AI News

JUNE 14, 2024

Researchers have introduced a novel approach called natural language embedded programs (NLEPs) to improve the numerical and symbolic reasoning capabilities of large language models (LLMs). Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

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AssemblyAI

SEPTEMBER 18, 2023

However, among all the modern-day AI innovations, one breakthrough has the potential to make the most impact: large language models (LLMs). These feats of computational linguistics have redefined our understanding of machine-human interactions and paved the way for brand-new digital solutions and communications.

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Marktechpost

MAY 13, 2024

Tokenization is essential in computational linguistics, particularly in the training and functionality of large language models (LLMs). This process involves dissecting text into manageable pieces or tokens, which is foundational for model training and operations.

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Viso.ai

JULY 18, 2024

What are Large Language Models (LLMs)? In generative AI, human language is perceived as a difficult data type. If a computer program is trained on enough data such that it can analyze, understand, and generate responses in natural language and other forms of content, it is called a Large Language Model (LLM).

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Marktechpost

MARCH 12, 2024

The advent of large language models (LLMs) has ushered in a new era in computational linguistics, significantly extending the frontier beyond traditional natural language processing to encompass a broad spectrum of general tasks.

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Marek Rei

NOVEMBER 4, 2024

It is probably good to also to mention that I wrote all of these summaries myself and they are not generated by any language models. They focus on coherence, as opposed to correctness, and develop an automated LLM-based score (BooookScore) for assessing summaries. Are Emergent Abilities of Large Language Models a Mirage?

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Topbots

JANUARY 30, 2023

In the last couple of years, Large Language Models (LLMs) such as ChatGPT, T5 and LaMDA have developed amazing skills to produce human language. We are quick to attribute intelligence to models and algorithms, but how much of this is emulation, and how much is really reminiscent of the rich language capability of humans?

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