Unite.AI

NOVEMBER 11, 2024

Machines are demonstrating remarkable capabilities as Artificial Intelligence (AI) advances, particularly with Large Language Models (LLMs). They process and generate text that mimics human communication. At the leading edge of Natural Language Processing (NLP) , models like GPT-4 are trained on vast datasets.

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AI Weekly

JULY 27, 2023

techcrunch.com The Essential Artificial Intelligence Glossary for Marketers (90+ Terms) BERT - Bidirectional Encoder Representations from Transformers (BERT) is Google’s deep learning model designed explicitly for natural language processing tasks like answering questions, analyzing sentiment, and translation.

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Marktechpost

MAY 30, 2024

Google plays a crucial role in advancing AI by developing cutting-edge technologies and tools like TensorFlow, Vertex AI, and BERT. Natural Language Processing on Google Cloud This course introduces Google Cloud products and solutions for solving NLP problems.

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Marktechpost

MAY 27, 2024

Knowledge-intensive Natural Language Processing (NLP) involves tasks requiring deep understanding and manipulation of extensive factual information. Existing research includes frameworks like REALM and ORQA, which integrate pre-trained neural language models with differentiable retrievers for enhanced knowledge access.

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Unite.AI

MARCH 24, 2024

In a significant leap forward for artificial intelligence (AI), a team from the University of Geneva (UNIGE) has successfully developed a model that emulates a uniquely human trait: performing tasks based on verbal or written instructions and subsequently communicating them to others.

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Towards AI

OCTOBER 19, 2024

Photo by Amr Taha™ on Unsplash In the realm of artificial intelligence, the emergence of transformer models has revolutionized natural language processing (NLP). In this guide, we will explore how to fine-tune BERT, a model with 110 million parameters, specifically for the task of phishing URL detection.

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Marktechpost

APRIL 16, 2024

In recent years, there has been a great inclination toward Large Language Models (LLMs) due to their amazing text generation, analysis, and classification capabilities. These models use billions of parameters to execute a variety of Natural Language Processing (NLP) tasks.

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Analytics Vidhya

AUGUST 29, 2023

Introduction Embark on a journey through the evolution of artificial intelligence and the astounding strides made in Natural Language Processing (NLP). The seismic impact of finetuning large language models has utterly transformed NLP, revolutionizing our technological interactions.

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Marktechpost

JANUARY 10, 2024

BERT is a language model which was released by Google in 2018. However, in the past half a decade, many significant advancements have been made with other types of architectures and training configurations that have yet to be incorporated into BERT. BERT-Base reached an average GLUE score of 83.2% hours compared to 23.35

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Unite.AI

JULY 11, 2023

The Artificial Intelligence (AI) ecosystem has evolved rapidly in the last five years, with Generative AI (GAI) leading this evolution. What is Generative Artificial Intelligence, how it works, what its applications are, and how it differs from standard machine learning (ML) techniques. billion in 2023.

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Marktechpost

SEPTEMBER 14, 2024

Researchers have focused on developing and building models to process and compare human language in natural language processing efficiently. This technology is crucial for semantic search, clustering, and natural language inference tasks.

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Marktechpost

AUGUST 7, 2023

Language model pretraining has significantly advanced the field of Natural Language Processing (NLP) and Natural Language Understanding (NLU). Models like GPT, BERT, and PaLM are getting popular for all the good reasons. Models like GPT, BERT, and PaLM are getting popular for all the good reasons.

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Marktechpost

MARCH 3, 2025

Encoder models like BERT and RoBERTa have long been cornerstones of natural language processing (NLP), powering tasks such as text classification, retrieval, and toxicity detection. For example, GTEs contrastive learning boosts retrieval performance but cannot compensate for BERTs obsolete embeddings.

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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. Check out the Paper and Project.

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Unite.AI

FEBRUARY 7, 2024

This is why Machine Learning Operations (MLOps) has emerged as a paradigm to offer scalable and measurable values to Artificial Intelligence (AI) driven businesses. LLMs are deep neural networks that can generate natural language texts for various purposes, such as answering questions, summarizing documents, or writing code.

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Marktechpost

JULY 19, 2023

Examples of text-only LLMs include GPT-3 , BERT , RoBERTa , etc. Why is there a need for Multimodal Language Models The text-only LLMs like GPT-3 and BERT have a wide range of applications, such as writing articles, composing emails, and coding.

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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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Unite.AI

SEPTEMBER 18, 2023

With the widespread attention, and potential applications of blockchain and artificial intelligence technologies, the privacy protection techniques that arise as a direct result of integration of the two technologies is gaining notable significance.

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Unite.AI

DECEMBER 4, 2023

In the ever-evolving domain of Artificial Intelligence (AI), where models like GPT-3 have been dominant for a long time, a silent but groundbreaking shift is taking place. Small Language Models (SLM) are emerging and challenging the prevailing narrative of their larger counterparts.

