Unite.AI

MARCH 11, 2024

Interpretable and Explainable: Using multiple components allows us to interpret how each component contributes to the final output, making these systems interpretable and transparent. The goal is to merge the intuitive data processing abilities of neural networks with the structured, logical reasoning of symbolic AI.

AI Modeling 298

AI Modeling Neural Network Large Language Models AI 298

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

JUNE 26, 2023

AI models are extremely good at solving narrow problems, such as image classification, natural language processing , speech recognition, etc., They lack subjective experience, self-consciousness, or an understanding of context beyond what they have been trained to process. but they don’t possess consciousness.

AI 348

AI AI Neural Network Natural Language Processing 348

IBM Journey to AI blog

AUGUST 13, 2024

Where it all started During the second half of the 20 th century, IBM researchers used popular games such as checkers and backgammon to train some of the earliest neural networks, developing technologies that would become the basis for 21 st -century AI.

Machine Learning 291

Machine Learning Neural Network Robotics Natural Language Processing 291

Unite.AI

APRIL 9, 2024

These techniques include Machine Learning (ML), deep learning , Natural Language Processing (NLP) , Computer Vision (CV) , descriptive statistics, and knowledge graphs. Explainability is essential for accountability, fairness, and user confidence. Explainability also aligns with business ethics and regulatory compliance.

Composite AI 176

Composite AI Explainability Neural Network Explainable AI 176

AI Weekly

JANUARY 18, 2024

Powered by superai.com In the News Bill Gates explains how AI will change our lives in 5 years It’s no secret that Bill Gates is bullish on artificial intelligence, but he’s now predicting that the technology will be transformative for everyone within the next five years.

Robotics 264

Robotics Artificial Intelligence Artificial Intelligence Machine Learning 264

Flipboard

DECEMBER 3, 2024

The agent uses natural language processing (NLP) to understand the query and uses underlying agronomy models to recommend optimal seed choices tailored to specific field conditions and agronomic needs. What corn hybrids do you suggest for my field?”.

Generative AI 149

Generative AI Metadata Machine Learning Natural Language Processing 149

Dlabs.ai

DECEMBER 9, 2021

Natural language processing (NLP) is a core part of artificial intelligence. Natural Language Processing Succinctly Author : Joseph D. You’ll find all you need to know to build NLP solutions, starting with an overview of natural language processes and what the technology can do.

Natural Language Processing 59

Natural Language Processing Neural Network NLP Deep Learning 59

Marktechpost

DECEMBER 5, 2023

The Hierarchically Gated Recurrent Neural Network (HGRN) technique developed by researchers from the Shanghai Artificial Intelligence Laboratory and MIT CSAI addresses the challenge of enhancing sequence modeling by incorporating forget gates in linear RNNs. Check out the Paper , Github, and Project.

Neural Network 101

Neural Network Artificial Intelligence Artificial Intelligence Natural Language Processing 101

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.

Neural Network 52

Neural Network Machine Learning Convolutional Neural Networks Natural Language Processing 52

Towards AI

SEPTEMBER 7, 2023

How is attention computed using Recurrent Neural Networks (RNNs)? Machine Translation We will look at Neural machine translation (NMT) as a running example in this article. NMT aims to build and train a single, large neural network that reads a sentence and outputs a correct translation.

Explainability 126

Explainability Neural Network Natural Language Processing NLP 126

Pickl AI

SEPTEMBER 3, 2024

Summary: Artificial Neural Network (ANNs) are computational models inspired by the human brain, enabling machines to learn from data. Introduction Artificial Neural Network (ANNs) have emerged as a cornerstone of Artificial Intelligence and Machine Learning , revolutionising how computers process information and learn from data.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing Machine Learning 52

Marktechpost

MAY 5, 2024

The course covers numerous algorithms of supervised and unsupervised learning and also teaches how to build neural networks using TensorFlow. Students learn to implement and analyze models like linear models, kernel machines, neural networks, and graphical models.

