Articles

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.

Understanding Neural Networks in AI

AI vs. ML vs. RBL: The differences between Artificial Intelligence and Machine Learning and Rules Based Learning

Artificial intelligence and machine learning are two terms that are often used interchangeably, but they are actually quite different.

Memory in Artificial Intelligence: The Key to Advanced Learning

AI School Reports

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

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.

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 Learning and Training Approaches

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

AI Algorithms: Traditional Machine Learning vs. Deep Learning

While traditional machine learning algorithms excel with structured data and well-defined problems, deep learning models use neural networks to process and learn from unstructured data.

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.

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

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

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.

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.

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 are critical for businesses in the digital age.

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.

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.

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.

AI Healthcare Bias

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

GPT-4 link up with Morgan Stanley

GPT-4 and Morgan Stanley's innovative partnership is revolutionising the financial industry by enhancing customer experiences, streamlining internal processes, and improving risk management.

AI Collaboration: GPT-4 and Be My Eyes

With the release of GPT4 we look at the Revolutionary Collaboration between GPT-4 and Be My Eyes - a global community aimed at assisting visually impaired individuals.

Virtual Humans

Soul Machines' mission is to "humanize technology" by creating AI-powered digital humans that can interact with people in a natural and empathetic way

AlphaGo

AlphaGo beat the Go world champion, Lee Sedol by 4 games to 1 in 2016

AI Open Code

"Not what I intended at all" Elon Musk's response to OpenAI's transformation from nonprofit to $30billion company.

Vision AI Startup

CrowdAI enables users to unlock the value hidden in their growing number of images and video