Part 6/9:
The past year has seen an explosion in interest around large language models following the release of ChatGPT. These models have captivated users with their ability to generate text-based responses that seem increasingly coherent and contextually relevant. Many startups have emerged, actively integrating AI APIs into their products, demonstrating both commercial interest and a playful exploration of AI capabilities.
However, despite their amazing abilities, these models are not foolproof. They are prone to learning biases from training data and may generate misleading or harmful information. To mitigate these risks, AI developers employ strategies akin to public education methods, where real people evaluate and refine the models' responses.