Category: Artificial Intelligence

Invariant Risk Minimization

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Model Optimisation Techniques, Model Training & Tuning

Invariant Risk Minimisation is a machine learning technique designed to help models perform well across different environments or data sources. It aims to find patterns in data that stay consistent, even when conditions change. By focusing on these stable features, models become less sensitive to variations or biases present in specific datasets.

Continual Learning

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Deep Learning, Model Training & Tuning

Continual learning is a method in artificial intelligence where systems are designed to keep learning and updating their knowledge over time, instead of only learning once from a fixed set of data. This approach helps machines adapt to new information or tasks without forgetting what they have already learned. It aims to make AI more…

Memory-Augmented Neural Networks

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Deep Learning, Embeddings & Representations

Memory-Augmented Neural Networks are artificial intelligence systems that combine traditional neural networks with an external memory component. This memory allows the network to store and retrieve information over long periods, making it better at tasks that require remembering past events or facts. By accessing this memory, the network can solve problems that normal neural networks…

Dynamic Neural Networks

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Deep Learning, Model Training & Tuning

Dynamic Neural Networks are artificial intelligence models that can change their structure or operation as they process data. Unlike traditional neural networks, which have a fixed sequence of layers and operations, dynamic neural networks can adapt in real time based on the input or the task at hand. This flexibility allows them to handle a…

Neural Module Networks

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Deep Learning, Multimodal AI

Neural Module Networks are a type of artificial intelligence model that break down complex problems into smaller tasks, each handled by a separate neural network module. These modules can be combined in different ways, depending on the question or task, to produce a final answer or result. This approach is especially useful for tasks like…

Knowledge Amalgamation

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Data Science, Model Training & Tuning

Knowledge amalgamation is the process of combining information, insights, or expertise from different sources to create a more complete understanding of a subject. This approach helps address gaps or inconsistencies in individual pieces of knowledge by bringing them together into a unified whole. It is often used in fields where information is spread across multiple…

Model Compression

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Deep Learning, Model Optimisation Techniques

Model compression is the process of making machine learning models smaller and faster without losing too much accuracy. This is done by reducing the number of parameters or simplifying the model’s structure. The goal is to make models easier to use on devices with limited memory or processing power, such as smartphones or embedded systems.

Data Augmentation Strategies

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Data Science, Model Training & Tuning

Data augmentation strategies are techniques used to increase the amount and variety of data available for training machine learning models. These methods involve creating new, slightly altered versions of existing data, such as flipping, rotating, cropping, or changing the colours in images. The goal is to help models learn better by exposing them to more…

Teacher-Student Models

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Deep Learning, Model Training & Tuning

Teacher-Student Models are a technique in machine learning where a larger, more powerful model (the teacher) is used to train a smaller, simpler model (the student). The teacher model first learns a task using lots of data and computational resources. Then, the student model learns by imitating the teacher, allowing it to achieve similar performance…

Sparse Coding

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Embeddings & Representations, Model Optimisation Techniques

Sparse coding is a technique used to represent data, such as images or sounds, using a small number of active components from a larger set. Instead of using every possible feature to describe something, sparse coding only uses the most important ones, making the representation more efficient. This approach helps computers process information faster and…