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'El transformador ilustrado' una traducción al español

Business Intelligence (BI) es un negocio basado en datos, un basado en datos recopilados. A menudo es utilizado por gerentes y ejecutivos para generar ideas procesables. Como resultado, BI siempre se conoce indistintamente como " " o " ". proceso de toma de decisiones Business Analytics Data Analytics Las se utilizan para , , crear análisis, etc. Por lo tanto, una herramienta de inteligencia empresarial fácil de usar es imprescindible para las operaciones comerciales. herramientas de inteligencia empresarial organizar su almacén de información mostrar datos visualizados #1 Tableau Tableau hace que el análisis de datos sea y . Con su funcionalidad de , puede editar y crear su gráfico analítico sin una comprensión profunda de las estructuras de datos. Permite a las personas visualizar ideas y compartirlas con sus equipos. intuitivo fácil de usar arrastrar y soltar Sitio oficial: www.tableau.com #2 QlikView QlikView es un producto de que permite a los usuarios buscar y explorar aplicaciones analíticas. Con el QlikView’s , los usuarios pueden generar fácilmente ideas al combinar diferentes bases de datos dentro de los clics descubrimiento de datos de autoservicio Associative Data Indexing Engine Sitio oficial: https://www.qlik.com/us/ #3 SAP Business Objects SAP Business Objects es un . Se conecta con recursos en segundo plano que contienen muchas aplicaciones de informes. Eso permite a los usuarios crear e implementar para generar información y predecir tendencias de marketing. BI de informes y análisis modelos de análisis predictivos Sitio oficial: https://www.sap.com/index.html #4 IBM Cognos Analytics IBM Cognos Analytics es una que incorpora inteligencia aumentada. Los paneles interactivos simplifican el análisis de datos. También tiene de análisis que incluyen análisis hipotético, análisis avanzado, informes analíticos y análisis de tendencias. Además, Cognos Analytics permite a los usuarios interactuar con inform desde sus o incluso sin conexión. plataforma de análisis de autoservicio una amplia gama de características dispositivos móviles Sitio oficial: https://www.ibm.com/products/cognos-analytics #5 Microsoft SQL Server Microsoft Business Intelligence Platform es una solución todo en uno que incluye la función de servicios de análisis, servicios de integración, servicios de datos maestros, servicios de informes, etc. Analysis Services e Reporting Services se pueden instalar como . También pueden ser . standalone servers SharePoint Farm Sitio oficial: https://www.microsoft.com/en-us/sql-server #6 Oracle Business Intelligence Oracle Business Intelligence 14c es un servicio de inteligencia empresarial que . El servidor proporcionará servicio a otras demandas, incluidas . brinda accesibilidad a toda la información relacionada minería de datos, informes y aplicaciones analíticas Sitio oficial: https://www.oracle.com/solutions/business-analytics/business-intelligence/ #7 Yellowfin Yellowfin es un conjunto de productos que consiste en . Los usuarios pueden generar ideas procesables y compartir con los colaboradores en forma de narración de historias. Su suite analítica está compuesta por 5 componentes que incluyen . Además, puede incrustar Yellowfin en su aplicación. Y esto proporciona una gran flexibilidad para la personalización. BI, data análisis e informes señales, tableros, historia, descubrimiento de datos y preparación de datos Sitio oficial: https://www.yellowfinbi.com/ #8 WebFOCUS WebFOCUS es un . Permite a los usuarios crear un panel basado en datos recopilados en varios formatos. También permite a los y . generador de información usuarios visualizar los datos, obtener información procesable, generar informes compartir el resultado con los colaboradores Sitio oficial: https://www.informationbuilders.com/products/bi-and-analytics-platform #9 TIBCO Spotfire TIBCO Spotfire es un software de BI todo en uno que proporciona funcionalidades que incluyen la . Lo que hace que TIBCO sea diferente es que permite a los usuarios establecer su propio y , esto hace posible el trabajo en Windows. recopilación, el análisis y la visualización de datos KPI enviar notificaciones a iPhone/Android Sitio oficial: https://www.tibco.com/ #10 SAS SAS Business Intelligence (SAS BI) es parte de la solución SAS Enterprise. El software proporciona análisis en tiempo real que permite a los encargados de la toma de decisiones poder monitorear sus métricas comerciales y obtener información procesable. El software consta de seis módulos que incluyen Visual Analytics, Visual Statistics, Office Analytics, Enterprise Guide y Enterprise BI Server. Sitio oficial: https://www.sas.com/en_hk/home.html #11 TARGIT TARGIT Decision Suite es la única plataforma de inteligencia de negocios que ofrece herramientas de . Es una excelente opción para los , ya que permite la manipulación de datos de varias maneras. Se conecta a CRM y ERP, lo que hace que todo el proceso sea interactivo. descubrimiento de datos visuales, análisis de negocios, informes y paneles informes de ventas Sitio oficial: https://www.targit.com/en #12 Izenda Embedded BI & Analytics Izenda permite el . Es una para empresas que desean funcionalidades de BI y análisis en sus aplicaciones. Puede acceder a Izenda a través de un navegador web o dispositivo móvil. También que permiten la integración con Ruby, Python, Java, .NET, PHP, etc. descubrimiento de datos en tiempo real plataforma integrada incorpora arquitecturas flexibles Sitio oficial: www.izenda.com #13 MicroStrategy Desde y hasta y , solo MicroStrategy brinda a las organizaciones toda la gama de capacidades que necesitan para transformar sus datos en inteligencia del mundo real y avanzar hacia la empresa inteligente. informes empresariales descubrimiento de datos productividad móvil telemetría en tiempo real Sitio oficial: https://www.microstrategy.com/us #14 Junta Board es un sistema de BI con todas las funciones que combina la y el . Permite a los usuarios extraer fuentes de datos y hacer informes. También tiene un para que las compañías multinacionales entreguen informes en otro idioma. Con sus funciones de recopilación y análisis de datos, las empresas pueden generar decisiones gestión del rendimiento análisis empresarial paquete multilingüe Sitio oficial: https://www.board.com/en #15 Sisense Sisense ha ganado el Premio a la Mejor Inteligencia de Negocios por el Premio Supremo de Software 2018 y 2018. Puede con su función de arrastrar y soltar. Convierte los datos en gráficos y cuadros perspicaces. Tiene grandes capacidades para negocios en varios tamaños, incluidos los gigantes de Fortune 500 como Sony, ESPN e incluso la NASA. visualizar los datos desde su tablero Sitio oficial: https://www.sisense.com/ #16 Statsbot Statsbot permite desde la base de datos SQL sin una configuración compleja como otras herramientas de BI. Sus usuarios han elogiado su conexión sin esfuerzo a Mixpanel, Salesforce y el servidor SQL. Además de eso, Statsbot también permite , como el control de versiones y la reutilización de código para construir una lógica de transformación limpia y sostenible para sus datos. visualizar métricas empresariales aplicar prácticas de ingeniería Sitio oficial: https://statsbot.co/ #17 Panorama - Necto Necto Telecom puede descubrir las bajo los datos. Permite , lo cual es muy conveniente para los tomadores de decisiones empresariales para mantenerse al día con las métricas empresariales sobre la marcha. Es capaz de manejar múltiples fuentes de datos y combinarlas en una. Una buena opción si necesita crear análisis e informes complejos. tendencias ocultas configurar alertas y notificaciones para KPI Sitio oficial: http://www.panorama.com/necto/ #18 InetSoft La plataforma de inteligencia de datos de InetSoft combina el modelado de datos en tiempo real con la visualización de datos. Eso permite el desarrollo , como paneles interactivos e informes perfectos en píxeles. Los modelos de datos dinámicos no solo ofrecen sino que también permiten a los "desarrolladores ciudadanos" componer . El motor analítico de datos desplegable Apache Hadoop/Spark garantiza un crecimiento ilimitado para la inteligencia de datos avanzada. rápido e iterativo de vistas de datos vistas de datos diseñadas vistas de datos de autoservicio Sitio oficial: https://www.inetsoft.com/ #19 Birst Birst es una solución de análisis y BI en la nube que y ayuda a tomar decisiones informadas. Su experiencia de usuario adaptativa le brinda una gran cantidad de análisis de autoservicio y opciones de consumo de datos. conecta los conocimientos de varios equipos Sitio oficial: https://www.birst.com/ #20 Domo Domo es un sistema basado en la nube, por lo que no es necesario descargarlo ni instalarlo. Con Domo, puede manipular Extraer, Transformar y Cargar (ELT) en el motor. También tiene una que le permiten integrar datos en las instalaciones. amplia gama de conectores de aplicaciones Sitio oficial: https://www.domo.com/ Autor: Melisa Previously published at http://www.octoparse.es/blog/20-herramientas-de-bi-m%C3%A1s-populares-en-2020

