Simplex is an AI safety research organization founded in 2024 by Paul Riechers (theoretical physicist) and Adam Shai (computational neuroscientist). The organization applies computational mechanics -- a mathematical framework from physics -- to develop a principled understanding of how neural networks internally organize their representations and how that structure relates to computation and behavior. Operating as a program under the Astera Institute with offices in Emeryville, California and London, UK, Simplex's core thesis is that understanding intelligence is safety. Their foundational result demonstrated that transformers trained on next-token prediction spontaneously organize their activations into geometric structures predicted by Bayesian inference over world models.
Funding Details
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- Fiscal Sponsor
- Epistea, z.s.
Theory of Change
Simplex believes that understanding intelligence is the key to AI safety. Their theory of change holds that by developing a rigorous, principled science of how neural networks internally represent and process information -- drawing on computational mechanics from physics and insights from neuroscience -- researchers can create the theoretical foundations needed to make advanced AI systems interpretable, controllable, and compatible with humanity. By uncovering the geometric structures and computational principles that emerge in trained neural networks, Simplex aims to provide the scientific basis for meaningful AI alignment interventions, safety benchmarks, and a deep understanding of AI cognition that goes beyond surface-level behavioral testing.
Grants Received
from Open Philanthropy
from Survival and Flourishing Fund
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Details
- Last Updated
- Apr 2, 2026, 9:50 PM UTC
- Created
- Mar 18, 2026, 11:18 PM UTC