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. Both BERT and GPT are based on the Transformer architecture. 2013 Word2Vec is a neural network model that uses n-grams by training on context windows of words.

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BERT Neural Network Natural Language Processing NLP 104

Unite.AI

JULY 23, 2024

By leveraging advances in artificial intelligence (AI) and neuroscience, researchers are developing systems that can translate the complex signals produced by our brains into understandable information, such as text or images. These patterns are then decoded using deep neural networks to reconstruct the perceived images.

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Convolutional Neural Networks Neural Network Artificial Intelligence Artificial Intelligence 313

AssemblyAI

MAY 3, 2023

These architectures are based on artificial neural networks , which are computational models loosely inspired by the structure and functioning of biological neural networks, such as those in the human brain. A simple artificial neural network consisting of three layers.

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Large Language Models Neural Network LLM ChatGPT 363

Unite.AI

APRIL 30, 2024

It includes deciphering neural network layers , feature extraction methods, and decision-making pathways. These systems rely heavily on neural networks to process vast amounts of information. During training, neural networks learn patterns from extensive datasets.

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Chatbots Neural Network BERT OpenAI 201

Unite.AI

NOVEMBER 6, 2023

Neural Network: Moving from Machine Learning to Deep Learning & Beyond Neural network (NN) models are far more complicated than traditional Machine Learning models. Advances in neural network techniques have formed the basis for transitioning from machine learning to deep learning.

Machine Learning 201

Machine Learning Neural Network Deep Learning Convolutional Neural Networks 201

Unite.AI

DECEMBER 13, 2024

Large language models (LLMs) , such as GPT-4 , BERT , Llama , etc., Once an interaction ends, all prior information is lost, requiring users to start anew with each use. Once an interaction ends, all prior information is lost, requiring users to start anew with each use.

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LLM Neural Network Chatbots AI 246

Flipboard

MARCH 27, 2023

Project Structure Accelerating Convolutional Neural Networks Parsing Command Line Arguments and Running a Model Evaluating Convolutional Neural Networks Accelerating Vision Transformers Evaluating Vision Transformers Accelerating BERT Evaluating BERT Miscellaneous Summary Citation Information What’s New in PyTorch 2.0?

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Neural Network Convolutional Neural Networks BERT Deep Learning 158

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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BERT Automation Neural Network Machine Learning 114

AssemblyAI

JUNE 27, 2023

Audio signals can be represented as waveforms , possessing specific characteristics such as frequency, amplitude, and phase , whose different combinations can encode various types of information like pitch and loudness in sound. Map a prompt , a description of the desired audio qualities and its content, to a generated waveform output.

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Generative AI BERT Neural Network Deep Learning 298

Unite.AI

AUGUST 1, 2023

Prompt 1 : “Tell me about Convolutional Neural Networks.” ” Response 1 : “Convolutional Neural Networks (CNNs) are multi-layer perceptron networks that consist of fully connected layers and pooling layers. They are commonly used in image recognition tasks. .”

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Prompt Engineering Prompt Engineer ChatGPT Convolutional Neural Networks 246

Unite.AI

FEBRUARY 7, 2024

LLMs are deep neural networks that can generate natural language texts for various purposes, such as answering questions, summarizing documents, or writing code. LLMs, such as GPT-4 , BERT , and T5 , are very powerful and versatile in Natural Language Processing (NLP).

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Machine Learning Large Language Models LLM BERT 288

Unite.AI

SEPTEMBER 18, 2023

To prevent these scenarios, protection of data, user assets, and identity information has been a major focus of the blockchain security research community, as to ensure the development of the blockchain technology, it is essential to maintain its security.

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Pickl AI

AUGUST 14, 2024

Summary: Neural networks are a key technique in Machine Learning, inspired by the human brain. Different types of neural networks, such as feedforward, convolutional, and recurrent networks, are designed for specific tasks like image recognition, Natural Language Processing, and sequence modelling.

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Neural Network Machine Learning Convolutional Neural Networks Natural Language Processing 52

Marktechpost

DECEMBER 12, 2024

A Deep Neural Network (DNN) is an artificial neural network that features multiple layers of interconnected nodes, also known as neurons. The deep aspect of DNNs comes from multiple hidden layers, which allow the network to learn and model complex patterns and relationships in data.

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Neural Network Convolutional Neural Networks Natural Language Processing Artificial Intelligence 56

Pickl AI

NOVEMBER 26, 2024

Summary: Recurrent Neural Networks (RNNs) are specialised neural networks designed for processing sequential data by maintaining memory of previous inputs. Introduction Neural networks have revolutionised data processing by mimicking the human brain’s ability to recognise patterns.

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Neural Network Natural Language Processing NLP Deep Learning 52

Pickl AI

JANUARY 26, 2025

These models mimic the human brain’s neural networks, making them highly effective for image recognition, natural language processing, and predictive analytics. Feedforward Neural Networks (FNNs) Feedforward Neural Networks (FNNs) are the simplest and most foundational architecture in Deep Learning.

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Deep Learning Neural Network Convolutional Neural Networks Natural Language Processing 52

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. The course also includes information on using Google tools to develop LLM applications, providing practical insights into deploying these models.

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Artificial Intelligence Artificial Intelligence BERT Large Language Models 137

Unite.AI

MAY 24, 2024

In modern machine learning and artificial intelligence frameworks, transformers are one of the most widely used components across various domains including GPT series, and BERT in Natural Language Processing, and Vision Transformers in computer vision tasks.

