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- DictionaryNLP/ɛnɛlˈpiː/
abbreviation
- 1. natural language processing.
- 2. neurolinguistic programming.
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Oct 10, 2024 · Natural Language Processing. Much of the information that can help transform enterprises is locked away in text, like documents, tables, and charts. We’re building advanced AI systems that can parse vast bodies of text to help unlock that data, but also ones flexible enough to be applied to any language problem.
Abstract. Recently, there has been a surge of interest in applying deep learning on graphs techniques (i.e., Graph Neural Networks (GNNs)) to NLP, and has achieved considerable success in many NLP tasks. Despite these successes, deep learning on graphs for NLP still face many challenges, including automatically transforming textual data into ...
Jun 23, 2021 · The same institute that is now partnering with IBM Research to create a new innovation lab in Bengaluru—the IBM-IISc Hybrid Cloud Lab. The aim is to further advance the research in artificial intelligence and hybrid cloud in this already very tech-savvy nation. IBM Research has been in India since 1998, continuously producing crucial ...
Using NLP technologies, target documents are transformed into collections of concepts, which are described using terms discovered within the texts. Often, "text mining" is used to refer to a text search technique, but we think of text mining from a more functional perspective.
Dec 4, 2020 · Table 1 illustrates the kinds of questions NSQA can handle and the form of reasoning required to answer different questions. This approach provides interpretability, generalizability, and robustness— all critical requirements in enterprise NLP settings.
May 18, 2023 · The integration of Intel OneAPI and IBM Watson NLP library can significantly improve the performance of NLP tasks. In October 2022, IBM expanded the embeddable AI portfolio with the release of IBM Watson Natural Language Processing Library for Embed, which is designed to help developers provide capabilities to process human language to derive meaning and context through intent and sentiment.
The system visually organizes and illustrates XAI-NLP publications and distills their content to allow users to gain insights, generate ideas, and explore the field. We hope that XNLP can become a leading demonstrative example of a living survey, balancing the depth and quality of a traditional well-constructed survey paper with the collaborative dynamism of a widely available interactive tool.
Apr 20, 2023 · The rise of deep generative models. Generative AI refers to deep-learning models that can take raw data — say, all of Wikipedia or the collected works of Rembrandt — and “learn” to generate statistically probable outputs when prompted. At a high level, generative models encode a simplified representation of their training data and draw ...
Jul 6, 2022 · The groundbreaking AI paper at the foundations of multilingual natural language processing. BLEU, a seminal benchmark for testing the efficacy of machine translation and other natural language generation tasks, was published 20 years ago this month. Twenty years ago, a group of IBM Researchers came together to think of a better way of ...
Oct 12, 2021 · Neuro-symbolic AI. We see Neuro-symbolic AI as a pathway to achieve artificial general intelligence. By augmenting and combining the strengths of statistical AI, like machine learning, with the capabilities of human-like symbolic knowledge and reasoning, we're aiming to create a revolution in AI, rather than an evolution.
