Artificial Intelligence - Basic Concepts and Educated Use

Basic Concepts  

• Prompt 

Prompt Engineering is a technique that involves crafting clear, concise, and informative prompts in natural language. These prompts are then fed into large language models (LLMs) to elicit specific, tailored responses. By carefully designing prompts, users can guide the LLM to understand the intent behind their query and generate relevant, informative output. This iterative process of prompt refinement and response evaluation ensures that the LLM's output aligns closely with the user's needs.

• Large Language Models (LLM)

Generative Pre-trained Transformer (GPT) models are a type of artificial intelligence that can generate human-quality text. These models are trained on massive amounts of text data, allowing them to learn complex patterns and relationships between words. By analyzing the statistical properties of language, GPT models can produce coherent, contextually relevant, and often creative text.

• Machine Learning 

Machine learning is a subfield of computer science that employs statistical techniques to give computers the ability to learn from data, adapt to new inputs, and improve performance over time without being explicitly programmed.

• Deep Learning 

Deep Learning is a specialized subset of machine learning that utilizes artificial neural networks, inspired by the human brain's structure. By employing multiple layers of interconnected nodes, deep learning models can learn complex patterns and representations from data, leading to superior performance on a wide range of tasks. This includes applications in image recognition, natural language processing, and more.

• Artificial Intelligence (AI)

Artificial Intelligence (AI) is a broad field that emerged in the 1950s and focuses on creating intelligent agents, which are systems capable of performing tasks that typically require human intelligence. These tasks include understanding natural language, recognizing patterns, making decisions, and learning from experience. 

Educated Use

• The use of AI tools is less reliable in identifying research sources, but it helps convert keywords from natural language to research language for searching databases, as well as in extracting information from various online sources, some of which are academic. 
• Please pay attention to how you write your prompts: the more specific and detailed you are about your needs, the better the results will be.  
• AI tools are always learning, so let them know if the information they provided was helpful or not. Your feedback helps them improve. 
• Among the tools available on the website, you will also find writing assistants. Please be aware of your department's limitations on the use of AI tools and use them only as an aid.
   

Essential Information

• The majority of the information is derived from Open-Access articles rather than university subscription databases.
• Privacy and Data Security: Please note that AI tools are not fully secure. When you upload materials, such as PDF files, they are not kept private but are automatically shared online.
• Hallucinations: AI tools can sometimes generate incorrect or misleading information, known as hallucinations. These errors can manifest as plausible-sounding claims that are not supported by the underlying data. For example, AI tools may conflate information, fabricate quotes, or generate false or non-existent sources. It's essential to verify the accuracy of AI-generated responses by cross-referencing them with information from other reliable sources, such as research databases.
• Note that the information obtained from AI tools is often biased socially, politically, gendered, etc.