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Convolutional Neural Networks Neural Network BERT Machine Learning 130

Marktechpost

NOVEMBER 15, 2023

This model consists of two primary modules: A pre-trained BERT model is employed to extract pertinent information from the input text, and A diffusion UNet model processes the output from BERT. It is built upon a pre-trained BERT model. The E3 TTS employs an iterative refinement process to generate an audio waveform.

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BERT Convolutional Neural Networks Neural Network Machine Learning 120

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. Inspect Rich Documents with Gemini Multimodality and Multimodal RAG This course covers using multimodal prompts to extract information from text and visual data and generate video descriptions with Gemini.

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Artificial Intelligence Artificial Intelligence BERT Computer Vision 130

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. Retrieval : The system queries a vector database or document collection to find information relevant to the user's query.

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BERT Large Language Models Natural Language Processing NLP 157

NVIDIA

FEBRUARY 11, 2025

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. Earlier neural networks were narrowly tuned for specific tasks.

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Neural Network Large Language Models Robotics BERT 55

Unite.AI

AUGUST 2, 2023

To tackle the issue of single modality, Meta AI released the data2vec, the first of a kind, self supervised high-performance algorithm to learn patterns information from three different modalities: image, text, and speech. Why Does the AI Industry Need the Data2Vec Algorithm?

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IBM Journey to AI blog

AUGUST 1, 2023

A foundation model is built on a neural network model architecture to process information much like the human brain does. BERT (Bi-directional Encoder Representations from Transformers) is one of the earliest LLM foundation models developed. An open-source model, Google created BERT in 2018.

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Unite.AI

OCTOBER 22, 2024

AI models like neural networks , used in applications like Natural Language Processing (NLP) and computer vision , are notorious for their high computational demands. Models like GPT and BERT involve millions to billions of parameters, leading to significant processing time and energy consumption during training and inference.

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Neural Network Convolutional Neural Networks Deep Learning Natural Language Processing 144

Unite.AI

AUGUST 28, 2023

Neural Networks & Deep Learning : Neural networks marked a turning point, mimicking human brain functions and evolving through experience. Systems like ChatGPT by OpenAI, BERT, and T5 have enabled breakthroughs in human-AI communication. BabyAGI Then, there's BabyAGI , a simplified yet powerful agent.

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Auto-complete ChatGPT Large Language Models Neural Network 240

Mlearning.ai

MARCH 2, 2023

Pre-training of Deep Bidirectional Transformers for Language Understanding BERT is a language model that can be fine-tuned for various NLP tasks and at the time of publication achieved several state-of-the-art results. Finally, the impact of the paper and applications of BERT are evaluated from today’s perspective. 1 Architecture III.2

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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. Accuracy: SLMs produce factually correct information and are less prone to display biases because of their smaller scale.

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BERT Large Language Models Neural Network Natural Language Processing 132

Marktechpost

JUNE 27, 2023

Activation functions for neural networks are an essential part of deep learning since they decide the accuracy and efficiency of the training model used to create or split a large-scale neural network and the output of deep learning models. An artificial neural network contains a large number of linked individual neurons.

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Neural Network Convolutional Neural Networks Deep Learning NLP 52

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. in 2017, marking a departure from the previous reliance on recurrent neural networks (RNNs) and convolutional neural networks (CNNs) for processing sequential data.

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Large Language Models NLP Convolutional Neural Networks Neural Network 120

Marktechpost

MAY 19, 2024

RAG has significantly improved the performance of virtual assistants, chatbots, and information retrieval systems by ensuring that generated responses are accurate and contextually appropriate. The synergy of retrieval and generation enhances the user experience by providing detailed and specific information. Image Source Verba 1.0

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Neural Network BERT OpenAI Artificial Intelligence 120

Marktechpost

APRIL 25, 2024

Parameter In the context of neural networks, including LLMs, a parameter is a variable part of the model’s architecture learned from the training data. Parameters (like weights in neural networks) are adjusted during training to reduce the difference between predicted and actual output.

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Large Language Models LLM Neural Network Natural Language Processing 128

Marktechpost

JULY 22, 2024

However, these models face significant challenges, including temporal limitations of their knowledge base, difficulties with complex mathematical computations, and a tendency to produce inaccurate information or “hallucinations.” However, this is just one component within a broader, more complex framework.

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Large Language Models Neural Network Natural Language Processing LLM 124

Unite.AI

JULY 25, 2024

A significant breakthrough came with neural networks and deep learning. Models like Google's Neural Machine Translation (GNMT) and Transformer revolutionized language processing by enabling more nuanced, context-aware translations. IBM's Model 1 and Model 2 laid the groundwork for advanced systems.

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Neural Network AI AI Machine Learning 200

Marktechpost

MARCH 8, 2025

Current datasets for search and recommendation tasks contain textual information or statistically dense features, severely limiting the development of effective multimodal search and recommendation (S&R) services. Vision-Language Models (VLM) achieve even better performance by incorporating visual information.

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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). The team has shared information on benchmark datasets and open-source scripts to help in applying and assessing these methods.

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Large Language Models AI Research AI Researcher Neural Network 126

TheSequence

NOVEMBER 24, 2024

Created Using Midjourney Next Week in The Sequence: Edge 451: Explores the ideas behind multi-teacher distillation including the MT-BERT paper. The system leverages a recurrent, transformer-based neural network architecture inspired by the successful use of Transformers in large language models (LLMs).

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Neural Network BERT Large Language Models LLM 52