LLM/AI

Learning Agents

Can improve their performance over time based on previous experiences, adapting their responses based on new data. Example with LLM: An adaptive content recommendation system for a streaming platform. The recommendation system uses an LLM to analyze user reviews and feedback in natural language. The system figures out over time which content characteristics are most appreciated by each user, improving its recommendations based on textual analysis of user interactions.

What is explainable AI (XAI)

Detailed: Involves techniques and methods that make AI systems' outputs and operations transparent and understandable, enabling clearer insight into their decision-making processes. ELI5: Like a robot that can perform tasks and also explain how and why it did them. Example: An AI system in healthcare that elucidates its diagnostic conclusions.

What are embeddings

Detailed: Numeric representations of data, like words, enabling computers to process and understand similarities and differences. ELI5: Assigning unique codes to items, illustrating their characteristics and relationships. Example: Word2Vec positioning similar words proximately in vector space.

What are vector stores

Detailed: Specialized databases for storing and retrieving vector representations, facilitating efficient data handling. ELI5: A library where books are organized for rapid similarity-based retrieval. Example: Quickly locating akin images through their vector representations.

What are popular agent building methodologies

Detailed: Strategies like reinforcement learning and evolutionary algorithms guide agents in learning and decision-making. ELI5: Teaching a robot to enhance game strategies via trial and error. Example: Reinforcement learning employed in robotic arm training for object manipulation.

What is model evaluation in machine learning

Detailed: The process of assessing a model's performance using various metrics, typically by comparing predicted outputs to actual values. ELI5: Like taking a test to see how many answers you got right. Example: Evaluating a classifier's accuracy or F1 score.

What are token semantics

Detailed: The significance or function of tokens (text pieces) in understanding or generating language, influencing model interpretation. ELI5: Recognizing each word's role in a sentence, akin to understanding job responsibilities. Example: In "I ate an apple," recognizing 'ate' as the action.

Model-Based Reflex Agents

Have a model of the world and use it to make more informed decisions based on how the world changes in response to their actions. Example with LLM: A home automation system that adjusts settings based on user behavior patterns. The system uses an LLM to understand and respond to text-based commands or queries from users, such as "It's too dark in here," by interpreting the natural language and controlling the lighting based on the learned model of the user's preferences.

Simple Reflex Agents

Operate on a simple condition-action rule, which means they consider the current state of the environment to decide their next action without any consideration of the history or future consequences. Example with LLM: In a customer support chatbot. The chatbot uses an LLM to interpret customer queries and generate predefined responses based on specific keywords or phrases identified in the customer's input. For instance, if a customer mentions "password reset," the LLM helps the agent generate an appropriate response guiding the customer through the password reset process.

Utility-Based Agents

Similar to goal-based agents but with a utility function they seek to maximize, providing a measure of success at achieving the goal. Example with LLM: A financial advising system that provides investment advice. This agent utilizes an LLM to understand and process detailed financial inquiries from users, such as interpreting market trend queries or specific investment questions. It then generates advice optimized to the user, considering their risk tolerance and investment goals.

Goal-Based Agents

These agents have goals and make decisions based on how likely actions are to achieve these goals. They often use planning and forecasting techniques. Example with LLM: A virtual travel assistant that helps users plan trips. The agent uses an LLM to understand complex user requests, such as "I need a flight and hotel in Paris next week," and to generate a list of options that meet the user's criteria. The LLM helps parse detailed preferences and maintain a conversational flow to clarify and refine travel plans.

What is a convolutional neural network (CNN)

Detailed: A deep learning algorithm often employed for image processing, utilizing convolutional layers to capture hierarchical patterns. ELI5: Analyzing parts of an image with a magnifying glass to understand the whole picture. Example: Recognizing faces or objects within images.

What is a generative adversarial network (GAN)

Detailed: A framework involving two neural networks, a generator and a discriminator, trained simultaneously to produce realistic outputs. ELI5: An art forger (generator) and a detective (discriminator) improving through their interaction. Example: Creating lifelike images that are indistinguishable from real ones.

What is reinforcement learning

Detailed: A learning method where an agent makes decisions, receiving rewards or penalties, to maximize cumulative reward in an environment. ELI5: Training a pet with treats to reinforce good behaviors. Example: Optimizing a game AI's strategy to enhance its score.

What is supervised learning in AI

Detailed: A learning paradigm where a model is trained with labeled data, learning to associate specific inputs with corresponding outputs. ELI5: Learning from a teacher who corrects your answers. Example: Teaching a model to differentiate between photos of cats and dogs.

What is perplexity in language modeling

Detailed: A measure indicating how well a model predicts a sample, where lower values signify better prediction accuracy. ELI5: Measures how confused a model is when guessing words, with less confusion being better. Example: A model's lower perplexity improves its next-word predictions.

What is ReAct

Detailed: A mechanism allowing AI to reconsider and modify past decisions, enhancing adaptability and accuracy in evolving contexts. ELI5: Correcting a drawing's color based on later insights or changes in the scene. Example: An AI amending an earlier conversation misunderstanding based on new input.

What is Retrieval-Augmented Generation (RAG)

Detailed: A method where a language model generates responses using information from retrieved documents, enhancing output relevance and accuracy. ELI5: Crafting a story with the aid of facts and ideas from referenced books. Example: Producing informed answers by synthesizing details from pertinent documents.

