"Fine-tuned" in the context of a Large Language Model (LLM) refers to the process of further training a pre-existing model on a smaller, domain-specific dataset. Large language models like GPT series from OpenAI have already learned patterns and features on a large dataset. Fine-tuning involves adjusting the model's parameters with task-specific data while maintaining its original training knowledge. This process is crucial in enhancing large language models through transfer learning, allowing t

A prompt and a search are two different things. Here are the differences between them: Prompt A prompt is a specific form of assistance given by an adult before or as the learner attempts to use a skill. It is direct and leads to the correct answer. It can be an instruction, gesture, demonstration, touch, or other things that we arrange or do to increase the likelihood that children will make correct responses. Prompting procedures provide a systematic way of providing and removing prompts so t

In the context of AI, tokens are the basic units of text or code that AI models use to process and generate language. These tokens can be characters, words, subwords, or other segments of text or code, depending on the chosen tokenization method or scheme. Here are some key points about tokens in AI: Tokenization: Tokenization is the process of splitting input and output texts into smaller units that can be processed by AI models. Tokens can be words, characters, subwords, or symbols, depending

GPT-4 and Claude 2 are both advanced AI models, but they have different strengths and weaknesses based on anecdotal evidence. GPT-4 has more expansive features than Claude 2 when it comes to handling different types of input. It can process images and respond to multimodal prompts combining text, images, audio, and more, giving it an edge in flexibility. GPT-4 is also more precisely accurate for broad general knowledge, while Claude 2 has an edge in specialized domains like law and math. On sta

A prompt is a starting point for a conversation with a computer program, like an AI, to get it to do something for you. It's like asking a question or giving a command to the program to set the stage for what you want to know or get done. A prompt can be thought of as asking a chef for a specific dish - you'll get what you ask for, so it's important to be clear and specific. Here are some key features of a prompt: Anatomy of a Prompt: A prompt should seamlessly blend your goal and background i

Artificial Intelligence (AI) and Machine Learning (ML) are often used interchangeably, but they are actually distinct concepts. AI is the broader term that refers to the general ability of computers to emulate human thought and perform tasks in real-world environments. On the other hand, ML is a subset of AI that uses algorithms trained on data to produce models that can perform complex tasks. Here are some key differences between AI and ML: Artificial Intelligence (AI): Refers to the general a

A Large Language Model (LLM) is a type of artificial intelligence (AI) algorithm that uses deep learning techniques and massive data sets to understand and generate human-like responses to natural language queries. LLMs are characterized by their large size, which can range from a billion to a trillion weights. They are artificial neural networks that are pre-trained using self-supervised learning and semi-supervised learning. LLMs can be used for various natural language processing (NLP) tasks,

In the context of AI, prompting refers to the process of structuring text that can be interpreted and understood by a generative AI model. It involves providing natural language text describing the task that an AI should perform, which is known as a prompt. A prompt can take different forms, such as a query, a command, a statement of feedback, or a longer statement including context, instructions, and input data. The goal of prompting is to enable an AI or machine learning model to produce the d