High-quality, interactive feedback facilitates growth. At Perceptible, we design autonomous agents capable of thoughtful feedback discussions.
Active Empathetic Listening
Our agents are designed to listen attentively. They are focused on comprehending the full context before responding, like a counselor giving their undivided attention. Multi-modal analysis of inputs and output allow sensing both the literal meanings and emotional subtext of what is said. Tone, word choices and context provide insight into the unspoken significance behind the words. Perceptible's goal is to build agents that aim to understand before thoughtfully reacting.
Thought-Provoking Questions
To encourage elaboration, Perceptible envisages agents that ask open-ended questions that create space for explanation. For example, "What factors led you to that conclusion?" Follow-up questions then draw out additional nuances to progressively deepen the dialogue, like an investigative journalist aiming to uncover the full story. The objective is prompting introspective responses that provide maximum context.
Constructive Suggestions
Building collaborative agents necessitates AI that offers feedback focused on developing strengths. Perceptible is focused on providing cognitive models that provide personalized recommendations tailored to individuals' specific goals. Suggestions aim to be additive, extending capabilities through care and encouragement. The feedback conveys a belief in each person's potential.
Interactive Clarification
To verify mutual understanding, Perceptible's internal multi-agent approach aims to build agents that summarize the key points covered and invite the participant to ask clarifying questions. Any misconceptions are addressed through continued dialogue. With agents that clarify interactively, and environment is developed that evolves understanding through ongoing exploration like a teacher guiding a student toward their own insights.
Adaptive Communication
Similar to socially intelligent people, Perceptible's agents can analyse conversations to identify optimal communication styles, progressively adapting their approach over time. By engaging in supportive conversation, discussions are more productive, friendly, and comfortable for all participants. Communication can adjust interactively to customs, cultures and individuals' preferences by storing and retrieving preferences.
The aim is designing agents that provide the thoughtful feedback essential for progress through cooperative conversation. Please reach out to explore Perceptible's humanistic approach to AI.
