Issue link: https://iconnect007.uberflip.com/i/1520213
32 SMT007 MAGAZINE I MAY 2024 definition; ChatGPT is a specific example of GenAI. Grounding: Grounding is the process of anchoring artificial intelligence (AI) systems in real-world experiences, knowledge, or data. e objective is to improve the AI's under- standing of the world so it can effectively inter- pret and respond to user inputs, queries, and tasks. Grounding helps AI systems become more context-aware, allowing them to provide better, more relatable, and relevant responses or actions. Intelligence augmentation (IA): Augment- ing makes it possible to do the same task with less effort. is might include letting a human engineer or operator choose to automate redundant tasks so they can do more things that only a human can do. Large language models (LLMs): Large lan- guage models form the foundation for gener- ative AI (GenAI) systems. LLMs are artificial neural networks. At a very basic level, in their training, the LLM detects statistical relation- ships between how likely a word is to appear following the previous. As they answer ques- tions or write text, LLMs use the model of the likelihood of a word occurring to predict the next word to generate. LLMs are a type of foundation model, which are pre-trained with deep learning techniques on massive data sets of text documents. Examples of GenAI sys- tems currently available include chatbots and tools, such as OpenAI's GPTs, Meta's LLaMA, xAI's Grok, and Google's PaLM and Gemini. Machine learning (ML): Machine learning algorithms will identify rules and patterns in the data without a human specifying those rules and patterns. ese algorithms build a model for decision-making as they go through data. Algorithms used in machine learning require massive amounts of data to be trained to make decisions. In most cases the algorithm is learning an association (when X occurs, it usually means Y ) from training data that is from the past. Two, since the data is historical, it may contain biases and assumptions that we do not want to perpetuate. Figure 1: Illustration of the topology of a generic artificial neural network. This file is licensed under the Creative Commons Attribution—ShareAlike 3.0 Unported license.