Computational Creativity (Horizontal Thesis)

Concept

As AI/ML progresses, there will be massive disruption and efficiencies created within creative industries.

Longer Description

Ever since the advent of Generative Adversarial Networks from Ian Goodfellow et al we have believed that a wide variety of businesses that control the middle and application layers could be created to enable more efficient, scalable, and impressive creativity.

We’ve invested against this thesis multiple times since 2017 and have seen it come to fruition increasingly throughout 2022 with models like Dall-E, Stable Diffusion, and more reaching the mainstream.

Investments include:

• Shadows
• We incubated Shadows, a ML-first animation studio. The high level is seeing progress of GANs and unsupervised learning largely in japanese academic communities focused around anime datasets was eye opening (long thread here) and the shifting media landscape valuing IP and animation specifically was really compelling. Dylan (ceo/co-founder) was leading a group in new media at CAA so knew the space incredibly well, Corey (CCO, co-founder) runs a large animation studio called Shadow Machine (responsible for BoJack Horseman, among others), and so our three lenses of industry experience and technical experience on my end made for a compelling vision. Ultimately the thesis of building in-house tools to scale animation played out well in short-term, though in the longer-term the company focused less on native ML-tooling and more on unique 3D pipelines.