Marktechpost

APRIL 26, 2024

More sophisticated methods like TARNet, Dragonnet, and BCAUSS have emerged, leveraging the concept of representation learning with neural networks. In some cases, the neural network might detect and rely on interactions between variables that don’t actually have a causal relationship.

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Marktechpost

JUNE 22, 2024

Neural networks, despite their theoretical capability to fit training sets with as many samples as they have parameters, often fall short in practice due to limitations in training procedures. Key technical aspects include the use of various neural network architectures (MLPs, CNNs, ViTs) and optimizers (SGD, Adam, AdamW, Shampoo).

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Marktechpost

MARCH 9, 2024

The evolution of artificial intelligence, particularly in the realm of neural networks, has significantly advanced our data processing and analysis capabilities. Among these advancements, the efficiency of training and deploying deep neural networks has become a paramount focus.

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Marktechpost

FEBRUARY 4, 2024

Meta-learning, a burgeoning field in AI research, has made significant strides in training neural networks to adapt swiftly to new tasks with minimal data. This technique centers on exposing neural networks to diverse tasks, thereby cultivating versatile representations crucial for general problem-solving.

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Marktechpost

MAY 30, 2024

Introduction to AI and Machine Learning on Google Cloud This course introduces Google Cloud’s AI and ML offerings for predictive and generative projects, covering technologies, products, and tools across the data-to-AI lifecycle. It includes labs on feature engineering with BigQuery ML, Keras, and TensorFlow.

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Marktechpost

JUNE 28, 2024

Artificial Intelligence (AI) has been making significant strides over the past few years, with the emergence of Large Language Models (LLMs) marking a major milestone in its growth. The author talks about machine intelligence’s historical background and provides beginners with information on how advanced algorithms work.

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Unite.AI

SEPTEMBER 21, 2023

The crossover between artificial intelligence (AI) and blockchain is a growing trend across various industries, such as finance, healthcare, cybersecurity, and supply chain. What is Artificial Intelligence (AI)? Artificial intelligence enables computer programs to mimic human intelligence.

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Marktechpost

AUGUST 4, 2024

Representational similarity measures are essential tools in machine learning, used to compare internal representations of neural networks. These measures help researchers understand learning dynamics, model behaviors, and performance by providing insights into how different neural network layers and architectures process information.

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Marktechpost

SEPTEMBER 3, 2024

Recent neural architectures remain inspired by biological nervous systems but lack the complex connectivity found in the brain, such as local density and global sparsity. Researchers from Microsoft Research Asia introduced CircuitNet, a neural network inspired by neuronal circuit architectures.

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Marktechpost

MAY 10, 2024

Redundant execution introduces the concept of a hybrid (convolutional) neural network designed to facilitate reliable neural network execution for safe and dependable AI. The method has scope for further extension to more complex neural network architectures and applications with additional optimization.

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Marktechpost

SEPTEMBER 6, 2024

Spiking Neural Networks (SNNs), a family of artificial neural networks that mimic the spiking behavior of biological neurons, have been in discussion in recent times. These networks provide a fresh method for working with temporal data, identifying the complex relationships and patterns seen in sequences.

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Marktechpost

OCTOBER 18, 2024

Deep neural networks are powerful tools that excel in learning complex patterns, but understanding how they efficiently compress input data into meaningful representations remains a challenging research problem. Don’t Forget to join our 50k+ ML SubReddit. If you like our work, you will love our newsletter.

Neural Network 108

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Marktechpost

NOVEMBER 16, 2024

Artificial Intelligence (AI) has been making significant strides over the past few years, with the emergence of Large Language Models (LLMs) marking a major milestone in its growth. The author talks about machine intelligence’s historical background and provides beginners with information on how advanced algorithms work.

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Marktechpost

MAY 28, 2024

Traditionally, Recurrent Neural Networks (RNNs) have been used for their ability to process sequential data efficiently despite their limitations in parallel processing. Rapid machine learning advancement has highlighted existing models’ limitations, particularly in resource-constrained environments.

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Marktechpost

JANUARY 23, 2024

There are two major challenges in visual representation learning: the computational inefficiency of Vision Transformers (ViTs) and the limited capacity of Convolutional Neural Networks (CNNs) to capture global contextual information. Join our 36k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and LinkedIn Gr oup.

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Marktechpost

JUNE 30, 2024

Deep learning models like Convolutional Neural Networks (CNNs) and Vision Transformers achieved great success in many visual tasks, such as image classification, object detection, and semantic segmentation. Join our Telegram Channel and LinkedIn Gr oup. If you like our work, you will love our newsletter.

Convolutional Neural Networks 138

Convolutional Neural Networks Neural Network Deep Learning ML 138

Marktechpost

MARCH 30, 2024

The methodology behind Mini-Gemini involves a dual-encoder system that includes a convolutional neural network for refined image processing, enhancing visual tokens without increasing their number. It utilizes patch info mining for detailed visual cue extraction. Join our Telegram Channel , Discord Channel , and LinkedIn Gr oup.

Artificial Intelligence 138

Artificial Intelligence Artificial Intelligence Convolutional Neural Networks Computer Vision 138

Marktechpost

SEPTEMBER 17, 2024

In deep learning, neural network optimization has long been a crucial area of focus. Training large models like transformers and convolutional networks requires significant computational resources and time. One of the central challenges in this field is the extended time needed to train complex neural networks.

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Marktechpost

JULY 26, 2024

Sparsity in neural networks is one of the critical areas being investigated, as it offers a way to enhance the efficiency and manageability of these models. By focusing on sparsity, researchers aim to create neural networks that are both powerful and resource-efficient. Check out the Paper.

