No-Code AI and Predictive Problems
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No-Code AI and Predictive Problems

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Questions and Answers

What defines how a rational agent should act in a given environment?

  • Performance metrics
  • Percept sequences
  • Actuators only
  • Agent function (correct)

    • Which aspect is not included in the PEAS framework for evaluating a self-driving car?

  • User preferences (correct)
  • Performance measure
  • Environment
  • Actuators

    • What would be a primary performance measure for a rational agent working as a navigation app?

  • User satisfaction
  • Number of routes explored
  • Cost of fuel
  • Time efficiency (correct)

    • When analyzing the PEAS framework for a vacuum cleaner, what describes its environment?

    <p>Obstacles in various rooms</p> Signup and view all the answers

    Which of the following accurately represents an actuator in the PEAS framework for a self-driving car?

    <p>Steering system</p> Signup and view all the answers

    Which performance measure is NOT applicable to an automated taxi?

    <p>Patient health</p> Signup and view all the answers

    In the context of the PEAS framework, what would be considered an actuator for the medical diagnosis system?

    <p>Screen display showing tests</p> Signup and view all the answers

    What advantage does no-code AI offer to non-technical users?

    <p>It democratizes AI, making it accessible without coding skills.</p> Signup and view all the answers

    Which type of problem is best suited for no-code AI solutions?

    <p>Predictive problems that require pattern recognition in data.</p> Signup and view all the answers

    Which component is associated with the environment of the part-picking robot within the PEAS framework?

    <p>Correct bins for parts</p> Signup and view all the answers

    Which statement best describes an intelligent agent based on the provided definitions?

    <p>It can learn and adapt to achieve specified goals.</p> Signup and view all the answers

    What is a key feature of building AI models with no-code platforms?

    <p>The use of drag-and-drop functionality for model building.</p> Signup and view all the answers

    Which statement correctly describes prescriptive problems?

    <p>They can be resolved by following a set of repetitive steps.</p> Signup and view all the answers

    What is a common characteristic of both human and robotic agents?

    <p>They rely on sensors to gather information.</p> Signup and view all the answers

    Which of the following describes the collaborative nature of no-code AI projects?

    <p>Teams from varying departments can work together without technical expertise.</p> Signup and view all the answers

    In the PEAS framework for an interactive English tutor, what aspect is primarily assessed?

    <p>Maximize student's score on test</p> Signup and view all the answers

    What is the first step in building an image classification model using no-code AI?

    <p>Select the 'Image Project' option on Teachable Machine.</p> Signup and view all the answers

    Which of these is NOT considered a performance measure for the part-picking robot?

    <p>Cost of the robot</p> Signup and view all the answers

    What kind of problems can AI effectively predict?

    <p>Problems requiring historical data analysis.</p> Signup and view all the answers

    Which of the following items would NOT be categorized as an actuator for a self-driving car?

    <p>Traffic light sensors</p> Signup and view all the answers

    What defines the environment for the medical diagnosis system?

    <p>Interaction among patients and hospital staff</p> Signup and view all the answers

    How do no-code AI platforms impact project costs?

    <p>They remove the requirement for hiring developers, reducing costs.</p> Signup and view all the answers

    Which best describes the role of sensors in the context of a robotic agent?

    <p>To perceive and interpret the environment.</p> Signup and view all the answers

    What distinguishes deliberative agents from reactive agents?

    <p>Deliberative agents have an internal model for planning.</p> Signup and view all the answers

    How does a learning agent improve its recommendations over time?

    <p>By adjusting based on user feedback and interactions.</p> Signup and view all the answers

    What role does the critic play in a learning agent's system?

    <p>It measures the agent's performance and provides feedback.</p> Signup and view all the answers

    Which of the following statements is true regarding no-code AI?

    <p>It allows non-technical users to create AI models without coding.</p> Signup and view all the answers

    What is the primary advantage of a learning agent compared to traditional agents?

    <p>Learning agents adapt and improve performance over time.</p> Signup and view all the answers

    What does a problem generator do in a learning agent's context?

    <p>It suggests actions for new and informative experiences.</p> Signup and view all the answers

    In the context of image classification, how does a learning agent improve its model?

    <p>By constantly adjusting parameters based on feedback from labeled training data.</p> Signup and view all the answers

    Which aspect of a music streaming service exemplifies a feedback system in machine learning?

