IPI Talk – Yuri Kadin, Netherlands - Saturday, 4th of July @ 17:00 UK time

Our next IPI Talk will be on Saturday, 4^th of July at 17:00 London time zone. 

Title: Second law of info-dynamics and the language diversity decline

 Abstract: The recently formulated second law of infodynamics manifests itself in multiple physical systems, indicating the fundamental nature of this law. In some cases, the second law of infodynamics can be interpreted in terms of minimum energy principle, while in other cases the mechanisms that lead to a decrease in information entropy are practically impossible to understand. We propose a new metaphysical principle, termed "the majority swallows the minority" and explain why the Shannon's informational entropy decreases due to this principle. As an example of the this principle application, the well-known phenomenon of the decline in linguistic diversity is considered; u
nlike other phenomena, the mechanisms associated with the decline and extinction of human languages ​​are well understood. This allows us to develop a simple mathematical model which reflects the aforementioned principle ("the majority swallows the minority”). Our numerical simulations are consistent with data showing the dynamics of decline in global Indigenous Linguistic Diversity (ILD) in America and Africa, for the time segment 1975 to 2005. We emphasize once again that this principle has an ontological nature and can be applied to other physical systems, even if their physical behavior is not yet fully understood. In addition to mathematical analysis, the proposed principle is also considered from a philosophical point of view. Quality (representing the informational entropy) versus quantity (equivalent to the classical thermal entropy) will be discussed in the lecture from the perspective of the René Guénon's philosophy.

Speaker: Yuri Kadin

Bio: Yuri graduated in 2004 with a Bachelor of Science (BSc) from the Faculty of Mechanical Engineering at the Technion (Israel Institute of Technology) with honors (Summa Cum Laude). During the undergraduate studies, he specialized in micromechanics and biomechanics. From 2004 to 2008, he undertook studies towards PhD (at the Faculty of Mechanical Engineering at the Technion) in the fields of contact mechanics, plasticity, rough surface analysis, tribology, and adhesion. Since 2009, Yuri has been working at the SKF Research Center in Netherlands, in the areas of fatigue modeling, computational fracture mechanics and contact mechanics, viscoelasticity and creep, hydrogen diffusion/embrittlement of steels, polymer and composite modeling, and several other topics related to computational materials science.

Hard-Coding the Cosmos: Emergent Gravity and Information Transmutation in a Discrete D4 Lattice

 For decades, theoretical physics has debated the simulation hypothesis—the idea that the universe, at its most fundamental level, operates as a computational engine. But debating philosophy only gets us so far. Eventually, you have to write the code and run the simulation.

That is exactly what the Single-Instance Computational Cosmos (SICC) framework was built to do.

Recently, the SICC transitioned from theoretical architecture into a live, executable physics engine built on a discrete D4 geometric substrate. Rather than using massive supercomputers to run probabilistic Monte Carlo models, the SICC is a deterministic, bottom-up cellular automaton where particles have genuine "topological weight" and interact according to strict quantum parity rules.

During our latest execution runs, we didn't just model physics; we watched emergent behavior break the system in all the right ways.

Emergent Gravity and the Pauli Override

In the SICC engine, mass isn't an absolute property—it is dynamically calculated through the interaction between a particle's Higgs coupling and the vacuum expectation value.

To stress-test the framework's thermodynamics, we surgically spiked the fundamental Higgs coupling scalar of a single vector. The kinematic engine computed a massive weight that instantly shattered the local Pauli/Fermi fermionic capacity limits. The result? The underlying spatial coordinate permanently collapsed. The discrete lattice successfully formed a stable, localized singularity—an informational sink—without fragmenting the grid or crashing the memory pool. Gravity emerged naturally from the rules of information density.

Transmuting Mass into Information

Even more critically, we tested the framework's Gauge Mediator by forcing a high-energy collision between two discrete state vectors (P19 and P20) occupying the same spatial coordinate with opposing quantum parities.

When the annihilation event triggered, the particles didn't just disappear. The engine successfully converted their combined topological mass into an exact burst of 20 gauge tokens. The SICC engine proved a closed-loop system where matter is actively transmuted into force-carrying information, conserving total system entropy.

We are no longer just theorizing about whether information is the fundamental building block of reality. We are watching it execute.

The complete Phase 9 manuscript detailing the SICC lattice mechanics, alongside the raw telemetry logs and the open-source GitHub repository, will be dropping soon.

Stay tuned. The void is officially compiling.

IPI Talk – Chris Royse, USA – Saturday, 6 June @ 17.00 UK time

Our next IPI Talk will be on Saturday, 6^th of June at 17.00 London time zone. 

Live stream link: https://youtube.com/live/XY_YJiukBe8?feature=share

Title: A Fourth Kind of Compression — Decomposing a Fixed Corpus Through Frozen Instruments, and Its Bridge to the Second Law of Infodynamics

Abstract: Information is physical, countable, and I will argue compressible in a way that has not yet been named. I will present three linked ideas and the systems that run them. Derived Data Abundance (DDA): a fixed corpus of real data, projected through a panel of N frozen, approximately-independent measurement instruments (embedders), yields up to N + C(N,2) (+1) structured supervisory signals per input - no synthetic generation, and structurally outside the model-collapse regime that degrades recursive AI training. Meaning compression is the ratio view: structured signal extracted per unit of raw data, which I propose as a fourth category of compression alongside bit-, weight-, and activation-compression. Teleological Constellation Training (TCT): the same frozen panel becomes an alignment target - a "constellation" of identity centroids, each in its own measurement space, never flattened into one vector - and a generator is trained to land inside it, with every output verified geometrically at inference. Where this meets information physics: a well-designed panel is built to maximise differentiated information per instrument - each must add new bits, and a redundant instrument is noise and is retired (Shannon information made an engineering contract, measured in bits against a real outcome). And aligning a generator to a frozen constellation drives its output distribution toward a high-symmetry, low-entropy configuration around the identity centroid - the preferred low-entropy state your second law of infodynamics predicts, here observable in a learning machine. I will show this running across three production systems (panels of 7, 13, and 21 frozen instruments, spanning video, code, and civic matching) and present measured results: a voice reproduced at 0.961 mean speaker-embedding similarity (encoder-matched - I will state the cross-encoder caveat plainly) and a style model that holds character under adversarial prompting (public weights). I will close with a concrete joint experiment: measuring the entropy of generated outputs collapsing toward the constellation across training, open to scrutiny by IPI.

Speaker: Chris Royse

Bio: Chris Royse is the founder of Leapable.ai and socialmedia2.com and the author of "Teleological Constellation Training: Multi-Embedding Decomposition as Meaning Compression" (2026). His work treats a panel of frozen, independent embedders as measurement instruments — decomposing a fixed corpus into structured supervisory signals (Derived Data Abundance) and using the same frozen panel as a geometric alignment target for identity-locked generation. He has applied the method across text, video, and civic matching, reproducing a voice at 0.961 speaker-embedding similarity and training a style model with public weights. He also wrote "The Symmetry of Knowing," accepted to the 2026 AEJMC conference.

6^th of June @ 17.00 London time zone. Live YouTube talk and debates via online Teams after – a link will be emailed to the IPI members.