Unite.AI

JULY 5, 2023

Their latest large language model (LLM) MPT-30B is making waves across the AI community. The MPT-30B: A Powerful LLM That Exceeds GPT-3 MPT-30B is an open-source and commercially licensed decoder-based LLM that is more powerful than GPT-3-175B with only 17% of GPT-3 parameters, i.e., 30B.

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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. Using their extensive training data, LLM-based agents deeply understand language patterns, information, and contextual nuances.

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Analytics Vidhya

MAY 20, 2024

Introduction Artificial intelligence has made tremendous strides in Natural Language Processing (NLP) by developing Large Language Models (LLMs). These models, like GPT-3 and GPT-4, can generate highly coherent and contextually relevant text.

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Analytics Vidhya

JANUARY 24, 2024

Introduction Welcome to the world of Large Language Models (LLM). However, in 2018, the “Universal Language Model Fine-tuning for Text Classification” paper changed the entire landscape of Natural Language Processing (NLP).

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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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Analytics Vidhya

JUNE 13, 2024

Introduction Large language models (LLMs) have revolutionized natural language processing (NLP), enabling various applications, from conversational assistants to content generation and analysis.

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Unite.AI

SEPTEMBER 13, 2024

As the demand for large language models (LLMs) continues to rise, ensuring fast, efficient, and scalable inference has become more crucial than ever. NVIDIA's TensorRT-LLM steps in to address this challenge by providing a set of powerful tools and optimizations specifically designed for LLM inference.

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Marktechpost

APRIL 10, 2024

For too long, the world of natural language processing has been dominated by models that primarily cater to the English language. However, a groundbreaking new development is set to challenge this status quo and usher in a more inclusive era of language models – the Chinese Tiny LLM (CT-LLM).

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Marktechpost

SEPTEMBER 20, 2024

Large language models (LLMs) have made significant leaps in natural language processing, demonstrating remarkable generalization capabilities across diverse tasks. This limitation poses a significant hurdle for AI-driven applications requiring structured LLM outputs integrated into their data streams.

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LLM Large Language Models NLP Natural Language Processing 119

Marktechpost

NOVEMBER 1, 2024

Natural Language Processing (NLP) focuses on building computational models to interpret and generate human language. However, NLP for Hindi still needs to be improved, mainly due to a need for high-quality Hindi data and language-specific models.

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Large Language Models NLP Natural Language Processing Artificial Intelligence 128

Marktechpost

SEPTEMBER 27, 2024

Current document processing methods often rely on manual techniques or basic automation that need more sophistication to handle unstructured data effectively. Natural language processing (NLP) tools may offer some capabilities but fall short when processing complex documents that require higher-level understanding.

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Marktechpost

JULY 3, 2024

In the dynamic world of technology, Large Language Models (LLMs) have become pivotal across various industries. Their adeptness at natural language processing, content generation, and data analysis has paved the way for numerous applications.

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Unite.AI

SEPTEMBER 7, 2023

Today, there are numerous proprietary and open-source LLMs in the market that are revolutionizing industries and bringing transformative changes in how businesses function. Despite rapid transformation, there are numerous LLM vulnerabilities and shortcomings that must be addressed.

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SAS Software

SEPTEMBER 6, 2024

The post Three ways NLP can be used to identify LLM-related private data leakage and reduce risk appeared first on SAS Blogs. We often hear about cyberattacks, hackers, ransomware, and other nefarious deeds in the news, but not all data breaches are caused by third parties.

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Marktechpost

NOVEMBER 14, 2023

Medical data extraction, analysis, and interpretation from unstructured clinical literature are included in the emerging discipline of clinical natural language processing (NLP). Even with its importance, particular difficulties arise while developing methodologies for clinical NLP.

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Marktechpost

SEPTEMBER 8, 2024

Large language models (LLMs) have revolutionized natural language processing (NLP), particularly for English and other data-rich languages. However, this rapid advancement has created a significant development gap for underrepresented languages, with Cantonese being a prime example.

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Marktechpost

MAY 25, 2024

Large Language Models (LLMs) have driven remarkable advancements across various Natural Language Processing (NLP) tasks. The progression in this field continues to transform how machines comprehend and process language, opening new avenues for research and development. Check out the Paper.

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Analytics Vidhya

MAY 6, 2023

Introduction Large Language Models (LLMs) are now widely used in a variety of applications, like machine translation, chat bots, text summarization , sentiment analysis , making advancements in the field of natural language processing (NLP).

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Unite.AI

NOVEMBER 29, 2023

Furthermore, developers have demonstrated that these smaller LLM frameworks can be trained further using a proprietary-models based dSFT or Distilled Supervised Fine-Tuning approach, that uses the output from an effective teacher model as supervised data for the student model in an attempt to boost the accuracy.

