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.

Deep Learning 52

Deep Learning Neural Network Convolutional Neural Networks Natural Language Processing 52

Unite.AI

OCTOBER 22, 2024

Put simply, if we double the input size, the computational needs can increase fourfold. AI models like neural networks , used in applications like Natural Language Processing (NLP) and computer vision , are notorious for their high computational demands.

Neural Network 147

Neural Network Convolutional Neural Networks Deep Learning Natural Language Processing 147

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.

Neural Network 56

Neural Network Convolutional Neural Networks Natural Language Processing Artificial Intelligence 56

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.

Convolutional Neural Networks 130

Convolutional Neural Networks Neural Network BERT Machine Learning 130

Marktechpost

MARCH 20, 2025

Case studies from five cities demonstrate reductions in carbon emissions and improvements in quality of life metrics." }, { "id": 6, "title": "Neural Networks for Computer Vision", "abstract": "Convolutional neural networks have revolutionized computer vision tasks.

Natural Language Processing 57

Natural Language Processing Convolutional Neural Networks Neural Network Computer Vision 57

Unite.AI

SEPTEMBER 18, 2023

Artificial Intelligence is a very vast branch in itself with numerous subfields including deep learning, computer vision , natural language processing , and more. NLP in particular has been a subfield that has been focussed heavily in the past few years that has resulted in the development of some top-notch LLMs like GPT and BERT.

Deep Learning 321

Deep Learning Artificial Intelligence Artificial Intelligence AI 321

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.

Generative AI 176

Generative AI Data Scientist BERT Machine Learning 176

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.

Neural Network 52

Neural Network Convolutional Neural Networks Deep Learning NLP 52

Viso.ai

MARCH 26, 2024

Arguably, one of the most pivotal breakthroughs is the application of Convolutional Neural Networks (CNNs) to financial processes. This drastically enhanced the capabilities of computer vision systems to recognize patterns far beyond the capability of humans. Applications of Computer Vision in Finance No.

Computer Vision 52

Computer Vision Neural Network Machine Learning Convolutional Neural Networks 52

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

BERT 52

BERT NLP Deep Learning Neural Network 52

Towards AI

JANUARY 14, 2025

Understanding Vision Transformers (ViTs) And what I learned while implementing them! Transformers have revolutionized natural language processing (NLP), powering models like GPT and BERT. But recently, theyve also been making waves in computer vision.

Convolutional Neural Networks 116

Convolutional Neural Networks Neural Network Computer Vision Natural Language Processing 116

Heartbeat

SEPTEMBER 20, 2023

Pixabay: by Activedia Image captioning combines natural language processing and computer vision to generate image textual descriptions automatically. Image captioning integrates computer vision, which interprets visual information, and NLP, which produces human language.

Natural Language Processing 52

Natural Language Processing Computer Vision NLP Algorithm 52

Google Research AI blog

FEBRUARY 7, 2023

Context-augmented models In the quest for higher quality and efficiency, neural models can be augmented with external context from large databases or trainable memory. The basic idea of MoEs is to construct a network from a number of expert sub-networks, where each input is processed by a suitable subset of experts.

Deep Learning 118

Deep Learning Algorithm Neural Network ML 118

Unite.AI

JUNE 21, 2024

The field of artificial intelligence (AI) has witnessed remarkable advancements in recent years, and at the heart of it lies the powerful combination of graphics processing units (GPUs) and parallel computing platform. This engine can then be used to perform efficient inference on the GPU, leveraging CUDA for accelerated computation.

Deep Learning 130

Deep Learning Neural Network Convolutional Neural Networks Large Language Models 130

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. He specializes in building machine learning pipelines that involve concepts such as natural language processing and computer vision.

