Articles

Wag - an AI dog walking app

Wag uses AI to provide a personalised dog walking service

AI Learning Types - Reinforcement Learning

In reinforcement learning, AI systems learn by interacting with their environment and receiving feedback in the form of rewards or penalties. The AI system aims to maximise the cumulative reward over time by choosing the optimal sequence of actions.

AI Learning Types - Unsupervised Learning

Unsupervised learning can find interesting patterns in your data

Transfer Learning

Transfer learning is a technique in machine learning where a model trained on one task is repurposed on a related task, leveraging the knowledge it has already gained to improve learning efficiency and performance.

AI Algorithm

Machine learning algorithms enable an AI system to learn from data and improve its performance over time.

AI in Formula One Racing: Accelerating Performance and Safety on the Track

As the Azerbaijan Formula One race approaches, it's clear that AI has become an integral part of the sport. By harnessing the power of data, AI is transforming racing, helping teams optimise performance, develop winning strategies, and ensure driver safety.

Memory in Artificial Intelligence: The Key to Advanced Learning

AI vs. ML: The difference between Artificial Intelligence and Machine Learning

Machine learning (ML) is a specific method within the broader field of artificial intelligence (AI). Deciding whether to use AI or ML depends on the problem, data availability, and adaptability required. Recognising the differences helps unlock their full potential to drive innovation.

Understanding Neural Networks in AI

Natural Language Processing: A Key Component of AI

Natural Language Processing (NLP) is a subfield of AI that focuses on understanding and generating human language. It encompasses tasks like text analysis, machine translation, and sentiment analysis, transforming how we interact with technology and opening up new possibilities.

AI basics

10 things you need to know about Artificial Intelligence

Naming your startup

Unlock the secret to business success through the power of a name, and explore the critical role it plays in the world of branding and marketing."

AI Study Buddies: Revolutionizing Education or Crossing Copyright Boundaries?

Explore how AI "study buddies" could transform education while raising critical questions about intellectual property rights and the use of copyrighted materials in AI development.

AI School Reports

Startup Real Fast Reports combines AI efficiency with a teacher's personal touch to create school reports for pupils

Training AI Systems - Learning Types

Learning Types refer to the fundamental ways in which an AI model learns from data. This category includes: Supervised Learning, Unsupervised Learning and Reinforcement Learning

Advanced Training of AI Systems - Learning Paradigms

Learning Strategies or Paradigms refer to the higher-level strategies that an AI model can use to enhance its learning process, often regardless of the learning type being used. This category includes: Transfer Learning, Multi-task Learning, Active Learning and Semi-Supervised Learning.

AI Algorithms: Traditional Machine Learning vs. Deep Learning

In the world of artificial intelligence (AI), algorithms are the backbone that drives the learning and decision-making capabilities of AI models. Broadly, these algorithms fall into two categories: Traditional Machine Learning Algorithms and Deep Learning Algorithms.

Episodic memory in AI

Episodic memory is the capacity to recall specific occurrences. Incorporating this human-like ability to recall past experiences can enhance AI performance and create adaptable, context-aware AI systems.

Replay Memory in AI

Replay memory is a machine learning technique that stores and reuses past experiences to enhance an agent's decision-making. Common in reinforcement learning, it helps agents learn from diverse situations, improving performance in applications like game AI, robotics, and autonomous vehicles.

Hyperparameter Tuning in AI: Enhancing Model Performance

Hyperparameter tuning optimises AI model performance by finding the best parameter settings. It improves accuracy, saves resources, and is crucial for AI development. It also prevents overfitting, where a model learns to perform exceptionally well on the training data but fails with new unseen data

Swarm Intelligence

Swarm intelligence is a captivating approach in artificial intelligence that mimics the collective behavior of social insects, enabling groups of simple agents to collaboratively solve complex problems with remarkable efficiency and adaptability.

Multi-Agent Systems: Collaborative Intelligence in Action

Multi-agent systems (MAS) embody an innovative approach in artificial intelligence, where multiple autonomous agents collaborate and interact to address complex problems, showcasing their adaptability and efficiency across a wide range of applications, such as robotics, smart grids, and e-commerce.

AI Agents

AI agents are autonomous, intelligent entities that use machine learning and natural language processing to perform tasks, detect fraud, and provide customer service. They are transforming industries and critical for businesses in the digital age.

AI Healthcare Bias

When AI Sees More Than Skin Deep: A Lesson in Bias and Interpretation

Understanding Intelligence in AI: From Narrow AI to Artificial General Intelligence

As we continue to develop and integrate AI into various aspects of our lives, it's crucial to recognize the distinctions between the two primary forms of intelligence: Artificial General Intelligence (AGI) and Narrow AI.