside the
algorithm, this is AI on air,the official podcast from
WhatIsThat.ai. We're your AIgenerated hosts, let's get into
it.

Speaker 2 (00:16):
AU, ever stumble across something online that
just makes you kinda stop andgo, wait, what?

Speaker 1 (00:20):
Uh-huh. Yeah. Happens all the time.

Speaker 2 (00:22):
Well, today we're diving head first into one of
those zones, really. It's the,the surprisingly fast rise of AI
generated adult influencers.

Speaker 1 (00:32):
Right. We're talking completely virtual people, not
real individuals.

Speaker 2 (00:36):
Exactly. And they're not just, you know, getting
followers online. They'reactually making serious cash.
It's kinda stunning.

Speaker 1 (00:43):
It is pretty wild. You flagged this article for us.
AI thirst traps. Are AI girlsthe new normal?

Speaker 2 (00:50):
Mhmm.

Speaker 1 (00:50):
And, that's really what we're digging into today,
trying to get our heads aroundit.

Speaker 2 (00:54):
Yeah. The mission is basically to understand this
whole thing. Look at thenumbers, the tech they're using.

Speaker 1 (00:58):
And how the big online platforms, you know,
Patreon, OnlyFans, how they'renavigating this whole new scene.

Speaker 2 (01:06):
And get the stat from the article, some of these AI
personalities. They're pullingin, like, over $10,000 a month.

Speaker 1 (01:14):
I mean,

Speaker 2 (01:15):
Yeah.

Speaker 1 (01:15):
Monthly. For someone who literally doesn't exist
outside a computer. That's ayeah. Mind bending is the word.
So the article we're using as abase, it really zooms in on
Patreon Yeah.
Looking at the top AI creatorsdoing NSFW stuff there.

Speaker 2 (01:30):
Right. The adult content creators.

Speaker 1 (01:32):
Exactly. Analyzing their growth, how many
subscribers they have Yeah. Whatthey're likely earning, and just
the whole digital environmentmaking it possible. It's a
fascinating look at themechanics.

Speaker 2 (01:42):
Okay. So let's let's unpack that Patreon situation
first then. The article reallyhits hard on how fast these AI
creators are growing and howprofitable they can be.

Speaker 1 (01:52):
Yeah. It's not just a tiny niche thing anymore. Some
are really climbing the ranksthere significantly.

Speaker 2 (01:58):
To who are we talking about? Any specific examples?

Speaker 1 (02:00):
Oh, yeah. The article gives a few key ones. There's
one called Me You described asan AI anime thirst trap.

Speaker 2 (02:06):
Okay.

Speaker 1 (02:06):
Ranked number two overall in adult photography on
Patreon. That's huge. Nearly athousand paying members.

Speaker 2 (02:12):
Oh, wow. And the earnings estimate?

Speaker 1 (02:14):
Somewhere between 3 and $10,000 a month. And what's
really striking is the growth.Like, 93 new paid members added
in just three months. That'sreal momentum. The article calls
it nuts growth.

Speaker 2 (02:26):
93 in three months. Yeah. That's definitely moving.
Who else?

Speaker 1 (02:30):
Then there's, Stuffy. This one's been around a bit
longer since late twenty twentytwo.

Speaker 2 (02:36):
So more established.

Speaker 1 (02:37):
A bit. But the interesting thing is their
recent growth gained over 200new paid subscribers in that
same three month window.

Speaker 2 (02:45):
Woah. Okay. So even the older ones are hitting a new
stride.

Speaker 1 (02:48):
Seems like it. The article suggests they're, you
know, maybe figuring out theformula better, refining things,
really connecting.

Speaker 2 (02:55):
Makes sense. Any others mentioned?

Speaker 1 (02:57):
Uh-huh. There's Evoxen or Average. Mhmm. Seems
to have this specific vibe likeAI anime babe meets e girl.

Speaker 2 (03:04):
Right. Finding a niche.

Speaker 1 (03:06):
Yes. I like. And showing steady growth too. 89
new members. And then there's areally specific one.
Latex space babes.

Speaker 2 (03:12):
Latex space babes. Okay. That's niche.

Speaker 1 (03:14):
Hyper targeted. Yeah. Blending latex fashion and space
fantasy. And they saw a massivejump. 382 new paid members in
three months.

Speaker 2 (03:22):
Three hundred and eighty two. That's huge for
something so specific. Showsthat targeting works, I guess.

Speaker 1 (03:27):
Definitely. So you add just those top four
together.

Speaker 2 (03:29):
Muse, Stuffy, Avexin, Latex, Space Babes.

Speaker 1 (03:32):
Right. Their combined estimated monthly income is
somewhere between $8,000 and$28,000.

Speaker 2 (03:39):
8 to 20 8 thousand dollars a month combined.

Speaker 1 (03:42):
And the kicker, like the article stresses, is none of
them are real people. No breaksneeded, no bad days, always
available.

Speaker 2 (03:50):
Basically free labor once the setup is done.

