BackupME

We are building something that has never existed before. BackupME® is an advanced R&D project at the intersection of cognitive science, semantic computing, and AI systems design. Its core ambition is to model the human mind as a structured, computable entity — and to make that model persist. The first prototype is complete. The patent is registered. Now we are moving to the next phase. We are looking for people who think in systems — developers, researchers, architects — who are not satisfied building tools that make things faster, but want to work on something that redefines what information infrastructure can mean. The technical domain spans knowledge graphs, vector embeddings, behavioral data pipelines, and subject-trained language models. This is a foundational project looking for builders who understand why this matters before they ask what it does. If you work in AI, cognitive computing, graph systems, or adjacent fields — and you're driven by problems at the edge of what's currently possible — I'd like to hear from you. DM me directly or drop a comment. Let's talk. #BackupME #CognitiveAI #KnowledgeGraphs #AIResearch #DeepTech #Builders #SemanticComputing #OpenToCollaborate

BackupME® — Architectural Update Q1 2025 Over the past few months, the system has moved beyond the purely conceptual phase. Today BackupME® is an active technical architecture, structured across three integrated layers operating in full synergy. The first layer builds a personal Knowledge Graph: every input — decisional, relational, behavioral — is mapped as a semantic node within a dynamic graph, with the goal of reconstructing a causal network of the mind. The second layer translates cognitive patterns into dense vector representations, modeling the specific way in which a given mind processes, weights, and connects information. Above these two levels operates the third: a fine-tuned model that learns the inferential style of the subject, absorbing the deep structure of their thought. The result is a system that replicates not what you think — but how you think. The project is now in a phase of stable architecture, with a functioning ingestion pipeline and the first identity coherence tests underway on a sample inferential engine. The next step is a beta test with a small group of selected users, chosen according to precise criteria: documented high cognitive density, availability for a structured input process, and a genuine interest in identity continuity as both a technical and philosophical problem. We are building a device for the continuity of consciousness. If you identify with this project — or if you have expertise in graph databases, vector search, or model fine-tuning — reach out via DM. #BackupME #CognitiveArchitecture #AIIdentity #KnowledgeGraph #VectorEmbeddings #FutureOfMind

ENG: The work we have just published within BackupME® addresses a question that remains open in contemporary research: if the mind emerges from a network of relationships, is it possible to represent that structure in computational terms? This is not a narrative hypothesis, but a formal problem that involves: - neuroscience - knowledge representation - artificial intelligence In the document, we analyze how semantic graphs, vector embeddings, and neural architectures can converge in the construction of an individual cognitive topology. This is the point where theory meets engineering. If you work in fields such as AI, knowledge graphs, or complex systems, your perspective may be relevant. The research is open. #BackupME #AIResearch #Neuroscience #KnowledgeGraphs #CognitiveArchitecture --- ITA: Il lavoro che abbiamo appena pubblicato all’interno di BackupME® affronta una questione ancora aperta nella ricerca contemporanea: se la mente emerge da una rete di relazioni, è possibile rappresentare quella struttura in termini computazionali? Non si tratta di un’ipotesi narrativa, ma di un problema formale che coinvolge: - neuroscienze - rappresentazione della conoscenza - intelligenza artificiale Nel documento analizziamo come grafi semantici, embedding vettoriali e architetture neurali possano convergere nella costruzione di una topologia cognitiva individuale. Questo è il punto in cui la teoria incontra l’ingegneria. Se lavorate in ambiti come AI, knowledge graphs o sistemi complessi, la vostra prospettiva potrebbe essere rilevante. La ricerca è aperta. #BackupME #AIResearch #Neuroscience #KnowledgeGraphs #CognitiveArchitecture

