About • Visual Arts • Performing Arts
NuMedia • Emerging Tech.


Early adoption of new technology's always run in my family. My father was the founding CTO of Pepsi and helped integrate 3DCGI and computer graphic designs into the comapny's portfolio of brands in the mid 1980's, as well as now industry standard CAD procedures in mass production. He would continue to chase developments in IT solutions into the .com boom of the late 1990's, passing down his love of these technologies and the wherewithal to actively teach oneself newer tech to myself and my siblings, effectively since birth in the new millennium.

In the mid-2010's, I started leveraging restorative AI in memes I'd post online (more info in the "New Media" page), many of which would go viral over the coming years and pave the way for future developments and opportunities. By around 2016, I had helped hone AI models with the community of content creators I associated with at the time to isolate vocals from music tracks, without use of traditional methods of phase inverting studio instrumentals. Not too much more time had passed, and we had already further perfected the technology to demix audio recordings down even further. My own developments over the course of the early 2020's have substantially grown into workflows that lead to my ability to demix a track down to separate instrumental frequencies, including separation of individual voices from a multitrack with several voices hard-layered into the mix (or backup singers in a song), as well as the means to upmix as simple as monoural audio upwards of 5.1 surround sound.

My expertise leveraging restorative AI solutions in memes in my youth directly led to a spot in OpenAI's beta testing program in 2018, where I was first granted playtesting rights to the state-of-the-art generative AI suite that includes the likes of GPT and Dall-E.

In direct response to the then-volatile status of a coastal Self Storage company's workforce, I'd trained a suite of custom GPT-based agents on the company's entire backend and strictures, treating the internal GPT suite, as well as the public-facing Swivl chatbot, as its own virtual wave of hires. the main focus being to streamline as much of the menial deliverables as far as daily accounting and facility maintenance, as well as “virtual call centers” on public websites, and a general assistant to help enforce and maintain a consistent brand tone across all external communications, such as with tenants, prospectives, and third party collaborators such as storage unit liquidators. The former use cases, have also involved heavy reevaluation and restructuring of the chain of internal sites that comprise the company’s backend; as the company is still surprisingly small after almost 20 years, our main goal is to automate as much as possible, freeing up human staff to properly thrive at work. Another huge ripple effect from my own AI push with this franchise has also been that, since so much of this involves effectively training machines on all the same beats you’d teach living people, actual internal training materials have been updating for the first time since 2016—ALL of the training materials have been notoriously outdated across the entire workforce beforehand. It could never be understated how much hats everyone wears already. For some reason, the AI suite I’ve been developing has sincerely been so innovative across all departments, freeing up busywork from people in the call centers, to middle management on-site, literally all the way up to the executive board, including the company’s dedicated IT department, which for some reason has been ridiculously slow to adopt anything. Note: I DO NOT work for their IT staff.

Under Mattel's employment, I've also contributed training to their enterprise's internal forks of such LLM tools, helping fine-tune models based on their near century's portfolio of brands. Several projects from Barbie, American Girl, as well as the global relaunches of Barney the Dinosaur and Angelina Ballerina have heavily utitlized LLM datasets I've contributed to.

Concurrent with traditional art, I've also grown to leverage gen AI to further accelerate and enchance workflows, particularly developing style transfer (image-to-image) models for use in expediting ink & paint procedures in cel animation.

From my early days of testing GPT in its infancy, I quickly realized the importance of the written word as a new programming language for gen. AI. Once ChatGPT was first made widely available to the general public, I was one of the trailblazers for the concept of "prompt engineering", leveraging the English language to explicitly instruct models down to the most initmate minutia for all sorts of freelance bases.

When I worked at Dr. Seuss, I helped leverage gen AI with all sorts of company communications, helping enforce the master brand's signature rhyming scheme with character dialogue, public documentation and marketing communications. Dr. Seuss was my premiere vehicle to pilot my vast self-taught knowledge of gen AI before moving onto Mattel and other enterprises, being able to pinpoint the company's signature aesthetics and language down to an exact science, which their internal models were able to replicate down to a T.