20 Herramientas de Inteligencia Empresarial (BI) más Populares en 2020

In this fifth and final post of our series on link prediction using Neptune ML, we’re diving into the inference process: setting up an inference endpoint to use our trained GNN model for link predictions. To establish the endpoint, we’ll use the Neptune cluster’s API and the model artifacts stored in S3. With the endpoint live, we’ll query it for link prediction, using a Gremlin query to identify high-confidence potential connections in our graph. By now, we have already loaded the Twitch social networking data into the Neptune cluster (as described in Part 1 of this series), exported the data using the ML profile (check out Part 2 for details), preprocessed the data (as explained in Part 3), trained the model (see Part 4), and now we're ready to use the trained model to generate predictions. Read part 1 here; part 2 here; part 3 here; and part 4 here. CREATING THE ENDPOINT Let's create the inference endpoint using the cluster's API and the model artifacts we have in S3. As usual, we need an IAM role that has access to S3 and SageMaker first. The role must also have a trust policy that allows us to add it to the Neptune cluster (the trust policy can be found in Part 3 of this guide). We also need to provide access to SageMaker and CloudWatch API from inside the VPC, so we need the VPC endpoints as explained in Part 1 of this series. Let's use the cluster's API to create an inference endpoint with this curl command: curl -XPOST https://(YOUR_NEPTUNE_ENDPOINT):8182/ml/endpoints \
  -H 'Content-Type: application/json' \
  -d '{
          "mlModelTrainingJobId": YOUR_MODEL_TRAINING_JOB_ID,
	"neptuneIamRoleArn": "arn:aws:iam::123456789012:role/NeptuneMLNeptuneRole"
      }' We can use 'instanceType' and 'instanceCount' parameters to choose the EC2 instance type that will be used for link prediction, and deploy more than one instance. The full list of parameters can be found here. We'll use the default 'ml.m5(d).xlarge' instance as it has enough CPU and RAM for our small graph, and this instance type was recommended in infer_instance_recommendation.json that was generated after model training in our previous stage: {
    "disk_size": 12023356,
    "instance": "ml.m5d.xlarge",
    "mem_size": 13847612
} The API responds with the inference endpoint ID: {"id":"b217165b-7780-4e73-9d8a-5b6f7cfef9f6"} Then we can check the status of the inference endpoint with this command: curl https://YOUR_NEPTUNE_ENDPOINT:8182/ml/endpoints/INFERENCE_ENDPOINT_ID?neptuneIamRole='arn:aws:iam::123456789012:role/NeptuneMLNeptuneRole' and once it responds with 'status: InService' like this, {
  "endpoint": {
    "name": "YOUR_INFERENCE_ENDPOINT_NAME-endpoint",
    "arn": "...",
    "status": "InService"
  },
  "endpointConfig": {...},
  "id": "YOUR_INFERENCE_ENDPOINT_ID",
  "status": "InService"
} it means we're ready to start using it with database queries. The endpoint can also be viewed and managed from the AWS console, under SageMaker -> Inference -> Endpoints. QUERYING THE ENDPOINT Let's use the endpoint to predict new 'follow' links in the graph. In order to do that, we need to choose the source vertex of the possible new links. It helps if the source vertex already has links, so we’ll use this query to get the vertex with the highest number of existing links (outE and inE connections): g.V()
 .group()
   .by()
   .by(bothE().count())
 .order(local)
   .by(values, Order.desc)
 .limit(local, 1)
 .next() The result is {v[1773]: 1440} which means that vertex with ID = 1773 has 1440 connections (720 inE and 720 outE). To get the number of edges that start at node 1773 and the number of edges that end at that node we can use these queries: g.V('1773').outE().count()
g.V('1773').inE().count() The same number of inE and outE connections is expected because the initial dataset contains mutual friendships, and we augmented the data with reverse edges to make it work with Neptune directed graph. Now let's get the predicted connections. To do that, we'll run a Gremlin query with Neptune ML predicates. We'll use the inference endpoint and the SageMaker role which was added to the DB cluster to get the users that user 1773 might follow with a confidence threshold (minimum likelihood of link existence according to the model) of at least 0.1 (10%), while excluding the users that user 1773 is already following: %%gremlin

g.with('Neptune#ml.endpoint', 'YOUR_INFERENCE_ENDPOINT_NAME')
 .with('Neptune#ml.iamRoleArn', 'arn:aws:iam::123456789012:role/NeptuneMLSagemakerRole')
 .with('Neptune#ml.limit', 10000)
 .with('Neptune#ml.threshold', 0.1D)
 .V('1773')
 .out('follows')
 .with('Neptune#ml.prediction')
 .hasLabel('user')
 .not(
  __.in('follows').hasId('1773')
 ) That returns 4 results: "Result"
"v[755]"
"v[6086]"
"v[6382]"
"v[7005]" According to our model, there's at least 10% chance that user 1773 will follow each of these 4 users. Perhaps we can improve the model by increasing the number of training jobs to at least to 10 as recommended by AWS, and then compare the performance of the resulting model and the predicted links. In real applications, adding user profile and activity data to the graph also improves prediction accuracy. Predicted connections in social networking datasets can be used to provide personalized recommendations like friend and content suggestions, enhancing user engagement and community growth, reducing churn, and providing additional data for targeted advertising. Although we applied link prediction to a social networking dataset, it's just one of many possible applications of this technology. From recommendation engines to network optimization, link prediction is a versatile tool that brings value by uncovering hidden relationships within data. As graph-based applications continue to expand, the potential of link prediction across industries promises new insights, efficiency, and enhanced user experiences. In this fifth and final post of our series on link prediction using Neptune ML, we’re diving into the inference process: setting up an inference endpoint to use our trained GNN model for link predictions. To establish the endpoint, we’ll use the Neptune cluster’s API and the model artifacts stored in S3. With the endpoint live, we’ll query it for link prediction, using a Gremlin query to identify high-confidence potential connections in our graph. By now, we have already loaded the Twitch social networking data into the Neptune cluster (as described in Part 1 of this series), exported the data using the ML profile (check out Part 2 for details), preprocessed the data (as explained in Part 3), trained the model (see Part 4), and now we're ready to use the trained model to generate predictions. Read part 1 here; part 2 here; part 3 here; and part 4 here. Read part 1 here ; part 2 here ; part 3 here; and part 4 here . here here part 3 here CREATING THE ENDPOINT Let's create the inference endpoint using the cluster's API and the model artifacts we have in S3. As usual, we need an IAM role that has access to S3 and SageMaker first. The role must also have a trust policy that allows us to add it to the Neptune cluster (the trust policy can be found in Part 3 of this guide). We also need to provide access to SageMaker and CloudWatch API from inside the VPC, so we need the VPC endpoints as explained in Part 1 of this series. Let's use the cluster's API to create an inference endpoint with this curl command: curl -XPOST https://(YOUR_NEPTUNE_ENDPOINT):8182/ml/endpoints \
  -H 'Content-Type: application/json' \
  -d '{
          "mlModelTrainingJobId": YOUR_MODEL_TRAINING_JOB_ID,
	"neptuneIamRoleArn": "arn:aws:iam::123456789012:role/NeptuneMLNeptuneRole"
      }' curl -XPOST https://(YOUR_NEPTUNE_ENDPOINT):8182/ml/endpoints \
  -H 'Content-Type: application/json' \
  -d '{
          "mlModelTrainingJobId": YOUR_MODEL_TRAINING_JOB_ID,
	"neptuneIamRoleArn": "arn:aws:iam::123456789012:role/NeptuneMLNeptuneRole"
      }' We can use ' instanceType ' and ' instanceCount ' parameters to choose the EC2 instance type that will be used for link prediction, and deploy more than one instance. The full list of parameters can be found here . We'll use the default ' ml.m5(d).xlarge ' instance as it has enough CPU and RAM for our small graph, and this instance type was recommended in infer_instance_recommendation.json that was generated after model training in our previous stage: instanceType instanceCount here ml.m5(d).xlarge infer_instance_recommendation.json {
    "disk_size": 12023356,
    "instance": "ml.m5d.xlarge",
    "mem_size": 13847612
} {
    "disk_size": 12023356,
    "instance": "ml.m5d.xlarge",
    "mem_size": 13847612
} The API responds with the inference endpoint ID: {"id":"b217165b-7780-4e73-9d8a-5b6f7cfef9f6"} {"id":"b217165b-7780-4e73-9d8a-5b6f7cfef9f6"} Then we can check the status of the inference endpoint with this command: curl https://YOUR_NEPTUNE_ENDPOINT:8182/ml/endpoints/INFERENCE_ENDPOINT_ID?neptuneIamRole='arn:aws:iam::123456789012:role/NeptuneMLNeptuneRole' curl https://YOUR_NEPTUNE_ENDPOINT:8182/ml/endpoints/INFERENCE_ENDPOINT_ID?neptuneIamRole='arn:aws:iam::123456789012:role/NeptuneMLNeptuneRole' and once it responds with ' status: InService ' like this, status: InService {
  "endpoint": {
    "name": "YOUR_INFERENCE_ENDPOINT_NAME-endpoint",
    "arn": "...",
    "status": "InService"
  },
  "endpointConfig": {...},
  "id": "YOUR_INFERENCE_ENDPOINT_ID",
  "status": "InService"
} {
  "endpoint": {
    "name": "YOUR_INFERENCE_ENDPOINT_NAME-endpoint",
    "arn": "...",
    "status": "InService"
  },
  "endpointConfig": {...},
  "id": "YOUR_INFERENCE_ENDPOINT_ID",
  "status": "InService"
} it means we're ready to start using it with database queries. The endpoint can also be viewed and managed from the AWS console, under SageMaker -> Inference -> Endpoints. QUERYING THE ENDPOINT Let's use the endpoint to predict new 'follow' links in the graph. In order to do that, we need to choose the source vertex of the possible new links. It helps if the source vertex already has links, so we’ll use this query to get the vertex with the highest number of existing links (outE and inE connections): g.V()
 .group()
   .by()
   .by(bothE().count())
 .order(local)
   .by(values, Order.desc)
 .limit(local, 1)
 .next() g.V()
 .group()
   .by()
   .by(bothE().count())
 .order(local)
   .by(values, Order.desc)
 .limit(local, 1)
 .next() The result is {v[1773]: 1440} {v[1773]: 1440} which means that vertex with ID = 1773 has 1440 connections (720 inE and 720 outE). To get the number of edges that start at node 1773 and the number of edges that end at that node we can use these queries: g.V('1773').outE().count()
g.V('1773').inE().count() g.V('1773').outE().count()
g.V('1773').inE().count() The same number of inE and outE connections is expected because the initial dataset contains mutual friendships, and we augmented the data with reverse edges to make it work with Neptune directed graph. Now let's get the predicted connections. To do that, we'll run a Gremlin query with Neptune ML predicates . We'll use the inference endpoint and the SageMaker role which was added to the DB cluster to get the users that user 1773 might follow with a confidence threshold (minimum likelihood of link existence according to the model) of at least 0.1 (10%) , while excluding the users that user 1773 is already following: Neptune ML predicates We'll use the inference endpoint to get the users that user 1773 might follow with a confidence threshold (minimum likelihood of link existence according to the model) of at least 0.1 (10%) %%gremlin

