Marktechpost

JULY 7, 2024

Artificial neural networks (ANNs) traditionally lack the adaptability and plasticity seen in biological neural networks. Overall, LNDPs demonstrated superior adaptation speed and learning efficiency, highlighting their potential for developing adaptable and self-organizing AI systems. Check out the Paper.

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Neural Network Artificial Intelligence Artificial Intelligence Robotics 109

Marktechpost

JANUARY 2, 2024

Without this framework, comprehending the model’s structure becomes cumbersome for AI researchers. This tool functions as a viewer specifically designed for neural networks, supporting frameworks like TensorFlow Lite, ONNX, Caffe, Keras, etc.

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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.

Neural Network 116

Neural Network Machine Learning AI Research AI Researcher 116

Marktechpost

OCTOBER 16, 2023

In a recent paper, “Towards Monosemanticity: Decomposing Language Models With Dictionary Learning,” researchers have addressed the challenge of understanding complex neural networks, specifically language models, which are increasingly being used in various applications. Join our AI Channel on Whatsapp.

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Neural Network Large Language Models AI AI 126

Marktechpost

DECEMBER 19, 2023

A new AI research introduces TorchExplorer, a novel AI tool designed for researchers working with unconventional neural network architectures, which provides an interactive and insightful exploration of network layers.

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Neural Network Deep Learning AI Tools AI Research 106

AI Weekly

OCTOBER 10, 2024

Join the AI conversation and transform your advertising strategy with AI weekly sponsorship aiweekly.co reuters.com Sponsor Personalize your newsletter about AI Choose only the topics you care about, get the latest insights vetted from the top experts online! Department of Justice. You can also subscribe via email.

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AI Research AI Researcher Robotics Artificial Intelligence 226

Marktechpost

DECEMBER 21, 2023

ReLoRA accomplishes a high-rank update, delivering a performance akin to conventional neural network training. link] Scaling laws have been identified, demonstrating a strong power-law dependence between network size and performance across different modalities, supporting overparameterization and resource-intensive neural networks.

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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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Neural Network Machine Learning Algorithm AI Research 143

Marktechpost

NOVEMBER 7, 2023

Neural networks have become indispensable tools in various fields, demonstrating exceptional capabilities in image recognition, natural language processing, and predictive analytics. The sum of these vectors is then passed to the next layer, creating a sparse and discrete bottleneck within the network.

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Marktechpost

DECEMBER 17, 2023

Neural networks, the marvels of modern computation, encounter a significant hurdle when confronted with tabular data featuring heterogeneous columns. The essence of this challenge lies in the networks’ inability to handle diverse data structures within these tables effectively.

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Neural Network Deep Learning Data Analysis AI Research 109

Marktechpost

DECEMBER 26, 2023

Conventional methods in this field have heavily relied on deep neural networks (DNNs) due to their exceptional ability to model complex patterns. Reduction of model complexity through neural network sparsification. Gradual decrease of nonlinearity in neural models, optimizing them for efficient use in automatic control.

Neural Network 109

Neural Network Robotics Automation AI Research 109

Marktechpost

NOVEMBER 25, 2023

Addressing this, Jason Eshraghian from UC Santa Cruz developed snnTorch, an open-source Python library implementing spiking neural networks, drawing inspiration from the brain’s remarkable efficiency in processing data. Traditional neural networks lack the elegance of the brain’s processing mechanisms.

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Neural Network Python Deep Learning Artificial Intelligence 127

Marktechpost

SEPTEMBER 8, 2023

It offers a versatile platform not only for neural networks but also for handling a wide range of tasks, including ODEs, SDEs, linear solves, and more. The post Meet Equinox: A JAX library for Neural Networks and sciML appeared first on MarkTechPost. If you like our work, you will love our newsletter.

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Neural Network Machine Learning Data Science AI Research 104

Marktechpost

JULY 12, 2023

Artificial neural networks have advanced significantly over the past few decades, propelled by the notion that more network complexity results in better performance. Modern technology has amazing processing capacity, enabling neural networks to perform these jobs excellently and efficiently.

