Artificial Intelligence (AI) systems, such as ChatGPT, have made remarkable progress, yet they still need human assistance for enhancement and accuracy. According to a new study published by Nature, AI systems remain heavily reliant on large datasets curated and labelled by humans to learn and generate their responses.
Despite significant advancements in large language models (LLMs), one major limitation is their inability to train on their content to improve intelligence. Training an AI involves feeding it vast amounts of data to help it understand context, language patterns, and various nuances before fine-tuning based on performance.