g.with('Neptune#ml.endpoint', 'YOUR_INFERENCE_ENDPOINT_NAME')
 .with('Neptune#ml.iamRoleArn', 'arn:aws:iam::123456789012:role/NeptuneMLSagemakerRole')
 .with('Neptune#ml.limit', 10000)
 .with('Neptune#ml.threshold', 0.1D)
 .V('1773')
 .out('follows')
 .with('Neptune#ml.prediction')
 .hasLabel('user')
 .not(
  __.in('follows').hasId('1773')
 ) %%gremlin

g.with('Neptune#ml.endpoint', 'YOUR_INFERENCE_ENDPOINT_NAME')
 .with('Neptune#ml.iamRoleArn', 'arn:aws:iam::123456789012:role/NeptuneMLSagemakerRole')
 .with('Neptune#ml.limit', 10000)
 .with('Neptune#ml.threshold', 0.1D)
 .V('1773')
 .out('follows')
 .with('Neptune#ml.prediction')
 .hasLabel('user')
 .not(
  __.in('follows').hasId('1773')
 ) That returns 4 results: That returns 4 results: "Result"
"v[755]"
"v[6086]"
"v[6382]"
"v[7005]" "Result"
"v[755]"
"v[6086]"
"v[6382]"
"v[7005]" According to our model, there's at least 10% chance that user 1773 will follow each of these 4 users. Perhaps we can improve the model by increasing the number of training jobs to at least to 10 as recommended by AWS, and then compare the performance of the resulting model and the predicted links. In real applications, adding user profile and activity data to the graph also improves prediction accuracy. According to our model, there's at least 10% chance that user 1773 will follow each of these 4 users. Predicted connections in social networking datasets can be used to provide personalized recommendations like friend and content suggestions, enhancing user engagement and community growth, reducing churn, and providing additional data for targeted advertising. Although we applied link prediction to a social networking dataset, it's just one of many possible applications of this technology. From recommendation engines to network optimization, link prediction is a versatile tool that brings value by uncovering hidden relationships within data. As graph-based applications continue to expand, the potential of link prediction across industries promises new insights, efficiency, and enhanced user experiences.

AI Is Mapping Hidden Connections—And It’s Just Getting Started

AI ukax imantat Conexiones ukanakaruw Mapeo luraski —Ukatx jichhakiw qalltaski

এআই লুকানো সংযোগগুলি ম্যাপ করছে—এবং এটি কেবল শুরু হচ্ছে

La IA está mapeando conexiones ocultas y recién está comenzando

هوش مصنوعی در حال ترسیم اتصالات پنهان است – و تازه شروع شده است

AI ממפה חיבורים נסתרים - וזה רק מתחיל

AI が隠れたつながりをマッピング — そしてそれは始まったばかり

AI ກໍາລັງສ້າງແຜນທີ່ການເຊື່ອມຕໍ່ທີ່ເຊື່ອງໄວ້ - ແລະມັນພຽງແຕ່ເລີ່ມຕົ້ນ

AI cartografiază conexiunile ascunse – și abia începe

AI සැඟවුණු සම්බන්ධතා සිතියම්ගත කරමින් සිටී - එය ආරම්භ කිරීම පමණි

Ang AI ay Nagmamapa ng Mga Nakatagong Koneksyon—At Nagsisimula Pa Lang Ito

Yapay Zeka Gizli Bağlantıları Haritalıyor ve Daha Yeni Başlıyor

I-AI Ifaka Imephu Ukuxhumana Okufihliwe-Futhi Iqala Ukuqalisa

As Valentine’s Day draws near, Dating.com is revolutionizing digital dating with Virtual Spaces — a breathtakingly immersive way for singles to meet, interact, and build real connections in a fully customized online world. A Digital Story, Tailored for You Picture this: a virtual space designed just for you and your match, where your 3D digital persona — crafted from your profile photo and gender — mirrors your emotions in real time. Users can express themselves like never before with customizable outfits, stylish avatars, and beautifully curated spaces that reflect their personality and mood. Your title has the power to make or break your article so take some time to think about it. Why Virtual Connections are the Future According to a Social Discovery Group study, singles crave affordability, companionship, and escapism, and Virtual Spaces delivers on all fronts. Forget overpriced dates and awkward first meetings — this is a stress-free, interactive, and intimate way to truly connect. 👾 Authentic Avatars: Authentic Avatars: Your digital persona evolves with every interaction, making each moment feel even more personal and real. 🍬 Exclusive & Private: Your Virtual Space is a secure sanctuary, offering a safe and intimate space for meaningful, judgment-free conversations. 🦄 Total Customization: Personalize your avatar’s style, redesign your virtual space, and surprise your match with thoughtful digital gifts! The Numbers Don’t Lie A 2025 Virtual Intimacy report revealed: ✔ 71%of users say virtual messaging has eased their loneliness✔83%have dated someone in another state virtually✔71% have had a digital relationship with a match from another country. ✔ 62% feel more comfortable expressing their desires online than in person. “When people can connect in a space free from physical, financial, and geographic limitations, they have the freedom to be fully themselves. This kind of environment encourages deeper, more authentic connections, where people feel safe to open up and engage in meaningful conversations,” said Sabrina Bendory, relationship expert at Dating.com. “ In many cases, these virtual interactions allow for a level of emotional intimacy that can be even stronger than what we typically experience in traditional dating settings.” What’s Next? Trend Alert! Immersive Digital Experiences: The rise of 3D avatars means online dating feels more real than ever.
Virtual Intimacy Environments: Bespoke virtual spaces let singles craft their own dreamworld.
Real-time Avatar Mood Detection: Mood-based avatar expressions add depth and authenticity to users’ emotional engagement. Industry Disruptions Ahead ↘ Online Dating Evolution: Say goodbye to outdated swiping — Virtual Spaces are taking matchmaking to the next level. ↘ Virtual Reality Boom: As VR tech advances, dating platforms will blur the line between real and virtual romance. ↘Next-Gen Avatars: The future of digital love lies in hyper-personalized, interactive avatars. Connections Have No Limits 💡 Dating.com’s Virtual Spaces aren’t just about finding a date — it’s about creating experiences, fostering intimacy, and breaking barriers. Are you ready to meet your perfect virtual match? The future of dating is just a click away! As Valentine’s Day draws near, Dating.com is revolutionizing digital dating with Virtual Spaces — a breathtakingly immersive way for singles to meet, interact, and build real connections in a fully customized online world. As Valentine’s Day draws near, Dating.com is revolutionizing digital dating with Virtual Spaces — a breathtakingly immersive way for singles to meet, interact, and build real connections in a fully customized online world. A Digital Story, Tailored for You A Digital Story, Tailored for You Picture this: a virtual space designed just for you and your match, where your 3D digital persona — crafted from your profile photo and gender — mirrors your emotions in real time. Users can express themselves like never before with customizable outfits, stylish avatars, and beautifully curated spaces that reflect their personality and mood. Your title has the power to make or break your article so take some time to think about it. Why Virtual Connections are the Future Why Virtual Connections are the Future According to a Social Discovery Group study, singles crave affordability, companionship, and escapism, and Virtual Spaces delivers on all fronts. Forget overpriced dates and awkward first meetings — this is a stress-free, interactive, and intimate way to truly connect. Social Discovery Group Virtual Spaces 👾 Authentic Avatars: Authentic Avatars: Your digital persona evolves with every interaction, making each moment feel even more personal and real. Authentic Avatars: 🍬 Exclusive & Private : Your Virtual Space is a secure sanctuary, offering a safe and intimate space for meaningful, judgment-free conversations. Exclusive & Private 🦄 Total Customization: Personalize your avatar’s style, redesign your virtual space, and surprise your match with thoughtful digital gifts! Total Customization: The Numbers Don’t Lie The Numbers Don’t Lie A 2025 Virtual Intimacy report revealed: Virtual Intimacy report ✔ 71%of users say virtual messaging has eased their loneliness✔83%have dated someone in another state virtually✔71% have had a digital relationship with a match from another country. ✔ 62% feel more comfortable expressing their desires online than in person. 71% of users say virtual messaging has eased their loneliness✔ 83% have dated someone in another state virtually✔ 71% of users say virtual messaging has eased their loneliness ✔ have dated someone in another state virtually ✔ 62% “When people can connect in a space free from physical, financial, and geographic limitations, they have the freedom to be fully themselves. This kind of environment encourages deeper, more authentic connections, where people feel safe to open up and engage in meaningful conversations,” said Sabrina Bendory, relationship expert at Dating.com. “ In many cases, these virtual interactions allow for a level of emotional intimacy that can be even stronger than what we typically experience in traditional dating settings.” “When people can connect in a space free from physical, financial, and geographic limitations, they have the freedom to be fully themselves. This kind of environment encourages deeper, more authentic connections, where people feel safe to open up and engage in meaningful conversations ,” said Sabrina Bendory, relationship expert at Dating.com. “ In many cases, these virtual interactions allow for a level of emotional intimacy that can be even stronger than what we typically experience in traditional dating settings.” encourages deeper, more authentic connections, where people feel safe to open up and engage in meaningful conversations What’s Next? Trend Alert! What’s Next? Trend Alert! Immersive Digital Experiences: The rise of 3D avatars means online dating feels more real than ever. Virtual Intimacy Environments: Bespoke virtual spaces let singles craft their own dreamworld. Real-time Avatar Mood Detection: Mood-based avatar expressions add depth and authenticity to users’ emotional engagement. Immersive Digital Experiences: The rise of 3D avatars means online dating feels more real than ever. Immersive Digital Experiences: Virtual Intimacy Environments: Bespoke virtual spaces let singles craft their own dreamworld. Virtual Intimacy Environments: Real-time Avatar Mood Detection : Mood-based avatar expressions add depth and authenticity to users’ emotional engagement. Real-time Avatar Mood Detection Industry Disruptions Ahead Industry Disruptions Ahead ↘ Online Dating Evolution: Say goodbye to outdated swiping — Virtual Spaces are taking matchmaking to the next level. Online Dating Evolution: ↘ Virtual Reality Boom: As VR tech advances, dating platforms will blur the line between real and virtual romance. Virtual Reality Boom: ↘ Next-Gen Avatars: The future of digital love lies in hyper-personalized, interactive avatars. Next-Gen Avatars: Connections Have No Limits 💡 Connections Have No Limits 💡 Dating.com’s Virtual Spaces aren’t just about finding a date — it’s about creating experiences, fostering intimacy, and breaking barriers. Virtual Spaces Are you ready to meet your perfect virtual match? The future of dating is just a click away ! a click away

