Part 7/14:
Tuning the models through prompt engineering and embedding techniques can reduce hallucinations, but not eliminate them entirely. Striking the right balance between accuracy and generating insightful responses remains a key challenge.
Another critical issue is bias. As with all AI systems trained on human-generated data, biases—racial, gender, or cultural—are ingrained and can manifest in outputs. Addressing bias and ensuring explainability (i.e., understanding how decisions are made) are ongoing societal and technological imperatives.
Limitations: When Does Generative AI Fall Short?
While gen AI excels at understanding language and context, it is less adept at other types of analytical tasks: