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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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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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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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

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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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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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

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 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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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 environments. LangChain.js TensorFlow.js TensorFlow.js environments. What distinguishes TensorFlow.js

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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.

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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.

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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

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.

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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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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

DECEMBER 5, 2024

Researchers from IBM Research, Tel Aviv University, Boston University, MIT, and Dartmouth College have proposed ZipNN, a lossless compression technique specifically designed for neural networks. ZipNN can compress neural network models by up to 33%, with some instances showing reductions exceeding 50% of the original model size.

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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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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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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.

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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?

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IBM Journey to AI blog

FEBRUARY 14, 2024

When thinking of artificial intelligence (AI) use cases, the question might be asked: What won’t AI be able to do? The easy answer is mostly manual labor, although the day might come when much of what is now manual labor will be accomplished by robotic devices controlled by AI. We’re all amazed by what AI can do.

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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).

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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

DECEMBER 13, 2024

Neural networks have become foundational tools in computer vision, NLP, and many other fields, offering capabilities to model and predict complex patterns. This understanding is essential for designing more efficient training algorithms and enhancing the interpretability and robustness of neural networks.

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Marktechpost

NOVEMBER 25, 2024

Researchers have developed alternative learning mechanisms tailored for spiking neural networks (SNNs) and neuromorphic hardware to address these challenges. A spiking neural network implements these computations using a leaky integrate-and-fire neuron model on Intel’s Loihi chip.

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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

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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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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

AUGUST 5, 2024

This model incorporates a static Convolutional Neural Network (CNN) branch and utilizes a variational attention fusion module to enhance segmentation performance. Hausdorff Distance Using Convolutional Neural Network CNN and ViT Integration appeared first on MarkTechPost. Dice Score and 27.10 Dice Score and 27.10

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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

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.

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Marktechpost

DECEMBER 1, 2024

Graph Neural Networks (GNNs) are a rapidly advancing field in machine learning, specifically designed to analyze graph-structured data representing entities and their relationships. These networks have been widely used in social network analysis, recommendation systems, and molecular data interpretation applications.

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Marktechpost

NOVEMBER 16, 2024

Researchers from Google Research, Mountain View, CA, and Google Research, New York, NY have proposed a novel method called Learned Augmented Residual Layer (LAUREL), which revolutionizes the traditional residual connection concept in neural networks. Don’t Forget to join our 55k+ ML SubReddit.

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Marktechpost

OCTOBER 31, 2024

It elicits the need to design models that allow researchers to understand how AI predictions are achieved so they can trust them in decisions involving materials discovery. XElemNet, the proposed solution, employs explainable AI techniques, particularly layer-wise relevance propagation (LRP), and integrates them into ElemNet.

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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 theage.com.au

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