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  2. Artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence

    Various subfields of AI research are centered around particular goals and the use of particular tools. The traditional goals of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception, and support for robotics.

  3. Nutritional science - Wikipedia

    en.wikipedia.org/wiki/Nutritional_science

    Nutritional science is often combined with food science (nutrition and food science). Trophology is a term used globally for nutritional science in other languages, in English the term is dated. Today, it is partly still used for the approach of food combining that advocates specific combinations (or advises against certain combinations) of food.

  4. Open-source artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Open-source_artificial...

    Open-source artificial intelligence is an AI system that is freely available to use, study, modify, and share. [1] These attributes extend to each of the system's components, including datasets, code, and model parameters, promoting a collaborative and transparent approach to AI development. [ 1 ]

  5. Recursive self-improvement - Wikipedia

    en.wikipedia.org/wiki/Recursive_self-improvement

    Recursive self-improvement (RSI) is a process in which an early or weak artificial general intelligence (AGI) system enhances its own capabilities and intelligence without human intervention, leading to a superintelligence or intelligence explosion.

  6. Nutritional genomics - Wikipedia

    en.wikipedia.org/wiki/Nutritional_genomics

    Nutritional genomics, also known as nutrigenomics, is a science studying the relationship between human genome, human nutrition and health. People in the field work toward developing an understanding of how the whole body responds to a food via systems biology, as well as single gene/single food compound relationships.

  7. Retrieval-augmented generation - Wikipedia

    en.wikipedia.org/wiki/Retrieval-augmented_generation

    Retrieval-augmented generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.

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  9. Outline of artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Outline_of_artificial...

    Allen Institute for Artificial Intelligence – research institute funded by Microsoft co-founder Paul Allen to construct AI systems with reasoning, learning and reading capabilities. The current flagship project is Project Aristo, the goal of which is computers that can pass school science examinations (4th grade, 8th grade, and 12th grade ...