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

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. It covers how to develop NLP projects using neural networks with Vertex AI and TensorFlow. Participants learn how to improve model accuracy and write scalable, specialized ML models.

Artificial Intelligence 132

Artificial Intelligence Artificial Intelligence BERT Computer Vision 132

Unite.AI

APRIL 2, 2024

These problems, commonly referred to as degradations in low-level computer vision, can arise from difficult environmental conditions like heat or rain or from limitations of the camera itself. Many frameworks employ a generic neural network for a wide range of image restoration tasks, but these networks are each trained separately.

Computer Vision 130

Computer Vision Neural Network Convolutional Neural Networks Deep Learning 130

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. Source: A pipeline on Generative AI This figure of a generative AI pipeline illustrates the applicability of models such as BERT, GPT, and OPT in data extraction.

Data Extraction 273

Data Extraction Neural Network Large Language Models NLP 273

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 Natural Language Processing 130

Unite.AI

AUGUST 2, 2023

To overcome the challenge presented by single modality models & algorithms, Meta AI released the data2vec, an algorithm that uses the same learning methodology for either computer vision , NLP or speech. For computer vision, the model practices block-wise marking strategy.

Computer Vision 246

Computer Vision Convolutional Neural Networks Natural Language Processing Algorithm 246

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 Development 52

AI Development AI Developer 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

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

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

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 189

Generative AI BERT Data Scientist Machine Learning 189

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

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

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

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 BERT 118

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

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 116

Large Language Models Natural Language Processing LLM Computer Vision 116

Viso.ai

DECEMBER 22, 2023

The Segment Anything Model (SAM), a recent innovation by Meta’s FAIR (Fundamental AI Research) lab, represents a pivotal shift in computer vision. SAM performs segmentation, a computer vision task , to meticulously dissect visual data into meaningful segments, enabling precise analysis and innovations across industries.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Auto-classification 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

Viso.ai

JUNE 12, 2024

provides a robust end-to-end computer vision infrastructure – Viso Suite. Our software helps several leading organizations start with computer vision and implement deep learning models efficiently with minimal overhead for various downstream tasks. All three GPT generations utilize artificial neural networks.

Large Language Models 52

Large Language Models ChatGPT Computer Vision Neural Network 52

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

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

Bugra Akyildiz

DECEMBER 18, 2022

Brown researchers compared human visual recognition systems and Deep Neural Networks for what they believe where the important features of images are. Collecting, labeling, and cleaning data for computer vision is a pain. Dragon can be used as a drop-in replacement for BERT.

Neural Network 52

Neural Network ChatGPT Machine Learning Deep Learning 52

Viso.ai

DECEMBER 27, 2023

Architecture and training process How CLIP resolves key challenges in computer vision Practical applications Challenges and limitations while implementing CLIP Future advancements How Does CLIP Work? It typically uses a convolutional neural network (CNN) architecture, like ResNet , for extracting image features.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network NLP 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 83

BERT Deep Learning ML Neural Network 83

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 89

Computer Vision Deep Learning Algorithm Neural Network 89

Heartbeat

FEBRUARY 8, 2024

Cross-modal retrieval is a branch of computer vision and natural language processing that links visual and verbal descriptions. Convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are often employed to extract meaningful representations from images and text, respectively.

Neural Network 52

Neural Network Deep Learning Convolutional Neural Networks Computer Vision 52

TensorFlow

MARCH 29, 2023

This plug-in enables neural network inferencing on AMD EPYC CPUs with the AMD ZenDNN library. ZenDNN ZenDNN, which is available open-source from GitHub , is a low-level AMD deep neural network library that includes basic neural network building blocks optimized for AMD EPYC CPUs. ZD-045 thru ZD-051

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

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

NVIDIA Developer

JUNE 2, 2021

Transformer-based models, such as Bidirectional Encoder Representations from Transformers (BERT), have revolutionized NLP by offering accuracy comparable to human baselines on benchmarks like SQuAD for question-answer, entity recognition, intent recognition, sentiment analysis, and more. Basic understanding of neural networks.

Natural Language Processing 40

Natural Language Processing Neural Network BERT Deep Learning 40

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 Large Language Models Data Science Big Data 96

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

Pragnakalp

JANUARY 1, 2024

Transformer models are a type of neural network architecture designed to process sequential material, such as sentences or time-series data. Transformer technology has also heralded generative pretrained transformers (GPTs) and Bidirectional Encoder Representations from Transformers (BERT)."}

Neural Network 52

Neural Network Natural Language Processing Convolutional Neural Networks NLP 52

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 Auto-classification Neural Network ML 110

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

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

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