Step into the Future of Relationships: Virtual Spaces Redefine Connections!

ወደፊት ወደ ግንኙነቶች ይሂዱ፡ ምናባዊ ክፍተቶች ግንኙነቶችን እንደገና ያስተካክሉ!

Зрабіце крок у будучыню адносін: віртуальныя прасторы пераасэнсоўваюць сувязі!

Adéntrese en el futuro de las relaciones: ¡los espacios virtuales redefinen las conexiones!

人間関係の未来へ踏み出そう: 仮想空間がつながりを再定義します!

Hamuq pachaman yaykuy: ¡Espacios Virtuales T'inkisqakunata musuqmanta riqsichinku!

Шагните в будущее отношений: виртуальные пространства меняют представление о связях!

Intambwe mugihe kizaza cyimibanire: Umwanya wubusa Wongeye guhuza!

Закорачите у будућност односа: Виртуелни простори редефинишу везе!

ก้าวเข้าสู่อนาคตของความสัมพันธ์: พื้นที่เสมือนช่วยกำหนดความเชื่อมต่อใหม่!

İlişkilerin Geleceğine Adım Atın: Sanal Alanlar Bağlantıları Yeniden Tanımlıyor!

Munosabatlar kelajagiga qadam qo'ying: virtual maydonlar ulanishlarni qayta belgilaydi!

Inyathelo kwiKamva loBudlelwane: iZithuba ezibonakalayo zichaza ngokutsha uQhagamshelwano!

DUBAI, United Arab Emirates, January 31st, 2025/Chainwire/--Following a recent article in Fortune Magazine, Musk It has sparked speculation as the next breakout memecoin, driven by its undeniable ties to the Musk family. While Elon Musk has yet to officially endorse a token, history suggests that when he does, the results can be explosive. Could Musk It be the one to carry that legacy forward? The Musk Factor: Exploring Musk It's Connection to Elon Elon Musk has made it clear that he’s a fan of memecoins, single-handedly pushing Dogecoin to unprecedented heights. While he hasn’t officially commented on Musk It yet, his father Errol Musk has embraced the project, and that connection alone fuels speculation that Elon and Kimbal could be paying attention. After all, if there’s one thing the crypto world knows, it’s that Elon moves markets—and anything remotely tied to his name has explosive potential. Dogecoin started as a joke, then skyrocketed to a $60 billion market cap. Shiba Inu (SHIB) followed suit, peaking at $40 billion. Floki, PEPE, and countless others have turned early adopters into millionaires. What do they all have in common? A strong community, a compelling story, and viral potential. Musk It has all three—and then some. A Coin With Family Ties Musk It is being positioned as the Musk family coin, and while Errol Musk has publicly endorsed it, the bigger question remains: Could Kimbal or Elon step in? In December 2024, Errol Musk met with Kimbal Musk in Dubai, a meeting that has left crypto enthusiasts speculating whether Kimbal might take an interest in Musk It. Given Kimbal’s entrepreneurial spirit and past involvement in innovative projects, his potential endorsement could be a game-changer. And if Elon ever tweets about Musk It? That could be the catalyst that propels it to Doge-level dominance. Risk-Adjusted Gains: Evaluating Musk It's Growth Potential Musk It stands at a $10 million market cap compared to Dogecoin’s $60 billion. That’s a massive risk-adjusted ratio—a potential 6000x upside if Musk It follows a similar trajectory. For those looking for the next viral, community-driven crypto project, Musk It presents a unique opportunity. With undeniable ties to the Musk family and speculation swirling around potential future endorsements, the project continues to attract attention. About Musk It Musk It is more than just a meme coin—it's a movement. A mindset that embodies taking bold action, breaking barriers, and achieving greatness. Inspired by the revolutionary spirit of innovation and efficiency, Musk It represents the drive to do things better, challenge the status quo, and redefine success. With over 40,000 holders already holding Musk It, its expanding community reflects its growing presence. Unlike traditional meme coin, which is meant only to embody an idea, Musk It is backed by the Musk Family and will serve as the official coin of Errol's Musk Institute. Musk It: the coin for those who don’t let anything stand in their way. Musk Family Endorsed and Approved. Official Links: Website: https://www.muskit.io/ Telegram: https://t.me/JustMusk_It X: https://x.com/JustMuskIt Dexscreener: https://dexscreener.com/solana/Hd8LeEdJsspSJAJm15nmpFjQdntn1ZpBFV35ppRDrevE Contact Cognitio Strategies Musk It contact@cognitiostrategies.io This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here DUBAI, United Arab Emirates, January 31st, 2025/Chainwire/--Following a recent article in Fortune Magazine, Musk It has sparked speculation as the next breakout memecoin, driven by its undeniable ties to the Musk family. While Elon Musk has yet to officially endorse a token, history suggests that when he does, the results can be explosive. Could Musk It be the one to carry that legacy forward? Musk It Musk It The Musk Factor: Exploring Musk It's Connection to Elon Elon Musk has made it clear that he’s a fan of memecoins, single-handedly pushing Dogecoin to unprecedented heights. While he hasn’t officially commented on Musk It yet, his father Errol Musk has embraced the project , and that connection alone fuels speculation that Elon and Kimbal could be paying attention. Errol Musk has embraced the project Errol Musk has embraced the project After all, if there’s one thing the crypto world knows, it’s that Elon moves markets—and anything remotely tied to his name has explosive potential. Dogecoin started as a joke, then skyrocketed to a $60 billion market cap. Shiba Inu (SHIB) followed suit, peaking at $40 billion. Floki, PEPE, and countless others have turned early adopters into millionaires. What do they all have in common? A strong community, a compelling story, and viral potential. Musk It has all three—and then some. A Coin With Family Ties Musk It is being positioned as the Musk family coin, and while Errol Musk has publicly endorsed it, the bigger question remains: Could Kimbal or Elon step in? In December 2024, Errol Musk met with Kimbal Musk in Dubai, a meeting that has left crypto enthusiasts speculating whether Kimbal might take an interest in Musk It. Given Kimbal’s entrepreneurial spirit and past involvement in innovative projects, his potential endorsement could be a game-changer. And if Elon ever tweets about Musk It? That could be the catalyst that propels it to Doge-level dominance. Risk-Adjusted Gains: Evaluating Musk It's Growth Potential Musk It stands at a $10 million market cap compared to Dogecoin’s $60 billion. That’s a massive risk-adjusted ratio—a potential 6000x upside if Musk It follows a similar trajectory. For those looking for the next viral, community-driven crypto project, Musk It presents a unique opportunity. With undeniable ties to the Musk family and speculation swirling around potential future endorsements, the project continues to attract attention. About Musk It Musk It is more than just a meme coin—it's a movement. A mindset that embodies taking bold action, breaking barriers, and achieving greatness. Musk It Musk It Inspired by the revolutionary spirit of innovation and efficiency, Musk It represents the drive to do things better, challenge the status quo, and redefine success. With over 40,000 holders already holding Musk It, its expanding community reflects its growing presence. Unlike traditional meme coin, which is meant only to embody an idea, Musk It is backed by the Musk Family and will serve as the official coin of Errol's Musk Institute. Musk It: the coin for those who don’t let anything stand in their way. Musk Family Endorsed and Approved. Official Links: Website: https://www.muskit.io/ https://www.muskit.io/ https://www.muskit.io/ Telegram: https://t.me/JustMusk_It https://t.me/JustMusk_It https://t.me/JustMusk_It X: https://x.com/JustMuskIt https://x.com/JustMuskIt https://x.com/JustMuskIt Dexscreener: https://dexscreener.com/solana/Hd8LeEdJsspSJAJm15nmpFjQdntn1ZpBFV35ppRDrevE https://dexscreener.com/solana/Hd8LeEdJsspSJAJm15nmpFjQdntn1ZpBFV35ppRDrevE https://dexscreener.com/solana/Hd8LeEdJsspSJAJm15nmpFjQdntn1ZpBFV35ppRDrevE Contact Cognitio Strategies Musk It contact@cognitiostrategies.io This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here here here

