Analytics Vidhya

MARCH 30, 2024

Introduction With the advent of Large Language Models (LLMs), they have permeated numerous applications, supplanting smaller transformer models like BERT or Rule Based Models in many Natural Language Processing (NLP) tasks.

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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. Generative AI represents a significant advancement in deep learning and AI development, with some suggesting it’s a move towards developing “ strong AI.”

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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. In fact, the Generative AI market is expected to reach $36 billion by 2028 , compared to $3.7 However, advancing in this field requires a specialized AI skillset.

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Unite.AI

SEPTEMBER 25, 2023

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. Today platforms like Spotify are leveraging AI to fine-tune their users' listening experiences.

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IBM Journey to AI blog

AUGUST 1, 2023

True to their name, generative AI models generate text, images, code , or other responses based on a user’s prompt. But what makes the generative functionality of these models—and, ultimately, their benefits to the organization—possible? An open-source model, Google created BERT in 2018.

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Towards AI

OCTOBER 31, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! We’re also excited to share updates on Building LLMs for Production, now available on our own platform: Towards AI Academy.

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Marktechpost

JULY 28, 2024

The rapid advancements in Generative AI have underscored the importance of text embeddings. This extensive training allows the embeddings to capture semantic meanings effectively, enabling advanced NLP tasks. Limitations: NLP-only: Gensim focuses solely on NLP without support for image or multimodal embeddings.

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Unite.AI

MAY 29, 2024

This advancement has spurred the commercial use of generative AI in natural language processing (NLP) and computer vision, enabling automated and intelligent data extraction. Named Entity Recognition ( NER) Named entity recognition (NER), an NLP technique, identifies and categorizes key information in text.

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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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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. Conclusion By implementing SageMaker AI, Lumi has achieved significant improvements to their business. Follow him on LinkedIn.

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Topbots

APRIL 11, 2023

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. BERT by Google Summary In 2018, the Google AI team introduced a new cutting-edge model for Natural Language Processing (NLP) – BERT , or B idirectional E ncoder R epresentations from T ransformers.

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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. Its AI courses provide valuable knowledge and hands-on experience, helping learners build and optimize AI models, understand advanced AI concepts, and apply AI solutions to real-world problems.

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Marktechpost

JUNE 24, 2024

This interest is not just about the impressive capabilities of ChatGPT in generating human-like text but also about its profound implications for the workforce. These skills underscore the need for workers to adapt and develop new competencies to work effectively alongside advanced AI systems like ChatGPT.

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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). In a mere blink, AI has surged, shaping our world. The seismic impact of finetuning large language models has utterly transformed NLP, revolutionizing our technological interactions.

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Snorkel AI

DECEMBER 27, 2023

While large language models (LLMs) have claimed the spotlight since the debut of ChatGPT, BERT language models have quietly handled most enterprise natural language tasks in production. Additionally, while the data and code needed to train some of the latest generation of models is still closed-source, open source variants of BERT abound.

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IBM Journey to AI blog

JANUARY 25, 2024

This holds true in the areas of statistics, science and AI. Today, a tiny homogeneous group of people determine what data to use to train generative AI models, which is drawn from sources that greatly overrepresent English. Models created with a lack of domain expertise can lead to erroneous outputs.

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AI Weekly

JANUARY 4, 2024

Sissie Hsiao, Google Sissie Hsiao, Google's vice president and the general manager of Bard and Google Assistant. macdailynews.com The Evolution Of AI Chatbots For Finance And Accounting At the end of 2023, these key components have rapidly merged through the evolution of large language models (LLMs) like ChatGPT and others.

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Snorkel AI

DECEMBER 27, 2023

While large language models (LLMs) have claimed the spotlight since the debut of ChatGPT, BERT language models have quietly handled most enterprise natural language tasks in production. Additionally, while the data and code needed to train some of the latest generation of models is still closed-source, open source variants of BERT abound.

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Unite.AI

FEBRUARY 23, 2024

Prompt engineering is the art and science of crafting inputs (or “prompts”) to effectively guide and interact with generative AI models, particularly large language models (LLMs) like ChatGPT. The final course, “Trustworthy Generative AI,” is an 8-hour journey into ensuring reliability and trust in AI outputs.

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AWS Machine Learning Blog

FEBRUARY 6, 2024

We address this skew with generative AI models (Falcon-7B and Falcon-40B), which were prompted to generate event samples based on five examples from the training set to increase the semantic diversity and increase the sample size of labeled adverse events.

