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
Guide users to understand what makes a good prompt will help them learn how to craft prompts that result in better outputs.
Automatic model switching in AI can boost efficiency by selecting the most appropriate model for each query, ensuring a balance between quick and accurate responses.
Starting with a blank canvas can be intimidating, but providing prompt starters can help individuals overcome this initial hurdle and jumpstart their creativity.
Ordering content along different interpretable dimensions, like style or similarity, makes it navigable on x and y axes facilitating exploration and discovery of relationships between the data.
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.
Textual information often misses intuitive cues for understanding relationships between ideas. AI can clarify these connections, making complex information easier to grasp quickly.