Marktechpost

MARCH 1, 2024

The prowess of Large Language Models (LLMs) such as GPT and BERT has been a game-changer, propelling advancements in machine understanding and generation of human-like text. These models have mastered the intricacies of language, enabling them to tackle tasks with remarkable accuracy.

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Large Language Models Artificial Intelligence Artificial Intelligence Natural Language Processing 111

NYU Center for Data Science

JUNE 30, 2023

When Eric became a neurosurgeon, the idea fully formulated when he considered the usefulness of having an AI assistant who could read along with him and chime in with advice. Through this work, I have become interested in learning more about conversational AI, interpretability, privacy and fairness, and causality.

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Large Language Models Natural Language Processing BERT Computer Scientist 93

ODSC - Open Data Science

FEBRUARY 14, 2023

Trained with 570 GB of data from books and all the written text on the internet, ChatGPT is an impressive example of the training that goes into the creation of conversational AI. and is trained in a manner similar to OpenAI’s earlier InstructGPT, but on conversations. Google-killer?

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ChatGPT Large Language Models OpenAI Conversational AI 124

Mlearning.ai

JUNE 7, 2023

Photo by Eugene Zhyvchik on Unsplash I wanted to share a short perspective of the radical evolution we have seen in NLP. I’ve been working on NLP problems since word2vec was released, and it has been remarkable to see how quickly the models, problems, and applications have evolved. GPT-2 released with 1.5

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ODSC - Open Data Science

JUNE 9, 2023

The last 12 years though, is where some of the big magic has happened in NLP. Word vectorization is an NLP methodology used to map words or phrases from a vocabulary to a corresponding vector of real numbers used to find word predictions and word similarities or semantics. BERT was designed to understand the meanings of sentences.

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AWS Machine Learning Blog

NOVEMBER 29, 2023

In today’s rapidly evolving landscape of artificial intelligence, deep learning models have found themselves at the forefront of innovation, with applications spanning computer vision (CV), natural language processing (NLP), and recommendation systems. device batch = [t.to(device) device batch = [t.to(device)

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Marktechpost

JULY 3, 2023

With the release of the latest chatbot developed by OpenAI called ChatGPT, the field of AI has taken over the world as ChatGPT, due to its GPT’s transformer architecture, is always in the headlines. Almost every industry is utilizing the potential of AI and revolutionizing itself.

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Large Language Models Natural Language Processing LLM BERT 98

Topbots

OCTOBER 4, 2023

The basic difference is that predictive AI outputs predictions and forecasts, while generative AI outputs new content. Here are a few examples across various domains: Natural Language Processing (NLP) : Predictive NLP models can categorize text into predefined classes (e.g., a social media post or product description).

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Pickl AI

DECEMBER 5, 2024

Summary: Retrieval Augmented Generation (RAG) is an innovative AI approach that combines information retrieval with text generation. By leveraging external knowledge sources, RAG enhances the accuracy and relevance of AI outputs, making it essential for applications like conversational AI and enterprise search.

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Topbots

JULY 6, 2023

To test this suggestion, they trained a 175B-parameter autoregressive language model, called GPT-3 , and evaluated its performance on over two dozen NLP tasks. However, unlike most language models, LaMDA was trained on dialogue to pick up on nuances that distinguish open-ended conversation from other forms of language.

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ML Review

DECEMBER 16, 2019

The main venue alone had more than 100 graph-related publications, and even more were available at three workshops: Graph Representation Learning (about 100 more papers), Knowledge Representation & Reasoning Meets Machine Learning (KR2ML) (about 50 papers), Conversational AI. So we’ll consider all events jointly. Have a look ?

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Topbots

JUNE 15, 2023

Language Disparity in Natural Language Processing This digital divide in natural language processing (NLP) is an active area of research. 2 ] Multilingual models perform worse on several NLP tasks on low resource languages than on high resource languages such as English.[ Are All Languages Created Equal in Multilingual BERT?

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Natural Language Processing Computational Linguistics NLP ChatGPT 59

Snorkel AI

AUGUST 24, 2023

Then, they can distill that model’s expertise into a deployable form by having it “teach” a smaller model like BERT and applying it to their specific problem. Banks can use these models to fine-tune their interactive voice responses and train conversational AI to automatically respond to queries over chat, email, and text.

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Large Language Models AI AI Natural Language Processing 52

Unite.AI

AUGUST 8, 2023

These advanced AI deep learning models have seamlessly integrated into various applications, from Google's search engine enhancements with BERT to GitHub’s Copilot, which harnesses the capability of Large Language Models (LLMs) to convert simple code snippets into fully functional source codes. How Are LLMs Used?

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Topbots

JUNE 6, 2023

In October 2022, I published an article on LLM selection for specific NLP use cases , such as conversation, translation and summarisation. Since then, AI has made a huge step forward, and in this article, we will review some of the trends of the past months as well as their implications for AI builders.

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