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Neural Network Computer Vision AI Research AI Researcher 98

Marktechpost

OCTOBER 8, 2023

Yes, the field of study is called Neural networks. Researchers at the University of Copenhagen present a graph neural network type of encoding in which the growth of a policy network is controlled by another network running in each neuron. They call it a Neural Developmental Program (NDP).

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Neural Network Deep Learning Automation Algorithm 128

Marktechpost

DECEMBER 23, 2023

Deep Neural Networks (DNNs) represent a powerful subset of artificial neural networks (ANNs) designed to model complex patterns and correlations within data. These sophisticated networks consist of multiple layers of interconnected nodes, enabling them to learn intricate hierarchical representations.

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Neural Network Machine Learning Natural Language Processing Computer Vision 125

Marktechpost

SEPTEMBER 15, 2023

The traditional theory of how neural networks learn and generalize is put to the test by the occurrence of grokking in neural networks. This behavior is basically grokking in neural networks. Generalizing Solution: With this approach, the neural network is well-suited to generalizing to new data.

Neural Network 125

Neural Network AI Research AI Researcher ML 125

Marktechpost

OCTOBER 22, 2023

In the pursuit of replicating the complex workings of the human sensory systems, researchers in neuroscience and artificial intelligence face a persistent challenge: the disparity in invariances between computational models and human perception. Join our AI Channel on Whatsapp. If you like our work, you will love our newsletter.

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Neural Network Artificial Intelligence Artificial Intelligence AI 142

Marktechpost

SEPTEMBER 1, 2023

These intricate neural networks, with their complex processes and hidden layers, have captivated researchers and practitioners while obscuring their inner workings. The crux of the challenge stems from the inherent complexity of deep neural networks. Check out the Paper.

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Neural Network Deep Learning Categorization Artificial Intelligence 113

Marktechpost

DECEMBER 30, 2023

While PDE discovery seeks to determine a PDE’s coefficients from data, PDE solvers use neural networks to approximate a known PDE’s solution. In recent research, researchers from the University of Cambridge and Cornell University have provided a step-by-step mathematical guide to operator learning.

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Neural Network Deep Learning Computer Vision Machine Learning 127

Marktechpost

JULY 2, 2023

Deep learning hardware has previously been extensively developed in digital electronics, including GPUs, mobile accelerator chips, FPGAs, and large-scale AI-dedicated accelerator systems. What happens if you run a Transformer model with an optical neural network?* appeared first on MarkTechPost.

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Neural Network Deep Learning Computer Vision Machine Learning 104

Marktechpost

DECEMBER 18, 2023

In a groundbreaking study, MIT researchers have delved into the realm of deep neural networks, aiming to unravel the mysteries of the human auditory system. The foundation of this research builds upon prior work where neural networks were trained to perform specific auditory tasks, such as recognizing words from audio signals.

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Neural Network Explainability AI Research AI Researcher 101

Marktechpost

DECEMBER 15, 2023

Complex tasks like text or picture synthesis, segmentation, and classification are being successfully handled with the help of neural networks. However, it can take days or weeks to obtain adequate results from neural network training due to its computing demands. If you like our work, you will love our newsletter.

Neural Network 128

Neural Network Machine Learning Algorithm Deep Learning 128

Marktechpost

DECEMBER 7, 2023

Also, don’t forget to join our 33k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and Email Newsletter , where we share the latest AI research news, cool AI projects, and more. If you like our work, you will love our newsletter.

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Prompt Engineering Large Language Models Prompt Engineer Neural Network 120

Marktechpost

OCTOBER 28, 2023

To address this issue, NYU researchers have introduced an “interpretable-by-design” approach that not only ensures accurate predictive outcomes but also provides insights into the underlying biological processes, specifically RNA splicing. Join our AI Channel on Whatsapp. If you like our work, you will love our newsletter.

Neural Network 125

Neural Network Explainability Machine Learning Python 125

Marktechpost

OCTOBER 13, 2023

In the realm of deep learning, the challenge of developing efficient deep neural network (DNN) models that combine high performance with minimal latency across a variety of devices remains. Join our AI Channel on Whatsapp. If you like our work, you will love our newsletter. We are also on WhatsApp.

