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Willy Marroquin (WillyDevNET)

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Inteligencia artificial y crecimiento económico. Oportunidades y desafíos par...

Willy Marroquin (WillyDevNET)

Artificial neural networks are the heart of machine learning algorithms and artificial intelligence protocols. Historically, the simplest implementation of an artificial neuron traces back to the classical Rosenblatt’s “perceptron”, but its long term practical applications may be hindered by the fast scal- ing up of computational complexity, especially relevant for the training of multilayered perceptron networks. Here we introduce a quantum information-based algorithm implementing the quantum computer version of a perceptron, which shows exponential advantage in encoding resources over alternative realizations. We experimentally test a few qubits version of this model on an actual small-scale quantum processor, which gives remarkably good answers against the expected results. We show that this quantum model of a perceptron can be used as an elementary nonlinear classifier of simple patterns, as a first step towards practical training of artificial quantum neural networks to be efficiently implemented on near-term quantum processing hardware

An Artificial Neuron Implemented on an Actual Quantum Processor

Willy Marroquin (WillyDevNET)

En los ̇ltimos 20 aÒos la Enfermedad de Alzheimer pasÛ de ser el paradigma del envejecimiento normal -aunque prematuro y acelerado-, del cerebro, para convertirse en una enfermedad autÈntica, nosolÛgicamente bien defini- da y con una clara raÌz genÈtica. La enfermedad afecta hoy a m·s de 20 millones de personas, tiene enormes consecuencias sobre la economÌa de los paÌses y constituye uno de los temas de investigaciÛn m·s activos en el ·rea de salud. Este artÌculo revisa el conocimiento actual sobre el tema. En esta primera parte se analizan su epidemiologÌa, patogenia y genÈtica; se enumeran los temas prioritarios de investigaciÛn; se revisa su relaciÛn con el concepto de muerte celular programada (apoptosis) y se enumeran los elementos indis- pensables para el diagnÛstico. Palabras Clave :Enfermedad de Alzhaimer; Demencia; GenÈtica; TerapÈuti- ca.

ENFERMEDAD DE ALZHEIMER PRESENTE TERAP...UTICO Y RETOS FUTUROS

Willy Marroquin (WillyDevNET)

Artificial intelligence and machine learning capabilities are growing at an unprecedented rate. These technologies have many widely beneficial applications, ranging from machine translation to medical image analysis. Countless more such applications are being developed and can be expected over the long term. Less attention has historically been paid to the ways in which artificial intelligence can be used maliciously. This report surveys the landscape of potential security threats from malicious uses of artificial intelligence technologies, and proposes ways to better forecast, prevent, and mitigate these threats. We analyze, but do not conclusively resolve, the question of what the long-term equilibrium between attackers and defenders will be. We focus instead on what sorts of attacks we are likely to see soon if adequate defenses are not developed.

The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and...

Willy Marroquin (WillyDevNET)

There is an increasing interest in exploiting mobile sensing technologies and machine learning techniques for mental health monitoring and intervention. Researchers have effectively used contextual information, such as mobility, communication and mobile phone usage patterns for quantifying individuals’ mood and wellbeing. In this paper, we investigate the effectiveness of neural network models for predicting users’ level of stress by using the location information collected by smartphones. We characterize the mobility patterns of individuals using the GPS metricspresentedintheliteratureandemploythesemetricsasinputtothenetwork. We evaluate our approach on the open-source StudentLife dataset. Moreover, we discuss the challenges and trade-offs involved in building machine learning models for digital mental health and highlight potential future work in this direction.

TowardsDeepLearningModelsforPsychological StatePredictionusingSmartphoneData:...

Willy Marroquin (WillyDevNET)

La Hipertensión, es una de las mayores enfermedades que sufren los Hispanohablantes en el planeta . Es grato poder colocar este documento al público y haber podido hacer parte del equipo , ojalá sirvan a muchos las implementaciones. idioma más hablado según el foro Económico mundial - Me refiero al español ó castellano según sea - segundo idioma y haber podido hacer parte de este equipo. Genuinamente, espero que se curen la mayor cantidad de personas con . Espero genuinamente puedan hacer algúna donación a este esfuerzo grupal. Espero Compartamos este "Paper" así como compartimos memes - En el sentido literal de la significancia- ** Refierase a Wikipedia sino tiene un diccionario a mano.