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Marktechpost

AUGUST 2, 2024

AI, particularly through ML and DL, has advanced medical applications by automating complex tasks. ML algorithms learn from data to improve over time, while DL uses neural networks to handle large, complex datasets. Further research is required to address these challenges and advance AI’s role in healthcare.

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Marktechpost

FEBRUARY 21, 2024

Graph-based machine learning is undergoing a significant transformation, largely propelled by the introduction of Graph Neural Networks (GNNs). These networks have been pivotal in harnessing the complexity of graph-structured data, offering innovative solutions across various domains.

Neural Network 138

Neural Network Machine Learning ML Artificial Intelligence 138

Marktechpost

JANUARY 13, 2025

Artificial Intelligence (AI) has made significant strides in various fields, including healthcare, finance, and education. Understanding Artificial Intelligence AI refers to the simulation of human intelligence in machines that are designed to think, learn, and adapt. Dont Forget to join our 65k+ ML SubReddit.

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Artificial Intelligence Artificial Intelligence Neural Network Natural Language Processing 82

AI Weekly

SEPTEMBER 12, 2024

In the News AI Stocks: The 10 Best AI Companies Artificial intelligence, automation and robotics are disrupting virtually every industry. reuters.com Here’s what your iPhone 16 will do with Apple Intelligence — eventually Apple Intelligence will miss the launch of the new iPhones, but here’s what’s coming in the iOS 18.1

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Unite.AI

OCTOBER 27, 2024

As artificial intelligence continues to reshape the tech landscape, JavaScript acts as a powerful platform for AI development, offering developers the unique ability to build and deploy AI systems directly in web browsers and Node.js Key Features: Hardware-accelerated ML operations using WebGL and Node.js environments.

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Unite.AI

NOVEMBER 6, 2023

With these advancements, it’s natural to wonder: Are we approaching the end of traditional machine learning (ML)? The two main types of traditional ML algorithms are supervised and unsupervised. Data Preprocessing and Feature Engineering: Traditional ML requires extensive preprocessing to transform datasets as per model requirements.

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Marktechpost

JULY 21, 2024

Large language models (LLMs) have revolutionized the field of artificial intelligence, enabling the creation of language agents capable of autonomously solving complex tasks. introduce agent symbolic learning framework as an innovative approach for training language agents that draws inspiration from neural network learning.

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Artificial Intelligence Artificial Intelligence Neural Network Large Language Models 113

AI Weekly

OCTOBER 10, 2024

Try our Beta Now getessentialspro.com In The News Researcher Who Just Won the Nobel Prize Quit Google to Warn About Evil AI Coming for Us All Both of the men who won this year's Nobel Prize in Physics are artificial intelligence pioneers — and one of them is considered the technology's "godfather." politico.eu politico.eu

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Marktechpost

JUNE 9, 2024

xECGArch uniquely separates short-term (morphological) and long-term (rhythmic) ECG features using two independent Convolutional Neural Networks CNNs. Researchers at the Institute of Biomedical Engineering, TU Dresden, developed a deep learning architecture, xECGArch, for interpretable ECG analysis.

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Marktechpost

SEPTEMBER 10, 2024

The intersection of computational physics and machine learning has brought significant progress in understanding complex systems, particularly through neural networks. Traditional neural networks, including many adapted to consider Hamiltonian properties, often need help with these systems’ high dimensionality and complexity.

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IBM Journey to AI blog

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. However, the growing influence of ML isn’t without complications.

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Analytics Vidhya

APRIL 26, 2022

Introduction on Binary Classification Artificial Intelligence, Machine Learning and Deep Learning are transforming various domains and industries. ML is used in healthcare for a variety of purposes. This article was published as a part of the Data Science Blogathon. One such domain is the field of Healthcare.

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Marktechpost

OCTOBER 4, 2024

Evaluated Models Ready Tensor’s benchmarking study categorized the 25 evaluated models into three main types: Machine Learning (ML) models, Neural Network models, and a special category called the Distance Profile model. Prominent models include Long-Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN).

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Marktechpost

MAY 23, 2024

Artificial Intelligence (AI) has revolutionized multiple facets of modern life, driving significant advancements in technology, healthcare, finance, and beyond. Reinforcement Learning (RL) and Generative Adversarial Networks (GANs) are particularly transformative among the myriad AI paradigms.

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AI Weekly

JULY 13, 2023

In the News Elon Musk unveils new AI company set to rival ChatGPT Elon Musk, who has hinted for months that he wants to build an alternative to the popular ChatGPT artificial intelligence chatbot, announced the formation of what he’s calling xAI, whose goal is to “understand the true nature of the universe.” Powered by pluto.fi

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Marktechpost

OCTOBER 7, 2024

Recurrent neural networks (RNNs) have been foundational in machine learning for addressing various sequence-based problems, including time series forecasting and natural language processing. The post Revisiting Recurrent Neural Networks RNNs: Minimal LSTMs and GRUs for Efficient Parallel Training appeared first on MarkTechPost.

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Marktechpost

OCTOBER 16, 2024

A team of researchers from Huazhong University of Science and Technology, hanghai Jiao Tong University, and Renmin University of China introduce IGNN-Solver, a novel framework that accelerates the fixed-point solving process in IGNNs by employing a generalized Anderson Acceleration method, parameterized by a small Graph Neural Network (GNN).

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Marktechpost

MARCH 23, 2024

Don’t Forget to join our 39k+ ML SubReddit The post FeatUp: A Machine Learning Algorithm that Upgrades the Resolution of Deep Neural Networks for Improved Performance in Computer Vision Tasks appeared first on MarkTechPost. Join our Telegram Channel , Discord Channel , and LinkedIn Gr oup.

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