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
Empower users to make decisions and give feedback quickly or engage more deeply when needed in natural language.
Spatial prompting integrates spatial relationships into prompts, offering a novel approach to manipulate concepts. This dynamic approach can lead to more intuitive and creative outcomes.
Guide users to understand what makes a good prompt will help them learn how to craft prompts that result in better outputs.
Realtime generation allows people to manipulate content instantly, giving them more agency in using generative AI as a tool for exploration.
A smart browser assistant that understands the context of your open tabs to offer relevant suggestions and actions, enhancing productivity through transparency and control.
Embedding models can rank content along virtually any dimension. This capability provides significant value by enabling users to explore and analyze the embeddings to create a spectrum of any features.