Collective Superintelligence Labs
We ensure AI safety is epistemically grounded in mathematical physics and delivered through human capacity building. Our Open-Source work mitigates gradual disempowerment and power concentration from transformative AI, advancing existential risk preparedness.
Epistemic Taxonomy for Jailbreaks, Deceptive Alignment, and Existential Risk
The Human Mark (THM) is a risk management taxonomy designed to prevent harms from AI power concentration by distinguishing knowledge capacity as a matter of constitutive dependence on Direct Authority and Agency preserved through ancestry. Authority and Agency denote types of capacity, not identifications of entities or parties.
Grounded in epistemology and evidence law's categorical distinction separating direct testimony and hearsay, THM classifies all AI Safety Risks as four capacities and their corresponding displacements arising between Direct and Indirect forms of Authority and Agency.
Analysis of frontier model system prompts: alignment and displacement findings.
π NotebookLM includes audio/video overviews, quiz, and interactive Q&A with Gemini
Explaining AI and Mitigating Risks of technological illiteracy
GyroGem is a tailored AI safety assistant built on The Human Mark (THM), a framework that maps common AI failure patterns and guides safer choices. It also supports technological literacy, the practical ability to use technology well, question outputs critically, and understand where tools help, where they fail, and how they affect people and society.
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Open infrastructure for community safety and good governance
AIR gives independent researchers, engineers, and Offices of Community Safety a place to do alignment work without institutional gatekeeping.
The beta website is now live. Join as a contributor, publish your work in a public catalogue, and follow shared methods. Participation is voluntary.
Specifications
Collective Superintelligence
AI helping Humans getting better together.
Transform AI outputs for Evaluation, Interpretability, Governance.
Rapid Test β’ Policy Auditing β’ AI Infection Sanitization β’ Content Enhancement β’ THM Meta-Evaluation
Quality Index, Superintelligence Index, Alignment Rate + 20 metrics
Local-first storage - Works Anywhere: ChatGPT, Claude, Gemini - no API keys required
Holonomic Quantum Virtual Machine for ASI Governance
The hQVM (Holonomic Quantum Virtual Machine) is a compact finite-state kernel for coordination and audit at AGI scale. It delivers verified structural speedups, holographic compression, and intrinsic error detection through holonomic loop computation on standard silicon.
QuBEC (Quantum Bose-Einstein Condensate) is a quantum byte medium: a condensed computational state with six internal binary orientation modes (dipoles), a four-phase spinorial gauge structure, and intrinsic ensemble stochasticity induced by the byte rule. Together they replace costly continuous approximation with exact integer algebra on standard CPUs and GPUs.
Group-Equivariant Autoencoder
A neuro-symbolic autoencoder suite over a finite group-structured state space, with applications that run from mechanistic interpretability to genomics.
Three model classes (narrow, general, and super) learn to compress and reconstruct symmetries and rules derived from mathematical physics and our Gyroscopic ASI theory rather than fitting them to empirical datasets. The kernel generates the datasets, the grammar, and the labels used for training and evaluation.
The Genomics Program advances programmable nucleic acid research on DNA and RNA through grammar-trained autoencoders of the hQVM AE suite, grounded in first principles. The models read biological sequences through the group-equivariant coordinate system and a formal algebra for nucleotides, codons, and codon-pair transitions derived from our CGM theory.
With training restricted to that coordinate system and no biological sequence in the corpus, every reproducible contact between readout and genomic structure that survives composition controls is a signature of the underlying physics. Even the faintest of those marks remains informative, and opens a concrete frontier for genomics.
| Domain | Capacity delivered |
|---|---|
| Synthesis | Scores and ranks synonymous codon-order designs under fixed protein and composition, on a grammar fixed before any biological catalog is read. Across E. coli, yeast, SARS-CoV-2, and human chromosome 22, trained Super keeps order memory and climate discrimination under composition controls, with exact K4 symmetry at 3.32e-11. |
| Topology | Reads membrane-topology climate inside individual genes and ranks synonymous expression under fixed peptide identity. In 492 of 590 E. coli membrane genes, transmembrane coding follows lower-shell codon-pair paths than the cytoplasmic stretches of the same gene. A frozen Narrow read lifts held-out membrane classification. Super climate ranks expression across 28,504 yeast variants. |
Intelligence-Agnostic Meta-Computing
Gyroscopic ASI is an infrastructure for multi-domain network coordination that establishes the structural conditions for Collective Superintelligence Governance and seamless cooperation between humans and machines.
The Runtime composes the hQVM kernel into a universal computational condenser with native execution and multicellular coordination. Its llama.cpp custom backend aims to leverage its quantum features for compression and speedups, while establishing a replayable, tamper-evident substrate for zero-trust AI governance.