Musk It: The Next Big Meme Coin With An Unmatched Connection To The Musk Legacy

Musk It: Jutïr Jach’a Meme Moneda Ukax Mä Jan Uñt’at Conexión Ukamp Musk Legacy Ukampi

Musk It: The Next Big Meme Coin med en uovertruffen forbindelse til Musk Legacy

Musk It: la próxima gran moneda meme con una conexión inigualable con el legado de Musk

Musk It: Seuraava iso meemikolikko, jolla on vertaansa vailla oleva yhteys Muskin perintöön

マスク・イット：マスクの遺産と比類のないつながりを持つ次のビッグミームコイン

Musk It: следната голема монета за мем со неспоредлива врска со наследството на мошус

Musk It: Kolejna wielka moneta memowa z niezrównanym powiązaniem z dziedzictwem Muska

Musk It: A próxima grande moeda meme com uma conexão incomparável com o legado de Musk

කස්තුරි ඉට්: කස්තුරි උරුමයට අසමසම සම්බන්ධයක් සහිත මීළඟ විශාල මේම් කාසිය

Musk It: Sarafu Inayofuata Kubwa ya Meme Na Muunganisho Usiolinganishwa na Urithi wa Musk

Musk It: Musk mirasyna deňi-taýy bolmadyk baglanyşyk bilen indiki uly meme teňňesi

Musk It: Đồng tiền meme lớn tiếp theo có mối liên hệ vô song với di sản Musk

It´s the season of celebrating love, friendship, and connection and gift-giving trends have evolved as the dating world becomes more complex. Dating.com, a leading global online communication platform under Social Discovery Group (SDG), has observed a shift in gift-giving between partners, friends, and new connections during big festivities. Individual preferences and broader societal changes are reflecting the changes in dynamic relationships and consumer behavior. Thoughtful and Personalized Gifts Take Center Stage A top trend observed during the holidays is an increased emphasis on personalized gifts. Generic presents like chocolate, socks, or candles are no longer a go-to. Do we really need more stuff anyway? Instead many daters are opting for a more personal touch to their gifts to express their care. Custom-made gifts like engraved jewelry, artwork, and even personalized playlists have become increasingly popular. Nowadays, relationships are more about meaningful connections than superficial interactions. The rise of online communication platforms, where users from diverse backgrounds can easily meet, has led to a huge desire to stand out from the crowd with a unique or tailored gift. Customized gifts, especially when they represent an inside joke or a shared experience demonstrate thoughtfulness. How Digital Platforms Shape Modern Dating Global online digital communication platforms have played a huge role in how people approach relationships and gift-giving. More people are turning to online dating and increasing virtual interactions to get to know their potential partners. Meaningful and thoughtful connections that are made have translated into great gift-giving. Dating.com has also reported an uptick in virtual gifting options, like sending digital gift cards, virtual experiences, or online subscriptions. Gifting shared experiences while being physically apart is especially important during the holiday season. Societal Changes and Consumer Behavior Consumer behavior has shifted significantly during the holiday season. People are moving away from materialistic things and prioritizing sentimental value over cost. According to a study, 45% of users prefer gifts that have sentimental meaning rather than extravagant presents, which reflects a new cultural trend. Digital communication and dating platforms are becoming increasingly popular and consumers are opting for gifts that align with their digital lifestyles, such as virtual date nights, online games, and streaming service subscriptions. The Future of Holiday Gifting in Modern Dating As holiday gifting trends evolve on online communication platforms, sentimentality, customization, and virtual gifts are shaping the future of not only dating, but gift-giving. Online daters are redefining relationships through thoughtful gestures with the influence of SDG and its popular platforms like DateMyAge and Dating.com. It´s safe to say as we move toward a more and more complex digital reality, that the act of gift-giving will continue to evolve to changing relationship dynamics and shifting consumer behavior. It´s the season of celebrating love, friendship, and connection and gift-giving trends have evolved as the dating world becomes more complex. Dating.com , a leading global online communication platform under Social Discovery Group (SDG), has observed a shift in gift-giving between partners, friends, and new connections during big festivities. Individual preferences and broader societal changes are reflecting the changes in dynamic relationships and consumer behavior. Dating.com Social Discovery Group observed a shift Thoughtful and Personalized Gifts Take Center Stage Thoughtful and Personalized Gifts Take Center Stage A top trend observed during the holidays is an increased emphasis on personalized gifts. Generic presents like chocolate, socks, or candles are no longer a go-to. Do we really need more stuff anyway? Instead many daters are opting for a more personal touch to their gifts to express their care. Custom-made gifts like engraved jewelry, artwork, and even personalized playlists have become increasingly popular. A top trend observed during the holidays is an increased emphasis on personalized gifts. Generic presents like chocolate, socks, or candles are no longer a go-to. Do we really need more stuff anyway? Instead many daters are opting for a more personal touch to their gifts to express their care. Custom-made gifts like engraved jewelry, artwork, and even personalized playlists have become increasingly popular. stuff Nowadays, relationships are more about meaningful connections than superficial interactions. The rise of online communication platforms, where users from diverse backgrounds can easily meet, has led to a huge desire to stand out from the crowd with a unique or tailored gift. Customized gifts, especially when they represent an inside joke or a shared experience demonstrate thoughtfulness. How Digital Platforms Shape Modern Dating How Digital Platforms Shape Modern Dating Global online digital communication platforms have played a huge role in how people approach relationships and gift-giving. More people are turning to online dating and increasing virtual interactions to get to know their potential partners. Meaningful and thoughtful connections that are made have translated into great gift-giving. Dating.com has also reported an uptick in virtual gifting options, like sending digital gift cards, virtual experiences, or online subscriptions. Gifting shared experiences while being physically apart is especially important during the holiday season. Societal Changes and Consumer Behavior Societal Changes and Consumer Behavior Consumer behavior has shifted significantly during the holiday season. People are moving away from materialistic things and prioritizing sentimental value over cost. According to a study, 45% of users prefer gifts that have sentimental meaning rather than extravagant presents, which reflects a new cultural trend. Digital communication and dating platforms are becoming increasingly popular and consumers are opting for gifts that align with their digital lifestyles, such as virtual date nights, online games, and streaming service subscriptions. The Future of Holiday Gifting in Modern Dating The Future of Holiday Gifting in Modern Dating As holiday gifting trends evolve on online communication platforms, sentimentality, customization, and virtual gifts are shaping the future of not only dating, but gift-giving. Online daters are redefining relationships through thoughtful gestures with the influence of SDG and its popular platforms like DateMyAge and Dating.com. It´s safe to say as we move toward a more and more complex digital reality, that the act of gift-giving will continue to evolve to changing relationship dynamics and shifting consumer behavior.

