Decision trees are a popular and intuitive method used in artificial intelligence (AI) for classification and regression tasks. They represent a model in the form of a tree-like structure, where each internal node corresponds to a decision based on an input feature, each branch represents the outcome of that decision, and each leaf node signifies Read More …
Tag: IT acronyms
SVM – Support Vector Machines
Support Vector Machines (SVMs) are a powerful supervised learning algorithm used in artificial intelligence (AI) for classification and regression tasks. Developed in the 1990s by Vladimir Vapnik and his colleagues, SVMs are particularly effective in high-dimensional spaces and are known for their robustness in handling both linear and non-linear data. How SVMs Work The primary Read More …
Neural Networks: The Foundation of Deep Learning
The quest to replicate the remarkable learning capabilities of the human brain has long been a central theme in the field of Artificial Intelligence (AI). Neural networks, inspired by the structure and function of biological nervous systems, represent a significant step towards achieving this goal. Their evolution, culminating in the powerful techniques of deep learning, Read More …
GPU – Graphics Processing Units
Graphics Processing Units (GPUs) have become a cornerstone of modern computing, particularly in the field of artificial intelligence (AI). Originally designed to accelerate the rendering of images and graphics in video games and applications, GPUs have evolved into powerful parallel processors capable of handling the massive computational demands of AI workloads. This article explores the Read More …
What is the Internet of Things – IoT
The Internet of Things, commonly known as IoT, refers to a network of physical objects or “things” that are connected to the internet and can communicate with each other. These objects can range from everyday household items to sophisticated industrial machines. The key idea behind IoT is that these devices can collect and share data, 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 …
RNN – Recurrent Neural Networks
In the realm of Artificial Intelligence, many tasks involve understanding data that unfolds over time or has a sequential structure. Think of comprehending spoken language, predicting stock prices, or even generating music. Traditional neural networks, designed to process independent inputs, often fall short in these scenarios. This is where Recurrent Neural Networks (RNNs) come into 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 …
DDoS – Distributed Denial of Service
A Distributed Denial of Service (DDoS) attack is a malicious attempt to disrupt the normal functioning of a targeted server, service, or network by overwhelming it with a flood of internet traffic. DDoS attacks are executed using multiple compromised computer systems, often referred to as a botnet, which are controlled by the attacker. These botnets Read More …
ESM – Exposure Surface Management
Exposure Surface Management (ESM) aims to proactively identify, assess, and mitigate vulnerabilities across an organization’s digital assets, including those external to the traditional IT infrastructure, to reduce the risk of cyberattacks. Here’s a breakdown of what ESM looks like: Comprehensive Asset Inventory: ESM starts with a thorough inventory of all assets, both internal and external, Read More …