Quantum computing is a type of computing based on quantum mechanics that employs qubits, which can represent both 0s and 1s simultaneously. The main difference between quantum and classical computing is that quantum computers can perform many calculations at once, making them more reliable for complex applications such as artificial intelligence (AI).

Machine learning has become a fundamental part of many large businesses and is allowing them to make data-driven decisions with greater accuracy. Sectors like banking and finance, healthcare, manufacturing, transportation, and retail are undergoing significant transformations due to the implementation of machine learning. The latest advancements in this technology have brought about a revolution that was once inconceivable.

Malware of different families often share specific behavioral patterns that can be studied and identified through Machine learning’s static and dynamic analysis. Static analysis involves the study of malicious files’ content without executing them. On the other hand, in dynamic analysis the behavioral aspects of malicious files are analyzed by executing tasks like function call monitoring, information flow tracking, and dynamic binary instrumentation. Through machine learning the static and dynamic artefacts of the malware can be used to predict the evolution of modern malware structure which can then empower systems to detect more complex malware attacks that otherwise are exceedingly difficult to predict by traditional methods.

While Virtual Reality (VR) has long passed the hype of being called “Futuristic Technology”, now the solutions built around it are solving many real-world problems. It has delivered use cases in many industries including healthcare, entertainment, and tourism, and has become a key component of many businesses’ new product development plans.

The wall between the real and virtual world is breaking

Robust transport infrastructure for goods and population is seen as a key driver for macroeconomic growth. Digital technologies like computer vision-based AI and machine learning can help monitor the quality and structural integrity of a vastly distributed network of roads, railway lines, bridges, transit stations, and cargo hubs. That helps in planning maintenance actions to ensure 100% availability of assets on critical network paths at optimal operational costs.