AssemblyAI

SEPTEMBER 18, 2023

However, among all the modern-day AI innovations, one breakthrough has the potential to make the most impact: large language models (LLMs). Large language models can be an intimidating topic to explore, especially if you don't have the right foundational understanding. What Is a Large Language Model?

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Unite.AI

JUNE 20, 2024

Large Language Models (LLMs) are capable of understanding and generating human-like text, making them invaluable for a wide range of applications, such as chatbots, content generation, and language translation. Large Language Models (LLMs) are a type of neural network model trained on vast amounts of text data.

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Unite.AI

MAY 29, 2024

Unlocking Unstructured Data with LLMs Leveraging large language models (LLMs) for unstructured data extraction is a compelling solution with distinct advantages that address critical challenges. Context-Aware Data Extraction LLMs possess strong contextual understanding, honed through extensive training on large datasets.

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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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Marktechpost

DECEMBER 13, 2023

The well-known Large Language Models (LLMs) like GPT, BERT, PaLM, and LLaMA have brought in some great advancements in Natural Language Processing (NLP) and Natural Language Generation (NLG). LLMs are becoming increasingly popular for graph-based applications.

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AssemblyAI

MAY 23, 2023

ChatGPT is part of a group of AI systems called Large Language Models (LLMs) , which excel in various cognitive tasks involving natural language. A language model can be fine-tuned on medical documents for specialized tasks in the medical field. A simple artificial neural network with three layers.

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Marktechpost

APRIL 6, 2024

Transformers have transformed the field of NLP over the last few years, with LLMs like OpenAI’s GPT series, BERT, and Claude Series, etc. The introduction of the transformer architecture has provided a new paradigm for building models that understand and generate human language with unprecedented accuracy and fluency.

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Artificial Corner

JULY 30, 2023

In this world of complex terminologies, someone who wants to explain Large Language Models (LLMs) to some non-tech guy is a difficult task. So that’s why I tried in this article to explain LLM in simple or to say general language. A transformer architecture is typically implemented as a Large language model.

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Unite.AI

FEBRUARY 7, 2024

But more than MLOps is needed for a new type of ML model called Large Language Models (LLMs). 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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Towards AI

JUNE 12, 2024

Photo by david clarke on Unsplash The most recent breakthroughs in language models have been the use of neural network architectures to represent text. There is very little contention that large language models have evolved very rapidly since 2018. The story starts with word embedding.

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AWS Machine Learning Blog

FEBRUARY 6, 2024

Transformers, BERT, and GPT The transformer architecture is a neural network architecture that is used for natural language processing (NLP) tasks. BERT can be fine-tuned for a variety of NLP tasks, including question answering, natural language inference, and sentiment analysis.

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Marktechpost

JULY 4, 2023

Computer programs called large language models provide software with novel options for analyzing and creating text. It is not uncommon for large language models to be trained using petabytes or more of text data, making them tens of terabytes in size.

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Unite.AI

NOVEMBER 6, 2023

Adaptability to Unseen Data: These models may not adapt well to real-world data that wasn’t part of their training data. Neural Network: Moving from Machine Learning to Deep Learning & Beyond Neural network (NN) models are far more complicated than traditional Machine Learning models.

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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. Let’s break down the key components: Model Definition TensorRT-LLM allows you to define LLMs using a simple Python API.

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Unite.AI

AUGUST 8, 2023

The Technologies Behind Generative Models Generative models owe their existence to deep neural networks, sophisticated structures designed to mimic the human brain's functionality. By capturing and processing multifaceted variations in data, these networks serve as the backbone of numerous generative models.

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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. What are Large Language Models and Why are They Important? Techniques like Word2Vec and BERT create embedding models which can be reused.

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Unite.AI

APRIL 30, 2024

It includes deciphering neural network layers , feature extraction methods, and decision-making pathways. The Inner Dialogue: How AI Systems Think AI systems, such as chatbots and virtual assistants, simulate a thought process that involves complex modeling and learning mechanisms.

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Unite.AI

AUGUST 1, 2023

The spotlight is also on DALL-E, an AI model that crafts images from textual inputs. One such model that has garnered considerable attention is OpenAI's ChatGPT , a shining exemplar in the realm of Large Language Models. Prompt 1 : “Tell me about Convolutional Neural Networks.”