Virtual Connections, Personal Touches: How Dating Apps Changed Holiday Gift Traditions

ምናባዊ ግንኙነቶች፣ የግል ንክኪዎች፡ የፍቅር ጓደኝነት መተግበሪያዎች እንዴት የበዓል ስጦታ ባህሎችን እንደቀየሩ

Virtuelne veze, lični dodiri: Kako su aplikacije za upoznavanje promijenile tradiciju prazničnih poklona

Connexions virtuals, tocs personals: com les aplicacions de cites van canviar les tradicions dels regals de vacances

Virtuelle forbindelser, personlige præg: Hvordan datingapps ændrede julegavetraditioner

Conexiones virtuales, toques personales: cómo las aplicaciones de citas cambiaron las tradiciones de los regalos navideños

קשרים וירטואליים, נגיעות אישיות: כיצד אפליקציות היכרויות שינו את מסורות המתנות לחגים

バーチャルなつながり、パーソナルなタッチ：出会い系アプリがホリデーギフトの伝統を変えた方法

Virtualūs ryšiai, asmeniniai prisilietimai: kaip pažinčių programos pakeitė šventinių dovanų tradicijas

Virtuālie sakari, personiski pieskārieni: kā iepazīšanās lietotnes mainīja svētku dāvanu tradīcijas

Virtual Connections, Kubata Kwemunhu: Mashandisiro Akaita Kufambidzana Mapurogiramu Akachinja Tsika dzeChipo cheHoridhe

Xidhiidhada Farshaxanka ah, Taabashada Shakhsi ahaaneed: Sida Shukaansiga Apps-ka u Bedeshay Hidiyadda Fasaxa

Lidhje virtuale, prekje personale: Si aplikacionet e takimeve ndryshuan traditat e dhuratave të festave

Cryptography comes from Ancient Greek, and it means something like a secret or hidden writing. That’s how this discipline started: someone would write a message for another party but use various techniques to keep it secret from others. For instance, they might change the usual order of letters or words, with the correct order known only to the recipient. Things have evolved a lot from that point, but that’s the gist. In more modern times, we can define cryptography as the science of securing digital information and communications through complex mathematical techniques, but it's also an intersection with computer science, information security, physics, and even more. It ensures that data (often digital data) remains confidential, authentic, and unaltered. Practical uses of cryptography in our era include protecting personal information on devices, ensuring the privacy of emails and messages, safeguarding sensitive material, enabling secure access to online accounts, and securing online transactions. As you may imagine, that’s where cryptocurrencies enter this topic. The “crypto” bit comes from cryptography, because cryptocurrencies are, basically, digital coins made of pure cryptography (complex mathematics). Beyond what we can or need to see, their inner workings are full of algorithms and long alphanumeric strings, sometimes only readable and understandable by machines. In the end, this is the reason why they exist at all. Public Key Cryptography There are numerous existing cryptographic techniques, and even new ones being developed right now. Cryptocurrencies use several of those techniques already, but maybe the main one for the absolute majority is public key cryptography or asymmetric cryptography. This method involves a pair of "keys": a public key, which can be shared with anyone, and a private key, which is kept secret. By "keys" here, we mean long strings of characters typically represented as sequences of bits (binary digits). In cryptocurrencies, private keys are used to sign transactions, and public keys are used to verify the signatures. This ensures that only the owner of a cryptocurrency address can authorize transactions from that address. Public key cryptography plays a vital role in ensuring the security and integrity of transactions for cryptocurrencies. For instance, when Alice wants to send five coins to Bob, she signs the transaction with her private key, generating a unique digital signature that proves she authorized it. She then broadcasts the signed transaction to the cryptocurrency network. Nodes in the network receive the transaction and use Alice's public key to verify the signature. Once verified, the transaction is added to the chain, reducing Alice’s balance by five coins and increasing Bob’s balance by the same amount. This process prevents unauthorized access and tampering, ensuring the transaction’s security. All of this happens in the background, though. Final users see public keys as crypto addresses (shareable with anyone) and private keys in the form of private seeds (strings of random words to keep private and recover wallets). Beneath what we can see in our apps, they both look like long and barely legible alphanumeric strings. Crypto addresses are, let’s say, the shorter version. Even if they still are sort of long and complex. Simplifying Cryptos Obyte simplifies cryptography in cryptocurrencies with textcoins, making digital currency accessible without a steep learning curve. Textcoins allow users to send and receive funds through familiar methods like email, instant messaging, or even on paper. A textcoin is essentially a string of twelve random words or a link that contains cryptocurrency. This means someone can carry a piece of paper with these words and redeem the funds later when they have access to the Internet and an Obyte wallet. Textcoins work seamlessly for people without the use of any crypto address, even if they don’t have a wallet yet. For example, Bob can create a textcoin in his Obyte wallet, which generates a string like "together-orange-pelican-tooth-fox-lucky-half-cup-window-coil-radar-pen" or a link. He can then send this textcoin via email or chat to Alice. Alice, upon receiving it, can claim the funds by clicking the link or entering the words into her Obyte wallet once she has Internet access. This simplicity allows even those unfamiliar with cryptocurrency to use it easily. Moreover, textcoins are refundable, adding a layer of security. If Alice doesn’t claim the textcoin for any reason, Bob can reclaim the funds by accessing the textcoin details in his Obyte wallet’s history. This feature ensures that funds aren’t lost if the recipient fails to claim them, providing both flexibility and security. Obyte’s textcoins effectively bridge the gap between the digital and physical worlds, making cryptocurrency transactions straightforward and accessible for everyone. Featured Vector Image by Freepik Cryptography comes from Ancient Greek, and it means something like a secret or hidden writing. That’s how this discipline started: someone would write a message for another party but use various techniques to keep it secret from others. For instance, they might change the usual order of letters or words, with the correct order known only to the recipient. Things have evolved a lot from that point, but that’s the gist. In more modern times, we can define cryptography as the science of securing digital information and communications through complex mathematical techniques, but it's also an intersection with computer science, information security, physics, and even more. It ensures that data (often digital data) remains confidential, authentic, and unaltered. In more modern times, we can define cryptography as the science of securing digital information and communications through complex mathematical techniques, cryptography Practical uses of cryptography in our era include protecting personal information on devices, ensuring the privacy of emails and messages, safeguarding sensitive material, enabling secure access to online accounts, and securing online transactions. As you may imagine, that’s where cryptocurrencies enter this topic. The “crypto” bit comes from cryptography, because cryptocurrencies are, basically, digital coins made of pure cryptography (complex mathematics). Beyond what we can or need to see, their inner workings are full of algorithms and long alphanumeric strings, sometimes only readable and understandable by machines. In the end, this is the reason why they exist at all. Public Key Cryptography There are numerous existing cryptographic techniques, and even new ones being developed right now. Cryptocurrencies use several of those techniques already, but maybe the main one for the absolute majority is public key cryptography or asymmetric cryptography . This method involves a pair of "keys": a public key, which can be shared with anyone, and a private key, which is kept secret. asymmetric cryptography asymmetric cryptography By "keys" here, we mean long strings of characters typically represented as sequences of bits (binary digits). In cryptocurrencies, private keys are used to sign transactions, and public keys are used to verify the signatures. This ensures that only the owner of a cryptocurrency address can authorize transactions from that address. Public key cryptography plays a vital role in ensuring the security and integrity of transactions for cryptocurrencies . For instance, when Alice wants to send five coins to Bob, she signs the transaction with her private key, generating a unique digital signature that proves she authorized it. She then broadcasts the signed transaction to the cryptocurrency network. Nodes in the network receive the transaction and use Alice's public key to verify the signature. Once verified, the transaction is added to the chain, reducing Alice’s balance by five coins and increasing Bob’s balance by the same amount. This process prevents unauthorized access and tampering, ensuring the transaction’s security. Public key cryptography plays a vital role in ensuring the security and integrity of transactions for cryptocurrencies All of this happens in the background, though. Final users see public keys as crypto addresses (shareable with anyone) and private keys in the form of private seeds (strings of random words to keep private and recover wallets). Beneath what we can see in our apps, they both look like long and barely legible alphanumeric strings. Crypto addresses are, let’s say, the shorter version. Even if they still are sort of long and complex. Simplifying Cryptos Obyte simplifies cryptography in cryptocurrencies with textcoins, making digital currency accessible without a steep learning curve. Textcoins allow users to send and receive funds through familiar methods like email, instant messaging, or even on paper. A textcoin is essentially a string of twelve random words or a link that contains cryptocurrency. This means someone can carry a piece of paper with these words and redeem the funds later when they have access to the Internet and an Obyte wallet . Obyte simplifies cryptography in cryptocurrencies with textcoins, making digital currency accessible without a steep learning curve. Obyte wallet Obyte wallet Textcoins work seamlessly for people without the use of any crypto address, even if they don’t have a wallet yet. For example, Bob can create a textcoin in his Obyte wallet, which generates a string like "together-orange-pelican-tooth-fox-lucky-half-cup-window-coil-radar-pen" or a link. He can then send this textcoin via email or chat to Alice. Alice, upon receiving it, can claim the funds by clicking the link or entering the words into her Obyte wallet once she has Internet access. This simplicity allows even those unfamiliar with cryptocurrency to use it easily. Textcoins Textcoins Moreover, textcoins are refundable, adding a layer of security. If Alice doesn’t claim the textcoin for any reason, Bob can reclaim the funds by accessing the textcoin details in his Obyte wallet’s history. This feature ensures that funds aren’t lost if the recipient fails to claim them, providing both flexibility and security. Obyte’s textcoins effectively bridge the gap between the digital and physical worlds, making cryptocurrency transactions straightforward and accessible for everyone. Moreover, textcoins are refundable , adding a layer of security. textcoins are refundable textcoins are refundable Featured Vector Image by Freepik Featured Vector Image by Freepik Freepik Freepik