Large Language Models 123

Large Language Models Natural Language Processing LLM Computer Vision 123

Viso.ai

MARCH 20, 2024

Models like GPT 4, BERT, DALL-E 3, CLIP, Sora, etc., Use Cases for Foundation Models Applications in Pre-trained Language Models like GPT, BERT, Claude, etc. Applications in Computer Vision Models like ResNET, VGG, Image Captioning, etc. Foundation models are recent developments in artificial intelligence (AI).

AI Developer 52

AI Developer AI Development Computer Vision BERT 52

Viso.ai

APRIL 26, 2024

Object detection systems typically use frameworks like Convolutional Neural Networks (CNNs) and Region-based CNNs (R-CNNs). Concept of Convolutional Neural Networks (CNN) However, in prompt object detection systems, users dynamically direct the model with many tasks it may not have encountered before.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Natural Language Processing 52

AWS Machine Learning Blog

MARCH 20, 2023

Quantization is a technique to reduce the computational and memory costs of running inference by representing the weights and activations with low-precision data types like 8-bit integer (INT8) instead of the usual 32-bit floating point (FP32). In the following example figure, we show INT8 inference performance in C6i for a BERT-base model.

BERT 94

BERT Deep Learning ML Neural Network 94

Unite.AI

APRIL 26, 2024

The introduction of the transformer framework proved to be a milestone, facilitating the development of a new wave of language models, including OPT and BERT, which exhibit profound linguistic understanding. The advancements in large language models have significantly accelerated the development of natural language processing , or NLP.

Large Language Models 162

Large Language Models Natural Language Processing Convolutional Neural Networks Neural Network 162

Google Research AI blog

FEBRUARY 10, 2023

We also had a number of interesting results on graph neural networks (GNN) in 2022. Furthermore, to bring some of these many advances to the broader community, we had three releases of our flagship modeling library for building graph neural networks in TensorFlow (TF-GNN).

Algorithm 110

Algorithm Neural Network Auto-classification ML 110

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.

NLP 98

NLP BERT Large Language Models Natural Language Processing 98

Snorkel AI

MARCH 1, 2023

Model architectures that qualify as “supervised learning”—from traditional regression models to random forests to most neural networks—require labeled data for training. BERT proved useful in several ways, including quantifying sentiment and predicting the words likely to follow in unfinished sentences.

BERT 83

BERT Natural Language Processing Large Language Models Neural Network 83

Marktechpost

JUNE 30, 2023

Well-known models like GPT, BERT, PaLM, etc., are some great additions to the long list of LLMs that are transforming how humans and computers interact. 3D scene understanding is also evolving, enabling the development of geometry-free neural networks that can be trained on a large dataset of scenes to learn scene representations.

Neural Network 98

Neural Network BERT Large Language Models Artificial Intelligence 98

Viso.ai

JULY 9, 2024

About us : Viso Suite is our end-to-end computer vision infrastructure for enterprises. The powerful solution enables teams to develop, deploy, manage, and secure computer vision applications in one place. To understand how transfer learning works, it is essential to understand the architecture of Deep Neural Networks.

Neural Network 52

Neural Network BERT Deep Learning Computer Vision 52

ODSC - Open Data Science

APRIL 11, 2023

We have seen these techniques advancing multiple fields in AI such as NLP, Computer Vision, and Robotics. We’ll learn how to automatically discover and describe the function of individual neurons within deep networks, and use these descriptions to identify model failures and improve their robustness.

NLP 96

NLP Data Science Large Language Models Data Scientist 96

Marktechpost

JULY 3, 2023

From deep learning, Natural Language Processing (NLP), and Natural Language Understanding (NLU) to Computer Vision, AI is propelling everyone into a future with endless innovations. The underlying architecture of LLMs typically involves a deep neural network with multiple layers.

Large Language Models 98

Large Language Models Natural Language Processing LLM BERT 98

PyImageSearch

AUGUST 14, 2023

Graph Construction Amazon uses graph neural networks (GNNs) to model these relationships between products by learning their respective product embeddings ( Figure 3 ). Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated? Or requires a degree in computer science?

