How AI is Empowering Solo Entrepreneurs to Turn Ideas into Reality
AI is transforming solo entrepreneurship by streamlining product design and marketing, making it easier for individuals to bring their ideas to life.
Episode 11: What Is “Test Data” That Measures the True Ability of AI? The System That Supports How AI Faces Unseen Challenges
Test data, which is used to measure the true capabilities of AI, plays a crucial role in evaluating how well an AI system can handle unfamiliar problems. It serves as a way to assess the AI’s ability to apply what it has learned to new situations, and therefore must be used with great care.
Episode 10: What Is Validation Data in AI? A Crucial Step to Fine-Tune Models Like Tasting and Adjusting a Recipe
Validation data in AI is a crucial step used to check the model’s generalization ability and to fine-tune its settings, known as hyperparameters. This process can be compared to tasting a dish while cooking—it helps adjust the recipe before it’s finished.
Episode 9: How Does AI Get Smarter? Understanding the Role and Mechanism of Training Data
To become smarter, AI relies heavily on “training data”—a vast collection of information from which it learns patterns and gains knowledge. This article explains how AI grows by learning from such data and why the quality and diversity of that data are essential to its development.
How AWS is Simplifying Generative AI Integration for Businesses Using RAG Technology
AWS simplifies generative AI integration for businesses with RAG technology, enabling efficient use of internal data without extensive retraining costs.
Episode 8: Why AI “Seems to Understand” — The Key Lies in Its Power to Generalize
The reason AI appears to “understand” lies in its ability to apply what it has learned to new situations—this is known as “generalization.” This skill is key to enhancing AI’s adaptability and usefulness across different contexts.
Episode 7: How Does AI Learn? A Gentle Introduction to Reinforcement Learning Through Trial and Error
Reinforcement learning in AI is a mechanism through which optimal actions are learned by trial and error. It resembles the way humans grow through experience, gradually improving by trying different approaches and learning from the outcomes.
How Swisscom is Using AI to Simplify Network Management and Enhance Efficiency
Swisscom’s AI-powered Network Assistant simplifies network management for engineers, enhancing efficiency and decision-making while ensuring data security.
Episode 6: How AI Learns in a World Without Clear Answers — A New Approach Called Unsupervised Learning
AI is developing the ability to identify patterns and organize information on its own through a method called “unsupervised learning,” which allows it to learn from data without being given the correct answers.
Episode 5: How Does AI Learn? Understanding the Basics of AI Training Through Supervised Learning
AI learns through a method called “supervised learning,” where it uses data that comes with correct answers to develop its ability to make decisions. This process is somewhat similar to how humans learn by being taught and gradually understanding patterns.