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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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. Typically, the generative AI model provides a prompt describing the desired data, and the ensuing response contains the extracted data.

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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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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.

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ODSC - Open Data Science

JUNE 9, 2023

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. This allows BERT to learn a deeper sense of the context in which words appear. or ChatGPT (2022) ChatGPT is also known as GPT-3.5

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Marktechpost

APRIL 21, 2024

Introduction to Generative AI: This course provides an introductory overview of Generative AI, explaining what it is and how it differs from traditional machine learning methods. This is crucial for ensuring AI technology is used in a way that is ethical and beneficial to society.

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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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Unite.AI

NOVEMBER 6, 2023

In recent years, Generative AI has shown promising results in solving complex AI tasks. Modern AI models like ChatGPT , Bard , LLaMA , DALL-E.3 3 , and SAM have showcased remarkable capabilities in solving multidisciplinary problems like visual question answering, segmentation, reasoning, and content generation.

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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

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. But what exactly is prompt engineering, and why has it become such a buzzword in the tech community?

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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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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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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

MAY 3, 2023

The core process is a general technique known as self-supervised learning , a learning paradigm that leverages the inherent structure of the data itself to generate labels for training. This concept is not exclusive to natural language processing, and has also been employed in other domains.

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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. The real game-changer, however, was the rise of Large Language Models (LLMs).

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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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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

APRIL 26, 2024

The advancements in large language models have significantly accelerated the development of natural language processing , or NLP. These extend far beyond the traditional text-based processing of LLMs to include multimodal interactions.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

With eight Qualcomm AI 100 Standard accelerators and 128 GiB of total accelerator memory, customers can also use DL2q instances to run popular generative AI applications, such as content generation, text summarization, and virtual assistants, as well as classic AI applications for natural language processing and computer vision.

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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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AWS Machine Learning Blog

AUGUST 30, 2023

It enables translation of reports into human readable language, thereby alleviating the patients’ burden of reading through lengthy and obscure reports. 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.

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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. Deep learning techniques can be used to automate processes that ordinarily require human intellect, such as text-to-sound transcription or the description of photographs.

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AWS Machine Learning Blog

JUNE 18, 2024

Traditional neural network models like RNNs and LSTMs and more modern transformer-based models like BERT for NER require costly fine-tuning on labeled data for every custom entity type. About the Authors Sujitha Martin is an Applied Scientist in the Generative AI Innovation Center (GAIIC).

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Large Language Models Natural Language Processing LLM Computer Vision 120

Marktechpost

JULY 22, 2024

Large Language Models (LLMs) have revolutionized natural language processing, demonstrating remarkable capabilities in various applications. Transformer architecture has emerged as a major leap in natural language processing, significantly outperforming earlier recurrent neural networks.

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Large Language Models Neural Network Natural Language Processing LLM 124

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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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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AWS Machine Learning Blog

JANUARY 31, 2024

Embeddings play a key role in natural language processing (NLP) and machine learning (ML). Text embedding refers to the process of transforming text into numerical representations that reside in a high-dimensional vector space. He is deeply passionate about exploring the possibilities of generative AI.

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Topbots

OCTOBER 4, 2023

Generated with Bing and edited with Photoshop Predictive AI has been driving companies’ ROI for decades through advanced recommendation algorithms, risk assessment models, and fraud detection tools. However, the recent surge in generative AI has made it the new hot topic. a social media post or product description).

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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. Want to dive deeper?

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Flipboard

JULY 4, 2023

Famous LLMs like GPT, BERT, PaLM, and LLaMa are revolutionizing the AI industry by imitating humans. MongoDB – MongoDB’s Atlas Vector Search feature is a significant advancement in the integration of generative AI and semantic search into applications.

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John Snow Labs

MARCH 4, 2025

NER is used in many fields of Natural Language Processing (NLP), and it can help to answer many real-world questions, such as: Which companies were mentioned in the news article? What is NER? Which tests applied to a patient (clinical reports)?

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AWS Machine Learning Blog

JUNE 25, 2024

Businesses can use LLMs to gain valuable insights, streamline processes, and deliver enhanced customer experiences. With Amazon Bedrock, developers can experiment, evaluate, and deploy generative AI applications without worrying about infrastructure management. Particularly beneficial if you don’t have much labeled data.

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AWS Machine Learning Blog

APRIL 3, 2024

Search engines and recommendation systems powered by generative AI can improve the product search experience exponentially by understanding natural language queries and returning more accurate results. He specializes in Generative AI, Artificial Intelligence, Machine Learning, and System Design.

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Snorkel AI

MARCH 1, 2023

Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning. This process results in generalized models capable of a wide variety of tasks, such as image classification, natural language processing, and question-answering, with remarkable accuracy.

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ODSC - Open Data Science

NOVEMBER 8, 2023

Generative AI is a new field. Over the past year, new terms, developments, algorithms, tools, and frameworks have emerged to help data scientists and those working with AI develop whatever they desire. The generative model then generates the output text, taking into account both the input text and the retrieved documents.

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