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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 ...
Tabnine is an artificial intelligence (AI) coding assistant developed by Tabnine, which was founded by Dror Weiss and Professor Eran Yahav in Tel Aviv, Israel, in 2013. [1] [2] [3] Initially established under the name Codota, the company underwent a rebranding in May 2021 following the release of the company’s first large language model based ...
Hubert Dreyfus was a critic of artificial intelligence research. In a series of papers and books, including Alchemy and AI (1965), What Computers Can't Do ( 1972; 1979; 1992) and Mind over Machine (1986), he presented a pessimistic assessment of AI's progress and a critique of the philosophical foundations of the field.
Knowledge representation and reasoning. Knowledge representation and reasoning ( KRR, KR&R, KR²) is the field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can use to solve complex tasks such as diagnosing a medical condition or having a dialog in a natural language.
Research on truthful AI includes trying to build systems that can cite sources and explain their reasoning when answering questions, which enables better transparency and verifiability. Researchers at OpenAI and Anthropic proposed using human feedback and curated datasets to fine-tune AI assistants such that they avoid negligent falsehoods or ...
Causal AI. Causal AI is a technique in artificial intelligence that builds a causal model and can thereby make inferences using causality rather than just correlation. One practical use for causal AI is for organisations to explain decision-making and the causes for a decision. [1] [2]
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