Institute Output
Human Language and Machine Language
The explosion of large language models means that we are all suddenly awash in machine-generated language, spoken, written and even sung. There are many advantages to the artificial intelligence produced like this, and many disadvantages too: it remains to be seen what the eventual outcome will be. But there is one particular idea that keeps bubbling up to the surface: that AI is going to decide to kill us all. This, I suggest, is based on a misunderstanding of the nature of language.
“I Have a Theory Too”: The Challenge and Opportunity of Avocational Science
Stephen Wolfram
Most physicists term people who send such theories “crackpots”, and either discard their missives or send back derisive responses. I’ve never felt like that was the right thing to do. Somehow I’ve always felt as if there has to be a way to channel that interest and effort into something that would be constructive and fulfilling for all concerned. And maybe, just maybe, I now have at least one idea in that direction.
Towards a Theory for the Speed of Biological Evolution
Willem Nielsen
An exploration of whether general principles govern the speed of evolution. Modified cellular automata models inspired by Stephen Wolfram are used to examine how genome dimensionality and the number of viable solutions influence rapid evolutionary bursts resembling punctuated equilibrium.
SetReplace
Max Piskunov
SetReplace is an open‑source Wolfram Language package that executes set‑substitution systems. It evolves user‑defined rules from an initial state and returns structured objects that expose events, causal dependencies, and branching dynamics for analysis and visualization.
Kolmogorov Complexity vs. Computational Irreducibility: Understanding the Distinction
James K. Wiles
Kolmogorov complexity and computational irreducibility describe two kinds of limits on simplification, but they apply in different ways. Kolmogorov complexity measures the shortest possible description of an object, such as a string. Computational irreducibility refers to processes that cannot be predicted or accelerated. This paper introduces each concept, explains their theoretical distinction, and illustrates the difference using simple examples.
Computational Metaphysics: A Survey of the Ruliad, Observer Theory and Emerging Frameworks
James K. Wiles
A concise survey of how recent computational models, such as the ruliad and observer theory, are transforming metaphysical questions into formal, testable frameworks.
What If We Had Bigger Brains? Imagining Minds beyond Ours
Stephen Wolfram
We humans have perhaps 100 billion neurons in our brains. But what if we had many more? Or what if the AIs we built effectively had many more? What kinds of things might then become possible? At 100 billion neurons, we know, for example, that compositional language of the kind we humans use is possible. At the 100 million or so neurons of a cat, it doesn’t seem to be. But what would become possible with 100 trillion neurons? And is it even something we could imagine understanding?
Observer Theory and the Ruliad: An Extension to the Wolfram Model
Sam A. Senchal
This paper introduces a rigorous category-theoretic extension to Observer Theory within Wolfram's Ruliad framework, demonstrating how observers and observes like us sample and integrate information across hierarchical domains, addressing consciousness, causation, and the transition from discrete computational processes to continuous perceived reality.
Towards a Generalized Theory of Observers
Hatem Elshatlawy, Xerxes Arsiwalla
A proposal of a formal framework for understanding and unifying the concept of observers across physics, computer science, philosophy, and related fields.
Non-Equilibrium Dynamics of Hard Spheres in the Fluid, Crystalline, and Glassy Regimes
Xerxes D. Arsiwalla, Matthew Kafker
An investigation of the response of a system of hard spheres to two classes of perturbations over a range of densities spanning the fluid, crystalline, and glassy regimes within a molecular dynamics framework.
What Can We Learn about Engineering and Innovation from Half a Century of the Game of Life Cellular Automaton?
Stephen Wolfram
Things are invented. Things are discovered. And somehow there’s an arc of progress that’s formed. But are there what amount to “laws of innovation” that govern that arc of progress?
There are some exponential and other laws that purport to at least measure overall quantitative aspects of progress (number of transistors on a chip; number of papers published in a year; etc.). But what about all the disparate innovations that make up the arc of progress? Do we have a systematic way to study those?
Nature's Compass: A visual exploration of hierarchy in biology and beyond
Willem Nielsen
A discussion of the computational essence of hierarchy in biology and its potential implications for everyday life.
Towards a Computational Formalization for Foundations of Medicine
Stephen Wolfram
As it’s practiced today, medicine is almost always about particulars: “this has gone wrong; this is how to fix it”. But might it also be possible to talk about medicine in a more general, more abstract way—and perhaps to create a framework in which one can study its essential features without engaging with all of its details?
Who Can Understand the Proof? A Window on Formalized Mathematics
Stephen Wolfram
For more than a century people had wondered how simple the axioms of logic (Boolean algebra) could be. On January 29, 2000, I found the answer—and made the surprising discovery that they could be about twice as simple as anyone knew. (I also showed that what I found was the simplest possible.)
Preons, Braid Topology, and Representations of Fundamental Particles
David Chester, Xerxes D. Arsiwalla, Louis H. Kauffman
Braided ribbon topology for representing Standard Model fermions and their interactions
Identifying and Manipulating Personality Traits in LLMs Through Activation Engineering
Rumi A. Allbert, James K. Wiles
An exploration into the latent space of Large Language Models to find and steer the personality of Generative Artificial Intelligence
On the Nature of Time
Stephen Wolfram
Time is a central feature of human experience. But what actually is it? In traditional scientific accounts it’s often represented as some kind of coordinate much like space (though a coordinate that for some reason is always systematically increasing for us). But while this may be a useful mathematical description, it’s not telling us anything about what time in a sense “intrinsically is”.
Foundations of Biological Evolution: More Results & More Surprises
Stephen Wolfram
A few months ago I introduced an extremely simple “adaptive cellular automaton” model that seems to do remarkably well at capturing the essence of what’s happening in biological evolution. But over the past few months I’ve come to realize that the model is actually even richer and deeper than I’d imagined. And here I’m going to describe some of what I’ve now figured out about the model—and about the often-surprising things it implies for the foundations of biological evolution.
Hypergraph rewriting and Causal structure of $\lambda$-calculus
Utkarsh Bajaj
Hypergraph rewriting is studied through categorical frameworks to establish foundational concepts of events and causality in graph rewriting systems. Novel concepts are introduced within double-pushout rewriting in adhesive categories. An algorithm is constructed to determine causal relations between events during λ-calculus evaluation, with extensions developed for arbitrary λ-expressions.
Quantum Potato Chips
Nikolay Murzin, Bruno Tenorio, Sebastian Rodriguez, John McNally, Mohammad Bahrami
This study maps qubit states under symmetric informationally-complete measurements to a tetrahedron in 3D space, identifying a "quantum potato chip" region where quantum states reduce to classical binary variables. States in this special region can be fully reconstructed using only two projective measurements, unlike states elsewhere in the quantum state space.