منابع مشابه
Learning to learn: From smart machines to intelligent machines
Since its birth, more than five decades ago, one of the biggest challenges of artificial intelligence remained the building of intelligent machines. Despite amazing advancements, we are still far from having machines that reach human intelligence level. The current paper tries to offer a possible explanation of this situation. For this purpose, we make a review of different learning strategies ...
متن کاملTeaching Machines to Learn by Metaphors
Humans have an uncanny ability to learn new concepts with very few examples. Cognitive theories have suggested that this is done by utilizing prior experience of related tasks. We propose to emulate this process in machines, by transforming new problems into old ones. These transformations are called metaphors. Obviously, the learner is not given a metaphor, but must acquire one through a learn...
متن کاملConcept selection for phenotypes and diseases using learn to rank
BACKGROUND Phenotypes form the basis for determining the existence of a disease against the given evidence. Much of this evidence though remains locked away in text - scientific articles, clinical trial reports and electronic patient records (EPR) - where authors use the full expressivity of human language to report their observations. RESULTS In this paper we exploit a combination of off-the...
متن کاملBuilding Machines That Learn and Think Like People
Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans in some respects. Despite their biological inspiration and performance ach...
متن کاملAn Exploratory Study Towards "Machines that Learn to Read"
This paper reports early results at the intersection of knowledge and language acquisition. Humans learn much by reading, a capability largely absent from machines. We assume that (1) some conceptual structure exists, represented in an ontology, (2) a handful of examples of each concept and relation is provided, and (3) the machine knows the grammatical structure and semantic structure of the l...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Nature Methods
سال: 2013
ISSN: 1548-7091,1548-7105
DOI: 10.1038/nmeth.2299