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AWS Machine Learning Blog

APRIL 4, 2025

To achieve this, Lumi developed a classification model based on BERT (Bidirectional Encoder Representations from Transformers) , a state-of-the-art natural language processing (NLP) technique. They have seen an increase of 56% transaction classification accuracy after moving to the new BERT based model.

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Marktechpost

JANUARY 3, 2024

Natural Language Processing (NLP) tasks extensively make use of text embeddings. Text embeddings encode semantic information contained in text by acting as vector representations of natural language. These techniques, however, are unable to capture the rich contextual information included in real language fully.

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Pickl AI

APRIL 6, 2025

Summary: Deep Learning vs Neural Network is a common comparison in the field of artificial intelligence, as the two terms are often used interchangeably. Use Cases: Natural Language Processing (NLP) (language modeling, machine translation, sentiment analysis), speech recognition, time series prediction, video analysis.

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Unite.AI

JUNE 5, 2024

Artificial Intelligence (AI) has seen tremendous growth, transforming industries from healthcare to finance. Across sectors like healthcare, finance, autonomous vehicles , and natural language processing , the demand for efficient AI models is increasing. It uses high precision (e.g.,

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ODSC - Open Data Science

JUNE 9, 2023

ELIZA was built by Joseph Weizenbaum at the MIT Artificial Intelligence Laboratory and was designed to imitate Rogerian psychotherapists. Once a set of word vectors has been learned, they can be used in various natural language processing (NLP) tasks such as text classification, language translation, and question answering.

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Marktechpost

MAY 5, 2024

However, the computational complexity associated with these mechanisms scales quadratically with sequence length, which becomes a significant bottleneck when managing long-context tasks such as genomics and natural language processing. Compared to the BERT-base, the Orchid-BERT-base has 30% fewer parameters yet achieves a 1.0-point

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Probably Approximately a Scientific Blog

JANUARY 12, 2021

Figure 1: adversarial examples in computer vision (left) and natural language processing tasks (right). This is generally a positive thing, but it sometimes over-generalizes , leading to examples such as this: Figure 4: BERT guesses that the masked token should be a color, but fails to predict the correct color.

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Unite.AI

SEPTEMBER 25, 2023

Creating music using artificial intelligence began several decades ago. However, as technology advanced, so did the complexity and capabilities of AI music generators, paving the way for deep learning and Natural Language Processing (NLP) to play pivotal roles in this tech.

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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. T5 standardizes NLP tasks as text-to-text, while RoBERTa enhances BERT’s training process for superior performance.

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Marktechpost

DECEMBER 5, 2023

Large Language Models (LLMs), like GPT, PaLM, LLaMA, etc., Their ability to utilize the strength of Natural Language Processing, Generation, and Understanding by generating content, answering questions, summarizing text, and so on have made LLMs the talk of the town in the last few months.

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Flipboard

DECEMBER 6, 2023

Tools like LangChain , combined with a large language model (LLM) powered by Amazon Bedrock or Amazon SageMaker JumpStart , simplify the implementation process. Tools like LangChain , combined with a large language model (LLM) powered by Amazon Bedrock or Amazon SageMaker JumpStart , simplify the implementation process.

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Unite.AI

AUGUST 2, 2023

Self Supervised Learning models build representations of the training data using human annotated labels, and it’s one of the major reasons behind the advancement of the NLP or Natural Language Processing , and the Computer Vision technology.

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Marktechpost

JULY 4, 2023

Natural language processing (NLP) activities, including speech-to-text, sentiment analysis, text summarization, spell-checking, token categorization, etc., rely on Language Models as their foundation. Unigrams, N-grams, exponential, and neural networks are valid forms for the Language Model.

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Unite.AI

APRIL 15, 2024

When it comes to natural language processing (NLP) and information retrieval, the ability to efficiently and accurately retrieve relevant information is paramount. ColBERT: Efficient and Effective Late Interaction One of the standout models in the realm of reranking is ColBERT ( Contextualized Late Interaction over BERT ).

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IBM Journey to AI blog

FEBRUARY 13, 2024

Generative AI ( artificial intelligence ) promises a similar leap in productivity and the emergence of new modes of working and creating. They are now capable of natural language processing ( NLP ), grasping context and exhibiting elements of creativity.

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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. NLP aims to make computers understand, interpret, and generate human language. This process enhances data diversity. Prepare a novel dataset (Dn) with only a few labeled samples.

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IBM Journey to AI blog

AUGUST 1, 2023

The term “foundation model” was coined by the Stanford Institute for Human-Centered Artificial Intelligence in 2021. A foundation model is built on a neural network model architecture to process information much like the human brain does. An open-source model, Google created BERT in 2018.

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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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