Techsplainers by IBM

This episode of Techsplainers explores qubits, the fundamental building blocks of quantum computing. Unlike classical bits that can only be 0 or 1, qubits can exist in superposition, representing both states simultaneously until measured. The episode explains how qubits harness quantum mechanics to potentially solve complex problems that would take classical computers thousands of years. We learn how qubits work through quantum superposition, why they can process multiple possibilities at once, and their applications in fields like cancer research, climate modeling, and drug discovery. The discussion also touches on the extreme conditions required to maintain qubit stability, setting the stage for future episodes about different types of qubits and quantum entanglement.Find more information at https://www.ibm.com/think/podcasts/techsplainers. Narrated by Ian Smalley

This episode of Techsplainers explores the revolutionary applications of quantum computing across diverse industries and disciplines. We dive into how quantum computers could transform pharmaceutical development by simulating molecular interactions digitally, potentially reducing drug discovery timelines from 15 years to just months. The discussion extends to quantum computing's applications in materials science, climate change mitigation, artificial intelligence, and financial modeling. We'll look at the critical distinction between "quantum utility" (already achieved) and "quantum advantage" (expected by 2026), while addressing the significant challenges facing the field, including qubit scaling and quantum error correction. The episode highlights how industries from healthcare to logistics to energy management are already investing in quantum research, with companies like Moderna, HSBC, and FedEx exploring quantum solutions for complex optimization problems. Listeners gain insight into IBM's quantum roadmap, which aims for 2,000 logical qubits by 2033, and learn how quantum-centric supercomputing—the strategic combination of quantum and classical systems—represents the most promising path forward. Rather than merely offering incremental improvements, quantum computing promises to solve problems that are currently impossible, potentially revolutionizing our approach to some of humanity's most complex challenges.Find more information at https://www.ibm.com/think/podcasts/techsplainers. Narrated by Ian Smalley

This episode of Techsplainers explores the inner workings of quantum computers, diving deep into the physical mechanisms and infrastructure that make quantum computing possible. We break down the fundamental concept of qubits and explain how their ability to exist in superpositions creates exponential computational power. The episode examines different qubit types, including superconducting, trapped ion, quantum dots, and photonic qubits, while explaining why quantum computers require massive cooling systems operating at temperatures colder than space. Listeners will gain insights into how quantum computers differ fundamentally from classical computers in their approach to problem-solving, the emerging field of quantum-centric supercomputing, and the development of accessible quantum programming tools like IBM's Qiskit. The discussion highlights that quantum computers won't replace classical systems but will complement them by tackling previously impossible calculations, with quantum technology advancing rapidly toward systems with thousands of qubits and improved error rates.Find more information at https://www.ibm.com/think/podcasts/techsplainers. Narrated by Ian Smalley

This episode of Techsplainers introduces quantum computing, a revolutionary technology that harnesses the principles of quantum mechanics to solve problems beyond the capabilities of classical computers. We explain the four foundational principles of quantum computing: superposition, entanglement, interference, and decoherence, breaking down complex concepts with accessible analogies. The episode explores how quantum computers differ fundamentally from classical computers by using qubits rather than binary bits, allowing them to process multiple possibilities simultaneously. Listeners will learn about practical applications in pharmaceuticals, materials science, and artificial intelligence, while gaining insight into the current state of quantum technology, including IBM's roadmap for scaling to 2,000 logical qubits by 2033. The episode also addresses common misconceptions, clarifying that quantum computers will complement rather than replace classical computers for specific complex computational challenges.Find more information at https://www.ibm.com/think/podcasts/techsplainersNarrated by Ian Smalley

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/techsplainersNarrated by Ian Smalley