Deep learning-approach

Willy Marroquin (WillyDevNET)

To thrive in the 21st century, students need more than traditional academic learning. They must be adept at collaboration, communication and problem-solving, which are some of the skills developed through social and emotional learning (SEL). Coupled with mastery of traditional skills, social and emotional proficiency will equip students to succeed in the swiftly evolving digital economy. In 2015, the World Economic Forum published a report that focused on the pressing issue of the 21st-century skills gap and ways to address it through technology (New Vision for Education: Unlocking the Potential of Technology). In that report, we defined a set of 16 crucial proficiencies for education in the 21st century. Those skills include six “foundational literacies”, such as literacy, numeracy and scientific literacy, and 10 skills that we labelled either “competencies” or “character qualities”. Competencies are the means by which students approach complex challenges; they include collaboration, communication and critical thinking and problem-solving. Character qualities are the ways in which students approach their changing environment; they include curiosity, adaptability and social and cultural awareness (see Exhibit 1). In our current report, New Vision for Education: Fostering Social and Emotional Learning through Technology, we follow up on our 2015 report by exploring how these competencies and character qualities do more than simply deepen 21st-century skills. Together, they lie at the heart of SEL and are every bit as important as the foundational skills required for traditional academic learning. Although many stakeholders have defined SEL more narrowly, we believe the definition of SEL is evolving. We define SEL broadly to encompass the 10 competencies and character qualities.1 As is the case with traditional academic learning, technology can be invaluable at enabling SEL.

WEF new vision for education

Willy Marroquin (WillyDevNET)

La expresión “futuro del trabajo” es actualmente uno de los conceptos más populares en las búsquedas en Google. Los numerosos avances tecnológicos de los últimos tiempos están modificando rápidamente la frontera entre las actividades realizadas por los seres humanos y las ejecutadas por las máquinas, lo cual está transformando el mundo del trabajo. Existe un creciente número de estudios e iniciativas que se están llevando a cabo con el objeto de analizar qué significan estos cambios en nuestro trabajo, en nuestros ingresos, en el futuro de nuestros hijos, en nuestras empresas y en nuestros gobiernos. Estos análisis se conducen principalmente desde la óptica de las economías avanzadas, y mucho menos desde la perspectiva de las economías en desarrollo y emergentes. Sin embargo, las diferencias en materia de difusión tecnológica, de estructuras económicas y demográficas, de niveles de educación y patrones migratorios inciden de manera significativa en la manera en que estos cambios pueden afectar a los países en desarrollo y emergentes. Este estudio, El futuro del trabajo: perspectivas regionales, se centra en las repercusiones probables de estas tendencias en las economías en desarrollo y emergentes de África; Asia; Europa del Este, Asia Central y el Mediterráneo Sur y Oriental, y América Latina y el Caribe. Se trata de un esfuerzo mancomunado de los cuatro principales bancos regionales de desarrollo: el African Development Bank Group, el Asian Development Bank, el Banco Interamericano de Desarrollo y el European Bank for Reconstruction and Development. En el estudio se destacan las oportunidades que los cambios en la dinámica del trabajo podrían crear en nuestras regiones. El progreso tecnológico permitiría a los países con los que trabajamos crecer y alcanzar rápidamente mejores niveles de vida que en el pasado

El futuro del trabajo perspectivas regionales

Willy Marroquin (WillyDevNET)

Superada la Guerra Fría, el orden mundial dirigido por Estados Unidos se ve cuestionado por China y Rusia, dos potencias revisionistas que están acercando sus alineamientos estratégicos. China está en camino de convertirse en la mayor economía del mundo y en una potencia militar formidable a la que irrita la hegemonía de Estados Unidos. Parece que China, más que derrocar el orden mundial establecido, busca remodelarlo, especialmente en Asia, con la instauración de un orden sinocéntrico en el que todos los países del área asiática ponganlos intereses chinos por delante de los suyos propios. Está por ver si China tendrá las capacidades para conseguirlo, evitando el conflicto con Estados Unidos.

ASIA Y EL NUEVO (DES)ORDEN MUNDIAL

Willy Marroquin (WillyDevNET)

The increasing use of electronic forms of communication presents new opportunities in the study of mental health, including the ability to investigate the manifestations of psychiatric diseases un- obtrusively and in the setting of patients’ daily lives. A pilot study to explore the possible connections between bipolar affective disorder and mobile phone usage was conducted. In this study, participants were provided a mobile phone to use as their primary phone. This phone was loaded with a custom keyboard that collected metadata consisting of keypress entry time and accelerometer movement. Individual character data with the exceptions of the backspace key and space bar were not collected due to privacy concerns. We propose an end-to-end deep architecture based on late fusion, named DeepMood, to model the multi-view metadata for the prediction of mood scores. Experimental results show that 90.31% prediction accuracy on the depression score can be achieved based on session- level mobile phone typing dynamics which is typically less than one minute. It demonstrates the feasibility of using mobile phone metadata to infer mood disturbance and severity

DeepMood: Modeling Mobile Phone Typing Dynamics for Mood Detection

Willy Marroquin (WillyDevNET)

