Unite.AI

AUGUST 2, 2023

These limitations are a major issue why an average human mind is able to learn from a single type of data much more effectively when compared to an AI model that relies on separate models & training data to distinguish between an image, text, and speech. Why Does the AI Industry Need the Data2Vec Algorithm?

Computer Vision 246

Computer Vision Algorithm Natural Language Processing Convolutional Neural Networks 246

Unite.AI

OCTOBER 22, 2024

Artificial Intelligence (AI) is changing our world incredibly, influencing industries like healthcare, finance, and retail. From recommending products online to diagnosing medical conditions, AI is everywhere. As AI models become more complex, they demand more computational power, putting a strain on hardware and driving up costs.

Neural Network 144

Neural Network Convolutional Neural Networks Deep Learning Natural Language Processing 144

Pickl AI

APRIL 6, 2025

Neural Networks are foundational structures, while Deep Learning involves complex, layered networks like CNNs and RNNs, enabling advanced AI capabilities such as image recognition and natural language processing. Introduction Deep Learning and Neural Networks are like a sports team and its star player.

Neural Network 52

Neural Network Deep Learning Natural Language Processing Convolutional Neural Networks 52

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.

Data Science 52

Data Science Neural Network Convolutional Neural Networks Large Language Models 52

Pickl AI

JANUARY 26, 2025

Convolutional Neural Networks (CNNs) Convolutional Neural Networks ( CNNs ) are specialised Deep Learning models that process and analyse visual data. Transformers are the foundation of many state-of-the-art architectures, such as BERT and GPT.

Deep Learning 52

Deep Learning Neural Network Convolutional Neural Networks Natural Language Processing 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.

Large Language Models 122

Large Language Models NLP Convolutional Neural Networks Neural Network 122

Towards AI

JANUARY 14, 2025

Last Updated on January 15, 2025 by Editorial Team Author(s): Yash Thube Originally published on Towards AI. Transformers have revolutionized natural language processing (NLP), powering models like GPT and BERT. Understanding Vision Transformers (ViTs) And what I learned while implementing them!

Convolutional Neural Networks 117

Convolutional Neural Networks Neural Network Computer Vision Natural Language Processing 117

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 59

Natural Language Processing Convolutional Neural Networks Neural Network Computer Vision 59

Marktechpost

JANUARY 15, 2025

Technical Details and Benefits Deep learning relies on artificial neural networks composed of layers of interconnected nodes. Notable architectures include: Convolutional Neural Networks (CNNs): Designed for image and video data, CNNs detect spatial patterns through convolutional operations.

Deep Learning 87

Deep Learning Neural Network Convolutional Neural Networks Natural Language Processing 87

Marktechpost

APRIL 20, 2024

Deep neural networks like convolutional neural networks (CNNs) have revolutionized various computer vision tasks, from image classification to object detection and segmentation. As models grew larger and more complex, their accuracy soared.

Machine Learning 103

Machine Learning Neural Network Convolutional Neural Networks Computer Vision 103

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).

Generative AI 119

Generative AI Natural Language Processing Machine Learning Convolutional Neural Networks 119

Mlearning.ai

APRIL 8, 2023

What is Natural Language Processing (NLP) Natural Language Processing (NLP) is a subfield of artificial intelligence (AI) that deals with interactions between computers and human languages. Additionally, Papers published by NVIDIA AI on efficiently pre-training models has really helped push the boundaries of efficiency and speed.

NLP 98

NLP Neural Network Natural Language Processing Convolutional Neural Networks 98

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 157

Large Language Models Natural Language Processing Convolutional Neural Networks Neural Network 157

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. As the field of AI continues to evolve, the importance of GPUs and CUDA will only grow.

Deep Learning 130

Deep Learning Neural Network Convolutional Neural Networks Large Language Models 130

ODSC - Open Data Science

APRIL 28, 2023

Be sure to check out his talk, “ Bagging to BERT — A Tour of Applied NLP ,” there! In the first example, we’ll be defining an architecture based on a Convolutional Neural Network (CNN) The dataset We’ll be using the same dataset as last time; a collection of 50k reviews from IMDB which are labeled as either positive or negative.

Deep Learning 98

Deep Learning Convolutional Neural Networks NLP Neural Network 98

AWS Machine Learning Blog

FEBRUARY 24, 2023

This satisfies the strong MME demand for deep neural network (DNN) models that benefit from accelerated compute with GPUs. These include computer vision (CV), natural language processing (NLP), and generative AI models. The impact is more for models using a convolutional neural network (CNN).

BERT 103

BERT NLP Computer Vision Neural Network 103

Marktechpost

SEPTEMBER 30, 2024

Large Language Models (LLMs) based on Transformer architectures have revolutionized AI development. While the Adam optimizer has become the standard for training Transformers, stochastic gradient descent with momentum (SGD), which is highly effective for convolutional neural networks (CNNs), performs worse on Transformer models.

Neural Network 57

Neural Network Convolutional Neural Networks BERT Explainability 57

Viso.ai

MARCH 20, 2024

Foundation models are recent developments in artificial intelligence (AI). Models like GPT 4, BERT, DALL-E 3, CLIP, Sora, etc., are at the forefront of the AI revolution. In this article, we’ll discuss the transformative impact of foundation models in modern AI developments.

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

Snorkel AI

MARCH 1, 2023

Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning. Foundation models underpin generative AI capabilities, from text-generation to music creation to image generation. Github Copilot GitHub Copilot is an AI-powered code assistant.

BERT 83

BERT Natural Language Processing Large Language Models Neural Network 83

Unite.AI

APRIL 2, 2024

These deep learning image restoration models propose to use neural networks based on Transformers and Convolutional Neural Networks. Recent deep learning methods have displayed stronger and more consistent performance when compared to traditional image restoration methods.

