Inteligencia Artificial jurídica y el desafío de la veracidad: análisis de alucinaciones, optimización de RAG y principios para una integración responsable

This technical report analyzes the challenge of "hallucinations" (false information) in LLMs applied to law. It examines their causes, manifestations, and the effectiveness of the RAG mitigation strategy, highlighting its limitations and proposing holistic optimizations. The paper explores the ethical and regulatory implications, emphasizing human oversight as an irreplaceable role. It concludes that the solution lies not in incrementally improving generative models, but in adopting a "consultative" AI paradigm that prioritizes veracity and traceability, acting as a tool to amplify, not replace, professional judgment. -- Este informe t\'ecnico analiza el desaf\'io de las "alucinaciones" (informaci\'on falsa) en los LLMs aplicados al derecho. Se examinan sus causas, manifestaciones y la efectividad de la estrategia de mitigaci\'on RAG, exponiendo sus limitaciones y proponiendo optimizaciones hol\'isticas. Se exploran las implicaciones \'eticas y regulatorias, enfatizando la supervisi\'on humana como un rol insustituible. El documento concluye que la soluci\'on no reside en mejorar incrementalmente los modelos generativos, sino en adoptar un paradigma de IA "consultiva" que priorice la veracidad y la trazabilidad, actuando como una herramienta para amplificar, y no sustituir, el juicio profesional.

Inteligencia Artificial para la conservación y uso sostenible de la biodiversidad, una visión desde Colombia (Artificial Intelligence for conservation and sustainable use of biodiversity, a view from Colombia)

The rise of artificial intelligence (AI) and the aggravating biodiversity crisis have resulted in a research area where AI-based computational methods are being developed to act as allies in conservation, and the sustainable use and management of natural resources. While important general guidelines have been established globally regarding the opportunities and challenges that this interdisciplinary research offers, it is essential to generate local reflections from the specific contexts and realities of each region. Hence, this document aims to analyze the scope of this research area from a perspective focused on Colombia and the Neotropics. In this paper, we summarize the main experiences and debates that took place at the Humboldt Institute between 2023 and 2024 in Colombia. To illustrate the variety of promising opportunities, we present current uses such as automatic species identification from images and recordings, species modeling, and in silico bioprospecting, among others. From the experiences described above, we highlight limitations, challenges, and opportunities for in order to successfully implementate AI in conservation efforts and sustainable management of biological resources in the Neotropics. The result aims to be a guide for researchers, decision makers, and biodiversity managers, facilitating the understanding of how artificial intelligence can be effectively integrated into conservation and sustainable use strategies. Furthermore, it also seeks to open a space for dialogue on the development of policies that promote the responsible and ethical adoption of AI in local contexts, ensuring that its benefits are harnessed without compromising biodiversity or the cultural and ecosystemic values inherent in Colombia and the Neotropics.

Métodos para la Selección y el Ajuste de Características en el Problema de la Detección de Spam

The email is used daily by millions of people to communicate around the globe and it is a mission-critical application for many businesses. Over the last decade, unsolicited bulk email has become a major problem for email users. An overwhelming amount of spam is flowing into users' mailboxes daily. In 2004, an estimated 62% of all email was attributed to spam. Spam is not only frustrating for most email users, it strains the IT infrastructure of organizations and costs businesses billions of dollars in lost productivity. In recent years, spam has evolved from an annoyance into a serious security threat, and is now a prime medium for phishing of sensitive information, as well the spread of malicious software. This work presents a first approach to attack the spam problem. We propose an algorithm that will improve a classifier's results by adjusting its training set data. It improves the document's vocabulary representation by detecting good topic descriptors and discriminators.

Enfoque Odychess: Un método dialéctico, constructivista y adaptativo para la enseñanza del ajedrez con inteligencias artificiales generativas

Chess teaching has evolved through different approaches, however, traditional methodologies, often based on memorization, contrast with the new possibilities offered by generative artificial intelligence, a technology still little explored in this field. This study seeks to empirically validate the effectiveness of the Odychess Approach in improving chess knowledge, strategic understanding, and metacognitive skills in students. A quasi-experimental study was conducted with a pre-test/post-test design and a control group (N=60). The experimental intervention implemented the Odychess Approach, incorporating a Llama 3.3 language model that was specifically adapted using Parameter-Efficient Fine-Tuning (PEFT) techniques to act as a Socratic chess tutor. Quantitative assessment instruments were used to measure chess knowledge, strategic understanding, and metacognitive skills before and after the intervention. The results of the quasi-experimental study showed significant improvements in the experimental group compared to the control group in the three variables analyzed: chess knowledge, strategic understanding, and metacognitive skills. The complementary qualitative analysis revealed greater analytical depth, more developed dialectical reasoning, and increased intrinsic motivation in students who participated in the Odychess method-based intervention. The Odychess Approach represents an effective pedagogical methodology for teaching chess, demonstrating the potential of the synergistic integration of constructivist and dialectical principles with generative artificial intelligence. The implications of this work are relevant for educators and institutions interested in adopting innovative pedagogical technologies and for researchers in the field of AI applied to education, highlighting the transferability of the language model adaptation methodology to other educational domains.