Computer Vision 88

Computer Vision Deep Learning Algorithm Neural Network 88

AWS Machine Learning Blog

APRIL 3, 2024

The following is a high-level overview of how it works conceptually: Separate encoders – These models have separate encoders for each modality—a text encoder for text (for example, BERT or RoBERTa), image encoder for images (for example, CNN for images), and audio encoders for audio (for example, models like Wav2Vec).

Machine Learning 125

Machine Learning Metadata Generative AI ML 125

Viso.ai

JULY 18, 2024

Emergence and History of LLMs Artificial Neural Networks (ANNs) and Rule-based Models The foundation of these Computational Linguistics models (CL) dates back to the 1940s when Warren McCulloch and Walter Pitts laid the groundwork for AI. Both contain self-attention mechanisms and feed-forward neural networks.

Large Language Models 52

Large Language Models Neural Network Natural Language Processing BERT 52

AWS Machine Learning Blog

JUNE 12, 2023

Transformer neural networks A transformer neural network is a popular deep learning architecture to solve sequence-to-sequence tasks. Deep learning (DL) models with more layers and parameters perform better in complex tasks like computer vision and NLP. and later) GPT-J (available in the SMP library v1.8.0

Deep Learning 82

Deep Learning Auto-classification Computer Vision Machine Learning 82

AWS Machine Learning Blog

JANUARY 17, 2023

Computer vision. BERT + Random Forest. After the tuning jobs are complete, we deploy the model that gives the best evaluation metric score on the validation dataset, perform inference on the same hold-out test dataset we did in the previous section, and compute evaluation metrics. BERT + Random Forest. 0.81115.

Categorization 87

Categorization BERT Machine Learning Neural Network 87

Viso.ai

MARCH 26, 2024

This enhances the interpretability of AI systems for applications in computer vision and natural language processing (NLP). Uniquely, this model did not rely on conventional neural network architectures like convolutional or recurrent layers. without conventional neural networks. Vaswani et al.

Deep Learning 52

Deep Learning Computer Vision Neural Network Natural Language Processing 52

Viso.ai

FEBRUARY 25, 2023

Vision Transformer (ViT) have recently emerged as a competitive alternative to Convolutional Neural Networks (CNNs) that are currently state-of-the-art in different image recognition computer vision tasks. This article will cover the following topics: What is a Vision Transformer (ViT)?

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Natural Language Processing 52

Topbots

OCTOBER 4, 2023

Image processing : Predictive image processing models, such as convolutional neural networks (CNNs), can classify images into predefined labels (e.g., Masking in BERT architecture ( illustration by Misha Laskin ) Another common type of generative AI model are diffusion models for image and video generation and editing.

Generative AI 119

Generative AI Natural Language Processing Machine Learning Convolutional Neural Networks 119

Lexalytics

APRIL 5, 2021

This book effectively killed off interest in neural networks at that time, and Rosenblatt, who died shortly thereafter in a boating accident, was unable to defend his ideas. (I Around this time a new graduate student, Geoffrey Hinton, decided that he would study the now discredited field of neural networks.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Viso.ai

DECEMBER 18, 2023

ONNX is an open standard for representing computer vision and machine learning models. ONNX (Open Neural Network Exchange) is an open-source format that facilitates interoperability between different deep learning algorithms for simple model sharing and deployment. A deep learning framework from Microsoft. Apache MXNet.

Explainability 52

Explainability Neural Network Deep Learning Machine Learning 52

Pickl AI

NOVEMBER 13, 2024

It’s a crucial technique in modern neural networks, enhancing performance and generalisation. However, training deep neural networks often encounters challenges such as slow convergence, vanishing gradients, and sensitivity to initialisation. BN improves the performance and stability of deep neural networks.

Deep Learning 52

Deep Learning Neural Network Convolutional Neural Networks Natural Language Processing 52