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Marktechpost

JULY 26, 2024

The inherent complexity of SQL syntax and the intricacies involved in database schema understanding make this a significant problem in natural language processing (NLP) and database management. Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Gr oup.

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Marktechpost

FEBRUARY 29, 2024

Large Language Models (LLMs) have transformed natural language processing, offering user modeling and personalization opportunities. Directly fine-tuning LLMs with interaction histories faces hurdles like sparse data, multimodal interactions, and lengthy sequences.

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Marktechpost

JUNE 21, 2024

Biomedical natural language processing (NLP) focuses on developing machine learning models to interpret and analyze medical texts. A significant challenge in biomedical NLP is ensuring that language models are robust and accurate when dealing with diverse and context-specific medical terminologies.

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Marktechpost

OCTOBER 1, 2024

Natural language processing (NLP) has experienced a surge in progress with the emergence of large language models (LLMs), which are utilized in various applications such as text generation, translation, and conversational agents.

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The MLOps Blog

MARCH 23, 2023

NLP models in commercial applications such as text generation systems have experienced great interest among the user. These models have achieved various groundbreaking results in many NLP tasks like question-answering, summarization, language translation, classification, paraphrasing, et cetera. For instance, a 1.5B

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Unite.AI

JANUARY 10, 2024

By integrating the sophisticated language processing capabilities of models like ChatGPT with the versatile and widely-used Scikit-learn framework, Scikit-LLM offers an unmatched arsenal for delving into the complexities of textual data. Why Scikit-LLM? and the user-friendly environment of Scikit-learn.

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Marktechpost

MARCH 19, 2024

IBM researchers have introduced LAB (Large-scale Alignment for chatbots) to address the scalability challenges encountered during the instruction-tuning phase of training large language models (LLMs). In conclusion, the paper introduces LAB as a novel methodology to address the scalability challenges in instruction tuning for LLMs.

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Explosion

MAY 17, 2023

A lot of people are building truly new things with Large Language Models (LLMs), like wild interactive fiction experiences that weren’t possible before. But if you’re working on the same sort of Natural Language Processing (NLP) problems that businesses have been trying to solve for a long time, what’s the best way to use them?

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Snorkel AI

OCTOBER 9, 2024

We’re excited to announce new natural language processing (NLP) features in Snorkel Flow’s 2024.R3 NLP is vital for our customers—it’s key to extracting insights from unstructured and structured text, and the first step to unlocking enterprise AI at scale. Building the future of NLP with Snorkel Flow With the 2024.R3

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Marktechpost

MAY 17, 2024

Natural Language Processing (NLP) is a cutting-edge field that enables machines to understand, interpret, & generate human language. It has applications in various domains, such as language translation, text summarization, sentiment analysis, and the development of conversational agents.

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Artificial Corner

JULY 30, 2023

So that’s why I tried in this article to explain LLM in simple or to say general language. Photo by Shubham Dhage on Unsplash Introduction Large language Models (LLMs) are a subset of Deep Learning. No training examples are needed in LLM Development but it’s needed in Traditional Development.

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Marktechpost

NOVEMBER 9, 2023

The biggest advancement in the field of Artificial Intelligence is the introduction of Large Language Models (LLMs). These Natural Language Processing (NLP) based models handle large and complicated datasets, which causes them to face a unique challenge in the finance industry.

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Marktechpost

MARCH 6, 2024

The natural language processing (NLP) field has witnessed significant advancements with the emergence of Large Language Models (LLMs) like GPT and LLaMA. These models have become essential tools for various tasks, prompting a growing need for proprietary LLMs among individuals and organizations.

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Marktechpost

FEBRUARY 29, 2024

Large Language Models (LLMs) have extended their capabilities to different areas, including healthcare, finance, education, entertainment, etc. These models have utilized the power of Natural Language Processing (NLP), Natural Language Generation (NLG), and Computer Vision to dive into almost every industry.

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Marktechpost

AUGUST 15, 2024

Biological data, such as DNA, RNA, and protein sequences, are fundamentally different from natural language text, yet they share sequential characteristics that make them amenable to similar processing techniques.

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Marktechpost

JULY 12, 2024

Natural Language Processing (NLP) focuses on the interaction between computers and humans through natural language. It encompasses tasks such as translation, sentiment analysis, and question answering, utilizing large language models (LLMs) to achieve high accuracy and performance.

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Marktechpost

SEPTEMBER 6, 2024

Large-scale language models have become integral to natural language processing (NLP) advancements, transforming how machines understand and generate human language. A key challenge facing the NLP community is the high computational cost of training and deploying state-of-the-art language models.

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Marktechpost

JUNE 13, 2024

Transformer-based generative Large Language Models (LLMs) have shown considerable strength in a broad range of Natural Language Processing (NLP) tasks. For this, top AI firms like OpenAI, Google, and Baidu offer a language model-as-a-service (LMaaS) by granting access to their LLMs through APIs.

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