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

JANUARY 20, 2025

AI and ML are expanding at a remarkable rate, which is marked by the evolution of numerous specialized subdomains. Recently, two core branches that have become central in academic research and industrial applications are Generative AI and Predictive AI. Ian Goodfellow et al.

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Marktechpost

APRIL 6, 2024

In deep learning, a unifying framework to design neural network architectures has been a challenge and a focal point of recent research. The researchers tackle the core issue of the absence of a general-purpose framework capable of addressing both the specification of constraints and their implementations within neural network models.

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Towards AI

JANUARY 29, 2025

Last Updated on January 29, 2025 by Editorial Team Author(s): Vishwajeet Originally published on Towards AI. How to Become a Generative AI Engineer in 2025? From creating art and music to generating human-like text and designing virtual worlds, Generative AI is reshaping industries and opening up new possibilities.

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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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AI News

DECEMBER 15, 2023

In an interview at AI & Big Data Expo , Alessandro Grande, Head of Product at Edge Impulse , discussed issues around developing machine learning models for resource-constrained edge devices and how to overcome them. The end-to-end development platform seamlessly integrates with all major cloud and ML platforms.

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Analytics Vidhya

FEBRUARY 24, 2023

Or maybe you’re curious about how to implement a neural network using PyTorch. Or perhaps you want to explore the exciting world of AI and its career opportunities? Introduction Are you interested in learning about Apache Spark and how it has transformed big data processing?

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Marktechpost

JANUARY 13, 2024

The challenge of interpreting the workings of complex neural networks, particularly as they grow in size and sophistication, has been a persistent hurdle in artificial intelligence. The traditional methods of explaining neural networks often involve extensive human oversight, limiting scalability.

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Unite.AI

FEBRUARY 6, 2025

AI and machine learning (ML) are reshaping industries and unlocking new opportunities at an incredible pace. There are countless routes to becoming an artificial intelligence (AI) expert, and each persons journey will be shaped by unique experiences, setbacks, and growth. The legal considerations of AI are a given.

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Artificial Intelligence Artificial Intelligence ML Responsible AI 165

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

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

NOVEMBER 16, 2024

Learning computer vision is essential as it equips you with the skills to develop innovative solutions in areas like automation, robotics, and AI-driven analytics, driving the future of technology. The program also covers practical applications like image captioning, facial keypoint detection, and skin cancer detection using neural networks.

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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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Neural Network Python Deep Learning Artificial Intelligence 138

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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Neural Network Machine Learning Algorithm Robotics 132

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. According to Fortune Business Insights, the global AI and blockchain market value is projected to grow to $930 million by 2027 , compared to $220.5

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AI Weekly

SEPTEMBER 12, 2024

Join the AI conversation and transform your advertising strategy with AI weekly sponsorship aiweekly.co In the News AI Stocks: The 10 Best AI Companies Artificial intelligence, automation and robotics are disrupting virtually every industry. Powered by dotai.io Welcome Interested in sponsorship opportunities?

Convolutional Neural Networks 264

Convolutional Neural Networks Robotics Neural Network Artificial Intelligence 264

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.

Neural Network 120

Neural Network BERT Machine Learning Artificial Intelligence 120

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

Neural Network Inference Engine ML Artificial Intelligence 108

Marktechpost

FEBRUARY 9, 2025

Meta AIs research into Brain2Qwerty presents a step toward addressing this challenge. Meta AI introduces Brain2Qwerty , a neural network designed to decode sentences from brain activity recorded using EEG or magnetoencephalography (MEG). Dont Forget to join our 75k+ ML SubReddit.

Deep Learning 96

Deep Learning Neural Network Conversational AI AI 96

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.

Convolutional Neural Networks 145

Convolutional Neural Networks Neural Network Computer Vision NLP 145

Unite.AI

NOVEMBER 6, 2023

In recent years, Generative AI has shown promising results in solving complex AI tasks. Modern AI models like ChatGPT , Bard , LLaMA , DALL-E.3 Moreover, Multimodal AI techniques have emerged, capable of processing multiple data modalities, i.e., text, images, audio, and videos simultaneously. What are its Limitations?

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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. Optimizing the training process is critical for deploying AI applications more quickly and efficiently.

Neural Network 113

Neural Network Machine Learning Convolutional Neural Networks Natural Language Processing 113

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! Welcome Interested in sponsorship opportunities? politico.eu

AI Research 278

AI Research AI Researcher Robotics Artificial Intelligence 278

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

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 theage.com.au

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Neural Network Robotics ChatGPT Computer Vision 242

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.

Neural Network 117

Neural Network Deep Learning Python ML 117

AI News

JULY 27, 2023

Gcore has joined forces with UbiOps and Graphcore to introduce a groundbreaking service catering to the escalating demands of modern AI tasks. This strategic partnership aims to empower AI teams with powerful computing resources on-demand, enhancing their capabilities and streamlining their operations.

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Unite.AI

MARCH 15, 2024

In 2023, the competition in the AI sector reached unprecedented heights, fueled by real, mind-bending breakthroughs. In the ever-evolving landscape of the tech industry, Nvidia continues to solidify its position as the key player in AI infrastructure. Challenging Nvidia, with its nearly $1.5

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Marktechpost

JUNE 9, 2024

Explainable AI (xAI) methods, such as saliency maps and attention mechanisms, attempt to clarify these models by highlighting key ECG features. xECGArch uniquely separates short-term (morphological) and long-term (rhythmic) ECG features using two independent Convolutional Neural Networks CNNs.

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Convolutional Neural Networks Neural Network Deep Learning Big Data 125

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

APRIL 17, 2024

Don’t Forget to join our 40k+ ML SubReddit Want to get in front of 1.5 Million AI Audience? Work with us here The post Google AI Proposes TransformerFAM: A Novel Transformer Architecture that Leverages a Feedback Loop to Enable the Neural Network to Attend to Its Latent Representations appeared first on MarkTechPost.

Neural Network 138

Neural Network Deep Learning AI AI 138

Unite.AI

AUGUST 28, 2024

The company implements AI to the task of preventing and detecting malware. The term “AI” is broadly used as a panacea to equip organizations in the battle against zero-day threats. ML is unfit for the task. Not all AI is equal. Unlike ML, DL is built on neural networks, enabling it to self-learn and train on raw data.

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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).

Neural Network 104

Neural Network Machine Learning Convolutional Neural Networks Categorization 104

Unite.AI

SEPTEMBER 4, 2024

Aman Sareen is the CEO of Aarki , an AI company that delivers advertising solutions that drive revenue growth for mobile app developers. What key experiences have shaped your approach to AI and AdTech? Think of it as the precursor to the hyper-localized, AI-driven targeting we see today.

Neural Network 261

Neural Network Machine Learning ML Continuous Learning 261

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

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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