Neural Network 130

Neural Network Deep Learning Algorithm Automation 130

Marktechpost

NOVEMBER 26, 2023

Neural network architectures, particularly created and trained for few-shot knowledge the ability to learn a desired behavior from a small number of examples, were the first to exhibit this capability. Since then, a substantial amount of research has examined or documented instances of ICL.

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Neural Network Categorization AI Research AI Researcher 133

Marktechpost

JULY 29, 2023

Join the fastest growing ML Community on Reddit Massive machine learning models that mimic the brain’s information processing are the basis of deep neural networks (DNNs) like the one powering ChatGPT. The discipline of data science is evolving due to the rise of deep neural networks (DNNs).

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Neural Network Machine Learning ChatGPT Big Data 98

Marktechpost

DECEMBER 16, 2023

” This innovative code, which simulates spiking neural networks inspired by the brain’s efficient data processing methods, originates from the efforts of a team at UC Santa Cruz. This publication offers candid insights into the convergence of neuroscience principles and deep learning methodologies.

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Neural Network Deep Learning Python Artificial Intelligence 111

Mlearning.ai

JULY 17, 2023

How taking inspiration from the brain can help us create Neural Networks. Data Scientists spend a lot of time and resources in improving the architecture of their AI Models. As such, there is a lot of research into figuring out different architectures and how different design decisions impact the performance of models.

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Neural Network Convolutional Neural Networks Machine Learning Data Scientist 52

Marktechpost

AUGUST 31, 2024

Deep neural network training can be sped up by Fully Quantised Training (FQT), which transforms activations, weights, and gradients into lower precision formats. They have experimented with their approach by optimizing popular neural network models, like VGGNet-16 and ResNet-18, using various datasets.

Neural Network 117

Neural Network AI Research AI Researcher Algorithm 117

Marktechpost

SEPTEMBER 26, 2023

Microsoft researchers propose a groundbreaking solution to these challenges in their recent “Neural Graphical Models” paper presented at the 17th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2023). If you like our work, you will love our newsletter.

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Neural Network Categorization Data Scientist Data Analysis 135

Marktechpost

DECEMBER 19, 2023

Natural language processing, conversational AI, time series analysis, and indirect sequential formats (such as pictures and graphs) are common examples of the complicated sequential data processing jobs involved in these. Recurrent Neural Networks (RNNs) and Transformers are the most common methods; each has advantages and disadvantages.

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Neural Network Natural Language Processing Artificial Intelligence Artificial Intelligence 135

Marktechpost

SEPTEMBER 30, 2023

This redundancy consumes extra energy and leads to an expanded chip footprint, raising concerns about space efficiency and scalability in large-scale optical neural networks (ONNs) and optimization problem solvers. Efforts to address this issue have been made, with solutions such as a pseudo-real-value MZI mesh.

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Neural Network Explainability AI Research AI Researcher 73

Marktechpost

DECEMBER 16, 2023

Researchers from various universities in the UK have developed an open-source artificial intelligence (AI) system, X-Raydar, for comprehensive chest x-ray abnormality detection. The dataset, spanning 13 years, included 2,513,546 chest x-ray studies and 1,940,508 usable free-text radiological reports.

Neural Network 96

Neural Network Auto-classification NLP Natural Language Processing 96

Marktechpost

NOVEMBER 26, 2023

Also, don’t forget to join our 33k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and Email Newsletter , where we share the latest AI research news, cool AI projects, and more. If you like our work, you will love our newsletter.

Neural Network 120

Neural Network AI Research AI Researcher ML 120

Marktechpost

AUGUST 21, 2023

The optical neural networks optimize the light and offer solutions to these problems by enabling high-speed, parallel, and energy-efficient consumption. The pluggable Diffractive neural networks act as a solution to the limitations of traditional deep learning by leveraging optical neural networks.

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Neural Network Deep Learning Machine Learning AI Research 98