Generative AI: Shaping Trends in Industries, Identity, Data
The Artificial Intelligence (AI) industry has experienced tremendous growth and buzz, with Generative AI leading the charge. However, it’s crucial to acknowledge that these impressive technologies are only part of the larger puzzle. In many situations, businesses require different technologies to achieve their desired outcomes.
To better understand the different areas of AI, it’s helpful to clarify some of the terminology. NLT (Natural Language Technology) is an umbrella term that encompasses NLP (Natural Language Processing), NLU (Natural Language Understanding), and NLG (Natural Language Generation), as well as related fields such as computational linguistics and language modeling. NLP deals with the interaction between computers and humans using natural language and allows computers to process, analyze, and understand human language. NLU focuses on a computer’s ability to understand human language in a similar way to humans. Generative AI, or NLG, concentrates on the generation of text by computers and has various applications, including automating routine tasks for businesses and helping artists generate new ideas. LLM (Large Language Model), the technology behind most generative AI tools we use, is an AI model trained on a vast corpus of text that uses deep neural networks to capture patterns and relationships in text data.
