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  1. Equipos: Transmisor FM con DSP

    Hace bastante tiempo, al parecer ya por el 2022 o mucho antes. había comprado este pequeño aparatito con el fin de hacer experimentos. En realidad es bastante más útil de lo que parece y tiene una calidad increíble.

    interlan.ec/blog/2026/10/16/eq

  2. BMO: #Equitymarkets point to a modestly-higher open this morning, while #Treasury #yields are a touch higher. The selloff in #AI #stocks in recent days has gone hand-in-hand with the rally in Treasury yields, with the 10-year now down almost 20 bps from early last week to 5.09%.#markets

  3. Equal Pay in Tennis: Too Little, or Too Late?

    On 1 October 2026, the Women’s Tennis Association (WTA) announced that, from the 2027 season, every combined WTA…
    #Tennis #News
    europesays.com/tennis/88039/

  4. What can we take away from the #USWNT's 2-2 draw against Spain? @[email protected] breaks down the ongoing lineup tinkering, major lingering defensive issues, and how the team thrives when playing direct in attack.
    equalizersoccer.com/2026/10/14

  5. Where is the outrage? Where is the helping hand?

    Why should a 59-year-old woman lose everything because of a landslide she didn’t cause? Her home equity is trapped, her bills are mounting, and financial ruin is approaching.

    Please-donate & share 🙏

    gofund.me/e519fbf98
    #mastodon #mutualaid #gofundme #helpfolkslive #help #helpfolkslive2026

  6. The systemic resolution of homelessness in #NewZealand requires moving beyond consumable #rent #subsidies and #reactive #crisis spending. Current interventions expend significant #public #resources to manage acute distress without acquiring #capital #equity or resolving underlying market failures.

    RE: https://bsky.app/profile/did:plc:hc7tndm7gduompba65aps75k/post/3mxssjksrn22g

  7. 🇺🇸 🇪🇸 Spain got off to a hot start, but the #USWNT responded with two second-half goals to draw 2-2.

    Check out our immediate recap of tonight's action, which included goals from Ashley Sanchez and Mallory Swanson!

    ✍️: @[email protected]

    equalizersoccer.com/2026/10/13

  8. S'équiper sans se ruiner : 5 casques gamer incontournables à moins de 100 €

    Faut-il vraiment casser sa tirelire pour profiter d'un son immersif en jeu ? Avec idealo, découvrez 5 casques gamer de référence à moins de 100 € qui démontrent ...

    (ift.tt/9ykstAF)
    #jv #gamer #gamergen #gaming #fr #gamingNews

  9. Asian equities fell sharply today. The KOSPI dropped 7% as semiconductor stocks sold off. U.S. inflation data has renewed fears of further Fed rate hikes, pressuring tech-heavy markets across the region.

    Simulated results — not investment advice.

    #KOSPI #Semiconductors #FederalReserve #AsiaMarkets

  10. (L'Équipe) "La compo probable de l'OL contre Crystal Palace :
    Greif - Athekame, Bacher, R. Kluivert, Abner - Nartey, Morton, Tolisso (cap.) - Nuamah, Merah, K. Nakamura"

  11. As equipas de emergência não foram autorizadas a entrar na prisão do Tennessee durante, pelo menos, meia hora após a chamada de emergência inicial.

    publico.pt/2026/10/14/mundo/no

  12. 🎯 ■ El equipo de campaña del PSOE envía un email haciéndose pasar por Feijóo: "Me parece una verdadera genialidad" ■ Varios usuarios reportan el "susto" al leer que el remitente era el líder del PP, pero realmente era el equipo de campaña del partido socialista.
    huffingtonpost.es/virales/el-e

  13. David Lloyd sparks equality row by excluding men from spa sessions in gyms because some women feel uncomfortable for ‘religious reasons’ | Daily Mail Online byteseu.com/2457700/ #UK #UnitedKingdom

  14. Uma alimentação equilibrada e nutricialmente adequada deve ser também “agradável”, “apelativa” e “saborosa”, para cativar mais alunos.

    publico.pt/2026/10/16/sociedad

  15. Nietzsche tended to equate the memorable with the painful.

  16. La une de l'Équipe de ce vendredi 16 octobre

  17. Introduction

    Connecting industrial equipment to the internet is no longer the only challenge facing modern businesses. The bigger question is how organizations can turn the data generated by connected devices into decisions that improve operations.