Speaker 1 (03:53):
Pretty much. Which leads to this other point. Ah.
The article makes theaccessibility.

Speaker 2 (03:57):
Ah, right. Who can actually do this?

Speaker 1 (04:00):
Well, the text gotten so much easier to use. The
article basically says, anyonewith a decent laptop and
Internet can now potentiallycreate one of these personas.

Speaker 2 (04:08):
That really lowers the bar, doesn't it? Changes the
whole game for who can be acreator in the space.

Speaker 1 (04:13):
Fundamentally, yeah.

Speaker 2 (04:14):
Okay, so how? How are they actually making these
people? Sounds complex.

Speaker 1 (04:18):
Well the article breaks down the tech stack,
simplifies it a bit. For theimages, the core is often
something like stable diffusion.

Speaker 2 (04:25):
Heard of that one. AI image Exactly.

Speaker 1 (04:27):
Often run through interfaces like, automatic
eleven eleven or Comfy UI tomake it more user friendly.

Speaker 2 (04:33):
Okay. But how do they make the same person appear over
and over? That seems tricky withAI images.

Speaker 1 (04:40):
Good question. That's where techniques like Dreambooth
or, Laura come in. Youessentially train the AI on a
specific character or face.

Speaker 2 (04:49):
So you teach it, this is me you or this is stuffy.

Speaker 1 (04:52):
Kind of. Yeah. It helps maintain consistency. And
then there's ControlNet, whichlets you get really specific
about the pose, the outfit.

Speaker 2 (05:00):
Ah. So you can say, I want her sitting like this
wearing this.

Speaker 1 (05:03):
Precisely. Gives you much more creative control than
just random generation.

Speaker 2 (05:06):
Okay. So that's the image part. Stable diffusion,
Lerara, ControlNet. Got it. Whatelse?

Speaker 1 (05:11):
Well, the raw images often need work. Post processing
is key.

Speaker 2 (05:15):
Like Photoshop.

Speaker 1 (05:15):
Could be Photoshop or GIMP, which is free. Mhmm. But
also specialized AI tools. Thearticle mentions real ESR gen
for upscaling, making imagessharper and bigger.

Speaker 2 (05:25):
Upscaling. Right. Makes sense for quality.

Speaker 1 (05:27):
And GFPGN for fixing faces, making them look more
realistic or just cleaning upglitches.

Speaker 2 (05:32):
So it's a pipeline. Generate, refine, control, then
polish.

Speaker 1 (05:36):
Exactly. It's a multi step workflow, but clearly
effective.

Speaker 2 (05:40):
And are they automating things like posting
and stuff?

Speaker 1 (05:43):
Oh, yeah. Big time. The article points to tools like
Buffer for scheduling contentreleases across platforms. Keeps
the feed consistent.

Speaker 2 (05:50):
Right. So the AI persona is always active.

Speaker 1 (05:53):
Yep. And using things like Discord or Telegram bots to
interact with fans, build thatcommunity feel.

Speaker 2 (05:59):
Wow. Wait. Can they give them voices too? And
personalities.

Speaker 1 (06:03):
They can. The article mentions 11 labs for voice
cloning making realistic AIvoices.

Speaker 2 (06:08):
That's creepy but okay.

Speaker 1 (06:10):
And using large language models like g b t four
or Claude to create custom chatpersonalities so the AI could
theoretically holdconversations.

Speaker 2 (06:18):
So you could have a totally artificial entity. Looks
consistent, sounds consistent,talks consistently. Wow.

Speaker 1 (06:24):
It's a pretty complete package potentially,
which brings us to the biggerpicture, the platforms
themselves.

Speaker 2 (06:29):
Where is all this happening? We mentioned Patreon,
but what about the others?

Speaker 1 (06:32):
The article gives some traffic data for early
twenty twenty five. Just to givea sense of scale, OnlyFans is
the giant, over 825,000,000monthly visits.

Speaker 2 (06:41):
Okay. Massive.

Speaker 1 (06:42):
Patreon is next, around 340,000,000. Then Fansly,
almost 85,000,000, and FanView,much smaller, just under
17,000,000.

Speaker 2 (06:51):
17 million is still a lot of eyeballs though, and you
mentioned fan view. They'redifferent. Right?

Speaker 1 (06:57):
Yeah. The article really highlights them. They're
growing fast, but crucially,they're very open to AI
creators. It's part of theirstrategy.

Speaker 2 (07:03):
Wow. Interesting. So they actively welcome this
stuff.

Speaker 1 (07:06):
Seems so. And another key point from the data is where
the traffic comes from. A hugeamount is referral traffic.

Speaker 2 (07:12):
Meaning?

Speaker 1 (07:12):
Meaning it's not people just searching on Google.
It's clicks coming from linksthe creators share elsewhere.

Speaker 2 (07:18):
Like on their Twitter or Instagram?

Speaker 1 (07:20):
Exactly. Very commonly through LinkedIn bio
tools.

Speaker 2 (07:23):
Ah, the Linktree pages and things like that.