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Unite.AI

DECEMBER 4, 2023

GPT 3 and similar Large Language Models (LLM) , such as BERT , famous for its bidirectional context understanding, T-5 with its text-to-text approach, and XLNet , which combines autoregressive and autoencoding models, have all played pivotal roles in transforming the Natural Language Processing (NLP) paradigm.

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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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Towards AI

JANUARY 30, 2024

Author(s): Abhinav Kimothi Originally published on Towards AI. Being new to the world of Generative AI, one can feel a little overwhelmed by the jargon. Designed to be general-purpose, providing a foundation for various AI applications. I’ve been asked many times about common terms used in this field.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

DL2q instances are the first instances to bring Qualcomm’s artificial intelligent (AI) technology to the cloud. Model category Number of models Examples​ NLP​ 157 BERT, BART, FasterTransformer, T5, Z-code MOE Generative AI – NLP 40 LLaMA, CodeGen, GPT, OPT, BLOOM, Jais, Luminous, StarCoder, XGen Generative AI – Image 3 Stable diffusion v1.5

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John Snow Labs

MARCH 4, 2025

Contextual Entity Ruler in Spark NLP refines entity recognition by applying context-aware rules to detected entities. Whether youre working with clinical NLP, financial documents, or any domain where accuracy matters, this approach can significantly enhance your entity extraction pipeline. What is NER?

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ODSC - Open Data Science

MARCH 10, 2025

Researchers and practitioners explored complex architectures, from transformers to reinforcement learning , leading to a surge in sessions on natural language processing (NLP) and computervision. Starting with BERT and accelerating with the launch of GPT-3 , conference sessions on LLMs and transformers skyrocketed.

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ODSC - Open Data Science

MARCH 12, 2025

The Boom of Generative AI and Large Language Models(LLMs) 20182020: NLP was gaining traction, with a focus on word embeddings, BERT, and sentiment analysis. 20212022: Transformer-based models took center stage, with GPT-3 driving conversations around text generation.

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Marktechpost

DECEMBER 5, 2023

Small Language Models, which are compact generative AI models, are distinguished by their small neural network size, number of parameters, and volume of training data. Examples of Small Language Models DistilBERT is a quicker, more compact version of BERT that transforms NLP by preserving performance without sacrificing efficiency.

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AWS Machine Learning Blog

AUGUST 30, 2023

To solve this problem, we propose the use of generative AI, a type of AI that can create new content and ideas, including conversations, stories, images, videos, and music. This solution involves fine-tuning the FLAN-T5 XL model, which is an enhanced version of T5 (Text-to-Text Transfer Transformer) general-purpose LLMs.

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John Snow Labs

SEPTEMBER 26, 2024

Traditional Natural Language Processing (NLP) has long relied on powerful Python libraries such as SpaCy and NLTK, which have proven effective for a wide range of text-processing tasks. Building on this foundation, we will then venture into the integration of Generative AI (GenAI) frameworks into these NLP pipelines.

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Unite.AI

AUGUST 1, 2023

Zero and Few-Shot Learning: Optimizing with Examples Generative Pretrained Transformers (GPT-3) marked an important turning point in the development of Generative AI models, as it introduced the concept of ‘ few-shot learning.'

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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. To get you started on your journey, we’ve released a new on-demand Introduction to NLP course. Here are some more details.

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NVIDIA

FEBRUARY 11, 2025

Like the prolific jazz trumpeter and composer, researchers have been generating AI models at a feverish pace, exploring new architectures and use cases. A year after the group defined foundation models, other tech watchers coined a related term generative AI.

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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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AWS Machine Learning Blog

OCTOBER 23, 2023

Given this mission, Talent.com and AWS joined forces to create a job recommendation engine using state-of-the-art natural language processing (NLP) and deep learning model training techniques with Amazon SageMaker to provide an unrivaled experience for job seekers.

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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). In 2023, we witnessed the substantial transformation of AI, marking it as the ‘year of AI.’

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AssemblyAI

SEPTEMBER 18, 2023

These models aren't just large in terms of size—they're also massive in their capacity to understand human prompts and generate vast amounts of original text. Original natural language processing (NLP) models were limited in their understanding of language. Read Introduction to Large Language Models for Generative AI.

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