An executive’s guide to AI
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Artificial intelligence
Machinelearning
Machinelearning
Deeplearning
Machine learning
Next: Major types
Most recent advances in AI have been achieved by applying machine learning to very large data sets. Machine-learning algorithms detect patterns and learn how to make predictions and recommendations by processing data and experiences, rather than by receiving explicit programming instruction. The algorithms also adapt in response to new data and experiences to improve efficacy over time.
Machine learning provides predictions and prescriptions
Types of analytics (in order of increasing complexity)
Descriptive
Describe what happened
Employed heavily across all industries
x
y
z
Predictive
Anticipate what will happen (inherently probabilistic)
Employed in data-driven organizations as a key source of insight
Prescriptive
A
Provide recommendations on what to do to achieve goals
B
Employed heavily by leading data and Internet companies
Focus of machine learning
Next: Major types
An executive’s guide to AI
Share
Artificial intelligence
Artificial intelligence
Machinelearning
Deeplearning
Artificial intelligence
Why AI now?
AI is typically defined as the ability of a machine to perform cognitive functions we associate with human minds, such as perceiving, reasoning, learning, interacting with the environment, problem solving, and even exercising creativity. Examples of technologies that enable AI to solve business problems are robotics and autonomous vehicles, computer vision, language, virtual agents, and machine
perceive
problem solve
reason
learn
Next: Why AI now?