Computer Vision 130

Computer Vision Neural Network Convolutional Neural Networks Deep Learning 130

Marktechpost

DECEMBER 12, 2024

Convolutional Neural Networks (CNNs) : Convolutional Neural Networks (CNNs) are specifically designed for processing grid-like data such as images or time-series data. They utilize convolutional layers to extract spatial features by applying filters to the input data.

Neural Network 57

Neural Network Convolutional Neural Networks Natural Language Processing Artificial Intelligence 57

Pickl AI

AUGUST 14, 2024

Neural networks come in various forms, each designed for specific tasks: Feedforward Neural Networks (FNNs) : The simplest type, where connections between nodes do not form cycles. Models such as Long Short-Term Memory (LSTM) networks and Transformers (e.g., Data moves in one direction—from input to output.

Neural Network 52

Neural Network Machine Learning Convolutional Neural Networks Natural Language Processing 52

Mlearning.ai

JUNE 8, 2023

Hidden secret to empower semantic search This is the third article of building LLM-powered AI applications series. A few embeddings for different data type For text data, models such as Word2Vec , GLoVE , and BERT transform words, sentences, or paragraphs into vector embeddings. using its Spectrogram ). using its Spectrogram ).

Machine Learning 52

Machine Learning BERT Neural Network OpenAI 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. For example, the popular ChatGPT AI chatbot is a transformer-based language model. Get a demo for your company.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Natural Language Processing 52

Mlearning.ai

MARCH 30, 2023

To understand this let’s take an example of a widely used neural network, CNN (Convolutional Neural Network) CNN is made of two parts: C — Convolution NN — Neural Network The most important part of training is feature extraction which is done by the convolutional part of the CNN.

Neural Network 52

Neural Network AI Developer AI Development Convolutional Neural Networks 52

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. This leap forward is due to the influence of foundation models in NLP, such as GPT and BERT. Over the years, Meta has released several influential models and tools.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Auto-classification 52

Viso.ai

DECEMBER 18, 2023

Developers can also find libraries for running these models on different AI hardware , including GPU and CPU. Real-World Applications of ONNX We can view ONNX as a sort of Rosetta stone of artificial intelligence (AI). This has the potential to enhance player experience through AI-driven personalization and interactions.

Explainability 52

Explainability Neural Network Deep Learning Machine Learning 52

DataRobot Blog

MARCH 9, 2022

These embeddings are sometimes trained jointly with the model, but usually additional accuracy can be attained by using pre-trained embeddings such as Word2Vec, GloVe, BERT, or FastText. Stanford – Reading Emotions From Speech Using Deep Neural Networks, a publication.

Machine Learning 52

Machine Learning Neural Network Convolutional Neural Networks Deep Learning 52

Viso.ai

DECEMBER 27, 2023

Contrastive learning is a method where we teach an AI model to recognize similarities and differences of a large number of data points. In a computer vision example of contrast learning, we aim to train a tool like a convolutional neural network to bring similar image representations closer and separate the dissimilar ones.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network NLP 52

Viso.ai

MARCH 26, 2024

The integration of Artificial Intelligence (AI) technologies within the finance industry has fully transitioned from experimental to indispensable. Initially, AI’s role in finance was limited to basic computational tasks. Furthermore, the introduction of GANs (Generative Adversarial Networks) has accelerated AI adoption.

Computer Vision 52

Computer Vision Neural Network Machine Learning Convolutional Neural Networks 52

Viso.ai

JULY 9, 2024

In today’s digital world, Artificial Intelligence (AI) and Machine learning (ML) models are used everywhere, from face detection in electronic devices to real-time language translation. But, there are open source models like German-BERT that are already trained on huge data corpora, with many parameters.

Neural Network 52

Neural Network BERT Deep Learning Computer Vision 52

TensorFlow

MARCH 29, 2023

TF-ZenDNN We have integrated ZenDNN into high-level AI frameworks for ease of use. TF-ZenDNN optimizes graphs at the network level and provides tuned primitive implementations at a library level, including Convolution, MatMul, Elementwise, and Pooling (Max and Average). For the ZenDNN plug-in, AOCL BLIS 3.0.6,

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Pragnakalp

JANUARY 1, 2024

Introduction Welcome to the world of Mistral AI, where revolutionary developments in Language Model Technology meet user-friendly innovation! Mistral AI proudly presents Mistral 7B, an intelligent solution designed to understand and manipulate language in a manner similar to human perception. in terms of performance.

Neural Network 52

Neural Network Natural Language Processing Convolutional Neural Networks NLP 52

NLP People

JULY 24, 2019

The rise of NLP in the past decades is backed by a couple of global developments – the universal hype around AI, exponential advances in the field of Deep Learning and an ever-increasing quantity of available text data. Especially pre-trained word embeddings such as Word2Vec, FastText and BERT allow NLP developers to jump to the next level.

NLP 52

NLP Neural Network Deep Learning Natural Language Processing 52

Pickl AI

DECEMBER 9, 2024

For example, in convolutional neural networks (CNNs), the lower layers detect basic features like edges and textures, while higher layers combine these features to recognise more complex patterns. By shaping how models interpret data and generalise, inductive bias influences their effectiveness in solving real-world problems.

Machine Learning 52

Machine Learning Neural Network Convolutional Neural Networks Natural Language Processing 52

Heartbeat

OCTOBER 12, 2023

These language models are breaking boundaries, venturing into a new era of AI — Multi-Modal Learning. In a world where words are just the beginning, AI is learning to speak the language of the senses. At its core, it encompasses integrating and interpreting diverse sensory inputs, including images, audio, videos, and more.

Large Language Models 59

Large Language Models Neural Network Convolutional Neural Networks Artificial Intelligence 59