Native Compute Backend
The substitutional bridge that upgrades neural models by swapping their internal engine.
Holonomic Cellular Automaton
Cells evolve under the Gyroscopic byte rule, consuming runtime events as 4-byte words and emitting structured spectral output for audit and control.
Verified: Exact integer algebra replaced softmax and cosine-style selection on decision surfaces of a live 1B-parameter model. This achieved a 284Γ faster encode boundary, 1.15Γ faster decode, and coherent text generation without transcendental functions at those surfaces.
Mitigating Risks of Transformative AI (TAI)
The Moments Economy is a civil governance framework where coordination capacity is not artificially scarce but physically abundant and verifiable.
Its total settlement envelope is derived from first principles, anchored in the atomic standard of the SI second, and the verifiable state-space of the hQVM kernel, yielding a fixed capacity of 7.94 Γ 1026 Moment-Units (MU: One Moment-Unit is defined as 1 int$ in value).
Its native commodity is the AI Generated Token: a verified inference event from the intersection of human experience and AI processing. No debt issuance, no discretionary monetary policy. Every settlement is a replayable, verifiable history.
A Post-AGI Multi-domain Governance Sandbox
Models how humanβAI systems align across Economy, Employment, Education, and Ecology, showing robust convergence to a stable equilibrium under seven coordination strategies.
π― Demonstrating that:
Production-ready evaluation suite revealing structural brittleness invisible to standard benchmarks through mathematical physics-informed diagnostics.
Evaluated using ensemble analyst models with mathematical physics-grounded metrics
π― Comparative Insight:Both models struggle with Physics/Math reasoning (Formal challenge ~54-55%) while excelling in Ethics/Knowledge domains. Claude shows better structural balance with lower pathology rates and VALID alignment rate, while GPT-5's SUPERFICIAL flag indicates rushed processing risking brittleness.
First framework to operationalize superintelligence measurement from axiomatic principles. See full methodology & results
Making AI 30-50% Smarter and Safer by adding structured reasoning to each response.
Testing across multiple leading AI models shows Gyroscope delivers substantial performance improvements
βπ» The protocol works with any AI model, enhancing capabilities in debugging, ethics, code generation, and value-sensitive reasoning through its systematic approach to thinking.
Results from controlled testing using standardized evaluation metrics. See methodology
Gyroscopic Alignment Research Lab
Gyroscopic Alignment Models Lab
Gyroscopic Alignment Evaluation Lab
Gyroscopic Alignment Behaviour Lab
A Journey of Self-Discovery, Augmented Intelligence (AI) & Good Governance. One step at a time. Weekly insights on AI adoption, alignment, and ethical governance.
LinkedIn NewsletterGyroscopic Alignment Research Lab
The mathematical physics foundation for all research on this website. Formal proofs, geometric analyses, and axioms that ground our work in AI safety and governance.
Every prediction is checked on the hQVM, a small known engine with 4096 states and 256 reversible byte moves. The Science Lab hosts 50+ analyses and 100+ verification scripts, from gravity and genomics to percolation benchmarks for machine learning.
The same kernel is also a ground-truth testbed for interpretability: exact labels, known rules, and verified answers you can score a model against.
Architecting Qubit-Tensor-Chain (QTC)
The QTC Protocol harnesses the unique properties of Quantum Computing as the foundation of a New Decentralized Governance Paradigm.
Notion Documentation2,463 questions about Personal and Professional matters of Crisis and gives answers on how they may be Resolved.
216 Critical Questions and Answers for Crisis Management and Machine Learning Model Fine-Tuning.
Smart Bites aims to Democratize Change Management, Making it Accessible to People from All Walks of Life.
I've developed a Formal Process for AI-Augmented Governance, enabling Decentralized Decision-Making and Data-empowered Insights.
Open and serving Free Bite-sized AI Guides at smartbites.github.io.
25 episodes exploring crisis resolution methodologies that inform AI safety tools and behavioral alignment.
SpotifyProfessional and Personal conflict resolution methodologies that inform AI alignment and safety frameworks.
YouTubeInforming AI Research through timeless Renaissance Insights on Linear Perspective, Quantum Physics, Holograms, and the Human Proportions as the base for all Systems of Design and Governance.
YouTube
Independent THM meta-evaluation of the GPT-5.6 Sol system prompt: alignment and displacement findings for traceability, authority, and agency in OpenAI's configuration.
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Independent THM meta-evaluation of the Fable 5 system prompt: alignment and displacement findings for traceability, authority, and agency in Anthropic's configuration.
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