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The RNNsearch model introduced an attention mechanism to seq2seq for machine translation to solve the bottleneck problem (of the fixed-size output vector), allowing the model to process long-distance dependencies more easily. The name is because it "emulates searching through a source sentence during decoding a translation".
In machine learning, grokking, or delayed generalization, is a transition to generalization that occurs many training iterations after the interpolation threshold, after many iterations of seemingly little progress, as opposed to the usual process where generalization occurs slowly and progressively once the interpolation threshold has been ...
The areas indicated in the previous section as GBK/1 and GBK/2, taken by themselves, is simply GB 2312-80 in its usual encoding, GBK/1 being the non-hanzi region and GBK/2 the hanzi region. GB 2312, or more properly the EUC-CN encoding thereof, takes a pair of bytes from the range A1 – FE , like any 94² ISO-2022 character set loaded into GR.
Two encoding schemes existed for GB 2312: a one-or-two byte 8-bit EUC-CN encoding commonly used, and a 7-bit encoding called HZ [1] for usenet posts. [2]: 94 A traditional variant called GB/T 12345 was published in 1990. The EUC-CN form was later extended into GBK to include all Unicode 1.1 CJK Ideographs in 1993, abandoning the ISO-2022 model.
Pronounced "A-star". A graph traversal and pathfinding algorithm which is used in many fields of computer science due to its completeness, optimality, and optimal efficiency. abductive logic programming (ALP) A high-level knowledge-representation framework that can be used to solve problems declaratively based on abductive reasoning. It extends normal logic programming by allowing some ...
Predictive coding was initially developed as a model of the sensory system, where the brain solves the problem of modelling distal causes of sensory input through a version of Bayesian inference. It assumes that the brain maintains an active internal representations of the distal causes, which enable it to predict the sensory inputs. [5]
The next audio clip is the AI-generated voice that was created by Voice Engine based on the above human speech and a written paragraph that told the machine what to say.
Reciprocal Human Machine Learning (RHML) is an interdisciplinary approach to designing human-AI interaction systems. [1] RHML aims to enable continual learning between humans and machine learning models by having them learn from each other. This approach keeps the human expert "in the loop" to oversee and enhance machine learning performance ...