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The alignment models that use first-order dependencies like the HMM or IBM Models 4 and 5 produce better results than the other alignment methods. The main idea of HMM is to predict the distance between subsequent source language positions. On the other hand, IBM Model 4 tries to predict the distance between subsequent target language positions.
It is used in natural language processing and information retrieval (IR). It disregards word order (and thus most of syntax or grammar) but captures multiplicity. The bag-of-words model is commonly used in methods of document classification where, for example, the (frequency of) occurrence of each word is used as a feature for training a ...
Content and language integrated learning (CLIL) is an approach for learning content through an additional language (foreign or second), thus teaching both the subject and the language. The idea of its proponents was to create an "umbrella term" which encompasses different forms of using language as medium of instruction.
A word n-gram language model is a purely statistical model of language. It has been superseded by recurrent neural network–based models, which have been superseded by large language models. [12] It is based on an assumption that the probability of the next word in a sequence depends only on a fixed size window of previous words.
IBM Granite is a series of decoder-only AI foundation models created by IBM. [3] It was announced on September 7, 2023, [4] [5] and an initial paper was published 4 days later. [6] Initially intended for use in the IBM's cloud-based data and generative AI platform Watsonx along with other models, [7] IBM opened the source code of some code models.
In 1988, the "Oryx" project at IBM, under the technical direction of Simon C. Nash, experimented with merging classic Rexx with the object model of Smalltalk. [3] [4] The motivation behind the project was to transfer the advantages of OOP to classic Rexx while remaining compatible and thus transferring the usability of classic Rexx to OOP. [5]
A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation. LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text. The largest and most capable LLMs are generative pretrained transformers (GPTs).
PL/I (Programming Language One, pronounced / p iː ɛ l w ʌ n / and sometimes written PL/1) [1] is a procedural, imperative computer programming language initially developed by IBM.It is designed for scientific, engineering, business and system programming.