This video provides a tutorial on using Garrick, a large language model vulnerability scanner, to test custom chat bots. Garrick employs probes (test cases) and detectors to identify vulnerabilities, drawing from a large, constantly updated probe library. The tutorial focuses on testing a simple chat application called Wy chat, which utilizes Llama 3 and the Read More …
Tag: artificial inteligence
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 …
GRU – Gated Recurrent Units
Gated Recurrent Units (GRUs) are a type of recurrent neural network (RNN) architecture designed to address some of the limitations of traditional RNNs, particularly in handling sequential data. Introduced by Kyunghyun Cho and his colleagues in 2014, GRUs have gained popularity in various applications within artificial intelligence (AI), especially in natural language processing, time series Read More …
LSTM – Long Short-Term Memory
Long Short-Term Memory (LSTM) networks are a specialized type of recurrent neural network (RNN) designed to address the limitations of traditional RNNs in processing sequential data. LSTMs have become a cornerstone in the field of artificial intelligence (AI), particularly in applications involving time series prediction, natural language processing, and speech recognition. Understanding LSTMs and their Read More …
Chats with AI – Shadows in the Cloud
In the bustling city of Techhaven, where skyscrapers gleamed with digital screens and the hum of innovation filled the air, a tech company named Cloud Sphere was making waves. Known for its cutting-edge cloud solutions, Cloud Sphere had rapidly become a leader in the industry. However, beneath the surface of success, a storm was brewing. Read More …
Computer Vision: Enabling AI to See and Understand the World
Computer vision, at its core, is a field of Artificial Intelligence (AI) that empowers computers to “see” and interpret the visual world, much like humans do with their eyes and brains. It’s about enabling machines to extract meaningful information from digital images, videos, and other visual inputs, and then use that information to understand, classify, 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 …
CNN – Convolutional Neural Networks
Convolutional Neural Networks (CNNs) were inspired by the way the human visual cortex works, CNNs are a specialized type of neural network particularly adept at analyzing and understanding images. They are the engine behind many impressive AI applications, from recognizing faces in photos to powering autonomous vehicles. Traditional neural networks, while powerful, can struggle with Read More …