Topbots

APRIL 11, 2023

In the rapidly evolving field of artificial intelligence, natural language processing has become a focal point for researchers and developers alike. We’ll start with a seminal BERT model from 2018 and finish with this year’s latest breakthroughs like LLaMA by Meta AI and GPT-4 by OpenAI. billion word corpus).

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Towards AI

DECEMBER 28, 2023

The introduction of attention mechanisms has notably altered our approach to working with deep learning algorithms, leading to a revolution in the realms of computer vision and natural language processing (NLP). These models are trained on massive amounts of text data to learn patterns and relationships in the language.

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Artificial Corner

JULY 30, 2023

Photo by Shubham Dhage on Unsplash Introduction Large language Models (LLMs) are a subset of Deep Learning. Image by YouTube video “Introduction to large language models” on YouTube Channel “Google Cloud Tech” What are Large Language Models? Natural Language Processing (NLP) is a subfield of artificial intelligence.

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IBM Journey to AI blog

FEBRUARY 13, 2024

They are now capable of natural language processing ( NLP ), grasping context and exhibiting elements of creativity. Innovators who want a custom AI can pick a “foundation model” like OpenAI’s GPT-3 or BERT and feed it their data.

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Unite.AI

JANUARY 23, 2024

Large language models (LLMs) have exploded in popularity over the last few years, revolutionizing natural language processing and AI. From chatbots to search engines to creative writing aids, LLMs are powering cutting-edge applications across industries. LLMs utilize embeddings to understand word context.

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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. Chatbots – LLMs are frequently utilized in the creation of chatbots and systems that use conversational AI.

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ODSC - Open Data Science

FEBRUARY 17, 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. BERT even accounts for the context of words, allowing for more accurate results related to respective queries and tasks.

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Unite.AI

NOVEMBER 20, 2023

Overview of Meta Llama Project Overview of Llama 2 pre-training and fine-tuning process As a pivotal tool within Meta's ecosystem, Llama has far-reaching implications. Its robust natural language capabilities empower developers to build and fine-tune powerful chatbots, language translation, and content generation systems.

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Marktechpost

JULY 5, 2023

ChatGPT, the latest chatbot developed by OpenAI, has been in the headlines ever since its release. translates languages, summarizes long textual paragraphs while retaining the important key points, and even generates code samples.

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Unite.AI

AUGUST 28, 2023

With advancements in deep learning, natural language processing (NLP), and AI, we are in a time period where AI agents could form a significant portion of the global workforce. These AI agents, transcending chatbots and voice assistants, are shaping a new paradigm for both industries and our daily lives.

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Flipboard

JULY 4, 2023

Famous LLMs like GPT, BERT, PaLM, and LLaMa are revolutionizing the AI industry by imitating humans. The well-known chatbot called ChatGPT, based on GPT architecture and developed by OpenAI, imitates humans by generating accurate and creative content, answering questions, summarizing massive textual paragraphs, and language translation.

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Flipboard

JUNE 20, 2023

Training experiment: Training BERT Large from scratch Training, as opposed to inference, is a finite process that is repeated much less frequently. Training a well-performing BERT Large model from scratch typically requires 450 million sequences to be processed. The first uses traditional accelerated EC2 instances.

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ODSC - Open Data Science

NOVEMBER 8, 2023

Do you want a chatbot, a Q&A system, or an image generator? It is also used to customize LLMs for specific applications, such as customer service chatbots or medical diagnosis systems. Natural Language Processing Last but certainly not least, you need to know quite a bit about natural language processing, aka NLP.

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Marktechpost

JULY 19, 2023

Large Language Models (LLMs) are becoming popular with every new update and new releases. LLMs like BERT, GPT, and PaLM have shown tremendous capabilities in the field of Natural Language Processing and Natural Language Understanding.

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Marktechpost

JULY 22, 2023

The well-known large language models such as GPT, DALLE, and BERT perform extraordinary tasks and ease lives. While GPT-3 can complete codes, answer questions like humans, and generate content given just a short natural language prompt, DALLE 2 can create images responding to a simple textual description.

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Unite.AI

FEBRUARY 23, 2024

The journey continues with “NLP and Deep Learning,” diving into the essentials of Natural Language Processing , deep learning's role in NLP, and foundational concepts of neural networks. Building a customer service chatbot using all the techniques covered in the course.

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ODSC - Open Data Science

SEPTEMBER 18, 2023

Getting started with natural language processing (NLP) is no exception, as you need to be savvy in machine learning, deep learning, language, and more. Large Language Models Finally, the course concludes with a look at large language models, such as BERT, ELMo, GPT, and ULMFiT.

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Topbots

OCTOBER 4, 2023

Here are a few examples across various domains: Natural Language Processing (NLP) : Predictive NLP models can categorize text into predefined classes (e.g., For example, large language models (LLMs) are trained by randomly replacing some of the tokens in training data with a special token, such as [MASK].

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Heartbeat

JANUARY 9, 2024

Large language models have emerged as ground-breaking technologies with revolutionary potential in the fast-developing fields of artificial intelligence (AI) and natural language processing (NLP). Open-Source Models: Open-source models are large language models made available to the public with their source code.

