Visual grounding
Using the source input as ground truth will help trust the system and makes it easy to interpret its process and what might have gone wrong.
When checking data, I want to be able to see how the system arrived at its answer, so I can trust the data and identify any potential errors in the process.
- AI Transparency and Explainability: Make AI systems transparent and understandable by explaining how and why decisions are made.
- Multimodal Context: In this example we used the context of an image of a receipt, but it can also include other modalities, such as audio.
More of the Witlist
Referencing nested data from your database in the form of tags can simplify the creation of elaborate prompt formulas.
You should control how products and services (not) access your data through a manageable profile. This allows you to create a relevant context across many platforms while maintaining control.
An intelligent assistant that analyzes emails to identify questions and feedback requests, providing pre-generated response options and converting them into complete and contextually appropriate replies.
Textual information often misses intuitive cues for understanding relationships between ideas. AI can clarify these connections, making complex information easier to grasp quickly.
Presenting multiple outputs helps users explore and identify their preferences and provides valuable insights into their choices, even enabling user feedback for model improvement.
When an observation is added to the context from an implicit action and a prediction is made, users should be able to easily evaluate and dismiss it.