Key topics include: Traditional vs. Kubernetes Challenges: Comparing the challenges of managing applications in traditional virtual machine environments versus containerized Kubernetes environments. Kubernetes Fundamentals: Defining Kubernetes, its origins, why it’s used, and key concepts like cluster architecture, API server, nodes, pods, and network policies. Kubernetes Security Fundamentals: Discussing control plane and data plane protection, including API protection, encryption, Read More …
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AGI – Artificial General Intelligence
Imagine the smartest person you know – someone who can learn anything, understand complex ideas across different subjects, solve novel problems they’ve never encountered before, and even exhibit creativity and common sense. Now, picture that level of intelligence not in a human, but in a machine. That, in essence, is the concept of Artificial General Read More …
Machine Learning – Journey Through the Mind of the Machine
The dream of creating artificial intelligence, of imbuing machines with the capacity to think and learn, is a long-standing one, stretching back centuries in philosophical thought and fictional tales. However, the formal history of Artificial Intelligence (AI) as a scientific discipline began in the mid-20th century, fueled by advancements in computing and a group of Read More …
Generative AI
While “Generative AI” isn’t an acronym, it’s a fundamental concept in the field. Think of it like this: traditional AI often focuses on analyzing existing data – identifying patterns, classifying information, or making predictions based on what it has already seen. Generative AI, on the other hand, goes a step further; it learns the underlying Read More …
Artificial Neural Networks
Imagine trying to teach a computer to recognize a cat in a picture. You could try to program specific rules – it has whiskers, pointy ears, a tail, etc. But what about a cat curled up in a ball? Or a blurry photo? Rule-based systems struggle with such variations. Artificial Neural Networks (ANNs) offer a Read More …
GAN – Generative Adversarial Network
Imagine you have two artists: a forger and an art critic. The forger tries to create fake paintings that look just like the real ones, while the critic tries to distinguish the fakes from the authentic pieces. As they both get better at their jobs, the forger becomes more skilled at creating convincing fakes, and Read More …
RAG: Giving AI a Better Memory
Imagine you’re trying to answer a tough question, but your brain doesn’t have the specific information. What do you do? You probably look it up – maybe on the internet or in a book. Retrieval-Augmented Generation, or RAG, is a way to give AI models a similar ability. Think of a powerful AI language model as Read More …