Techsplainers by IBM

This episode of Techsplainers examines quantum computing applications in pharmaceuticals, climate science, and finance, plus the timeline for when quantum advantage will impact our daily lives.

This episode of Techsplainers examines how quantum computers physically work, from qubit types and cooling systems to quantum programming tools and their complementary role to classical computing.

This episode of Techsplainers explores quantum computing fundamentals and how this revolutionary technology uses quantum mechanics to solve previously impossible computational problems.

This episode of Techsplainers explores AutoML—technology that automates machine learning development, making AI accessible to non-experts while boosting efficiency for data scientists.

This episode of Techsplainers examines data labeling—the process of annotating raw data to train machine learning models—and explores approaches, challenges, and best practices.

This episode of Techsplainers shines a light on Identity and Access Management (IAM). Learn how this critical cybersecurity framework ensures the right users access the right resources while protecting against credential theft and misuse.

This episode of Techsplainers explores authentication basics and advanced methods like MFA, SSO, and passwordless security. Learn how these vital cybersecurity measures protect against credential theft.

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.

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.

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.