Helivan Research

Join Waitlist

RESEARCH

Our research has allowed us to be the first to provide statistical evidence that ...

Toward a Digital Twin of U.S. Congress

Empirical evidence that a collection of language models parameterized by real people's data satisfies the definition of a digital twin.

Statistical inference on black-box generative models in the data kernel perspective space

Providing theoretical and empirical support for predicting the behavior of generative models using vector representations of population of models.

Investigating social alignment via mirroring in a system of interacting language models

Investigating the effect of a simple "mirroring" mechanism on the dynamics of a system of interacting language models.

Consistent estimation of generative model representations in the data kernel perspective space

Providing theoretical support for using vector representations of populations of generative model.

// HELIVAN

info@helivan.io

Research in collaboration with:

Johns Hopkins University

Microsoft Research

Nomic AI

Backed by:

Betaworks

Factorial

DARPA