Techsplainers by IBM

IBM
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Introducing the Techsplainers by IBM podcast, your new podcast for quick, powerful takes on today’s most important AI and tech topics. Each episode brings you bite-sized learning designed to fit your day, whether you’re driving, exercising, or just curious for something new. This is just the beginning. Tune in every weekday at 6 AM ET for fresh insights, new voices, and smarter learning.

  1. قبل يومين

    What is AutoML?

    This episode of Techsplainers explores automated machine learning (AutoML), a transformative approach that automates the end-to-end development of machine learning models. We explain how AutoML democratizes AI by enabling non-experts to implement intelligent systems while allowing data scientists to focus on more complex challenges rather than routine tasks. The podcast walks through how AutoML solutions streamline the entire machine learning pipeline—from data preparation and preprocessing to feature engineering, model selection, hyperparameter tuning, validation, and deployment. Particularly valuable is our discussion of automated feature engineering, which can reduce development time from days to minutes while increasing model explainability. We explore four major use cases where AutoML excels: classification tasks like fraud detection, regression problems for forecasting, computer vision applications for image processing, and natural language processing for text analysis. The episode concludes by acknowledging AutoML's limitations, including potentially high costs for complex models, challenges with interpretability, risks of overfitting, limited control over model design, and continued dependence on high-quality training data. Find more information at https://www.ibm.com/think/podcasts/techsplainers Narrated by Ian Smalley

    ١٢ من الدقائق

  2. قبل ٣ أيام

    What is data labeling?

    This episode of Techsplainers explores data labeling, the critical preprocessing stage where raw data is assigned contextual tags to make it intelligible for machine learning models. We examine how this process combines software tools with human-in-the-loop participation to create the foundation for AI applications like computer vision and natural language processing. The podcast compares five distinct approaches to data labeling: internal labeling (using in-house experts), synthetic labeling (generating new data from existing datasets), programmatic labeling (automating the process through scripts), outsourcing (leveraging external specialists), and crowdsourcing (distributing micro-tasks across many contributors). We also discuss the tradeoffs involved—while proper labeling significantly improves model accuracy and performance, it's often expensive and time-consuming. The episode concludes by sharing best practices like consensus measurement, label auditing, and active learning techniques that help organizations optimize their data labeling processes for maximum efficiency and accuracy across various use cases from image recognition to sentiment analysis. Find more information at https://www.ibm.com/think/podcasts/techsplainers Narrated by Ian Smalley

    ١٠ من الدقائق

  3. قبل ٤ أيام

    What is access management?

    This episode of Techsplainers explores Identity and Access Management (IAM), the cybersecurity discipline that controls who can access what in digital systems. We examine IAM's four foundational pillars—administration, authentication, authorization, and auditing—and how they work together to secure modern organizations. The episode details essential IAM capabilities, including directory services, authentication tools like multi-factor authentication and single sign-on, various access control methods, and specialized functions for privileged accounts and non-human users. With 30% of cyber attacks involving stolen credentials and non-human identities now outnumbering human users 10:1 in enterprises, IAM has evolved from basic IT functionality to a critical security foundation. The discussion concludes by examining emerging trends like identity fabrics that unite disparate systems and how AI is both challenging and enhancing IAM capabilities. Find more information at https://www.ibm.com/think/podcasts/techsplainers Narrated by Bryan Clark

    ١٢ من الدقائق

  4. قبل ٥ أيام

    What is authentication?

    This episode of Techsplainers introduces authentication, the cybersecurity process that verifies a user's identity before granting access to systems or data. The episode distinguishes authentication (proving who you are) from authorization (determining what you're allowed to do) and explores the four main authentication factors: something you know (passwords), something you have (security tokens), something you are (biometrics), and something you do (behavioral patterns). Modern authentication approaches are examined, including single sign-on (SSO), multi-factor authentication (MFA), adaptive authentication that uses AI to assess risk in real-time, and passwordless authentication using cryptographic passkeys. Technical standards like SAML, OAuth, and Kerberos are also explained. With account hijacking involved in 30% of cyber attacks, according to IBM's X-Force Threat Intelligence Index, strong authentication proves critical for security, access control, and regulatory compliance across industries like healthcare and finance. Find more information at https://www.ibm.com/think/podcasts/techsplainers Narrated by Bryan Clark

    ٦ من الدقائق

  5. قبل ٦ أيام

    What is full-stack observability?

    In this episode of Techsplainers, we dive into full-stack observability, a comprehensive approach that unifies telemetry across infrastructure, applications, and user experiences. Unlike siloed monitoring, full-stack observability provides a single source of truth for system health, enabling faster incident resolution, predictive optimization, and improved operational efficiency. We discuss how it works, including automated service discovery, leading factor analysis, unified dashboards, and AI-driven analytics. You will also learn about its benefits for performance, security, compliance, and business outcomes, as well as challenges like data scale, integration, and privacy. Finally, we explore how machine learning and natural language processing are shaping the future of observability. No matter your role, episode offers a complete guide to why full-stack observability is essential in today’s complex digital environments. Find more information at https://www.ibm.com/think/podcasts/techsplainers Narrated by PJ Hagerty

    ١٢ من الدقائق

  6. ٢٦‏/١٢‏/٢٠٢٥

    What is SRE observability?

    In this episode of Techsplainers, we dive into SRE observability, a critical practice for ensuring site reliability in today’s dynamic, cloud-native environments. Discover how SRE observability goes beyond traditional monitoring by using telemetry data—metrics, logs, and traces—to provide deep visibility into complex systems. We explain how it supports proactive issue detection, faster incident response, and data-driven decision-making. You will also learn about real-world use cases in ecommerce, finance, logistics, and healthcare, as well as emerging trends like AI-driven observability and causal AI. Whether you are an engineer, IT professional, or tech enthusiast, this episode will help you understand how SRE observability optimizes performance, enhances user experience, and drives better business outcomes. Find more information at https://www.ibm.com/think/podcasts/techsplainers Narrated by PJ Hagerty

    ١٠ من الدقائق

  7. ٢٥‏/١٢‏/٢٠٢٥

    What is data accuracy?

    This episode of Techsplainers explains what data accuracy is, why it matters, and how organizations can achieve it. We explore its role as a core dimension of data quality, the benefits of accurate data for decision-making, compliance, AI, and customer satisfaction, and the common causes of inaccuracies—from human error to outdated information and biased data. Find more information at https://www.ibm.com/think/podcasts/techsplainers Narrated by Matt Finio

    ١٠ من الدقائق

  8. ٢٤‏/١٢‏/٢٠٢٥

    What is data integrity?

    This episode of Techsplainers explains what data integrity is, why it matters, and how organizations can maintain it. We cover the processes and security measures that ensure data remains accurate, complete, and consistent throughout its lifecycle. Learn why data integrity is critical for analytics, compliance, and trust, and explore the five key types of data integrity. Find more information at https://www.ibm.com/think/podcasts/techsplainers Narrated by Matt Finio

    ١٦ من الدقائق
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Introducing the Techsplainers by IBM podcast, your new podcast for quick, powerful takes on today’s most important AI and tech topics. Each episode brings you bite-sized learning designed to fit your day, whether you’re driving, exercising, or just curious for something new. This is just the beginning. Tune in every weekday at 6 AM ET for fresh insights, new voices, and smarter learning.

المعلومات

  • صناع العمل
    IBM
  • سنوات النشاط
    ٢٠٢٥ - ٢٠٢٦
  • الحلقات
    ٤١
  • التقييم
    ملائم
  • حقوق النشر
    © IBM
  • موقع البرنامج على الويب
    Techsplainers by IBM

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