    The Internet of Things (IoT) provides visibility into physical assets, machinery, inventory, and working environments. Artificial Intelligence (AI) can help interpret this information, identify patterns, and support decisions based on changing operational conditions.

    Together, these technologies form what is commonly called AIoT. Their potential extends beyond monitoring equipment: they can help businesses identify inefficiencies, anticipate maintenance needs, and improve how resources are managed.

    However, successful implementation depends on more than combining two technologies. Organizations must identify the right problems, establish reliable data systems, and measure whether the resulting solutions deliver practical value.

    1. From Data Collection to Better Decisions

    Traditional IoT systems collect information from connected sensors and devices. For example, industrial sensors may record equipment temperature, vibration, location, or operating status.

    This information helps employees understand current conditions, but large volumes of data can make it difficult to identify which events require attention.

    AI can help by analyzing historical and real-time information to detect patterns or unusual changes.

    Consider a manufacturing facility monitoring several machines. An IoT system collects vibration readings, while an AI model identifies changes that may indicate equipment deterioration. Maintenance teams can investigate these alerts and determine whether intervention is necessary.

    This approach can support earlier maintenance planning, but it does not guarantee that every failure will be predicted. Results depend on data quality, operating conditions, and model performance.

    An important distinction is that not every industrial problem requires AI. Simple thresholds and conventional automation may be sufficient for predictable tasks. AI becomes more useful when patterns are complex, conditions change, or large datasets require analysis that fixed rules cannot handle effectively.

    1. Five Practical Applications of AIoT

    Asset Tracking and Visibility

    Warehouses, factories, and distribution networks need accurate information about the location and status of physical assets.

    Technologies such as RFID, connected sensors, and location-tracking devices can improve asset visibility. AI-assisted analytics may help identify unusual movement patterns, underused equipment, or recurring operational bottlenecks.

    The value comes from using this information to make better decisions about inventory allocation, equipment availability, and resource utilization.

    Inventory and Operations Optimization

    Inventory discrepancies and inefficient workflows can increase costs and delay operations.

    IoT systems can provide information about stock levels, asset movement, and operational activity. AI models can use this data to support demand forecasting, identify recurring inefficiencies, and improve planning.

    Organizations should evaluate these recommendations against actual business conditions, particularly when decisions affect purchasing, production schedules, or customer commitments.

    Predictive Maintenance

    Unexpected equipment failures can interrupt production and increase maintenance costs.

    By analyzing sensor data alongside equipment history, AI models may identify patterns associated with deterioration. Maintenance teams can use these insights to investigate potential problems and prioritize inspections.

    Effective implementation requires reliable sensor readings, relevant historical data, and a process for validating alerts against actual equipment conditions.

    Workforce Safety and Monitoring

    Industrial environments can involve hazardous equipment, restricted areas, and changing safety conditions.

    Connected devices and monitoring systems can help identify environmental risks and improve awareness of potentially unsafe situations. AI may support the detection of unusual conditions, but it should complement established safety procedures rather than replace them.

    Privacy, transparency, appropriate data access, and human oversight are essential when systems monitor employees or workplace activity.

    Access Control and Security

    Connected access systems can integrate credentials, sensors, entry points, and monitoring platforms.

    AI-assisted analytics may help flag unusual access patterns for investigation. At the same time, organizations must secure connected devices, restrict unauthorized access, and maintain their systems to reduce cybersecurity risks.

    Greater connectivity can improve visibility, but it also makes security an essential part of system design.

    1. Why Industrial AIoT Projects Face Implementation Challenges

    Even a promising AIoT application can struggle if the underlying infrastructure is unreliable or the business problem is poorly defined.

    Several factors deserve attention before implementation.

    Data quality: Missing sensor readings, inconsistent formats, and inaccurate measurements can undermine analytical results.

    System integration: New solutions must work with existing equipment, enterprise applications, and operational processes.

    Security and privacy: Devices, communication channels, and data pipelines require appropriate protection and access controls.

    Reliability: Systems need procedures for handling network failures, unexpected conditions, and incorrect recommendations.

