A Transformer model is a neural network architecture that has revolutionized natural language processing (NLP) and other AI fields by effectively capturing relationships in sequential data without relying solely on recurrent or convolutional operations. Introduced by Vaswani et al. in...

Transfer Learning is a machine learning technique that allows a model trained on one task or domain to be repurposed for another, often related, task or domain. Instead of starting from scratch, the model leverages the knowledge and patterns it...

Training datasets are collections of data used to teach machine learning models the patterns and relationships needed to perform specific tasks. These datasets consist of input features along with corresponding labels or target values, allowing algorithms to learn from examples....

Tokenization is the process of breaking down text into smaller units, called tokens. These tokens can be words, subwords, or even individual characters, depending on the specific approach and the language involved. Tokenization is a fundamental step in natural language...

TensorFlow is an open-source machine learning framework developed by Google Brain. Designed to simplify the building, training, and deployment of machine learning models, TensorFlow provides a wide range of tools and APIs for handling everything from linear regression to advanced...

Synthetic data refers to artificially generated information that replicates the statistical properties and patterns found in real-world datasets, without directly exposing sensitive or private content. In the context of large language model (LLM) evaluation, synthetic data can be especially valuable....

Supervised Learning is a machine learning paradigm where models are trained using labeled examples. Each training instance comes with input features and an associated correct output (label), enabling the model to learn the relationship between inputs and outputs. Over time,...

An sLLM (Specialized Large Language Model) is a large language model that has been tailored or fine-tuned for a specific domain, task, or use case. Unlike general-purpose LLMs, which are trained on vast and diverse datasets, sLLMs focus on a...

The Segment Anything Model (SAM) is a powerful AI tool designed to identify and isolate objects within images. Developed by Meta AI, SAM has been trained on a vast and diverse set of images, enabling it to “segment” virtually any...

SaaS (Software as a Service) is a cloud computing model where users access software applications over the internet without installing or maintaining them on their own hardware. Instead of purchasing and managing licenses or handling complex installations, organizations and individuals...