Educational Byte: Cryptography and Its Connection to Cryptocurrencies

শিক্ষাগত বাইট: ক্রিপ্টোগ্রাফি এবং ক্রিপ্টোকারেন্সির সাথে এর সংযোগ

Bildungsbyte: Kryptographie und ihre Verbindung zu Kryptowährungen

Byte Educativo: La Criptografía y su Conexión con las Criptomonedas

Byte éducatif : la cryptographie et son lien avec les cryptomonnaies

शैक्षिक बाइट: क्रिप्टोग्राफी और क्रिप्टोकरेंसी से इसका संबंध

教育バイト: 暗号化と暗号通貨とのつながり

교육 바이트: 암호화와 암호화폐와의 연결

Byte Educacional: Criptografia e sua conexão com criptomoedas

Образовательный байт: Криптография и ее связь с криптовалютами

Eğitim Byte: Kriptografi ve Kripto Para Birimleriyle Bağlantısı

Educational Byte: Mật mã học và mối liên hệ của nó với tiền điện tử

教育内容：密码学及其与加密货币的联系

Ola: More Than Infrastructure - A New Gateway Connecting Web2 and Web3 Worlds

ওলা: অবকাঠামোর চেয়েও বেশি - ওয়েব2 এবং ওয়েব3 ওয়ার্ল্ডকে সংযুক্ত করার একটি নতুন গেটওয়ে

Ola: Mehr als Infrastruktur – Ein neues Gateway, das die Web2- und Web3-Welten verbindet

Ola: Más que infraestructura: una nueva puerta de enlace que conecta los mundos Web2 y Web3

Ola : Plus qu'une infrastructure - Une nouvelle passerelle reliant les mondes Web2 et Web3

ओला: बुनियादी ढांचे से कहीं अधिक - वेब2 और वेब3 दुनिया को जोड़ने वाला एक नया प्रवेशद्वार

Ola: 単なるインフラストラクチャ以上のもの - Web2 と Web3 の世界をつなぐ新しいゲートウェイ

Ola: 인프라 그 이상 - Web2와 Web3 세계를 연결하는 새로운 게이트웨이

Ola: Mais que infraestrutura – um novo gateway conectando os mundos Web2 e Web3

Ола: Больше, чем инфраструктура: новый шлюз, соединяющий миры Web2 и Web3

Ola: Altyapıdan Daha Fazlası - Web2 ve Web3 Dünyalarını Birleştiren Yeni Bir Ağ Geçidi

Ola: Hơn cả cơ sở hạ tầng - Một cổng mới kết nối thế giới Web2 và Web3

Ola：不仅仅是基础设施——连接 Web2 和 Web3 世界的新网关

Ever heard the phrase, "Your network is your net worth?" I totally get the sentiment – but at the same time, I think networking should be so much more than the prospect of cash in the bank. If we're honest, networking is far more complex and demanding than a simple monetary exchange. It takes time. It takes trust. It takes vulnerability. When networking just isn't working for us, usually, the reason is a lack of authentic connection. Cold outreach messages are often forced; conversations at networking events are awkward and clearly transactional. Don't even get me started on LinkedIn! I propose we take a new approach to networking. If you really want your authentic self to shine through – if you truly want to make helpful connections that last – it's time to reframe networking and take a more meaningful approach. Let's talk about it. Our Flawed View of Networking Networking, as you know, is the art of building relationships for professional gain. A powerful connection can hook you up with your best job yet, on your highest salary to date. The right referral can get you much-needed VC funding to launch your startup off the runway. As an entrepreneur, networking is your lifeblood; it's your gateway to greater success. In Ronald Burt's words: "Instead of better glasses, your network gives you better eyes." But here's the problem – and I know you're thinking it – networking is freaking hard. It's like this strange social dance where you know you're being obvious, but you don't know how else you can do it. really Why is it so awkward? Let's unpack some of the warps in our perception of networking. Misconception 1: You Are the Product I'm convinced that one of our biggest barriers to networking is the way we try to 'market' ourselves. You aren't a product, you're a person, and the mindset of ‘selling yourself’ will only strip away your authenticity. For example: when you network on a regular basis, it's easy to find yourself rattling off the same script about your work or your experience. You might copy-paste the same blurb from one LinkedIn conversation to the next. But a sales script runs the risk of looking disingenuous – especially a copy-and-paste job. The reality is that networking isn't about selling yourself; it's about forming a connection first and foremost. Misconception 2: It's All About the Benefits “If we create networks with the sole intention of getting something, we won’t succeed. We can’t pursue the benefits of networks; the benefits ensue from investments in meaningful activities and relationships.” Adam Grant hits the nail on the head here – intentions are everything, and if you're networking only for the benefits, you're going to struggle. It's easy to get caught up in the idea of what someone can do for us. The messaging around networking is very much benefits-focused, so it's no wonder we approach it that way. But it's one of the worst things we can do for ourselves. In the social world, you'd be frowned upon for making friends with someone just to get something from them. So why do we network that way and pretend it'll work in our favor? Misconception 3: You Need to Be Interesting No, you don't need to be interesting – you need to be interest . ed Our problem with networking comes from our overly inward focus. We spend so much time and energy stressing about how we'll come across to the other person. Is our pitch nailed down? Are we dressed professionally for the meetup? Did we use too many exclamation points in our outreach? But in ruminating over all of these tiny details, we forget the most important factor: taking an interest in the other person. said Bob Burg. That's the skill we need to be honing. “The single greatest "people skill" is a highly developed & authentic interest in the other person,” People can very easily tell whether you're interested in what they have to say; there's a certain energy in genuine interest that can't be faked. What's the Fix? Believe it or not, aren't published on boards or via the main application portals. Investors don't walk around with 'VC money!' tattooed on their foreheads. 70 percent of jobs Opportunities don't always slap you in the face. That's why networking is so important: when you're connected to your industry, you're tapping into support and opportunities and advice most people don't even know is there. But as I said, our big misconceptions about networking are holding us back from success. It's time to take the unscripted and unconventional approach (aka, it's time to build real relationships!). Strategy 1: Ditch the Scripts and Take an Interest The reason that networking can feel so 'yucky' or 'salesy' is because, as I mentioned earlier, we're often taught to approach it with a script. We're taught to get our pitch sorted, and then send it to as many people as possible. "Hi, I hope you're well! I just wanted to reach out and introduce myself – I'm a business owner in LA, and I am looking to make new connections within my niche. Would you be interested in meeting up?" Bleh. Even the most oblivious person can tell what you're trying to do here, and it'll only make you feel like a salesperson. This is the moment – before reaching out, before making a connection and a time investment – to think about the person you're connecting with. really What do you have in common? What work are they doing? How are they innovating in their space, and what values do they seem to prioritize? Your network should be made up of people who you truly respect and admire and whose work inspires you. An interesting person will prompt you to naturally write a more authentic opening message – you'll be expressing your genuine interest in the person and their work rather than shoehorning a sales pitch. Strategy 2: Accept the Commitment While a casual conversation on LinkedIn is , networking is rarely a one-time effort. Building meaningful connections takes time, just like any other friendship. You need to build mutual trust. proven to be pretty effective Studies show it takes to properly build trust with people. (It takes a split second to lose it, so keep that in mind, too!) around seven months That means you're really playing the long game when it comes to networking. Again, it's in your best interests to connect with people you genuinely resonate with – because you're building a real relationship, not just a one-time exchange. It goes without saying that networking isn't the same as job hunting. You should be forming connections with like-minded people and developing your network over time (not looking for a quick fix). Strategy 3: Strive for Generosity – Keith Ferrazzi “The currency of real networking is not greed but generosity.” Let's completely flip the narrative. What if you were to approach networking with the mentality of 'what do I have to offer?' When you network with the intention of giving, it's incredibly freeing. Know your worth and your experience, and find people who could benefit from connecting with you; more often than not, the pure act of giving will unlock a new level of opportunities. Going back to strategy two, there's no better way to build trust than to give before you receive. You're saying it loud and clear: I'm not here to gain, I'm here to connect. Strategy 4: Be Unconventional There's no rulebook for networking, and yet, we all act as though we're bound to certain customs or etiquette. You don't need to confine your outreach to LinkedIn (even though it's a great place to start). Follow your prospects on social media to stay up-to-date on their latest accomplishments. Respond to a story that resonates with you – leave a casual note, and see if it blossoms into a conversation. When you're writing messages to potential connections, throw out everything you know about the typical outreach script and follow your instincts. Based on their personality and interests, what's going to spark their curiosity? If someone is clearly down-to-earth and super friendly, the last thing you want is to lead with 'dear [name], I hope this finds you in excellent health!' Speak their language – but more importantly, let your own authentic personality shine through. Are you a contractions person? Use contractions. Is your sense of humor intact? Throw in a joke or two if they come naturally. Drop little hints as to the kind of person you are. Wrap Up When it comes to networking, I'm a firm believer in forming honest, authentic relationships – not transactional ones. It's all about your approach. Network for the sake of meeting people and expanding your knowledge of the world; don't just network to get a free ride. Some of the most incredible connections I've made in my life were through networking efforts, and I've made my fair share of blunders, too. I know from experience that being authentic is your greatest weapon. Taking a vested interest in others is your ticket to success. Any other thoughts on how to network well? Drop a comment below or reply to my email – I'd love to hear more! If you enjoyed this article, I’d love to hear from you. Reply to this email or at me and I’ll do my best to get back to everyone! tweet @ScottDClary

You Need Authentic Connections: How to Reframe Your Network Narrative

আপনার প্রামাণিক সংযোগ প্রয়োজন: আপনার নেটওয়ার্ক বর্ণনাটি কীভাবে রিফ্রেম করবেন

Sie brauchen authentische Verbindungen: So gestalten Sie Ihre Netzwerkerzählung neu

Necesita conexiones auténticas: cómo reformular la narrativa de su red

Vous avez besoin de connexions authentiques : comment recadrer le récit de votre réseau

आपको प्रामाणिक कनेक्शन की आवश्यकता है: अपने नेटवर्क नैरेटिव को कैसे रीफ़्रेम करें

本物の接続が必要です: ネットワークの説明を再構築する方法

진정한 연결이 필요합니다: 네트워크 내러티브를 재구성하는 방법

Você precisa de conexões autênticas: como reformular sua narrativa de rede

Otantik Bağlantılara İhtiyacınız Var: Ağ Anlatımınızı Nasıl Yeniden Çerçevelendirebilirsiniz?

