Category: Artificial Intelligence

Graph Embedding Techniques

Graph embedding techniques are methods used to turn complex networks or graphs, such as social networks or molecular structures, into numerical data that computers can easily process. These techniques translate the relationships and connections within a graph into vectors or coordinates in a mathematical space. By doing this, they make it possible to apply standard…

AI for Forecasting

AI for forecasting uses artificial intelligence techniques to predict future events or trends based on data. It can analyse patterns from large amounts of past information and automatically learn which factors are important. This helps make more accurate predictions for things like sales, weather, or demand without needing manual calculations. Businesses and organisations use AI…

Quantum Data Mapping

Quantum data mapping is the process of transforming classical data into a format that can be used by a quantum computer. This involves encoding everyday information, such as numbers or images, into quantum bits (qubits) so it can be processed in quantum algorithms. The choice of mapping method affects how efficiently the quantum computer can…

Neural Weight Optimization

Neural weight optimisation is the process of adjusting the strength of connections between nodes in a neural network so that it can perform tasks like recognising images or translating text more accurately. These connection strengths, called weights, determine how much influence each piece of information has as it passes through the network. By optimising these…

Model Inference Scaling

Model inference scaling refers to the process of increasing a machine learning model’s ability to handle more requests or data during its prediction phase. This involves optimising how a model runs so it can serve more users at the same time or respond faster. It often requires adjusting hardware, software, or system architecture to meet…

Quantum Algorithm Efficiency

Quantum algorithm efficiency measures how quickly and effectively a quantum computer can solve a problem compared to a classical computer. It focuses on the resources needed, such as the number of steps or qubits required, to reach a solution. Efficient quantum algorithms can solve specific problems much faster than the best-known classical methods, making them…

Graph Signal Processing

Graph Signal Processing is a field that extends traditional signal processing techniques to data structured as graphs, where nodes represent entities and edges show relationships. Instead of working with signals on regular grids, like images or audio, it focuses on signals defined on irregular structures, such as social networks or sensor networks. This approach helps…

Process Automation Metrics

Process automation metrics are measurements used to track and evaluate the effectiveness of automated business processes. These metrics help organisations understand how well their automation is working, where improvements can be made, and if the intended goals are being achieved. Common metrics include time saved, error reduction, cost savings, and process completion rates.