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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. The task assigned to the BERT PLM can be a text-based task such as sentiment analysis, text classification, or Q&A.

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AWS Machine Learning Blog

JUNE 18, 2024

With more access to vast amounts of reports, books, articles, journals, and research papers than ever before, swiftly identifying desired information in large bodies of text is becoming invaluable. This makes adopting and scaling these approaches burdensome for many applications.

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Marktechpost

APRIL 21, 2024

Transformer Models and BERT Model : In this course, participants delve into the specifics of Transformer models and the Bidirectional Encoder Representations from Transformers (BERT) model. This course is ideal for those interested in the latest in natural language processing technologies.

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Towards AI

MARCH 12, 2025

🔎 Decoding LLM Pipeline Step 1: Input Processing & Tokenization 🔹 From Raw Text to Model-Ready Input In my previous post, I laid out the 8-step LLM pipeline, decoding how large language models (LLMs) process language behind the scenes. Tokens: Fundamental unit that neural networks process.

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AssemblyAI

JUNE 27, 2023

With various foundational ideas from large language models and text-to-image generation being adapted and incorporated into the audio modality , the latest AI-powered audio-generative systems are reaching a new unprecedented level of quality. At its core, it's an end-to-end neural network-based approach.

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Unite.AI

DECEMBER 13, 2024

Large language models (LLMs) , such as GPT-4 , BERT , Llama , etc., Technologies such as Recurrent Neural Networks (RNNs) and transformers introduced the ability to process sequences of data and paved the way for more adaptive AI. With advancements in machine learning, dynamic memory became possible.

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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

JULY 3, 2023

The excellent technological advancements, particularly in the areas of Large Language Models (LLMs), LangChain, and Vector Databases, are responsible for this remarkable development. Large Language Models The development of Large Language Models (LLMs) represents a huge step forward for Artificial Intelligence.

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AWS Machine Learning Blog

JUNE 7, 2023

Training large language models (LLMs) with billions of parameters can be challenging. In addition to designing the model architecture, researchers need to set up state-of-the-art training techniques for distributed training like mixed precision support, gradient accumulation, and checkpointing. billion parameters).

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NVIDIA

FEBRUARY 11, 2025

In a 2021 paper, researchers reported that foundation models are finding a wide array of uses. They said transformer models , large language models (LLMs), vision language models (VLMs) and other neural networks still being built are part of an important new category they dubbed foundation models.

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ODSC - Open Data Science

MARCH 10, 2025

By 2017, deep learning began to make waves, driven by breakthroughs in neural networks and the release of frameworks like TensorFlow. Sessions on convolutional neural networks (CNNs) and recurrent neural networks (RNNs) started gaining popularity, marking the beginning of data sciences shift toward AI-driven methods.

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Marktechpost

MARCH 25, 2024

Large Language Models (LLMs) like ChatGPT, Google’s Bert, Gemini, Claude Models, and others have emerged as central figures, redefining our interaction with digital interfaces. What are Large Language Models?

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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. It begins by emphasizing the importance of understanding how these models respond to natural language prompts.

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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. More recent frameworks like LLaMA and BLIP leverage tailored instruction data to devise efficient strategies that demonstrate the potent capabilities of the model.

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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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Viso.ai

JULY 18, 2024

What are Large Language Models (LLMs)? In generative AI, human language is perceived as a difficult data type. If a computer program is trained on enough data such that it can analyze, understand, and generate responses in natural language and other forms of content, it is called a Large Language Model (LLM).

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Unite.AI

AUGUST 28, 2023

Neural Networks & Deep Learning : Neural networks marked a turning point, mimicking human brain functions and evolving through experience. Transformers and Advanced NLP Models : The introduction of transformer architectures revolutionized the NLP landscape.

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AWS Machine Learning Blog

AUGUST 7, 2023

Part 2 will delve into the productionized solution, explaining the design decisions, data flow, and illustration of the model training and deployment architecture. The solution was to find and fine-tune an LLM to classify toxic language. Thus the basis of the transformer model was born.

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Heartbeat

MAY 29, 2023

LLMs are one of the most exciting advancements in natural language processing (NLP). This technique is commonly used in neural network-based models such as BERT, where it helps to handle out-of-vocabulary words. Stacking can help to combine the strengths of different models and improve their performance.

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