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  2. AI alignment - Wikipedia

    en.wikipedia.org/wiki/AI_alignment

    AI alignment is an open problem for modern AI systems and is a research field within AI. [41] [1] Aligning AI involves two main challenges: carefully specifying the purpose of the system (outer alignment) and ensuring that the system adopts the specification robustly (inner alignment). [2]

  3. Explainable artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Explainable_artificial...

    Explainable AI ( XAI ), often overlapping with interpretable AI, or explainable machine learning ( XML ), either refers to an artificial intelligence (AI) system over which it is possible for humans to retain intellectual oversight, or refers to the methods to achieve this. [1] [2] The main focus is usually on the reasoning behind the decisions ...

  4. Ethics of artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Ethics_of_artificial...

    The term "robot ethics" (sometimes "roboethics") refers to the morality of how humans design, construct, use and treat robots. [14] Robot ethics intersect with the ethics of AI. Robots are physical machines whereas AI can be only software. [15] Not all robots function through AI systems and not all AI systems are robots.

  5. Symbolic artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Symbolic_artificial...

    An artistic representation of AI. In artificial intelligence, symbolic artificial intelligence is the term for the collection of all methods in artificial intelligence research that are based on high-level symbolic (human-readable) representations of problems, logic and search. [1] Symbolic AI used tools such as logic programming, production ...

  6. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data and thus perform tasks without explicit instructions. Recently, artificial neural networks have been able to surpass many previous approaches in performance.

  7. Knowledge representation and reasoning - Wikipedia

    en.wikipedia.org/wiki/Knowledge_representation...

    Knowledge-representation is a field of artificial intelligence that focuses on designing computer representations that capture information about the world that can be used for solving complex problems. The justification for knowledge representation is that conventional procedural code is not the best formalism to use to solve complex problems.

  8. Neural network (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Neural_network_(machine...

    Neural network (machine learning) An artificial neural network is an interconnected group of nodes, inspired by a simplification of neurons in a brain. Here, each circular node represents an artificial neuron and an arrow represents a connection from the output of one artificial neuron to the input of another. Part of a series on.

  9. AI will make coding skills more, not less, valuable—and it’s ...

    www.aol.com/finance/ai-coding-skills-more-not...

    The power of learning how to code is in the intangible skills of breaking down a problem piece by piece and approaching it in different ways to find a solution. Coding is one of the best mediums ...

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