Defin ing artificial intelligence is no easy matter. Since the mid - 20th century when it was first recognized as a specific field of research, AI has always been envisioned as an evolving boundary, rather than a settled research field. Fundamentally, it refers to a programme whose ambitious objective is to understand and reproduce human cognition; creating cognitive processes comparable to those found in human beings. Therefore, we are naturally dealing with a wide scope here, both in terms of the technical proced ures that can be employed and the various disciplines that can be called upon: mathematics, information technology, cognitive sciences, etc. There is a great variety of approaches when it comes to AI: ontological, reinforcement learning, adversarial learni ng and neural networks, to name just a few. Most of them have been known for decades and many of the algorithms used today were developed in the ’60s and ’70s. Since the 1956 Dartmouth conference, artificial intelligence has alternated between periods of great enthusiasm and disillusionment, impressive progress and frustrating failures. Yet, it has relentlessly pushed back the limits of what was only thought to be achievable by human beings. Along the way, AI research has achieved significant successes: o utperforming human beings in complex games (chess, Go), understanding natural language, etc. It has also played a critical role in the history of mathematics and information technology. Consider how many softwares that we now take for granted once represen ted a major breakthrough in AI: chess game apps, online translation programmes, etc

FOR A MEANINGFUL ARTIFICIAL INTELLIGENCE TOWARDS A FRENCH AND EUROPEAN ST...

Willy Marroquin (WillyDevNET)

When Will AI Exceed Human Performance? Evidence from AI Experts

Willy Marroquin (WillyDevNET)

Vast amounts of data, faster processing power, and increas - ingly smarter algorithms are powering artificial intelligence (AI) applications and associated use cases across consumer, finance, healthcare, manufacturing, transportation & logistics, and government sectors around the world - enabling smarter & intelligent applications to speak, listen, and make decisions in unprecedented ways. As AI technologies and deployments sweep through virtually every industry, a wide range of use cases are beginning to illustrate the potential business oppor - tunities, a nd inspire changes to existing business processes leading to newer business models.

Microsoft AI Platform Whitepaper

Willy Marroquin (WillyDevNET)

In this paper, we propose an Attentional Generative Ad- versarial Network (AttnGAN) that allows attention-driven, multi-stage refinement for fine-grained text-to-image generation. With a novel attentional generative network, the At- tnGAN can synthesize fine-grained details at different sub- regions of the image by paying attentions to the relevant words in the natural language description. In addition, a deep attentional multimodal similarity model is proposed to compute a fine-grained image-text matching loss for training the generator. The proposed AttnGAN significantly out- performs the previous state of the art, boosting the best re- ported inception score by 14.14% on the CUB dataset and 170.25% on the more challenging COCO dataset. A detailed analysis is also performed by visualizing the attention layers of the AttnGAN. It for the first time shows that the layered attentional GAN is able to automatically select the condition at the word level for generating different parts of the image

AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Ad...

Willy Marroquin (WillyDevNET)

The Hamilton Project • Brookings i Seven Facts on Noncognitive Skills from Education to the Labor Market Introduction Cognitive skills—that is, math and reading skills that are measured by standardized tests—are generally understood to be of critical importance in the labor market. Most people find it intuitive and indeed unsurprising that cognitive skills, as measured by standardized tests, are important for students’ later-life outcomes. For example, earnings tend to be higher for those with higher levels of cognitive skills. What is less well understood—and is the focus of these economic facts—is that noncognitive skills are also integral to educational performance and labor-market outcomes. Due in large part to research pioneered in economics by Nobel laureate James J. Heckman, there is a robust and growing body of evidence that noncognitive skills function similarly to cognitive skills, strongly improving labor-market outcomes. These noncognitive skills—often referred to in the economics literature as soft skills and elsewhere as social, emotional, and behavioral skills—include qualities like perseverance, conscientiousness, and self-control, as well as social skills and leadership ability (Duckworth and Yeager 2015). The value of these qualities in the labor market has increased over time as the mix of jobs has shifted toward positions requiring noncognitive skills. Evidence suggests that the labor-market payoffs to noncognitive skills have been increasing over time and the payoffs are particularly strong for individuals who possess both cognitive and noncognitive skills (Deming 2015; Weinberger 2014). Although we draw a conceptual distinction between noncognitive skills and cognitive skills, it is not possible to disentangle these concepts fully. All noncognitive skills involve cognition, and some portion of performance on cognitive tasks is made possible by noncognitive skills. For the purposes of this document, the term “cognitive skills” encompasses intelligence; the ability to process, learn, think, and reason; and substantive knowledge as reflected in indicators of academic achievement. Since the No Child Left Behind Act of 2001, education policy has focused on accountability policies aimed at improving cognitive skills and closing test score gaps across groups. These policies have been largely successful, particularly for math achievement (Dee and Jacob 2011; Wong, Cook, and Steiner 2009) and among students most exposed to accountability pressure (Neal and Schanzenbach 2010). What has received less attention in policy debates is the importance of noncognitive skills.

