What is Mixture of Experts? Mixture of Experts (MoE) is a technique that uses many different sub-models (or “experts”) to improve the quality of LLMs. Two main components define a MoE: Experts – Each FFNN layer now has a set of “experts” of which a subset can be chosen. These “experts” are typically FFNNs themselves. Router or gate…
Mixture of Experts (MoE) is a machine learning technique where multiple specialized models (experts) work together, with a gating network selecting the best expert for each input. In the race to build ever-larger and more capable AI systems, a new architecture is gaining traction: Mixture of Experts (MoE). Unlike traditional models that activate every neuron…
In recent years, two major breakthroughs have revolutionized the field of Large Language Models (LLMs): 1. 2017: The publication of Google’s seminal paper, (https://arxiv.org/abs/1706.03762) by Vaswani et al., which introduced the Transformer architecture – a neural network that fundamentally changed Natural Language Processing (NLP). 2. 2022: The launch of ChatGPT by OpenAI, a transformer-based chatbot…
What Are LLMs? LLMs are machine learning models trained on vast amounts of text data. They use transformer architectures, a neural network design introduced in the paper “Attention Is All You Need”. Transformers excel at capturing context and relationships within data, making them ideal for natural language tasks. 1. Architectural Types of Language Models (Expanded with…
The large language model (LLM) landscape is rapidly evolving, and two powerful contenders—DeepSeek and ChatGPT—are emerging as core engines in generative AI applications. While they both excel at generating human-like text, answering questions, and powering chatbots, they differ significantly in architecture, training objectives, inference capabilities, and deployment paradigms. Not long ago, I had my first…
Large language models originated from natural language processing, but they have undoubtedlybecome one of the most revolutionary technological advancements in the field of artificial intelligence in recent years. An important insight brought by large language models is that knowledgeof the world and languages can be acquired through large-scale language modeling tasks, andin this way, we…
What is a large language model (LLM)? Large Language Models are machine learning models that employ Artificial Neural Networks and large data repositories to power Natural Language Processing (NLP) applications. An LLM serves as a type of AI model designed to be able to grasp, create, and manipulate natural language. These models rely on deep…
Key Concepts Explained Large Language Models (LLMs): – LLMs are sophisticated AI systems designed to understand and generate human language. They are trained on vast amounts of text data, learning the structure and nuances of language, enabling them to perform tasks like translation, summarization, and conversation. Fine-Tuning vs. Pre-Training: – Pre-Training: In this…
Course on Large Language Models NOTE: You’re only meant to change code marked with “# TODO:” Table of Contents Setting Up API Key Configuration Connecting to OpenAI API Exploring the API Creating Chat Completions Understanding Completion Parameters Prompt Engineering Crafting Effective Prompts Strategies and Best Practices Advanced Techniques Utilizing Embeddings Function Calling in LLMs Extras…
Large Language Models (LLMs) such as GPT (Generative Pre-trained Transformer) are a class of deep learning models that have revolutionized natural language processing (NLP).
