BTE 210 Exam 2 (Professor M.L. ESPINOSA)/exam study guide/questions and answers/correct/verified A+/latest updates fall 2024

BTE 210 Exam 2 (Professor M.L. ESPINOSA)/exam study guide/questions and answers/correct/verified A+/latest updates fall 2024 BTE 210 Exam 2 (Professor M.L. ESPINOSA)/exam study guide/questions and answers/correct/verified A+/latest updates fall 2024 artificial intelligence (AI) - correct answers-Subfield of Computer Science that studies the thought processes of humans and recreates the effects of those processes via machines, such as computers and robots. Behavior by a machine that, if performed by a human being, would be considered intelligent. Turing Test - correct answers-A test proposed by Alan Turing in which a machine would be judged "intelligent" if the software could use conversation to fool a human into thinking it was talking with a person instead of a machine. Alan Turing - correct answers-British AI pioneer The Imitation Game (2014) How AI works - correct answers-1. Creates perspectives 2. Understands language and its nuances 3. Learns from experience 4. Uses the learning to reason 5. Solves complex problems 6. Recognizes images Evolution of AI - correct answers-: AI as a concept, no real application : Military and academia begin to show interest in AI 2005 onwards: large tech companies invest in commercial applications of AI/machine learning (ML) Artificial Intelligence Includes: - correct answers-Neural Networks Planning Robotics Machine Learning Natural Language Processing Perception Knowledge Cognitive System Components of Expert System - correct answers-1. Knowledge Base 2. Inference Engine 3. User Interface Knowledge Base - correct answers-Facts: such as the problem situation. Rules: direct the use of knowledge to solve specific problems in a particular domain. Knowledge base needs computer language to store information / expertise Inference Engine - correct answers-a computer program that provides a methodology for reasoning and formulating conclusions. User Interface - correct answers-dialogue between the user and the computer triggers the inference engine to match the problem symptoms with the knowledge contained in the knowledge base and then generate advice. Benefits of Expert Systems - correct answers-1. Increased output and productivity: ESs can configure components for each custom order, increasing production capabilities. 2. Increased quality: ESs can provide consistent advice and reduce error rates. 3. Capture and dissemination of scarce expertise: Expertise from anywhere in the world can be obtained and used. 4. Operation in hazardous environments: Sensors can collect information that an ES interprets, enabling human workers to avoid hot, humid, or toxic environments. 5. Accessibility to knowledge and help desks: ESs can increase the productivity of help desk employees, or even automate this function. 6. Reliability: ESs do not become tired or bored, call in sick, or go on strike. They consistently pay attention to details. 7. Ability to work with incomplete or uncertain information: Even with an answer of "don't know," an ES can produce an answer, although it may not be a definite one. 8. Provision of training: The explanation facility of an ES can serve as a teaching device and a knowledge base for novices. 9. Enhancement of decision-making and problem-solving capabilities: ESs allow the integration of expert judgment into analysis (e.g., diagnosis of machine malfunction and even medical diagnosis). 10. Decreased decision-making time: ESs usually can make faster decisions than humans working alone. 11. Reduced downtime: ESs can quickly diagnose machine malfunctions and prescribe repairs. Difficulties of Using Expert Systems - correct answers-1. Transferring domain expertise from human experts to the expert system can be difficult because people cannot always explain what they know 2. Even if the domain experts can explain their entire reasoning process, automating that process may not be possible 3. In some contexts, there is a potential liability from the use of expert systems. Knowledge Acquisition - correct answers-Knowledge is acquired from domain experts or from documented sources. Knowledge Representation - correct answers-Acquired knowledge is organized as rules or frames (object-oriented) and stored electronically in a knowledge base. Knowledge Inferencing - correct answers-The computer is programmed so that it can make inferences based on the stored knowledge. Knowledge Transfer - correct answers-The inferenced expertise is transferred to the user in the form of a recommendation. Machine Learning Systems - correct answers-- Optical character recognition - Face recognition - Topic identification - Fraud detection - Customer segmentation Optical character recognition - correct answers-Printed, handwritten characters are recognized automatically based on previous examples. Face recognition - correct answers-Identify faces in images. Topic identification - correct answers-Categorize news articles as to whether they are about politics, sports, entertainment, and so on. Fraud detection - correct answers-Identify credit card transactions that may be fraudulent. Customer segmentation - correct answers-Identify which customers may respond positively to a particular promotion.