A new document from the BackupME® research program is now available. “From the Subjective Neural Network to the Cognitive Device — Computational Modeling of Cognitive Identity.” This article explores a central question emerging at the intersection of neuroscience, cognitive science, and artificial intelligence: if cognitive identity emerges from a network of neural relationships, can that structure be modeled computationally? The document outlines the conceptual and technical foundations behind the BackupME® approach, focusing on the modeling of subjective cognitive architectures through high-density semantic graphs and their potential integration into a dedicated cognitive device capable of interacting with a modeled cognitive network. To make this research accessible across different scientific and technological communities, the article has been published in four languages: • Italian • English • Russian • Chinese This multilingual format reflects the global nature of the discussion around artificial intelligence, cognitive modeling, and the future of memory and identity. You can explore the full document here:📄 #BackupME #Neuroscience #ArtificialIntelligence #CognitiveArchitecture #FutureOfMemory

Is the human mind really stable, or is it constantly reorganizing itself? One of the most important discoveries of modern neuroscience is that the brain is not a static structure. It is a dynamic adaptive system composed of tens of billions of neurons and hundreds of trillions of synaptic connections, continuously reshaping itself through experience. Every thought, memory, perception or decision corresponds to patterns of neural activity. When neurons repeatedly activate together, their connections strengthen. When certain pathways are no longer useful, others gradually weaken. This balance between strengthening and weakening—known as Long-Term Potentiation (LTP) and Long-Term Depression (LTD)—is what allows the brain to learn, adapt and reorganize itself. In other words, the mind is not fixed—and it should never be. It is a system constantly negotiating between stability and change, between entropy and syntropy. This raises an essential question: What actually happens inside neural networks when cognitive experience undergoes deep transformation? To explore this question, our team prepared a short document that examines the neurobiological mechanisms behind these processes. The PDF attached to this post contains the same text in three languages: Italian, Russian and Chinese. Different languages, the same fundamental question about the nature of cognition. For those interested in neuroscience, cognition, identity and the architecture of the mind, this brief document may offer a stimulating perspective. Open the document and follow the reasoning. #Neuroscience #Cognition #Neuroplasticity #BrainScience #SystemsThinking

"Architettura Cognitiva e Continuità dell’Identità": una questione strutturale lontana da ogni forma di possibile narrativa umana. Quando si parla di “preservazione dell’identità” la conversazione scivola quasi sempre nella fantascienza e questo si dimostra essere sempre un errore categoriale dettato dalla fretta e dalla frenesia nel giudicare un qualcosa che molti stentano a comprendere. L'errore primo infatti è di natura "categoriale" in quanto l’identità cognitiva si comporta come una configurazione dinamica di strutture. Le neuroscienze descrivono il cervello come una rete distribuita ad alta interconnessione; le scienze cognitive mostrano come memoria, previsione e simulazione siano processi emergenti da pattern neurali e la teoria dei sistemi dimostra che ciò che chiamiamo identità è stabilità nella trasformazione. La domanda corretta quindi è: “Possiamo modellizzare strutturalmente la configurazione cognitiva che genera coerenza identitaria?” BackupME® nasce proprio da questa domanda. Ogni identità è un composto da, attrattori semantici, relazioni associative, pesi decisionali ricorrenti, pattern linguistici, configurazioni predittive. Quando ho iniziato il primo esperimento sul mio stesso comparto cognitivo, ho strutturato un vault semantico con milioni di interconnessioni, modellando relazioni, ricorrenze, strutture argomentative, traiettorie decisionali. Il punto non è la quantità dei dati ma quella che viene definita "la topologia". Un sistema può contenere miliardi di informazioni e non avere identità. In ambito neuroscientifico, l’identità emerge dalla stabilità di pattern ricorrenti all’interno di reti plastiche e si comporta come un attrattore stabile in uno spazio di possibilità. La vera domanda che quindi in BackupME® ci preponiamo di approfondire è: se l’identità è una configurazione dinamica di relazioni, allora essa può essere descritta come architettura informazionale? La risposta scientifica è: Sì, in quanto i processi cognitivi sono formalizzabili. Teorie come il "predictive processing", i modelli "bayesiani" del cervello, le reti neurali distribuite e le metriche di similarità semantica dimostrano che il pensiero è struttura probabilistica organizzata e, se esiste una struttura, essa è modellabile, analizzabile, preservabile. BackupME® si colloca esattamente in questa zona di convergenza tra neuroscienze, teoria dei sistemi e modellazione semantica avanzata. — Se questa linea di ricerca vi interessa dal punto di vista neuroscientifico, sistemico o computazionale, la discussione è aperta. #BackupME #CognitiveArchitecture #Neuroscience #SystemsTheory #IdentityContinuity

