Exam 4: Chapter 14- Artificial Intelligence Flashcards
broad field that focuses on creating intelligent machines that can perform tasks that typically require human intelligence.
Artificial Intelligence (A.I.)
subset of AI that involves training algorithms to learn patterns from data and make predictions or decisions without being explicitly programmed; the study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and interference instead.
machine learning (ML)
subset of machine learning in which multilayered neural networks learn from vast amounts of data.
deep learning
What are the 4 reasons that A.I./ M.L are exploding right now?
- Computational power (GPUs) increasing
- Massive amounts of labeled data available
- Neural networks
- Demonetized training costs (99.5% decrease in the last 5 years)
hypothetical AI that matches or exceeds human intelligence – the intelligence of a machine that could successfully perform any intellectual task that a human being can.
strong A.I.
What is the risk of Strong A.I?
the ability to think
AI that performs a useful and specific function that once required human intelligence to perform, and does so at human levels or better; simulating thinking; robotics (AI in motion)
narrow or weak A.I.
T or F: Weak AI is already embedded in our environments today (both personal and professional).
true
What are the 3 types of machine learning?
- Supervised learning
- Unsupervised learning
- Reinforcement learning
system is trained with labeled training data to make predictions or classify new, unseen data.
supervised learning
system learns patterns and relationships within unlabeled data without specific feedback or guidance
unsupervised learning
system learns from its environment by interacting with it and receiving rewards for performing actions
reinforcement learning
Any of the 3 types of M.L. becomes “deep” when the system uses deep artificial _______ _______.
neural networks
______ ______ plays a critical role in machine learning.
Big Data
a video of a person in which their face or body has been digitally altered so that they appear to be someone else, typically used maliciously or to spread false information.
deep fakes
What are the four main capabilities that distinguish Watson as a cognitive system:
- Ability to understand human language
- Ability to absorb information and to learn
- Ability to formulate hypotheses
- Ability to understand the context of a question
Watson is __________, not deterministic.
probabilistic
The world’s most powerful, generally applicable technology.
machine learning
T or F: Today, ML is necessary to sustain competitive advantage.
true
because ML algorithms work (true), the models they generate are intrinsically valuable (false).
the ML fallacy
The value of ML comes only by:
enacting organizational change.
Most ML projects fail to deploy because project leaders didn’t properly plan for the ________ ______ that the deployment would cause.
operational change
for ML to succeed, we need improvement in human knowledge more than improvements in technology.
The ML paradox
Machine Learning Projects → Who is Involved? (tight integration and colaboration) (3)
- Business Professionals
- Business Analysts
- Data Scientists
Serve as liaisons and translators to bridge the gap between technology and the business (that is, between the technological project staff and line-of-business stakeholders in charge of the operations that the ML project will change)
Business Analysts
What people does this describe?
- Design and implement ML models to analyze large datasets to make predictions.
- Use mathematical and statistical procedures to build predictive models.
- They perform data wrangling, which includes data collection, data cleaning, and feature engineering.
data scientists
What people does this describe?
- Work with business professionals to identify and define the business requirements for new products, services, or processes.
- Work with the technical team to ensure that the prediction goal, deployment plan, and performance objectives are aligned with the operational team’s requirements.
business analysts
What people does this describe?
- Responsible for identifying business opportunities that can be addressed with ML applications.
- Need basic knowledge of ML fundamentals to understand how ML projects work from conception to deployment.
- They understand how ML deployment will impact and change business operations.
- They can define ML project performance goals, help prepare the data, and help develop and deploy
the ML model.
- They can provide sanity checks.
Business Professionals
What type of ML learning is this?
a type of machine learning in which the system is given labeled input data and the expected output results. Developers input massive amounts of data during the training phase as well as what output should be obtained from each specific input value. Developers then input unlabeled, never-been-seen data values to verify that the model is accurate
supervised
What type of ML learning does this describe?
a type of machine learning that searches for previously undetected patterns in a data set with no pre-existing labels and with minimal human supervision.
unsupervised
The best time to use unsupervised learning is when an organization…
does not have data on desired outcomes (ex: when the firm wants to determine a target market for an entirely new product that it has never before sold.)
What type of ML learning does this describe?
the system learns to achieve a goal in an uncertain, potentially complex environment. The system faces a game-like situation where it employs trial and error to find a solution to a problem.
reinforcement
