In this interview, Nina Schick argues that 2023 marks an inflection point for generative AI. Tools like ChatGPT have captured public attention, but she frames them as early interfaces to a broader wave of models that can generate text, images, audio, and video. She expects valuations across the space to rise and new applications to become universal across industries.

Nina revisits a prediction that AI will generate the majority of online content and now moves the timeline forward. Given exponential progress, she believes the internet could reach about 90 percent AI generated content much sooner than 2030. That reality will force rapid responses from educators, enterprises, and policymakers.

Regulation will lag innovation, so she expects 2023 and beyond to bring a more serious policy conversation. Key questions include how to govern foundational models, whether open source development should remain accessible, and how to balance augmentation of human work with fears of automation. She anticipates the European Union to take early steps through comprehensive AI regulation.

On education and copyright, Nina notes that plagiarism concerns are already visible, as students test ChatGPT for essays. In creative domains, training sets and the ability to imitate artist styles raise consent and compensation issues. She stresses that these systems are tools, yet their capabilities will evolve quickly, making today’s interfaces seem quaint by year end.

Competition will intensify. Big tech firms have data, talent, and research pipelines to launch their own generative tools, while partnerships and investments with newer players will continue. Microsoft’s stake in OpenAI is one signal, but she expects Google and others to unveil significant products. The strategic questions for leaders are where to adopt, how to govern, and how to prepare for content, search, and workflow changes.

Her bottom line: treat generative AI as a new communications infrastructure. Plan for rapid capability gains, build governance around IP and safety, and focus on human augmentation to unlock value while addressing legitimate risks.

Nina Schick opens by framing generative AI as a tipping point for human creativity and the digital ecosystem. She defines generative AI as systems that autonomously create text, images, audio, and video, and updates a bold prediction: by 2025, the majority of digital content online could be AI generated. That scale forces new thinking on policy, authenticity, and business models.

Guest Dan Li recounts building earlier AI companies and noticing cultural moments that signaled a shift, like viral synthetic music. He highlights the explosion of developers and users building with open tools and argues that creation barriers have collapsed. Li introduces Vermilio, a platform that combines generative models with blockchain to record authorship and lineage for every synthetic output. The goal is to authenticate origin, track derivatives, and enable creators to benefit as their work inspires new works.

Central to Vermilio is the idea of a personal style engine. Instead of platforms owning aesthetics, individuals define and own their creative style, then generate original outputs with simple prompts. Nina probes artist concerns about imitation and IP. Li responds that provenance and transparent attribution are the foundation for ethical participation and healthy creator economies. With verifiable lineage, artists can engage fans, license styles, and share in downstream value.

They preview Vermilio’s launch styles, from action figures to vintage comics and digital goods like sneakers, connecting this to a fast-growing market for virtual merchandise. Li expects text-to-video capabilities to follow quickly, pushing premium content creation to billions with smartphones. Both emphasize urgency. Without open, portable provenance, closed platforms or states could centralize control of generative engines. An open verification layer enables interoperability, user ownership, and trust across ecosystems.

The conversation closes on use cases for brands and institutions: disclose synthetic media, adopt provenance standards, pilot creator tools with consentful datasets, and design policies that prefer augmentation and inclusion over exclusion.