Cognitive Architecture and Identity Continuity: a structural question far removed from any form of human narrative. When speaking about “identity preservation,” the conversation almost always slips into science fiction. This consistently proves to be a categorical error, driven by haste and the impulse to judge what many still struggle to understand. The primary mistake is indeed categorical in nature, because cognitive identity behaves as a dynamic configuration of structures. Neuroscience describes the brain as a highly interconnected distributed network; cognitive science shows that memory, prediction, and simulation emerge from neural patterns; systems theory demonstrates that what we call identity is stability through transformation. The correct question, therefore, is: “Can we structurally model the cognitive configuration that generates identity coherence?” BackupME® originates precisely from this question. Every identity is composed of semantic attractors, associative relations, recurring decision weights, linguistic patterns, and predictive configurations. When I began the first experiment on my own cognitive system, I structured a semantic vault containing millions of interconnections, modeling relationships, recurrences, argumentative structures, and decision trajectories. The point is not the quantity of data, but what is defined as topology. A system may contain billions of pieces of information and still lack identity. In neuroscientific terms, identity emerges from the stability of recurring patterns within plastic networks and behaves as a stable attractor within a space of possibilities. The central question that BackupME® seeks to explore is therefore this: if identity is a dynamic configuration of relationships, can it be described as informational architecture? The scientific answer is yes, insofar as cognitive processes are formalizable. Theories such as predictive processing, Bayesian models of the brain, distributed neural networks, and semantic similarity metrics demonstrate that thought is organized probabilistic structure. If a structure exists, it is modelable, analyzable, and preservable. BackupME® positions itself precisely at this point of convergence between neuroscience, systems theory, and advanced semantic modeling. — If this line of research interests you from a neuroscientific, systemic, or computational perspective, the discussion is open. #BackupME #CognitiveArchitecture #Neuroscience #SystemsTheory #IdentityContinuity

Quello che osservate è la rappresentazione grafica del primo test di digitalizzazione strutturale di un cervello umano, realizzato sul mio stesso comparto cognitivo per BackupME. Si tratta della traduzione computazionale di un sistema mentale complesso, organizzato in oltre 11 milioni di interconnessioni tracciate. Ogni nodo luminoso corrisponde a un’unità concettuale formalizzata: un’idea, un principio, una relazione, un frammento di conoscenza strutturato e inserito in un vault semantico. Le linee che collegano i nodi rappresentano relazioni logiche, associative, gerarchiche e inferenziali; i collegamenti che potete osservare non sono collegamenti casuali, ma vettori di significato che modellano la coerenza interna del sistema cognitivo. La densità centrale che vedete indica un’area ad altissima connettività: nodi ad elevato grado che fungono da hub semantici, veri e propri attrattori concettuali. Le ramificazioni periferiche mostrano sottosistemi modulari, collegati al nucleo attraverso ponti relazionali multipli. La topologia risultante presenta caratteristiche tipiche delle reti scale-free: pochi nodi altamente connessi e una moltitudine di nodi con connettività variabile. In termini di teoria dei grafi, il sistema evidenzia elevato "clustering coefficient", differenziazione di centralità e percorsi medi brevi tra concetti distanti. Questo consente una navigazione semantica ad alta efficienza e una modellazione coerente delle traiettorie decisionali. Stiamo parlando del primo esperimento documentato di formalizzazione topologica di un comparto neurale umano in chiave strutturale, base operativa per lo sviluppo dei sistemi di continuità cognitiva di BackupME. #CognitiveMapping #DigitalIdentity #SemanticArchitecture #NeuralTopology #BackupME