Rastreo muscular móvil usando magnetomicrometría -- traducción al español del articulo "Untethered Muscle Tracking Using Magnetomicrometry" por el autor Cameron R. Taylor

Muscle tissue drives nearly all movement in the animal kingdom, providing power, mobility, and dexterity. Technologies for measuring muscle tissue motion, such as sonomicrometry, fluoromicrometry, and ultrasound, have significantly advanced our understanding of biomechanics. Yet, the field lacks the ability to monitor muscle tissue motion for animal behavior outside the lab. Towards addressing this issue, we previously introduced magnetomicrometry, a method that uses magnetic beads to wirelessly monitor muscle tissue length changes, and we validated magnetomicrometry via tightly-controlled in situ testing. In this study we validate the accuracy of magnetomicrometry against fluoromicrometry during untethered running in an in vivo turkey model. We demonstrate real-time muscle tissue length tracking of the freely-moving turkeys executing various motor activities, including ramp ascent and descent, vertical ascent and descent, and free roaming movement. Given the demonstrated capacity of magnetomicrometry to track muscle movement in untethered animals, we feel that this technique will enable new scientific explorations and an improved understanding of muscle function. -- -- El tejido muscular es el motor de casi todos los movimientos del reino animal, ya que proporciona fuerza, movilidad y destreza. Las tecnolog\'ias para medir el movimiento del tejido muscular, como la sonomicrometr\'ia, la fluoromicrometr\'ia y el ultrasonido, han avanzado considerablemente la comprensi\'on de la biomec\'anica. Sin embargo, este campo carece de la capacidad de rastrear el movimiento del tejido muscular en el comportamiento animal fuera del laboratorio. Para abordar este problema, presentamos previamente la magnetomicrometr\'ia, un m\'etodo que utiliza peque\~nos imanes para rastrear de forma inal\'ambrica los cambios de longitud del tejido muscular, y validamos la magnetomicrometr\'ia mediante pruebas estrechamente controladas in situ. En este estudio validamos la precisi\'on de la magnetomicrometr\'ia en comparaci\'on con la fluoromicrometr\'ia usando un modelo de pavo in vivo mientras corre libremente. Demostramos el rastreo en tiempo real de la longitud del tejido muscular de los pavos que se mueven libremente ejecutando varias actividades motoras, incluyendo el ascenso y el descenso en rampa, el ascenso y el descenso vertical, y el movimiento libre. Dada la capacidad demostrada de la magnetomicrometr\'ia para rastrear el movimiento muscular en animales en un contexto m\'ovil, creemos que esta t\'ecnica permitir\'a nuevas exploraciones cient\'ificas y una mejor comprensi\'on de la funci\'on muscular.

A Non Parametric Model for the Forecasting of the Venezuelan Oil Prices

A neural net model for forecasting the prices of Venezuelan crude oil is proposed. The inputs of the neural net are selected by reference to a dynamic system model of oil prices by Mashayekhi (1995, 2001) and its performance is evaluated using two criteria: the Excess Profitability test by Anatoliev and Gerko (2005) and the characteristics of the equity curve generated by a trading strategy based on the neural net predictions. ----- Se introduce aqui un modelo no parametrico para pronosticar los precios del petroleo Venezolano cuyos insumos son seleccionados en base a un sistema dinamico que explica los precios en terminos de dichos insumos. Se describe el proceso de recoleccion y pre-procesamiento de datos y la corrida de la red y se evaluan sus pronosticos a traves de un test estadistico de predictibilidad y de las caracteristicas del Equity Curve inducido por la estrategia de compraventa bursatil generada por dichos pronosticos.

Prototipo de video juego activo basado en una cámara 3D para motivar la actividad física en niños y adultos mayores

This document describes the development of a video game prototype designed to encourage physical activity among children and older adults. The prototype consists of a laptop, a camera with 3D sensors, and optionally requires an LCD screen or a projector. The programming component of this prototype was developed in Scratch, a programming language geared towards children, which greatly facilitates the creation of a game tailored to the users' preferences. The idea to create such a prototype originated from the desire to offer an option that promotes physical activity among children and adults, given that a lack of physical exercise is a predominant factor in the development of chronic degenerative diseases such as diabetes and hypertension, to name the most common. As a result of this initiative, an active video game prototype was successfully developed, based on a ping-pong game, which allows both children and adults to interact in a fun way while encouraging the performance of physical activities that can positively impact the users' health.

