Marktechpost

JULY 15, 2023

The advent of large language models (LLMs) has sparked significant interest among the public, particularly with the emergence of ChatGPT. These models, which are trained on extensive amounts of data, can learn in context, even with minimal examples.

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Marktechpost

DECEMBER 26, 2023

Computational linguistics focuses on developing advanced language models capable of understanding and generating human language. This dynamic field integrates the latest in machine learning and artificial intelligence, striving to create models that grasp the intricacies of language.

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Marktechpost

JANUARY 4, 2024

The development of Large Language Models (LLMs), such as GPT and BERT, represents a remarkable leap in computational linguistics. Training these models, however, is challenging. If you like our work, you will love our newsletter.

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Topbots

JANUARY 30, 2023

400k AI-related online texts since 2021) Disclaimer: This article was written without the support of ChatGPT. In the last couple of years, Large Language Models (LLMs) such as ChatGPT, T5 and LaMDA have developed amazing skills to produce human language. Association for Computational Linguistics. [2]

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Marktechpost

AUGUST 12, 2023

This innovative tool was presented at the 2023 Association for Computational Linguistics (ACL) conference. Its primary purpose is quantifying and identifying biases within advanced generative models, like Stable Diffusion, which can magnify existing prejudices in the images generated.

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Flipboard

SEPTEMBER 7, 2023

While we can only guess whether some powerful future AI will categorize us as unintelligent, what’s clear is that there is an explicit and concerning contempt for the human animal among prominent AI boosters. We have no reason to believe any current AIs are sentient, but we also have no way of knowing whether or how that could change.

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Topbots

JUNE 15, 2023

Large language models such as ChatGPT process and generate text sequences by first splitting the text into smaller units called tokens. Language Disparity in Natural Language Processing This digital divide in natural language processing (NLP) is an active area of research. Shijie Wu and Mark Dredze.

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