Chatbots and Large Language Models
Machine learning has many applications, and one important area is language understanding and generation. Chatbots and Large Language Models (LLMs) are AI systems designed to generate human-like text by predicting what word is most likely to come next based on patterns learned from massive text datasets.
Rather than understanding language the way humans do, LLMs analyze relationships between words, phrases, and context. They assign probabilities to possible next words and use complex mathematical calculations to select the most likely sequence. By repeating this process many times, the system produces responses that sound coherent, relevant, and conversational. For more information on how these systems are trained, visit our Machine Learning page.
For example, chatbots like ChatGPT can:
Answer questions in natural language
Summarize information or write short essays
Generate code or creative writing prompts
Some chatbots also improve their responses by learning from user interactions, which makes it important to be careful about what personal information you share with AI chatbots. For more information visit our Privacy, Consent and Data Responsibility page.
Limitations of Chatbots and Large Language Models
Although chatbots and large language models can be powerful tools, they have important limitations. These systems do not “know” facts or understand meaning in the human sense. Instead, they generate responses by identifying patterns in data and predicting what text is most likely to come next.
Because of this, AI-generated output may sometimes be inaccurate, incomplete, or misleading, even when it sounds confident or well written. These limitations are not always obvious, which makes it important to verify AI output when accuracy matters.
Common issues such as hallucinations, overtrust, and the use of AI in high-stakes situations are explored more deeply in our Hallucinations, Misinformation, and Overtrust section as part of our AI Ethics and Bias series.