Artificial Intelligence (AI)

Large Language Models (LLMs)

• LLMs are advanced AI models capable of understanding and generating human-like text. They power chatbots, search engines, and virtual assistants.
• They are based on Transformer architecture (e.g., GPT-4, BERT, LLaMA).
• These models process vast amounts of textual data to learn language structures and nuances.
• They can generate text, summarize content, translate languages, and even code.

Machine Learning (ML)

• Machine Learning is a subset of AI that allows machines to learn from data and improve over time without explicit programming.
• Supervised Learning: Uses labelled data to train models.
• Unsupervised Learning: Identifies patterns in unlabelled data.
• Reinforcement Learning: Trains models based on rewards and penalties.

Neural Networks in ML

• Neural Networks (Artificial Neural Networks - ANNs) mimic the human brain’s functioning and improve machine learning capabilities.
• Deep Neural Networks (DNNs): Multiple layers of neurons for complex tasks.
• Convolutional Neural Networks (CNNs): Used in image recognition.
• Recurrent Neural Networks (RNNs): Used in speech and language processing.

Emerging AI Variants

Large Action Models (LAMs)

• AI systems that understand and execute complex actions based on human intent.
• Used in robotics, autonomous systems, and automation.

AI Agents

• AI-powered assistants capable of real-time interactions.
• Engage in multimodal communication (text, voice, images).
• Examples: Virtual AI assistants, self-driving car software.

Ethical Considerations in AI

• Bias in AI: AI models can inherit biases present in training data.
• Privacy Concerns: Data collection and surveillance issues.
• AI in the Workforce: Automation replacing human jobs.
• Deepfake and Misinformation: AI-generated content used for deception.
• Regulations and Governance: Need for responsible AI development.

Future of AI

• AI is evolving rapidly and is expected to revolutionize industries through:
• AI-driven healthcare advancements (early disease detection, robotic surgeries).
• Smarter AI-powered automation in businesses.
• Ethical AI frameworks to ensure responsible AI use.
• Advancements in AGI, bringing machines closer to human-level intelligence.