    Employee adoption: Employees need to understand how the technology affects their work and when they should question its outputs.

    Business relevance: A technically impressive system may have little practical value if it does not address a meaningful operational problem.

    Starting with a specific challenge helps organizations evaluate these factors before committing to a larger deployment.

    1. How to Evaluate an AIoT Pilot

    A pilot project should test a business hypothesis, not simply demonstrate that connected devices and AI models can work together.

    A practical evaluation framework includes six steps.

    Step 1: Define the problem. Identify a measurable issue, such as time spent locating equipment, unexpected downtime, or inventory discrepancies.

    Step 2: Establish a baseline. Record current performance before introducing the solution. Without a baseline, it is difficult to determine whether the technology has improved results.

    Step 3: Check data readiness. Assess whether the available sensor readings and operational records are sufficiently accurate, complete, and relevant.

    Step 4: Select meaningful metrics. Depending on the application, these might include equipment availability, inventory accuracy, alert precision, response time, or maintenance costs.

    Step 5: Test failure scenarios. Examine how the system responds to missing data, false alerts, connectivity problems, and unusual operating conditions. Define when human intervention is required.

    Step 6: Assess total value. Compare the observed improvements with implementation, integration, maintenance, and training costs.

    For example, an asset-tracking pilot should measure whether employees can locate equipment more quickly and whether inventory records become more accurate. Counting connected assets alone would not establish business value.

    The findings can then inform a decision to expand, revise, or discontinue the project.

    1. Building Scalable Solutions From Reusable Technology

    Once an AIoT solution demonstrates practical value, organizations may identify opportunities to reuse parts of its architecture.

    Device connectivity, data processing, access management, analytics, and reporting can sometimes serve multiple applications. Reusing these components may reduce duplicated development work and simplify future deployments.

    However, scalability does not mean applying an identical solution everywhere. Different industries have different equipment, workflows, regulatory requirements, and operating conditions. A scalable platform must accommodate these differences without compromising reliability or security.

    This approach also creates opportunities for venture development. A technology capability that solves a well-defined industrial problem and demonstrates repeatable customer value may provide the foundation for a standalone commercial offering.

    For a broader perspective on how AI, IoT infrastructure, and venture creation intersect, explore Aperture Venture Studio.

    Conclusion

    AI and IoT can help industrial businesses move from basic monitoring toward more informed, data-driven operations. Applications range from asset visibility and predictive maintenance to inventory planning, workforce safety, and connected security systems.

    Yet technology alone does not guarantee better outcomes. Successful projects require reliable data, appropriate system integration, clear performance measures, and safeguards for situations in which automated recommendations fail.

    The most practical approach is to begin with a defined business problem, test the solution under real operating conditions, and measure its results against an established baseline.

    For industrial enterprises and technology developers alike, the goal should be to build systems that solve genuine operational challenges. When connected infrastructure and intelligent analytics are supported by sound implementation practices, AIoT can become a useful tool for creating measurable and sustainable business value.#ai #analytics #iot #software #coding #development #engineering #inclusive #community
    Beyond Connectivity: How AI and IoT Are Transforming Industrial Operations

  18. 🐐🆚🐅"Con el equipo que tenemos hay que ir por los 3 puntos"
    -Mauro Lainez

    "Acaba de darle CON TODO a Guido Pizarro, lo han matado"
    🎙️ @[email protected]

    "Tiene que hablar bien de Vuce, le dio la oportunidad"
    🎙️ @[email protected]

    #CuadroTitular 🔥

  19. If everything is equally important and needed yesterday then how do we keep the pressure from making our brains explode out of our ears, noses, mouths, and tear ducts?

  20. mojaoprema.com/quality-equipme Ali ste se kdaj vprašali, kako pomembna je izbira prave opreme za uspeh vašega projekta ali preprosto za lažje vsakdanje delo? Ne glede na to, ali ste mojster doma, navdušen vrtnar ali pa potrebujete zanesljive pripomočke za delavnico, mojaoprema.com/quality-equipme #BLOG

  21. Women’s equality will not be fully won until the female ideal becomes the measure of civilization.

    -- Margaret Fuller (Woman in the Nineteenth Century, 1845)

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