    <p>Evaluating user interactions to adjust future recommendations.</p> Signup and view all the answers

    How do predictive and prescriptive problems differ in machine learning applications?

    <p>Prescriptive problems include recommending actions based on predicted outcomes.</p> Signup and view all the answers

    What type of interface do no-code AI platforms typically offer to users?

    <p>An easy-to-use interface similar to a spreadsheet.</p> Signup and view all the answers

    Which of the following best describes the role of an Agent Program within an intelligent agent?

    <p>It maps the agent's percepts to the appropriate actions based on an algorithm.</p> Signup and view all the answers

    In what way do learning agents differ from non-learning agents?

    <p>Learning agents can adapt their actions based on prior experiences.</p> Signup and view all the answers

    What is one significant advantage of using no-code AI solutions?

    <p>They enable users without technical expertise to develop AI applications.</p> Signup and view all the answers

    In predictive and prescriptive analytics, which of the following statements is accurate?

    <p>Prescriptive analytics provides recommendations for actionable steps.</p> Signup and view all the answers

    Which option is an example of a reflex machine acting as an intelligent agent?

    <p>A thermostat that adjusts the temperature based on current readings.</p> Signup and view all the answers

    How does the percept sequence contribute to an intelligent agent's decision-making?

    <p>It influences the choice of action based on all past observations.</p> Signup and view all the answers

    What best captures the concept of an intelligent agent's architecture?

    <p>The specific sensors and actuators it employs to perceive and act.</p> Signup and view all the answers

    Which statement correctly defines the term 'percept' in relation to intelligent agents?

    <p>Percept relates to the sensory inputs received by an agent at a specific moment.</p> Signup and view all the answers

    In the context of intelligent agents, what does the term 'actuator' refer to?

    <p>The physical components that allow an agent to interact with its environment.</p> Signup and view all the answers

    Study Notes

    No-Code AI

    • Users input data to train AI models which can be built quickly, saving time and effort.
    • Accessible to those without coding skills, such as business analysts or marketers.
    • Quick model building is achieved through drag-and-drop functionality and simple data inputs.
    • Teams from different departments can collaborate because no technical expertise is needed.
    • Reduces the need for technical resources, cutting down costs related to hiring developers or data scientists.

    Types of AI Problems

    • Prescriptive Problems - tasks where steps can be repeated to get the same result, like adding sales figures in a spreadsheet (can be done in Excel).
    • Predictive Problems - Problems where there is no set of repeatable steps and predictions need to be made based on patterns in data. For example, predicting sales for next year based on market trends, seasonality and customer behavior.

    Examples of Predictive Problems Solved By AI

    • Forecasting future sales based on historical data.
    • Identifying customers who are most likely to buy a product.
    • Predicting when equipment is likely to fail.

    Teachable Machine Example

    • Teachable Machine is a platform that allows users to build an image classification AI model without code.
    • Users upload images of apples, oranges and bananas into separate classes.
    • Clicking the "Train Model" button allows Teachable Machine to learn from the uploaded images.
    • The model can then be tested by uploading images from a "Test Data" folder and observing if the AI correctly classifies them.

    Learning Agents

    • Performance Element - Executes actions in the environment.
    • Critic- Measures the agent's performance and provides feedback.
    • Problem Generator - Suggests actions that lead to new or informative experiences.

    Types of Learning Agents

    • Reactive Agents - Use machine learning to make decisions based on past experiences without an internal model of the world.
    • Deliberative Agents - Have an internal model and use past experiences to plane and reason about future actions.

    Music Streaming Service Example

    • A music streaming service that learns from your listening habits is a learning agent.
    • Learning Element - Notices which songs and genres you skip or listen to fully.
    • Performance Element - Plays music based on your preferences.
    • Critic - Uses your interactions (like skips or replays) to evaluate how well the recommendations match your taste.
    • Problem Generator - Might suggest a new genre or artist to see if you like them, enhancing your listening experience and its own data on your preferences.

    Other Learning Agents

    • A robot that learns to navigate a maze by adjusting its movements based on the feedback it receives from hitting walls or reaching the end of the maze.
    • A self-driving car that learns to drive safely by adjusting its steering, acceleration and braking based on the feedback it receives from cameras and sensors.
    • A machine learning algorithm that learns to classify images by adjusting the parameters of its neural network based on the feedback it receives from labelled training data.

    What is No-Code AI?

    • Allows business users to build AI models without writing any code.
    • No coding is required; no Python, no R, no technical programming at all.

