Cognitive automation
Cognitive automation is the encoding and operationalization of human skills and knowledge in computer systems.
Deep Learning with R, Third Edition
Cognitive automation is the encoding and operationalization of human skills and knowledge in computer systems.
- How it is used
- Frames modern AI as practical automation for narrowly defined tasks or tasks supported by abundant, precise examples.
- How deep it goes
- Distinguishes encoding skills from intelligence and explains local generalization, but stops short of specifying implementation methods.
- Examples
- Uses self-driving cars, domestic robots making coffee, cartoon characters, and language-model answers to contrast automation with adaptive intelligence.
- What you can do after
- Evaluate AI claims by separating useful task automation from adaptability to radically novel situations.
Read how Deep Learning with R, Third Edition explains cognitive automation →
Deep Learning with Python, Third Edition
The use of AI to automate tasks by encoding and operationalizing human skills and knowledge rather than achieving full human-like intelligence.
- How it is used
- Frames AI as practical automation of human skills rather than replication of human minds.
- How deep it goes
- Defines cognitive automation, contrasts it with intelligence, and explains local versus broad generalization without implementation detail.
- Examples
- Uses a cartoon analogy, language-model answers, self-driving cars, and domestic robots making coffee.
- What you can do after
- Evaluate/understand AI claims by separating trained-task automation from adaptive intelligence and broad generalization.
Read how Deep Learning with Python, Third Edition explains cognitive automation →
Related concepts
- artificial intelligenceequivalent to · Artificial intelligence is the field concerned with creating computational systems that perform tasks associated with human intelligence, such as learning, reasoning, perception, or decision-making.
- language modelincludes · A language model is a computational model that represents patterns in linguistic tokens to estimate sequence probabilities and predict or generate language from context.
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