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It's that time of year again when we talk about influencers. Sorry, influence. To influence, what does it mean? How does it happen? I've been an influencer for quite some time now. In fact, I'm probably like the Apex influencer because you never know when I'm being ironic or unironic. All you see is Filion, or at least your perception of who I am, what I do, how much money I make. I have my doctoral degree in influencerology, which makes me the perfect person to comment on which influencer makes the most money. It's the most tried and true way to make new money in 2023. Influencers have the potential to make absolute guap. There's a reason why every kid wants to be a YouTuber when they grow up. It's never Instagrammer, no, it's always YouTuber because they know there's levels to this. The Scooby-Doo gang has been revealed. It's The Usual Suspects. If we're gonna rank influencer income from least to most, I gotta know what platform or what they do on social media, and then I can give you a better idea. Typically, the hotter you are, the more money you make. That's just the reality of the world. I teach people how to be content creators, but I'm also a Twitch streamer. 'I don't sell a course because I believe in like making education free for people, so I don't like paywalling info.' Everything I just said was a lie. 'OnlyFans makes money.' Sex workers retire tomorrow. The moral of the story is I'm washed up and know nothing about the inner workings of modern influencers.

The episode explores how individuals can earn money by creating content with AI-generated influencers. The host walks through using an AI influencer studio to design a virtual character, emphasizing how appearance and retention affect video performance. He demonstrates selecting traits, generating a clip, and uploading it to social platforms, all while noting that the AI serves as a bridge to avoid showing one's face on camera. The discussion then turns to monetization: connecting accounts to platforms, choosing campaigns, and understanding per‑thousand‑view pay across networks. He explains that income often comes from a mix of short‑form revenue, posts, and off‑platform strategies such as collecting emails, selling products, or promoting affiliates. The value proposition centers on lowering entry barriers with tooling that can simulate human-like content while enabling creators to inject personal style. The host concludes by stressing the importance of acting quickly in a rapidly evolving landscape, as early adoption can lead to meaningful opportunities for those who leverage AI tools thoughtfully rather than shying away from them.

People are using AI to create influencers with Down syndrome who sell nudes. The video notes that "Only Fans girls using a Down Syndrome filter on their face to tap into that hypersexualized fetish content." With AI getting better, the speaker says we’ve entered a disturbing period where “the acceleration in the amount of spicy content being posted online” is obvious and faces can resemble real people, not just faked avatars. As AI gets better, the content is stolen from real women and edited with Down syndrome facial features. The speaker says "these accounts, profiles, personas, all exist in what I can only describe as clusters." They feed back to "Telegram or money raising platforms and spicy platforms like Fan View." Major examples named include Maria Depari and Truly Special Girl, with Liliana and Claraara Valdez also mentioned; accounts delete and reappear under new handles, a pattern described as a disease-like repetition. The content is "stolen content to make a profit while exploiting vulnerable communities." AI-generated faces get markedly convincing, making it harder to distinguish what’s real; the speaker notes, "People already when it comes to AI have a really hard time distinguishing real faces from AI faces." The videos use real women’s material repurposed with artificial features to monetize fetish content, often linked to platforms like Fan View and Patreon. Ultimately, the speaker asserts that AI can be a great tool when used responsibly in the correct contexts and warns the issue will persist as AI improves; he says, "AI can and will be a great tool when used responsibly in the correct contexts" and notes he does not see this issue going away or lessening anytime soon. In closing, a provocative claim appears: "it's actually okay. It falls under fair use. Checks out." The discussion frames this as a broader debate about consent, impersonation, and the ethical limits of AI-enabled content

The dead internet theory posits that much of online content and its consumers are fake, primarily generated by AI. Studies suggest that only about 50% of web traffic is human, with bots creating generic engagement. Platforms like Facebook allegedly overstate their traffic to profit from advertisers. The theory claims that AI is used to manipulate behavior and create repetitive content, while deep fakes and AI-generated personas like Lil Miquela raise concerns about authenticity. Autonomous drones like Kargu-2 further illustrate the dangers of AI, leading to fears that the internet is becoming a tool for profit and control.

In this conversation, Trevor McFedries and Isaac Bratzel discuss the creation and impact of Lil Miquela, a virtual influencer launched in 2016 by Brud. They explore the concept of "scalable celebrity," highlighting how Miquela, a photorealistic character, resonated with audiences and sparked fan engagement, including fan fiction. Trevor shares insights on the cultural climate of 2016, emphasizing the potential of social media for storytelling and the importance of creating relatable narratives for young audiences. Isaac details the design process, noting the challenges of making Miquela visually appealing while maintaining recognizability. They discuss the significance of narrative in building a character's identity and the role of fan interaction in shaping Miquela's story. The duo reflects on the evolution of technology, including the challenges of creating animated content and the potential for virtual influencers to engage with fans in real-time. They also touch on the ethical implications of virtual influencers and the shifting perceptions of reality in media. The conversation concludes with thoughts on the future of digital characters, the democratization of technology, and the possibility of virtual influencers becoming central figures in culture, potentially even akin to religious icons.

Sara Giusto manages IMA, a CGI virtual human from Tokyo, who shares her life on social media. Despite being fictional, IMA engages with real-world issues and has gained popularity among Gen Z. She has collaborated with major brands and been recognized for her impact. The potential for virtual humans to enhance human connection is limitless.