Seven facts noncognitive skills education labor market

Willy Marroquin (WillyDevNET)

Despite significant recent advances in the field of face recognition [10, 14, 15, 17], implementing face verification and recognition efficiently at scale presents serious challenges to current approaches. In this paper we present a system, called FaceNet, that directly learns a mapping from face images to a compact Euclidean space where distances directly correspond to a measure of face similarity. Once this space has been produced, tasks such as face recognition, verification and clustering can be easily implemented using standard techniques with FaceNet embeddings as fea- ture vectors. Our method uses a deep convolutional network trained to directly optimize the embedding itself, rather than an in- termediate bottleneck layer as in previous deep learning approaches. To train, we use triplets of roughly aligned matching / non-matching face patches generated using a novel online triplet mining method. The benefit of our approach is much greater representational efficiency: we achieve state-of-the-art face recognition performance using only 128-bytes per face. On the widely used Labeled Faces in the Wild (LFW) dataset, our system achieves a new record accuracy of 99.63% . On YouTube Faces DB it achieves 95.12% . Our system cuts the error rate in comparison to the best published result [15] by 30% on both datasets.

FaceNet: A Unified Embedding for Face Recognition and Clustering

Willy Marroquin (WillyDevNET)

Brain-Computer Interfaces are communication systems that use brain signals as commands to a device. Despite being the only means by which severely paralysed people can interact with the world most effort is focused on improving and testing algorithms offline, not worrying about their validation in real life conditions. The Cybathlon’s BCI-race offers a unique opportunity to apply theory in real life conditions and fills the gap. We present here a Neural Network architecture for the 4-way classification paradigm of the BCI-race able to run in real-time. The procedure to find the architecture and best combination of mental commands best suiting this architecture for personalised used are also described. Using spectral power features and one layer convolutional plus one fully connected layer network we achieve a performance similar to that in literature for 4-way classification and prove that following our method we can obtain similar accuracies online and offline closing this well-known gap in BCI performances

Deep Learning personalised, closed-loop Brain-Computer Interfaces for mu...

Willy Marroquin (WillyDevNET)

Dia del periodista unisabana

Willy Marroquin (WillyDevNET)

Visensia is ph ysiological monitoring software that collates and analyses data from bedside monitors on 5 vital signs to produce a single patient health status score. This is used for early identification of deterior ation that might lead to cardiac or respir atory arrest. One prospectiv e, single-centre, before-and-after study found that patients monitored with Visensia had a statistically significantly shorter a verage dur ation of an y cardio-respir atory instability and fewer episodes of serious and persistent instability , although changes in patient management ma y have influenced these findings. The Visensia software requires e xisting ph ysiological monitors to pro vide data and costs £1950 for a 1-bed perpetuity licence; individual hospital systems are priced according to size and include installation and configur ation charges

Visensia for early detection of deteriorating vital signs in adults in hospital

Willy Marroquin (WillyDevNET)

Psychlab is a simulated psychology laboratory inside the first-person 3D game world of DeepMind Lab (Beattie et al., 2016). Psychlab enables implementations of classical laboratory psychological experiments so that they work with both human and artificial agents. Psychlab has a simple and flex- ible API that enables users to easily create their own tasks. As examples, we are releasing Psychlab implementations of several classical experimental paradigms including visual search, change detection, random dot motion discrimination, and multiple object tracking. We also contribute a study of the visual psychophysics of a specific state-of-the-art deep reinforcement learning agent: UNREAL (Jaderberg et al., 2016). This study leads to the surprising conclusion that UNREAL learns more quickly about larger target stimuli than it does about smaller stimuli. In turn, this insight motivates a specific improvement in the form of a simple model of foveal vision that turns out to significantly boost UNREAL’s performance, both on Psychlab tasks, and on standard DeepMind Lab tasks. By open-sourcing Psychlab we hope to facilitate a range of future such studies that simultaneously advance deep reinforcement learning and improve its links with cognitive science.

Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents

Willy Marroquin (WillyDevNET)

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Data security is rapidly gaining importance as the volume of data companies collect, analyze and monetize grows exponentially. New data processing tools and platforms are emerging at an increasing rate, as are the ways in which an organization consumes data. In this presentation Mukund Sarma and Feni Chawla talk about the unique technical and cultural challenges of running a data security program and share some practical solutions that have worked well at our company. These slides were presented at the BSides Seattle 2024 conference.

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N-Grade deals with the maintenance of university, department, faculty, student information within the university. N-Grade is an automation system, which is used to store the department, faculty, student, courses and information of a university. Starting from registration of a new student in the university, it maintains all the details regarding the attendance and marks of the students. The project deals with retrieval of information through an INTRANET based campus wide portal. It collects related information from all the departments of an organization and maintains files, which are used to generate reports in various forms to measure individual and overall performance of the students.

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