    How No-Code AI Works

    • No-code AI platforms provide an easy-to-use web or mobile interface, similar to a spreadsheet.

    PEAS

    • Performance - A measure of how well the agent is performing.
    • Environment - The world in which the agent operates.
    • Actuators - How the agent takes action in the environment.
    • Sensors - How the agent perceives the environment.

    PEAS Examples

    • Automated Taxi Problem

      • Performance measure: Safe, fast, legal, max revenue, min cost, min fuel, etc.
      • Environment: City roads, traffic, pedestrians, bikers, construction. etc.
      • Actuators: Car controls (steering, gas pedal) and human interface.
      • Sensors: Cameras, radar, laser range finder, GPS, mapping, engine sensors, human input devices.

    • Medical Diagnosis System

      • Performance measure: Healthy patient, minimize costs, lawsuits.
      • Environment: Patient, hospital, staff.
      • Actuators: Screen display (questions, tests, diagnoses, treatments, referrals).
      • Sensors: Keyboard (entry of symptoms, findings, patient's answers).

    • Part-Picking Robot

      • Performance measure: Percentage of parts in correct bins.
      • Environment: Conveyor belt with parts, bins.
      • Actuators: Jointed arm and hand.
      • Sensors: Camera, joint angle sensors.

    • Interactive English Tutor

      • Performance measure: Maximize student's score on test.
      • Environment: Set of students.
      • Actuators: Screen display (exercises, suggestions, corrections).
      • Sensors: Keyboard.

    What is an Intelligent Agent?

    • An autonomous entity which acts to achieve goals in an environment.
    • Uses observation through sensors and consequent actuators.
    • May learn or use knowledge to achieve its goals.
    • Can be very simple or very complex.
    • Example: A reflex machine, such as a thermostat.

    Human Agent vs Robotic Agent

    • Human Agent
      • Sensors: Eyes, ears, and other organs.
      • Actuators: Hands, legs, mouth, and other body parts.
    • Robotic Agent
      • Sensors: Cameras and infrared range finders.
      • Actuators: Various motors.

    Agents and Environments

    • Thermostat
    • Cell Phone
    • Vacuum Cleaner
    • Robot
    • Alexa Echo
    • Self-Driving Car
    • Human
    • etc.

    What is a Percept?

    • An agent's perceptual inputs at any given moment.
    • Percept Sequence: Complete history of everything the agent has ever perceived.
    • An agent's choice of action can depend on the entire percept sequence observed to date, but not on anything it hasn't perceived.
    • The agent is fully specified by the choice of action for every possible percept sequence.

    The Structure of Intelligent Agents

    • Architecture - The hardware or machinery that the intelligent agent operates on, including sensors and actuators (i.e. a personal computer running a software agent, a self-driving car with sensors, or even a camera that responds to environmental inputs).
    • Agent Function - The abstract function that maps percepts (what the agent perceives) to actions.
    • Percept Sequence - The history of all the information the agent has sensed, which helps it decide what actions to take.
    • Agent Program - The concrete implementation of the agent function. The agent program takes percepts from sensors and computes the appropriate action.

    Agent Structure

    • Agent = Architecture + Agent Program
      • Architecture = the machinery that an agent executes on
      • Agent Program = an implementation of an agent function

    Behavior of Agent

    • The set of actions that an agent performs based on a sequence of percepts.
    • For instance, if a robot senses an obstacle (percept), it turns right (action).
    • Percept: The input an agent receives from its environment at any given moment. This could be visual, auditory, or sensor-based data.
    • Percept Sequence: The complete history of everything an agent has perceived up to a certain point.

    Rational Agents

    • Make decisions that maximize their chances of achieving goals, based on their knowledge and perceptions of the environment.
    • It acts to achieve the best possible outcome, or when faced with uncertainty, the best expected outcome.
    • Example: A navigation app (the agent) analyzes the available routes from point A to B and chooses the quickest route based on real-time traffic data.

    PEAS Revisited

    • Performance

    • Environment

    • Actuators

    • Sensors

    • Rational agents are grouped under PEAS, the problem specification for the task environment. The rational agent we want to design is the solution.

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    Week 4.1(1).pdf

    Description

    This quiz explores the concept of No-Code AI, focusing on how users can quickly build AI models without technical skills. It also covers various types of AI problems, including prescriptive and predictive challenges, with real-world examples of predictive applications in sales forecasting.

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