Estimacion de carga muscular mediante imagenes

Un problema de gran interes en disciplinas como la ocupacional, ergonomica y deportiva, es la medicion de variables biomecanicas involucradas en el movimiento humano (como las fuerzas musculares internas y torque de articulaciones). Actualmente este problema se resuelve en un proceso de dos pasos. Primero capturando datos con dispositivos poco pr\'acticos, intrusivos y costosos. Luego estos datos son usados como entrada en modelos complejos para obtener las variables biomecanicas como salida. El presente trabajo representa una alternativa automatizada, no intrusiva y economica al primer paso, proponiendo la captura de estos datos a traves de imagenes. En trabajos futuros la idea es automatizar todo el proceso de calculo de esas variables. En este trabajo elegimos un caso particular de medicion de variables biomecanicas: el problema de estimar el nivel discreto de carga muscular que estan ejerciendo los musculos de un brazo. Para estimar a partir de imagenes estaticas del brazo ejerciendo la fuerza de sostener la carga, el nivel de la misma, realizamos un proceso de clasificacion. Nuestro enfoque utiliza Support Vector Machines para clasificacion, combinada con una etapa de pre-procesamiento que extrae caracter{\i}sticas visuales utilizando variadas tecnicas (Bag of Keypoints, Local Binary Patterns, Histogramas de Color, Momentos de Contornos) En los mejores casos (Local Binary Patterns y Momentos de Contornos) obtenemos medidas de performance en la clasificacion (Precision, Recall, F-Measure y Accuracy) superiores al 90 %.

Diseño y desarrollo de aplicación móvil para la clasificación de flora nativa chilena utilizando redes neuronales convolucionales

Introduction: Mobile apps, through artificial vision, are capable of recognizing vegetable species in real time. However, the existing species recognition apps do not take in consideration the wide variety of endemic and native (Chilean) species, which leads to wrong species predictions. This study introduces the development of a chilean species dataset and an optimized classification model implemented to a mobile app. Method: the data set was built by putting together pictures of several species captured on the field and by selecting some pictures available from other datasets available online. Convolutional neural networks were used in order to develop the images prediction models. The networks were trained by performing a sensitivity analysis, validating with k-fold cross validation and performing tests with different hyper-parameters, optimizers, convolutional layers, and learning rates in order to identify and choose the best models and then put them together in one classification model. Results: The final data set was compounded by 46 species, including native species, endemic and exotic from Chile, with 6120 training pictures and 655 testing pictures. The best models were implemented on a mobile app, obtaining a 95% correct prediction rate with respect to the set of tests. Conclusion: The app developed in this study is capable of classifying species with a high level of accuracy, depending on the state of the art of the artificial vision and it can also show relevant information related to the classified species.

El Lenguaje Natural como Lenguaje Formal

Formal languages theory is useful for the study of natural language. In particular, it is of interest to study the adequacy of the grammatical formalisms to express syntactic phenomena present in natural language. First, it helps to draw hypothesis about the nature and complexity of the speaker-hearer linguistic competence, a fundamental question in linguistics and other cognitive sciences. Moreover, from an engineering point of view, it allows the knowledge of practical limitations of applications based on those formalisms. In this article I introduce the adequacy problem of grammatical formalisms for natural language, also introducing some formal language theory concepts required for this discussion. Then, I review the formalisms that have been proposed in history, and the arguments that have been given to support or reject their adequacy. ----- La teor\'ia de lenguajes formales es \'util para el estudio de los lenguajes naturales. En particular, resulta de inter\'es estudiar la adecuaci\'on de los formalismos gramaticales para expresar los fen\'omenos sint\'acticos presentes en el lenguaje natural. Primero, ayuda a trazar hip\'otesis acerca de la naturaleza y complejidad de las competencias ling\"u\'isticas de los hablantes-oyentes del lenguaje, un interrogante fundamental de la ling\"u\'istica y otras ciencias cognitivas. Adem\'as, desde el punto de vista de la ingenier\'ia, permite conocer limitaciones pr\'acticas de las aplicaciones basadas en dichos formalismos. En este art\'iculo hago una introducci\'on al problema de la adecuaci\'on de los formalismos gramaticales para el lenguaje natural, introduciendo tambi\'en algunos conceptos de la teor\'ia de lenguajes formales necesarios para esta discusi\'on. Luego, hago un repaso de los formalismos que han sido propuestos a lo largo de la historia, y de los argumentos que se han dado para sostener o refutar su adecuaci\'on.