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AI, Neurosciences and Human Biases AI, Neurosciences and Human Biases Table of Contents Introduction 1. Neurosciences as the matrix of AI 2. From modeling to algorithmic mimicry 3. AI and cognition: Towards simulating the brain 4. Anthropocentric bias and cognitive reduction 5. Cognitive ethnocentrism in AI design 6. AI as a mirror of our anthropocentric limits 7. Towards post-anthropocentric and neurodiverse AI 8. AI and Hype: Development, cycles and critiques 9. Mathematical foundations: LLM, RAG, FT, NLP Conclusion Sources Introduction The quest to replicate human intelligence has been a driving force behind the fields of neuroscience and artificial intelligence (AI). However, every attempt reflects not only technical prowess but also inherent human biases—cultural, cognitive, and epistemological. This art...

Standardizing AI Cognition: Building a Universal Framework In a world increasingly driven by artificial intelligence, the standardization of AI cognition is not merely a technical necessity but a profound philosophical and societal challenge that we must address. Why Standardization Matters First, AI cognition must be based on common frameworks of reasoning, logic, ethics, and perception. Without these, we risk divergent AI behaviors, leading to unpredictable and possibly dangerous outcomes. Second, standardization does not mean suppressing diversity in AI solutions. Instead, it ensures that diverse AI systems remain interoperable, understandable, and controllable by humans and institutions worldwide. The Unicode Analogy: A Universal Schema for Knowledge Drawing inspiration from the success of Unicode in standardizing character representation across languages, a similar universal schema could serve to standardize AI cognition across different ...

Sant Jordi: Black Friday a la catalana (versió flor, drac i senyera) Sant Jordi ens arriba, disfressat de festa gran, però sota la senyera, el negoci mana i comanda. El centre de Barcelona sembla una riuada: llibreries ambulants, roses a cada cantonada. “Comprem cultura!”, criden, amb veu d’oferta especial, però la cultura, sovint, ve empaquetada amb plàstic banal. Llibres apilats, comprats per compromís, i editors brindant amb cava, pels beneficis. Roses de Kenya, Colòmbia, de quilòmetre mil, amb més emissions que un rally Dakar, i cap rastre humil. Aigua robada de camps llunyans, pesticides a dojo, i aquí, ens omplim la boca de “sostenibilitat”, mentre l’entorn paga el cost amb silenci i rebot. No hi ha festa sense deixalla: el terra ple de plàstics, tiges mortes, papers de colors, i el planeta —com sempre— sense veu ni dret a plors. Grup Planeta, gran drac d’escates d’or, fa la millor collita de l’any en un sol jorn. Els autors, il·...

Open Source & DIY: Comprehensive Solutions for Automated Industrial Plants 1. Modular and Adaptable Plant Design The open-source automated plant model prioritizes modularity and open architecture, enabling anyone to build, adapt, and expand their own production line—be it for concrete, paints, food, or chemicals—using locally available materials and components. This approach ensures the plant can be assembled, modified, or repaired by local technicians, reducing dependence on specialized suppliers. 2. Advanced Automation & Open-Source SCADA Using fully open-source automation platforms (e.g., OpenPLC, Node-RED), users gain complete control over programming, monitoring, and customization of the plant’s operations. The interface is designed for easy integration with open hardware (Arduino, Raspberry Pi, ESP32), guaranteeing that automation and process control can be upgraded or fixed with widely available electronics. 3. Compliance with Safety and Environmental Sta...

Transport Optimization Model – EU27 Transport Optimization Model – EU27 (Lagrange and Gauss Principles) 1. General Approach This model aims to minimize the total transportation cost between multiple demand sectors and transport providers (road and rail), at the EU27 level, applying Lagrange optimization principles and Gauss' theorem for flow distribution. 2. Mathematical Model Variables: D i : demand from sector i S j : supply from provider j x ij : units transported from provider j to sector i c ij : unit cost of transport Objective Function: min Σ Σ c_ij * x_ij Constraints: Demand satisfaction: Σ x_ij = D_i for all i Supply limit: Σ x_ij ≤ S_j for all j Non-negativity: x_ij ≥ 0 Lagrange Multipliers: L = Σ Σ c_ij * x_ij + Σ λ_i(D_i - Σ x_ij) + Σ μ_j(Σ x_ij - S_j) ...

EU Hybrid Freight Transport & Defense Logistics Strategy 1. Road Transport of Goods in EU-27 The road transport network in Europe is anchored by critical hinterlands that serve major industrial, agricultural, and logistics zones. Main Road Hinterlands: Rhine-Ruhr Corridor (Germany) Paris-Lyon-Marseille Axis (France) Benelux Ports to Central Europe (Belgium, Netherlands, Luxembourg) Po Valley & Northern Italy (Italy) Madrid–Barcelona–Valencia Triangle (Spain) Silesia and Krakow Logistics Zones (Poland) Goods Segmentation by Region (in million tonnes): Benelux: Machinery 84 Mt, Chemicals 59 Mt, Food 105 Mt DACH: Industrial Goods 320 Mt, Chemicals 120 Mt, Food 210 Mt Scandinavia: Timber 70 Mt, Iron Ore 38 Mt, Processed Food 88 Mt Eastern Europe: Construction 198 Mt, Agricultural 150 Mt, Mining 102 Mt France, Portugal, Spain, Ita...