Artificial intelligence (AI) is a prevalent topic in tech, with companies frequently discussing their advancements in AI while marketing and advertisers seem to be debasing it. However, the jargon-filled nature of the field can make understanding these developments challenging. To clarify, here's a summary of key AI terms and concepts:
- Artificial Intelligence (AI) is the discipline of creating computer systems that can think like humans. Often used as a marketing buzzword, AI's definition can vary. Companies like Google use AI to improve products and develop tools like Gemini.
- Machine Learning (ML): A subset of AI where systems learn from data to make predictions. Critical to many AI technologies.
- Artificial General Intelligence (AGI): AI as smart or smarter than humans. It's a powerful yet potentially frightening prospect.
- Generative AI: AI that generates new content (text, images, code). Examples include ChatGPT and Google’s Gemini.
- Hallucinations: Errors where AI generates incorrect or nonsensical information due to flawed training data.
- Bias: AI systems can inherit biases from their training data, leading to discriminatory outcomes.
- AI Models: Trained on data to perform tasks autonomously. Types include:
- Training: The process of teaching AI models using data to recognize patterns and make predictions.
- Parameters: Variables learned during training determine how inputs are converted to outputs.
- Natural Language Processing (NLP): This technology enables machines to understand and generate human language (e.g., ChatGPT, Whisper).
- Inference: The generation of outputs by AI models in response to queries.
- Tokens: Chunks of text used by AI models to analyze and generate responses.
- Neural Networks: Computer architectures that process data similarly to the human brain, crucial for learning patterns.
- Transformer: A neural network architecture using "attention" mechanisms to relate parts of sequences, enhancing model training speed and capability (e.g., the T in ChatGPT).
- RAG (Retrieval-Augmented Generation): Enhances AI accuracy by using external data to inform responses.