Machine Learning 117

Machine Learning Python Neural Network Convolutional Neural Networks 117

Unite.AI

NOVEMBER 19, 2024

NR1, combined with Qualcomm Cloud AI 100 or NVIDIA H100 or L40S GPUs, delivers a substantial performance boost over traditional CPU-centric inference servers in real-world AI applications across large language models like Llama 3, computer vision, natural language processing and speech recognition. Our solution?

Neural Network 157

Neural Network Natural Language Processing Python Computer Vision 157

Unite.AI

NOVEMBER 8, 2023

Natural Language Processing (NLP) has experienced some of the most impactful breakthroughs in recent years, primarily due to the the transformer architecture. Recurrent Neural Networks (RNNs) became the cornerstone for these applications due to their ability to handle sequential data by maintaining a form of memory.

BERT 293

BERT NLP Neural Network Natural Language Processing 293

Marktechpost

JUNE 4, 2024

Modern Deep Neural Networks (DNNs) are inherently opaque; we do not know how or why these computers arrive at the predictions they do. An emerging area of study called Explainable AI (XAI) has arisen to shed light on how DNNs make decisions in a way that humans can comprehend.

Machine Learning 114

Machine Learning Neural Network Explainability Natural Language Processing 114

Marktechpost

MARCH 28, 2024

Machine Learning (in Python and R) for Dummies This book explains the fundamentals of machine learning by providing practical examples using Python and R. Neural Networks and Deep Learning This book covers the fundamental concepts of neural networks and deep learning.

Artificial Intelligence 142

Artificial Intelligence Artificial Intelligence Neural Network Deep Learning 142

Marktechpost

APRIL 21, 2024

Introduction to Generative AI: This course provides an introductory overview of Generative AI, explaining what it is and how it differs from traditional machine learning methods. It introduces learners to responsible AI and explains why it is crucial in developing AI systems.

Artificial Intelligence 137

Artificial Intelligence Artificial Intelligence BERT Large Language Models 137

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

Heartbeat

FEBRUARY 8, 2023

Source: Author The field of natural language processing (NLP), which studies how computer science and human communication interact, is rapidly growing. By enabling robots to comprehend, interpret, and produce natural language, NLP opens up a world of research and application possibilities.

Natural Language Processing 52

Natural Language Processing NLP Machine Learning Deep Learning 52

IBM Journey to AI blog

JANUARY 10, 2024

AI can also work from deep learning algorithms, a subset of ML that uses multi-layered artificial neural networks (ANNs)—hence the “deep” descriptor—to model high-level abstractions within big data infrastructures. This is where AI programming offers a clear edge over rules-based programming methods.

Artificial Intelligence 229

Artificial Intelligence Artificial Intelligence Neural Network Algorithm 229

Pickl AI

NOVEMBER 13, 2024

Summary: Backpropagation in neural network optimises models by adjusting weights to reduce errors. Despite challenges like vanishing gradients, innovations like advanced optimisers and batch normalisation have improved their efficiency, enabling neural networks to solve complex problems.

Neural Network 52

Neural Network Algorithm Convolutional Neural Networks Natural Language Processing 52

Viso.ai

MAY 17, 2024

Neural Networks have changed the way we perform model training. Neural networks, sometimes referred to as Neural Nets, need large datasets for efficient training. So, what if we have a neural network that can adapt itself to new data and has less complexity? What is a Liquid Neural Network?

Neural Network 52

Neural Network Deep Learning Computer Vision Artificial Intelligence 52

IBM Journey to AI blog

JUNE 14, 2023

If you want to start a different task or solve a new problem, you often must start the whole process over again—it’s a recurring cost. But that’s all changing thanks to pre-trained, open source foundation models. works alongside the platform’s other capabilities by clicking the buttons below.

Automation 258

Automation Neural Network Natural Language Processing AI 258

Unite.AI

FEBRUARY 16, 2024

Despite achieving remarkable results in areas like computer vision and natural language processing , current AI systems are constrained by the quality and quantity of training data, predefined algorithms, and specific optimization objectives.

Neural Network 190

Neural Network Machine Learning Algorithm Natural Language Processing 190

Marktechpost

SEPTEMBER 1, 2023

LLMs have become increasingly popular in the NLP (natural language processing) community in recent years. Scaling neural network-based machine learning models has led to recent advances, resulting in models that can generate natural language nearly indistinguishable from that produced by humans.