What is a character-level language model

Detailed: A model predicting the next character in a sequence, aiding in text generation and comprehension at a granular level. ELI5: Building a letter-based tower where each block's placement informs the next. Example: Anticipating 'd' following "hello worl."

What is a pre-trained model

Detailed: A model trained on large datasets that can be fine-tuned or utilized as-is for related tasks, optimizing time and resource usage. ELI5: Like adjusting a used but well-functioning bicycle to fit your needs. Example: Adapting an image recognition model to detect specific objects.

What is a transformer model

Detailed: A network architecture utilizing attention mechanisms to understand the relevance of different parts of input data, enhancing NLP capabilities. ELI5: Focusing intently on the most relevant conversation in a noisy room. Example: The BERT model's application in text comprehension.

What is a recurrent neural network (RNN)

Detailed: A neural network variant capable of remembering previous inputs through internal loops, useful for sequential data processing. ELI5: Recalling earlier parts of a story to understand the current context. Example: Predicting subsequent words in a text based on earlier content.

What is overfitting in machine learning

Detailed: A scenario where a model learns training data too well, including its noise and outliers, impairing its performance on new data. ELI5: Memorizing test answers without grasping the underlying concepts. Example: Excelling on training images but failing to generalize to new ones.

What is a language model

Detailed: A statistical model that predicts the likelihood of word or character sequences, used for text understanding or generation. ELI5: Similar to a phone's predictive text feature. Example: Anticipating the next word in a sentence.

What is a bigram language model

Detailed: A statistical model that predicts the next word in a sequence based on the preceding word, using pairs of words to calculate sequence probabilities. ELI5: Like looking at pairs of links in a chain to decide the shape of the next link. Example: More likely to predict "morning" after "good" than "night."

What is natural language processing (NLP)

Detailed: A subfield of AI that focuses on enabling computers to understand, interpret, and generate human language effectively. ELI5: Like teaching a computer to comprehend and converse in human languages. Example: Translating languages using an NLP model.

What is deep learning

Detailed: A subset of machine learning with multi-layered neural networks, capable of learning from vast data amounts. ELI5: Like exploring deep ocean layers to discover and learn from hidden patterns. Example: Speech recognition and text conversion.

What is GPT (Generative Pre-trained Transformer)

Detailed: A transformer model specializing in generating coherent and contextually relevant text, pre-trained on extensive text corpora. ELI5: A robot storyteller that crafts tales based on vast literature knowledge. Example: Completing a narrative based on an initial sentence.

What is a decision tree in machine learning

Detailed: A tree-like model where each node tests an attribute, each branch represents the test's outcome, and each leaf node indicates a class label. ELI5: A series of yes/no questions leading to a decision. Example: Deciding on outdoor activities based on weather conditions.

What is unsupervised learning in AI

Detailed: A type of learning where models discern patterns and relationships in unlabeled data. ELI5: Sorting toys into groups without a predefined categorization. Example: Segmenting customers based on buying behavior without predefined groups.

What is fine-tuning in machine learning models

Detailed: Adjusting a pre-trained model on a specific, smaller dataset to adapt it to a particular task or domain. ELI5: Modifying a general recipe to create a specific flavor. Example: Tailoring a language model to specialize in legal jargon.

How do agents differ from LLMs

Detailed: Agents interact with and perceive their environment to achieve objectives, unlike LLMs, which primarily process and generate text. ELI5: Comparing a mobile, task-performing robot to a knowledgeable but stationary book. Example: A navigating robot versus a text-generating language model.

What is a neural network

Detailed: Algorithms that recognize data patterns through a process akin to the human brain's function. ELI5: Comparable to interconnected brain cells in a computer. Example: Identifying animals in images.

What is an attention mechanism in AI

Detailed: Allows a model to focus on specific input parts, enhancing tasks where the output depends on certain input segments. ELI5: Focusing on the most intriguing story parts to remember them better. Example: Prioritizing sentence subjects in machine translation.

What is Chain of Thought (COT) reasoning

Detailed: An AI's process of articulating intermediate steps towards a conclusion, aiding in complex problem-solving. ELI5: Detailing puzzle-solving steps for clearer understanding and guidance. Example: Decomposing a math problem into solvable segments, elucidating each phase.

What is tokenization

Detailed: Breaking down text into manageable pieces or tokens, aiding in effective language processing by AI. ELI5: Segmenting a chocolate bar for easier sharing. Example: Dividing "Hello world!" into discrete components for analysis.

What is a hyperparameter in machine learning

Detailed: Configuration settings structuring the learning process, influencing model performance without adjustment during training. ELI5: Deciding on a recipe's sugar or salt amount before cooking. Example: Determining a neural network's learning rate or layer count.

What is anomaly detection in AI

Detailed: Identifying unusual patterns or data points that deviate from expected behavior, used in various domains like fraud detection. ELI5: Spotting a red apple in a pile of green ones. Example: Detecting odd credit card transactions to flag potential fraud.

What is LLM function calling

Detailed: Instructing a large language model to execute specific tasks, leveraging its broad understanding and capabilities. ELI5: Directing a smart robot to perform particular household chores. Example: Generating SQL queries from natural language instructions.