The discussion centers on the evolving perception of reality online, particularly with the rise of AI and virtual influencers. As media becomes easier to produce, the challenge will be distinguishing between good and excellent content. Authenticity is sought after, yet even scripted entertainment like K-pop can resonate as genuine. The conversation also touches on the initial pushback against virtual characters and the need to establish ethical boundaries in this new landscape.

The episode dives into a world where AI-generated assets power multimillion-dollar revenue streams, including AI influencers who don’t exist in real life. The co-host discusses a person claiming $10 million in annual revenue from AI-driven content, generated and amplified entirely through AI ads. The conversation centers on practical pathways for individuals who want to earn substantial income with minimal initial capital, proposing a lean model of creating dozens of ads per month for businesses that already spend heavily on advertising. The core idea is to package AI-generated video, voice, and scripts into scalable offerings—either as standalone AI influencers or as agencies producing ads for clients. Roma Torres, an expert in AI-generated video at Arc Ads, explains how the technology evolved from static images to fully talking, lip-synced avatars and how brands are using these assets to build trust and drive engagement. The discussion covers the mechanics of building an AI actor, selecting scripts and emotions, controlling accents, and designing visuals that hook viewers within the first seconds. The hosts emphasize the importance of niche selection and audience targeting, noting that some markets, such as international language learners or services for people with disabilities, respond well to AI-generated content. They also note that the quality and relatability of voice, emotion, and gestures dramatically affect perceived realism and effectiveness. The episode moves into tactical applications: using AI actors for ads across mobile apps, e-commerce, and lead-generation services, as well as for full-fledged AI influencer campaigns. The conversation highlights how agencies can acquire clients by demonstrating the cost-efficiency of AI-produced content and by offering bundled services—like 20 ads a month for a fixed fee—creating recurring revenue. They discuss practical steps, from spying on competitors in ad libraries to scouting niches with high demand and using trend insights to tailor content. The broader takeaway is that the future of advertising increasingly blends automation, creativity, and strategic targeting to scale quickly, while recognizing that consistency, originality, and smart experimentation remain essential.

Codie Sanchez hosts a guest who has built one of the leading AI companies that takes our human mind and recreates it online. The host asks, 'If any video you see online can be AI generated, how do you know what to trust?' The guest insists that 'the most unique thing that you have is your mind' and describes his work around a 'digital mind'—a bidirectional, personalized clone of a person’s thinking and voice. He notes that AI voiceovers almost caused a post to be made from someone else’s video, illustrating the trust challenge in a world of AI‑generated content. He sketches the arc from pattern recognition to a hyper-connected future. He says, 'AI is just math. It’s pattern recognition,' and argues that the endgame is hyperintelligent AI at our fingertips: 'I think the end in mine is AI that is hyper intelligent, generating realistic videos, generating infinitely all night, improving itself.' With that premise, he frames two camps: the doomer who fears disruption and the person who sees opportunity. He urges listeners to start with the end in mind: plan for a world where AI is at work and focus on what stands out. He predicts the creator economy will rise as distribution becomes easier but differentiation grows harder, so the 8020 likely becomes 955, where the 5% reap the benefits of the 95. On practical adoption, the guest explains how ordinary people can apply AI now. AI evolved from telling a cat from a dog in 2014 to predicting emotions from tweets. He highlights education as a positive AI outcome: Bloom's two sigma shows that private tutors boost achievement by two standard deviations. Alpha School’s model uses individualized education with AI assistance and two hours of active learning daily, then curiosity-driven exploration. Education becomes an interactive, choose-your-own-adventure guided by AI toward personalized paths and continual practice. On the future of work, he lists the first AI‑driven jobs as software engineering, consulting, and any role not focused on relationships. He notes that the 8020 becomes 955 because the best can scale while branding matters. He envisions UBI as likely to prevent mass disruption, and emphasizes data ownership—'you own your data, we're not sharing with other people it can be deleted at any time.' He argues authenticity and clear founder intent will shape trust, keeping the long‑term outlook hopeful: communities, creativity, and meaningful connection endure even as AI handles routine tasks.

I was struck by how easily AI generated videos are being used to shape views about Venezuela, turning manipulation into a form of public storytelling. The hosts recount multiple instances where misleading clips claimed to show broad celebrations or outrage, with some posts even amplified by prominent figures. They emphasize how easy it is now for misinformation to spread before anyone checks the details, highlighting a long pattern they’ve faced in past coverage of conflicts and protests. They scrutinize specific examples where videos were miscaptioned or misrepresented, noting where the real footage came from and how quickly sensational claims proliferated despite corrections. The conversation turns on accountability, with hosts arguing that simply leaving false content online without apology or retraction undermines trust. The discussion also grapples with audiences who prefer a narrative over accuracy, suggesting a broader cultural shift toward confirmation rather than verification. The dialogue moves from criticizing individual miscreants to examining systemic issues in journalism and foreign policy discourse. They draw connections to past interventions, the ethics of reporting under pressure, and the emotional appeal of triumphalist content. The episode ultimately centers on integrity, verification practices, and the tension between timely commentary and factual precision in a media landscape saturated with AI assisted misinformation.