Machine learning
The global GPU server market is expected to witness significant growth, driven by the increasing demand for high-performance computing, machine learning, and deep learning applications. According to a report by MarketsandMarkets, the market is projected to reach $730.56 billion by 2030, growing at a Compound Annual Growth Rate (CAGR)
Machine learning
The tinyML market is expected to grow significantly over the next five years, driven by the proliferation of IoT, imperative for edge intelligence, maturation of enabling hardware and software ecosystems, and increasing primacy of data privacy, security, and low latency. The market is forecasted to reach USD 5.66 billion
Machine learning
Researchers at Kafr El-Shaikh University in Egypt have developed an efficient IoT-based framework for predicting crop damage in smart agricultural systems. The framework uses Internet of Things (IoT) sensor data and advanced machine learning and ensemble learning techniques to predict crop health status. The primary objective of the framework is
Machine learning
Online entertainment platforms are leveraging artificial intelligence to create transformative experiences for users, drive competitive advantages, and optimize operational efficiency. By harnessing the power of machine learning, AI, and natural language processing, platforms like Bigclash Casino Online and others are revolutionizing the industry. Key Takeaways: * AI-powered recommendation engines enable sophisticated
Machine learning
The Bharat Sanchar Nigam Limited (BSNL) has announced the nationwide deployment of its network-level anti-spam and anti-smishing security system for mobile users. The system, developed in collaboration with Tanla, uses AI, machine learning, and other technologies to detect threats in real-time and block phishing and suspicious URLs within SMS messages
Machine learning
Bharat Sanchar Nigam Limited (BSNL) has signed agreements with four global tech giants - Nokia, Ericsson, Qualcomm, and Cisco - to roll out advanced training programs in 5G, artificial intelligence (AI), machine learning (ML), networking, and digital technologies. The partnerships aim to establish a Telecom Innovation, Research and Training Centre
Machine learning
Researchers from the Federal University of Mato Grosso do Sul (UFMS) have conducted a study to investigate the use of machine learning algorithms, specifically Support Vector Machines (SVMs), to predict soybean seed germination. The study involved the collection and analysis of a database of 1,000 soybean seed analysis samples,
Machine learning
The global GPU server market is projected to experience significant growth, driven by the increasing adoption of machine learning and deep learning algorithms, as well as the need for high computing power in various industries such as healthcare, research, and autonomous systems. The market is expected to reach $730.56
Machine learning
A new research study has demonstrated the effectiveness of a hybrid-powered dryer in reducing the weight, moisture content, and microbial load of Ganoderma lucidum mushrooms. The system, which incorporates an Internet of Things (IoT) platform, enables real-time monitoring of temperature, time, and humidity. Researchers from Rajamangala University of Technology Lanna
Machine learning
Researchers from the University of California San Francisco (UCSF) have made new findings in the field of artificial intelligence. According to their research, a novel machine learning (ML) algorithm was developed to predict early and late hospital discharge in patients who have undergone transcatheter aortic valve replacement (TAVR). The study
Machine learning
Researchers from Manipal University in Rajasthan, India, have developed a novel genetic algorithm, called Inverted Swap crossover, for automated machine learning (AutoML) in Convolutional Neural Networks (CNNs). This innovative technique is designed to optimally select the best convolutional and pooling layers, activation functions, and other architectural decisions for image classification
Machine learning
A recent research study published in PLOS Computational Biology has shed new light on the challenges of identifying novel and functional RNA structures. The study, conducted by researchers at New York University (NYU), introduces a computational topology-based approach with unsupervised machine-learning algorithms to estimate the database size and content of
