The Nous Institute’s foray into the world of artificial neural networks differs from the standard goal of exceeding human capacity through artificial intelligence.
Instead, our models are built and trained with one goal in mind; we aim to provide platforms that trigger novel human thought within the minds of users.
We believe that civilizational development occurs through human flourishing, and that growing dependence on AI is currently headed towards a reduction in general innovative capacity. Our family of finetuned machine learning models aims to transform machine learning into a tool that cultivates creativity in human beings, working in symbiosis with human ideas, rather than existing as a more efficient replacement.
FELIX, our generative fractal network, is consistently training itself to create 3D generative fractal models and subsequent rendered images. Displacement maps, painting styles, colors, and fractal geometry are all mutated through iterations; FELIX makes a record of these changes and allows users to manipulate these variables themselves with the use of particular sliders, providing an easily accessible tool for users to generate millions of different designs.
DELPHI explores the human ability to synthesize knowledge through semiotic form. A finetuned GPT-2 model trained on custom datasets, DELPHI provides semiotics that are canonically resonant with the input material, allowing readers to draw meaning using that information in order to form new philosophical conclusions. DELPHI presents with significant consistency, and is gradually evolving in both scope and translatability. In theme with its namesake, DELPHI attempts prophecy, uttered under a digital trance and suspect to our hermeneutics.