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Alibaba Researchers Unveil Unicron: An AI System Designed for Efficient Self-Healing in Large-Scale Language Model Training

Marktechpost

The development of Large Language Models (LLMs), such as GPT and BERT, represents a remarkable leap in computational linguistics. The computational intensity required and the potential for various failures during extensive training periods necessitate innovative solutions for efficient management and recovery.

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Large Language Models – Technical Overview

Viso.ai

Machine learning especially Deep Learning is the backbone of every LLM. Categorization of LLMs – Source One of the most common examples of an LLM is a virtual voice assistant such as Siri or Alexa. Read more related topics and blogs about LLMs and Deep Learning: What is Natural Language Processing ?

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Natural Language Processing with R

Heartbeat

Natural Language Processing (NLP) plays a crucial role in advancing research in various fields, such as computational linguistics, computer science, and artificial intelligence. R Source: i2tutorials Statisticians developed R as a tool for statistical computing. We pay our contributors, and we don’t sell ads.

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Testing the Robustness of LSTM-Based Sentiment Analysis Models

John Snow Labs

On the other hand, Sentiment analysis is a method for automatically identifying, extracting, and categorizing subjective information from textual data. Learning Word Vectors for Sentiment Analysis. The 49th Annual Meeting of the Association for Computational Linguistics (ACL 2011). Daly, Peter T.

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The State of Multilingual AI

Sebastian Ruder

This post is partially based on a keynote I gave at the Deep Learning Indaba 2022. These include groups focusing on linguistic regions such as Masakhane for African languages, AmericasNLP for native American languages, IndoNLP for Indonesian languages, GhanaNLP and HausaNLP , among others. Joshi et al. [92] 2340–2354).