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Pickl AI

SEPTEMBER 21, 2023

Evolution of Language Models Early Language Models: From ELIZA to ALICE To understand the significance of ChatGPT, we must first trace the evolution of language models. These early language models laid the foundation for natural language processing but were far from the human-like conversational agents we have today.

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Heartbeat

AUGUST 2, 2023

Large language models, such as GPT-3 (Generative Pre-trained Transformer 3), BERT, XLNet, and Transformer-XL, etc., Overall, transformer architecture has revolutionized the field of natural language processing by enabling efficient and effective modeling of long-range dependencies and capturing complex contextual relationships in text.

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Snorkel AI

AUGUST 24, 2023

By unlocking the rich context hiding in unstructured data such as call transcripts, chat logs, and customer surveys, AI tools can help banks enhance complaint responses through: Chatbots that answer customer questions about complaints and provide initial support. Natural language processing to extract key information quickly.

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Snorkel AI

AUGUST 24, 2023

By unlocking the rich context hiding in unstructured data such as call transcripts, chat logs, and customer surveys, AI tools can help banks enhance complaint responses through: Chatbots that answer customer questions about complaints and provide initial support. Natural language processing to extract key information quickly.

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Large Language Models AI AI Natural Language Processing 52

Snorkel AI

AUGUST 24, 2023

By unlocking the rich context hiding in unstructured data such as call transcripts, chat logs, and customer surveys, AI tools can help banks enhance complaint responses through: Chatbots that answer customer questions about complaints and provide initial support. Natural language processing to extract key information quickly.

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Large Language Models AI AI Natural Language Processing 52

AWS Machine Learning Blog

JANUARY 19, 2024

In this post, we demonstrate how to use neural architecture search (NAS) based structural pruning to compress a fine-tuned BERT model to improve model performance and reduce inference times. First, we use an Amazon SageMaker Studio notebook to fine-tune a pre-trained BERT model on a target task using a domain-specific dataset.

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ODSC - Open Data Science

JANUARY 29, 2024

Thus while crafting clever prompts for chatbots might be part of the picture, the prompt engineer role is far more intricate. Think of them as architects of language-driven AI. BERT While technically not an LLM (pre-dates LLMs), due to its 360 million parameters vs the (supposed) 1.76

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Unite.AI

APRIL 17, 2024

In recent years, Natural Language Processing (NLP) has undergone a pivotal shift with the emergence of Large Language Models (LLMs) like OpenAI's GPT-3 and Google’s BERT. Beyond traditional search engines, these models represent a new era of intelligent Web browsing agents that go beyond simple keyword searches.

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Marktechpost

JULY 11, 2023

LLMs, the Artificial Intelligence models that are designed to process natural language and generate human-like responses, are trending. The best example is OpenAI’s ChatGPT, the well-known chatbot that does everything from content generation and code completion to question answering, just like a human.

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Marktechpost

MAY 2, 2024

Natural language processing (NLP) focuses on enabling computers to understand and generate human language, making interactions more intuitive and efficient. Recent developments in this field have significantly impacted machine translation, chatbots, and automated text analysis.

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Marktechpost

NOVEMBER 10, 2023

NLP, or Natural Language Processing, is a field of AI focusing on human-computer interaction using language. Text analysis, translation, chatbots, and sentiment analysis are just some of its many applications. NLP aims to make computers understand, interpret, and generate human language.

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AssemblyAI

MAY 3, 2023

This is heavily due to the popularization (and commercialization) of a new generation of general purpose conversational chatbots that took off at the end of 2022, with the release of ChatGPT to the public. This concept is not exclusive to natural language processing, and has also been employed in other domains.

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John Snow Labs

MAY 26, 2023

Sentence embeddings are a powerful tool in natural language processing that helps analyze and understand language. Specifically, it involves using pre-trained transformer models, such as BERT or RoBERTa, to encode text into dense vectors that capture the semantic meaning of the sentences.

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Snorkel AI

MAY 25, 2023

A brief history of large language models Large language models grew out of research and experiments with neural networks to allow computers to process natural language. In the 2010s, this research intersected with the then-bustling field of neural networks, setting the ground for the first large language model.

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Snorkel AI

MAY 25, 2023

A brief history of large language models Large language models grew out of research and experiments with neural networks to allow computers to process natural language. In the 2010s, this research intersected with the then-bustling field of neural networks, setting the ground for the first large language model.

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Applied Data Science

DECEMBER 23, 2022

In our review of 2019 we talked a lot about reinforcement learning and Generative Adversarial Networks (GANs), in 2020 we focused on Natural Language Processing (NLP) and algorithmic bias, in 202 1 Transformers stole the spotlight. The debate was on again: maybe language generation is really just a prediction task?

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AssemblyAI

SEPTEMBER 18, 2023

Original natural language processing (NLP) models were limited in their understanding of language. LLMs leverage deep learning architectures to process and understand the nuances and context of human language. Bloom Bloom is an autoregressive large language model developed by BigScience with 176B parameters.

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Pragnakalp

JANUARY 1, 2024

The transformer “requires less training time than previous recurrent neural architectures, such as long short-term memory (LSTM), and its later variation has been prevalently adopted for training large language models on large (language) datasets,” notes Wikipedia.

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