Artificial intelligence in cybersecurity is a must-have combination for organizations nowadays. Artificial intelligence (AI) assists under-resourced security operations analysts in keeping pace with attacks, and this technology will have a greater role as cyberattacks increase in volume and complexity. AI technologies, such as machine learning and natural language processing that

Quantum Machine Learning (QML) is a young theoretical research discipline exploring the interplay of quantum computing and machine learning approaches. In the last couple of years, several experiments demonstrated the potential advantages of quantum computing for machine learning. The overall goal of Quantum Machine Learning is to make things move

Neuromorphic computing is a growing computer engineering approach that models and develops computing devices inspired by the human brain. Neuromorphic engineering focuses on using biology-inspired algorithms to design semiconductor chips that will behave similarly to a brain neuron and then work in this new architecture. What is neuromorphic computing? Neuromorphic

Hyperautomation is a framework and set of sophisticated technologies for scaling automation in enterprises. The term “automate everything that can be automated” is used to describe the concept of hyperautomation. Organizations that use hyperautomation want to reduce operational complexity across their company by applying artificial intelligence (AI), robotic process automation

Machine learning engineering aims to apply software engineering and data science methods to turn machine learning models into usable functions for products and consumers. Artificial intelligence technology is created using machine learning engineering with massive data sets. Machine learning engineering develops AI systems and algorithms to learn and ultimately make

Last year, San Francisco-based research lab OpenAI released Codex, an AI model for translating natural language commands into app code. The model, which powers GitHub’s Copilot feature, was heralded at the time as one of the most powerful examples of machine programming, the category of tools that automates the development and maintenance of

YouTube is the second-largest social media network and search engine on the planet, with over 2.3 billion active users.  Since its inception in 2005, YouTube has grown into a tech behemoth. It is now a hub for hobby content creators, professional influencers, and social media marketing specialists.  Over 12 million

For decades, managing data essentially meant collecting, storing, and occasionally accessing it. That has all changed in recent years, as businesses look for the critical information they can pull from the massive amounts of data generated, accessed, and stored in myriad locations, from corporate data centers to the cloud and

Google today released TensorFlow Graph Neural Networks (TF-GNN) in alpha, a library designed to make it easier to work with graph-structured data using TensorFlow, its machine learning framework. Used in production at Google for spam and anomaly detection, traffic estimation, and YouTube content labeling, Google says that TF-GNN is designed to “encourage

Our world revolves around data. Data science, machine learning, and AI have become some of the most critical technologies and industries in the 21st Century, penetrating almost every aspect of our lives, including fitness and wellbeing. The impact of technology on fitness industry On the consumer side, this technology triumvirate