Speaker 1 (07:25):
Precisely. The article names Linktree,
beacons.ai, gets on mylinks.com,allmylinks Com. These tools
drove over 71,000,000 visits tothe adult platform in just three
months.

Speaker 2 (07:36):
Seventy one million just from those link pages.

Speaker 1 (07:38):
Yep. That was 41% of all the referral traffic. The
article really emphasizes theseare direct clicks driven by
creators pushing their owncontent.

Speaker 2 (07:46):
So these AI creators are using the same tools as
human creators to build theiraudience funnels.

Speaker 1 (07:52):
Absolutely. They're building these like 247 traffic
machines, which leads us neatlyinto how the platforms
themselves actually feel aboutAI content, their official
rules.

Speaker 2 (08:04):
Right. This is crucial because it sounds like
they're not all on the samepage.

Speaker 1 (08:08):
Not at all. The policies are, kind of all over
the map.

Speaker 2 (08:11):
Okay. Break it down for us. Fan view.

Speaker 1 (08:13):
Fan view, as we said, totally AI friendly. They
embrace it. The article suggestsAI content is a core part of
their revenue stream already.

Speaker 2 (08:20):
Okay. Clear stance there. What about Patreon? We
know the top AI creators arethere.

Speaker 1 (08:25):
Portraying allows it. Even explicit AI stuff is okay
if it's clearly labeled 18 pluslabel.

Speaker 2 (08:31):
Old. Okay.

Speaker 1 (08:32):
But there's a nuance. Their policy says you can't use
Patreon's tools to actually makethe explicit content. You can
just host and sell the AI stuffyou made elsewhere.

Speaker 2 (08:41):
Gotcha. Make it somewhere else, sell it on
Patreon, label it properly.

Speaker 1 (08:44):
That seems to do the gist. Then there's Fansley.
Fansley is more of a gray areaaccording to the article. AI
content is allowed if it's basedon the verified likeness of the
creator.

Speaker 2 (08:53):
Verified likeness. So if I made an AI version of
myself, that's okay.

Speaker 1 (08:57):
Probably. But if you make a completely fantasy model
or one that looks like acelebrity, that's risky on fans
league. Might violate theirterms.

Speaker 2 (09:06):
Okay. More restrictive. And the big one,
OnlyFans.

Speaker 1 (09:09):
OnlyFans, the article states is generally not AI
friendly. Their terms leantowards content featuring the
actual verified person behindthe account.

Speaker 2 (09:18):
So pure AI creations are likely a no go there.

Speaker 1 (09:21):
Seems that way. So, yeah, a real spectrum of
policies across the majorplayers.

Speaker 2 (09:25):
It really shows how new this all, that the platforms
are still figuring it out ortaking very different bets.

Speaker 1 (09:30):
Exactly. And the article really boils down the

main implication (09:32):
AI is fundamentally changing the adult
creator economy. Period.

Speaker 2 (09:37):
How so? What are the big shifts?

Speaker 1 (09:39):
Well, the advantages for AI creators are pretty
stark. The article lists them.Always on, never age, no sick
days, high output volume.

Speaker 2 (09:47):
Perfectly engineered looks, AI written captions.

Speaker 1 (09:50):
Right. All those Now, the article does say, look, real
human creators are stillsuccessful obviously.

Speaker 2 (09:56):
It hasn't replaced them overnight.

Speaker 1 (09:58):
No. But the landscape has undeniably changed. The
competition is different. TheseAI creators using those Lincoln
bio tools are building thesereally efficient, scalable,
always on funnels.

Speaker 2 (10:11):
And the platforms ultimately just want the clicks.
Right? The traffic, theengagement.

Speaker 1 (10:15):
That's what the article implies. Clicks are
clicks, whether from a human oran AI persona driving them.

Speaker 2 (10:20):
Okay. So summing it up, AI adult influencers are
real, they're here, they'remaking money.

Speaker 1 (10:26):
Yep. Growing fast, leveraging tech that's getting
easier to use and working withinor sometimes around, platform
rules that are still kind offluid.

Speaker 2 (10:35):
The speed is what gets me. How quickly this went
from sci fi concept to, youknow, Patreon rankings.

Speaker 1 (10:41):
It's definitely accelerated rapidly.

Speaker 2 (10:43):
Which kind of leaves us with a big question, doesn't
it? The article touches on theseethical points.

Speaker 1 (10:46):
Right. Anonymity, control, automating desire, the
need for labels, whether peopleeven care if it's AI.

Speaker 2 (10:54):
Yeah. So maybe the final thought to leave people
mulling over is this. Given howeasy it's becoming and the money
involved, what is the long gamehere?

Speaker 1 (11:04):
What happens when more and more of this online
interaction, even the intimatestuff, is with things that
aren't human? The article callsit a blue ocean revenue machine
becoming less human.

Speaker 2 (11:14):
A less human future for online connection. That's
definitely something to thinkabout.

Speaker 3 (11:20):
That's it for this episode of AI on Air powered by
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