Automatic model switching
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.
I like knowing why my smart assistant sometimes responds quickly and other times takes a bit longer. It makes me trust it more when I see it's using the right tools for the job.
- Faster Response Times: Smaller models can deliver quicker responses for simpler queries, enhancing user experience by reducing wait times.
- Different Styles: Different models may produce responses in various styles or levels of detail, helping to match user expectations more closely.
- Transparency Builds Trust: Transparently indicating which model is being used for different queries helps set user expectations and builds trust in the AI’s operations.
More of the Witlist
Realtime generation allows people to manipulate content instantly, giving them more agency in using generative AI as a tool for exploration.
Referencing nested data from your database in the form of tags can simplify the creation of elaborate prompt formulas.
Textual information often misses intuitive cues for understanding relationships between ideas. AI can clarify these connections, making complex information easier to grasp quickly.
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.
Comprehend and compare large documents by visualizing embeddings and their scores, enabling a clear and concise understanding of vast data sources in a single, intuitive visualization.