Large Language Models 137

Large Language Models Neural Network Natural Language Processing LLM 137

Marktechpost

MAY 29, 2024

This article lists the top AI courses NVIDIA provides, offering comprehensive training on advanced topics like generative AI, graph neural networks, and diffusion models, equipping learners with essential skills to excel in the field. It also covers how to set up deep learning workflows for various computer vision tasks.

Neural Network 91

Neural Network Natural Language Processing Large Language Models Deep Learning 91

IBM Journey to AI blog

JANUARY 15, 2024

This technology excels at applying foundation models, which are large neural networks trained on extensive unlabeled data and fine-tuned for various tasks. Last year, the US Department of State sought feedback on the challenges and security considerations of introducing generative and natural language processing AI into its network.

Generative AI 200

Generative AI Responsible AI Neural Network Natural Language Processing 200

Marktechpost

JUNE 28, 2024

Machine Learning (in Python and R) for Dummies This book explains the fundamentals of machine learning by providing practical examples using Python and R. Neural Networks and Deep Learning This book covers the fundamental concepts of neural networks and deep learning.

Artificial Intelligence 114

Artificial Intelligence Artificial Intelligence Neural Network Deep Learning 114

Towards AI

NOVEMBER 19, 2023

Photo by Pietro Jeng on Unsplash Deep learning is a type of machine learning that utilizes layered neural networks to help computers learn from large amounts of data in an automated way, much like humans do. We will explain intuitively what each one means and how it contributes to the deep learning process.

Deep Learning 126

Deep Learning Neural Network Natural Language Processing Machine Learning 126

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?

Neural Network 158

Neural Network Convolutional Neural Networks BERT Deep Learning 158

Heartbeat

AUGUST 21, 2023

In this guide, we’ll talk about Convolutional Neural Networks, how to train a CNN, what applications CNNs can be used for, and best practices for using CNNs. What Are Convolutional Neural Networks CNN? CNNs are artificial neural networks built to handle data having a grid-like architecture, such as photos or movies.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Natural Language Processing Deep Learning 52

IBM Journey to AI blog

SEPTEMBER 24, 2024

“AI could lead to more accurate and timely predictions, especially for spotting diseases early,” he explains, “and it could help cut down on carbon footprints and environmental impact by improving how we use energy and resources.” We get tired, lose our focus, or just physically can’t see all that we need to.

Explainability 184

Explainability Computer Vision Convolutional Neural Networks AI 184

Marktechpost

JUNE 9, 2024

It explains the differences between hand-coded algorithms and trained models, the relationship between machine learning and AI, and the impact of data types on training. It also explores neural networks, their components, and the complexity of deep learning.

Artificial Intelligence 97

Artificial Intelligence Artificial Intelligence Natural Language Processing Large Language Models 97

Heartbeat

SEPTEMBER 20, 2023

Pixabay: by Activedia Image captioning combines natural language processing and computer vision to generate image textual descriptions automatically. This process involves utilizing various NLP models and techniques to develop textual descriptions. Various algorithms are employed in image captioning, including: 1.

Natural Language Processing 52

Natural Language Processing Computer Vision NLP Algorithm 52

Marktechpost

MAY 30, 2024

Natural Language Processing on Google Cloud This course introduces Google Cloud products and solutions for solving NLP problems. It covers how to develop NLP projects using neural networks with Vertex AI and TensorFlow. Learners will gain hands-on experience with image classification models using public datasets.

Artificial Intelligence 130

Artificial Intelligence Artificial Intelligence BERT Computer Vision 130

AWS Machine Learning Blog

MARCH 21, 2025

Generate metadata Using natural language processing, you can generate metadata for the paper to aid in searchability. /samples/2003.10304/page_5.png" However, the lower and fluctuating validation Dice coefficient indicates potential overfitting and room for improvement in the models generalization performance.

Metadata 113

Metadata Convolutional Neural Networks Generative AI Data Scientist 113