Bạn cần các kết nối xác thực: Cách điều chỉnh lại tường thuật mạng của bạn

你需要真实的联系：如何重构你的网络叙事

Over the last decade, the growth and success of machine learning have been phenomenal, driven primarily by the availability of vast amounts of data and advanced computational power. This surge was brought about by the digitization of various sectors, leading to an explosion of digital data—everything from social media posts to online transactions and sensor data. Advances in machine learning techniques, particularly in deep learning, facilitated the development of more complex and versatile models. Consequently, machine learning applications have become ubiquitous, contributing to improved efficiencies and capabilities across numerous sectors, including healthcare, finance, and transportation. Working with these massive amounts of event-based data and deriving value from the events themselves and their context in time – other events happening nearby – is still difficult. Doing so in a real-time or streaming manner is harder still. You often must use complex, low-level APIs or work around the limitations of a higher-level query language designed to solve very different problems, like SQL. To tackle these challenges, we introduce a new abstraction for time-based data, called timelines. Timelines organize data by time and entity, offering an ideal structure for event-based data with an intuitive, graphical mental model. Timelines simplify reasoning about time by aligning your mental model with the problem domain, allowing you to focus on what to compute, rather than how to express it. In this post, we present timelines as a natural way to organize event-based data and extract value – directly, and as the inputs for machine learning and prompt engineering. We delve into the timeline concept, its interaction with external data stores (inputs and outputs), and the lifecycle of queries using timelines. This post is the first in a series about , an open-source event-processing engine designed around the timeline abstraction. We’ll follow up with an explanation of how Kaskada builds an expressive temporal query language on the timeline abstraction, how the timeline data model enables Kaskada to efficiently execute temporal queries, and, finally, how timelines enable Kaskada to execute incrementally over event streams. Kaskada Making sense of time Dealing with a large variety of events is difficult when treating each kind of event as a separate, unordered table of data – the way SQL views the world. It is difficult to understand what motivated Carla to make purchases, or what caused Aaron to engage with other users via messages. By organizing the data – by time and user – it becomes much easier to spot patterns. Aaron sends messages after winning. Carla makes purchases when frustrated by a series of losses. We also see that Brad may have stopped playing. By organizing the data – by time and user – it becomes much easier to spot patterns. Aaron sends messages after winning. Carla makes purchases when frustrated by a series of losses. We also see that Brad might have stopped playing. By organizing the events in a natural way – by time and user – we were able to identify patterns. This same organization allows us to express feature values computed from the events and use those to train and apply machine learning models or compute values to use within a prompt. The timeline abstraction Reasoning about time – for instance, cause-and-effect between events – requires more than just an unordered set of event data. For temporal queries, we need to include time as a first-class part of the abstraction. This allows reasoning about when an event happened and the ordering – and time – between events. Kaskada is built on the timeline abstraction: a multiset ordered by time and grouped by entity. Timelines have a natural visualization, shown below. Time is shown on the x-axis and the corresponding values on the y-axis. Consider purchase events from two people: Ben and Davor. These are shown as discrete points reflecting the time and amount of the purchase. We call these discrete timelines because they represent discrete points. The time axis of a timeline reflects the time of a computation’s result. For example, at any point in time we might ask “what is the sum of all purchases?” Aggregations over timelines are cumulative – as events are observed, the answer to the question changes. We call these continuous timelines because each value continues until the next change. Compared to SQL, timelines introduce two requirements: ordering by time and grouping by entity. While the SQL relation – an unordered multiset or bag – is useful for unordered data, the additional requirements of timelines make them ideal for reasoning about cause-and-effect. Timelines are to temporal data what relations are to static data. Adding these requirements mean that timelines are not a fit for every data processing task. Instead, they allow timelines to be a better fit for data processing tasks that work with events and time. In fact, most event streams (eg., Apache Kafka, Apache Pulsar, AWS Kinesis, etc.) provide ordering and partitioning by key. When thinking about events and time, you likely already picture something like a timeline. By matching the way you already think about time, timelines simplify reasoning about events and time. By building in the time and ordering requirements, the timeline abstraction allows temporal queries to intuitively express cause and effect. Using timelines for temporal queries Timelines are the abstraction used in Kaskada for building temporal queries, but data starts and ends outside of Kaskada. It is important to understand the flow of data from input, to timelines, and finally to output. Every query starts from one or more sources of input data. Each input – whether it is events arriving in a stream or stored in a table, or facts stored in a table – can be converted to a timeline without losing important context such as the time of each event. The query itself is expressed as a sequence of operations. Each operation creates a timeline from timelines. The result of the final operation is used as the result of the query. Thus, the query produces a timeline which may be either discrete or continuous. The result of a query is a timeline, which may be output to a sink. The rows written to the sink may be a history reflecting the changes within a timeline, or a snapshot reflecting the values at a specific point-in-time. Inputting timelines Before a query is performed, each input is mapped to a timeline. Every input – whether events from a stream or table or facts in a table – can be mapped to a timeline without losing the important temporal information, such as when events happened. Events become discrete timelines, with the value(s) from each event occurring at the time of the event. Facts become continuous timelines, reflecting the time during which each fact applied. By losslessly representing all kinds of temporal inputs, timelines allow queries to focus on the computation rather than the kind of input. Outputting timelines After executing a query, the resulting timeline must be output to an external system for consumption. The sink for each destination enables configuration of data writing, with specifics depending on the sink and the destination (see for more). this connector documentation There are several options for converting the timeline into rows of data, affecting the number of rows produced: Include the entire history of changes within a range or just a snapshot of the value at some point in time. Include only events (changes) occurring after a certain time in the output. Include only events (changes) up to a specific time in the output. A full history of changes helps visualize or identify patterns in user values over time. In contrast, a snapshot at a specific time is useful for online dashboards or classifying similar users. Including events after a certain time reduces output size when the destination already has data up to that time or when earlier points are irrelevant. This is particularly useful when re-running a query to materialize to a data store. Including events up to a specific time also limits output size and enables choosing a point-in-time snapshot. With incremental execution, selecting a time slightly earlier than the current time reduces late data processing. Both “changed since” and “up-to” options are especially useful with incremental execution, which we will discuss in an upcoming article. History The history – the set of all points in the timeline – is useful when you care about past points. For instance, this may be necessary to visualize or identify patterns in how the values for each user change over time. The history is particularly useful for outputting training examples to use for creating a model. Any timeline may be output as a history. For a discrete timeline, the history is the collection of events in the timeline. For a continuous timeline, the history contains the points at which a value changes – it is effectively a changelog. Snapshots A snapshot – the value for each entity at a specific point in time – is useful when you just care about the latest values. For instance, when updating a dashboard or populating a feature store for connecting to model serving. Any timeline may be output as a snapshot. For a discrete timeline, the snapshot includes rows for each event happening at that time. For a continuous timeline, the snapshot includes a row for each entity with that entity’s value at that time. Conclusion This blog post highlighted the importance of temporal features when creating ML models from event-based data. The time and temporal context of events is critical to seeing patterns in activity. This post introduced the timeline abstraction, which makes it possible to work with the events and the temporal context. Timelines organize data by time and entity, providing a more suitable structure for event-based data compared to multisets. The timeline abstraction is a natural progression in stream processing, allowing you to reason about time and cause-and-effect relationships more effectively. We also explored the flow of data in a temporal query, from input to output, and discussed the various options for outputting timelines to external systems. Rather than applying a tabular (static) query to a sequence of snapshots, Kaskada operates on the history (the change stream). This makes it natural to operate on the time between snapshots, rather than only on the data contained in the snapshot. Using timelines as the primary abstraction simplifies working with event-based data and allows for seamless transitions between streams and tables. You can experimenting with your own temporal queries today. and let us know what you think about the timeline abstraction. In an upcoming post, we’ll delve into the Kaskada query language and its capabilities in expressive temporal queries. get started Join the Slack community By Ben Chambers and Therapon Skoteiniotis, DataStax

Connecting Event-Based Data to Predictive AI in Real-Time

Conexión de datos basados en eventos a IA predictiva en tiempo real

Connecter les données basées sur les événements à l'IA prédictive en temps réel

रीयल-टाइम में ईवेंट-आधारित डेटा को प्रिडिक्टिव AI से कनेक्ट करना

イベントベースのデータをリアルタイムで予測 AI に接続する

Conectando dados baseados em eventos à IA preditiva em tempo real

Kết nối dữ liệu dựa trên sự kiện với AI dự đoán trong thời gian thực

将基于事件的数据实时连接到预测性 AI

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