Semantic highlights
Embedding models can rank data based on semantic meaning, evaluating each individual segment on a spectrum to show its relevance throughout the artifact.


When scanning large amount of text, I want to be able to rank data based on meaning, so I can understand the significance of selected concepts easily.


- The flow of language: When we are able to rank content on specific parameters, we also make the flow of the language visible. This makes it easier to scan large amounts of text for the information you are searching for.

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.

In Arc, a playful pinch interaction lets you quickly distill any webpage into a brief summary, capturing the essence of the content in moments.

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.

AI excels at classifying vast amounts of content, presenting an opportunity for new, more fluid filter interfaces tailored to the content.

Starting with a blank canvas can be intimidating, but providing prompt starters can help individuals overcome this initial hurdle and jumpstart their creativity.

Textual information often misses intuitive cues for understanding relationships between ideas. AI can clarify these connections, making complex information easier to grasp quickly.