Techsplainers by IBM

This episode of Techsplainers explores cloud infrastructure—the hardware and software foundation enabling on-demand computing resources that power modern business innovation and digital transformation.

This episode of Techsplainers explores hybrid cloud computing—how combining public cloud, private cloud, and on-premises infrastructure creates flexible, cost-effective IT environments for businesses of all sizes.

This episode of Techsplainers explores how AI agents communicate and learn—from agent protocols to supervised, unsupervised, and reinforcement learning techniques that power intelligent systems.

This episode of Techsplainers explores tool calling—how AI models interact with external tools and APIs to perform complex tasks beyond their training data, transforming them from passive assistants into proactive agents.

This episode of Techsplainers explores AI agent memory and reasoning—how intelligent systems store experiences and make decisions, transforming passive AI into autonomous problem-solving agents.

This episode of Techsplainers explores how AI agents perceive their world and plan their actions—from visual and auditory perception to goal-setting and optimization techniques.

This episode of Techsplainers explores AI agent components: perception, planning, memory, reasoning, action, communication, and learning. These are the building blocks of intelligent autonomous systems.

This episode of Techsplainers explores reinforcement learning—how AI agents learn through trial and error by receiving rewards for good decisions, similar to training a pet.

This episode of Techsplainers explores semi-supervised learning—how AI combines small amounts of labeled data with unlabeled information to train effective models when labeling is scarce.

This episode of Techsplainers explores unsupervised learning—how AI discovers patterns in data without human guidance through clustering, association rules, and dimensionality reduction.

This episode of Techsplainers explores supervised learning—how AI models learn from labeled data to make predictions, the algorithms that power it, and its real-world applications and limitations.

This episode of Techsplainers breaks down machine learning basics, exploring how AI systems learn from data and the three key approaches: supervised, unsupervised, and reinforcement learning.

This episode of Techsplainers explores continuous testing in software development, showing how automation and early feedback improve code quality while accelerating delivery.

This episode of Techsplainers explores continuous delivery—how automating software releases creates a reliable pipeline from code changes to production, enabling faster, higher-quality updates.

This episode of Techsplainers explores continuous delivery—how automating software releases creates a reliable pipeline from code changes to production, enabling faster, higher-quality updates.

This episode of Techsplainers explores qubits—the powerful quantum bits that enable quantum computing by existing in multiple states simultaneously, unlike classical computer bits.

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 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 i...

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.

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.