AI changes almost everything
End users can ask contextual questions surrounding any data point (from a reference pdf, or general knowledge), manipulate visualizations on the fly, encouraging infinite exploration and discovery.
When creating Flows, AI speeds up the creation process through suggested visualizations and insights.
When creating Flows, AI speeds up the creation process through suggested visualizations and insights.
Building with AI
The fusion of AI and AR/MR empowers us to unlock greater potential of our cognitive abilities, enabling us to solve complex problems, make informed decisions, and share with colleagues.
Flow applies six meaningful functions in our AR/MR + AI data visualization platform:
Flow applies six meaningful functions in our AR/MR + AI data visualization platform:
To learn more, please read this AR Insider article written by our founder Jason Marsh, and contact us below!
- Spoken commands simplify the user interface
- The LLM explains and provides context that goes beyond the data
- Create and manipulate visualizations
- User-uploaded PDF documents ensure expert content-specific accuracy
- Manipulate the underlying data through AI-generated Python scripts
- “What should I notice about my data?” identifies trends & outliers, correlations, and insights
Multiuser AI + AR is magic
AI makes AR more useful, and overcomes some core limitations of AR, which include a constrained field of view within which it is difficult to include more than one panel of UI buttons and interactions.
The inverse is also true: AR helps AI make concrete. In the context of data visualization, LLMs can identify how to process massive amounts of data quickly, identify patterns, and present insights, but the results are usually limited to text. On the other hand, AR can provide an interactive, immersive platform to visualize these insights and/or anchor the insights within the larger context of the scope of the data.
The inverse is also true: AR helps AI make concrete. In the context of data visualization, LLMs can identify how to process massive amounts of data quickly, identify patterns, and present insights, but the results are usually limited to text. On the other hand, AR can provide an interactive, immersive platform to visualize these insights and/or anchor the insights within the larger context of the scope of the data.
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