Here are a few buzzwords that I often hear in GenAI. Hope this serves as a useful glossary:
Neural Networks - Neural networks are computer algorithms inspired by the human brain, which learn from data and improve their performance over time.
Foundation Model - A Foundation Model is a type of machine learning model that is pre-trained on a large amount of data to understand general patterns and knowledge. It serves as a base or foundation for developing more specialized models by fine-tuning it on specific tasks or datasets.
GenAI - Generative AI refers to a type of artificial intelligence that can create new data that is similar to, but not exactly the same as, the data it was trained on. It essentially generates new examples or ideas, rather than just analyzing existing data. Examples include creating new images, music, or text.
Large Language Models (LLM) - Large Language Models (LLMs) are advanced AI models trained on a vast amount of text data. They are capable of understanding and generating human-like text, making them useful for various applications like translation, question answering, and text summarization.
Hallucinations - AI, "hallucinations" refer to the instances where the model generates incorrect or nonsensical information that is not present in the input data. For example, a language model might generate a sentence that doesn't make sense or is factually wrong. It's called "hallucinating" because the model is essentially "seeing" something that isn't there.
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